Handbook of Approach and Avoidance Motivation

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HANDBOOK OF APPROACH AND AVOIDANCE MOTIVATION

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HANDBOOK OF APPROACH AND AVOIDANCE MOTIVATION Andrew J. Elliot Editor

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Psychology Press Taylor & Francis Group 270 Madison Avenue New York, NY 10016

Psychology Press Taylor & Francis Group 27 Church Road Hove, East Sussex BN3 2FA

© 2008 by Taylor & Francis Group, LLC Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-13: 978-0-8058-6019-1 (Hardcover) Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging-in-Publication Data Elliot, Andrew J. Handbook of approach and avoidance motivation / Andrew J. Elliot. p. cm. Includes bibliographical references and index. ISBN 978-0-8058-6019-1 (alk. paper) 1. Avoidance (Psychology) I. Title. BF337.A92E45 2008 155.9--dc22

2008011859

Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the Psychology Press Web site at http://www.psypress.com

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Contents Preface ...........................................................................................................................................................................xi Editor .......................................................................................................................................................................... xiii Contributors ..................................................................................................................................................................xv

PART I Introduction Introduction and Overview Chapter 1

Approach and Avoidance Motivation ........................................................................................................3 Andrew J. Elliot

PART II

Neurophysiology and Neurobiology

Brain Systems and Mechanisms Chapter 2

Emotional Processing and Motivation: In Search of Brain Mechanisms ............................................... 17 Christopher K. Cain and Joseph E. LeDoux

Cortical Asymmetry Chapter 3

Effects of Early Experience on the Development of Cerebral Asymmetry and Approach–Withdrawal......................................................................................................................35 Nathan A. Fox and Bethany C. Reeb

Cortex-Reflex Connections Chapter 4

Appetitive and Defensive Motivation Is the Substrate of Emotion ......................................................... 51 Peter J. Lang and Margaret M. Bradley

Subcortical Processes Chapter 5

Dopamine and SEEKING: Subcortical “Reward” Systems and Appetitive Urges ................................67 Jaak Panksepp and Joseph Moskal

Neurotransmitters Chapter 6

An Accumbens Dopamine–Acetylcholine System for Approach and Avoidance ..................................89 Bartley G. Hoebel, Nicole M. Avena, and Pedro Rada

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Hormones Chapter 7

The Role and Mechanisms of Steroid Hormones in Approach–Avoidance Behavior ..........................109 Cheryl A. Frye and Madeline E. Rhodes

Olfaction Chapter 8

Development of Olfactory Modulated Approach and Avoidance Motivated Behaviors.......................127 Regina M. Sullivan, Donna J. Toufexis, and Donald A. Wilson

PART III

Basic Dispositions, Goals, and States

Basic Personality Dispositions Chapter 9

Basic Personality Dispositions Related to Approach and Avoidance: Extraversion/Neuroticism, BAS/BIS, and Positive/Negative Affectivity ............................................. 151 Randy J. Larsen and Adam A. Augustine

Basic Dispositions in Nonhuman Animals Chapter 10 Individual Differences in Approach and Avoidance Motivation in Animals ....................................... 165 Amanda C. Jones and Samuel D. Gosling Behavioral Genetics Chapter 11 Genetic Influences on Individual Differences in Approach and Avoidance ......................................... 187 H. Hill Goldsmith and Kathryn Lemery-Chalfant Social Motives and Goals Chapter 12 Making Connections and Avoiding Loneliness: Approach and Avoidance Social Motives and Goals......................................................................................................................203 Shelly L. Gable and Elliot T. Berkman Achievement Motives and Goals Chapter 13 Approach and Avoidance Motivation in the Achievement Domain: Integrating the Achievement Motive and Achievement Goal Traditions ............................................................................................ 217 Todd M. Thrash and Anne L. Hurst Motivational States Chapter 14 Activation and Measurement of Motivational States ............................................................................235 Ronald S. Friedman and Jens Förster

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PART IV Evaluative Processes Evolution of Evaluative Processes I Chapter 15 Internal Regulatory Variables and the Design of Human Motivation: A Computational and Evolutionary Approach................................................................................................................... 251 John Tooby, Leda Cosmides, Aaron Sell, Debra Lieberman, and Daniel Sznycer Evolution of Evaluative Processes II Chapter 16 Approach and Avoidance Motivation(s): An Evolutionary Perspective ................................................273 Douglas T. Kenrick and Michelle N. Shiota Immediacy and Automaticity of Evaluation Chapter 17 Evaluative Readiness: The Motivational Nature of Automatic Evaluation...........................................289 Melissa J. Ferguson and John A. Bargh Structure of Evaluation Chapter 18 The Functional Neuroarchitecture of Evaluative Processes .................................................................307 Gary G. Berntson and John T. Cacioppo Evaluation Asymmetry Chapter 19 How Approach and Avoidance Decisions Influence Attitude Formation and Change .........................323 J. Richard Eiser and Russell H. Fazio

PART V Emotion and Well-Being Structure of Emotions Chapter 20 Motivations and Emotivations: Approach, Avoidance, and Other Tendencies in Motivated and Emotional Behavior ...............................................................................343 Ira J. Roseman Function of Emotions Chapter 21 Functions of Emotions and Emotion-Related Dysfunction...................................................................367 Eric Youngstrom and Carroll E. Izard Distinct Emotional Experience Chapter 22 Approach, Avoidance, and Emotional Experiences ..............................................................................385 Charles S. Carver, Yael E. Avivi, and Jean-Philippe Laurenceau

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Anger Chapter 23 Anger and Approach–Avoidance Motivation ........................................................................................399 Eddie Harmon-Jones, Carly Peterson, Philip A. Gable, and Cindy Harmon-Jones Well-Being Chapter 24 Approach–Avoidance Goals and Well-Being: One Size Does Not Fit All ........................................... 415 Maya Tamir and Ed Diener

PART VI Cognition Challenge and Threat Appraisal Chapter 25 Challenge and Threat ............................................................................................................................ 431 Jim Blascovich Mental Control Chapter 26 Thought Suppression and Psychopathology ..........................................................................................447 Sadia Najmi and Daniel M. Wegner Orienting and Attentional Processes Chapter 27 Motivational and Attentional Components of Personality .................................................................... 461 Douglas Derryberry and Marjorie Reed Framing Chapter 28 How Persons and Situations Regulate Message Framing Effects: The Study of Health Behavior ............................................................................................................... 475 Alexander J. Rothman, Jhon T. Wlaschin, Roger D. Bartels, Amy Latimer, and Peter Salovey

PART VII

The Self

Self-Regulation Chapter 29 Distinguishing Levels of Approach and Avoidance: An Analysis Using Regulatory Focus Theory ......................................................................................................................489 Abigail A. Scholer and E. Tory Higgins

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Self-Esteem and Self-Concept Chapter 30 Approach and Avoidance Motivations in the Self-Concept and Self-Esteem.......................................505 Dianne M. Tice and E. J. Masicampo Self-Knowledge Chapter 31 Secrets of Resilience: Approaching Negative Self-Aspects Without Aversion..................................... 521 Carolin J. Showers and Kristy L. Boyce Self-Access Chapter 32 The Functional Architecture of Approach and Avoidance Motivation................................................. 535 Julius Kuhl and Sander L. Koole

PART VIII Social Context Culture Chapter 33 Approach and Avoidance Motivation Across Cultures ......................................................................... 557 Takeshi Hamamura and Steven J. Heine Stereotyping Chapter 34 Interracial Interactions: Approach and Avoidance................................................................................ 571 E. Ashby Plant and Patricia G. Devine Social Comparison Chapter 35 A Reunion for Approach–Avoidance Motivation and Social Comparison ...........................................585 Jerry Suls and Ladd Wheeler Social Exclusion Chapter 36 I Am Approaching the Decision to Avoid You: An Approach and Avoidance Perspective on Research on Social Exclusion and Rejection ...................................................................................601 Roy F. Baumeister and Seth Gitter Sexual Behavior Chapter 37 A Dyadic Perspective on Approach and Avoidance Motives for Sexual Behavior ............................... 615 M. Lynne Cooper, Amelia E. Talley, Meli S. Sheldon, Ash Levitt, and Lindsay L. Barber Author Index .............................................................................................................................................................633 Subject Index .............................................................................................................................................................657

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Preface Of the many conceptual distinctions present in psychology today, the approach–avoidance distinction stands out as one of, if not, the most fundamental and basic. The distinction between approach and avoidance motivation has a venerable history, not only within but beyond scientific psychology, and the deep utility of this distinction is clearly evident across theoretical traditions, disciplines, and content areas. The Handbook of Approach and Avoidance Motivation is designed to illustrate and highlight the central importance of this distinction, to serve as a one-stop resource for scholars working in this area, and to facilitate integration among researchers and theorists with an explicit or implicit interest in approach and avoidance motivation. In an introductory chapter, I lay the groundwork for the volume by overviewing the history of the approach–avoidance distinction, explicating its fundamental role in motivational analyses of behavior, and providing definitional and terminological guidance. The main body of the Handbook is organized according to seven broad parts that represent core areas of interest in the study of approach and avoidance motivation (e.g., neurophysiology and neurobiology, evaluative processes). Each part contains a minimum of four chapters, each of which covers a specific aspect of approach and avoidance motivation. The coverage of the Handbook is not comprehensive (such coverage is an impossibility, given the widespread implicit, as well as explicit, use of the approach–avoidance distinction), but clearly encompasses the most central areas in the contemporary study of approach and avoidance motivation. I could not be happier with the lineup of scholars that have made contributions to this volume. Those working in this area will recognize the names in the Table of Contents as an all star team of researchers and theorists in the area of motivation. Furthermore, these top-of-the-line scholars have uniformly provided chapters worthy of their reputation. In short, in this volume I am pleased to present outstanding chapters by the best minds in the field. The Handbook of Approach and Avoidance Motivation is targeted toward those in academia, including advanced undergraduates, graduate students, postdoctoral students, and professors. The broad applicability of the approach– avoidance distinction will likely make the book a helpful resource for a diverse population. The volume may not only be used as a personal resource for researchers and theorists, but may also be used as a textbook for teachers of advanced undergraduate and graduate seminars; indeed I intend to use it in this capacity myself. I hope you enjoy reading these chapters as much as I enjoyed editing them. The study of approach and avoidance motivation is clearly as vibrant and generative now as it has ever been! Andrew J. Elliot

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Editor Andrew J. Elliot is a professor of psychology at the University of Rochester. He received his PhD from the University of Wisconsin–Madison in 1994. His research areas include approach and avoidance motivation, achievement and social motivation, the self, personal goals, subjective well-being, color, and parental, teacher, and cultural influences on motivation and self-regulation. He is currently an associate editor of Personality and Social Psychology Bulletin, is currently the motivation and emotion section editor of Social and Personality Psychology Compass, and has coedited the Handbook of Competence and Motivation. He has over 100 scholarly publications, has received research grants from public and private agencies, and has been awarded four different early and mid career awards for his research contributions.

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Contributors Adam A. Augustine Department of Psychology Washington University in St. Louis Saint Louis, Missouri Nicole M. Avena Department of Psychology Princeton University Princeton, New Jersey

Jim Blascovich Department of Psychology University of California– Santa Barbara Santa Barbara, California Kristy L. Boyce Department of Psychology University of Oklahoma Norman, Oklahoma

Patricia G. Devine Department of Psychology University of Wisconsin–Madison Madison, Wisconsin Ed Diener Department of Psychology University of Illinois Champaign–Urbana, Illinois

Margaret M. Bradley Department of Psychology University of Florida Gainesville, Florida

J. Richard Eiser Department of Psychology University of Sheffield Sheffield, South Yorkshire United Kingdom

Lindsay L. Barber Department of Psychology University of Missouri–Columbia Columbia, Missouri

John T. Cacioppo Department of Psychology University of Chicago Chicago, Illinois

Andrew J. Elliot Department of Psychology University of Rochester Rochester, New York

John A. Bargh Department of Psychology Yale University New Haven, Connecticut

Christopher K. Cain Center for Neural Science New York University New York, New York

Russell H. Fazio Department of Psychology The Ohio State University Columbus, Ohio

Roger D. Bartels Department of Psychology University of Minnesota Minneapolis, Minnesota

Charles S. Carver Department of Psychology University of Miami Coral Gables, Florida

Melissa J. Ferguson Department of Psychology Cornell University Ithaca, New York

Roy F. Baumeister Department of Psychology Florida State University Tallahassee, Florida

M. Lynne Cooper Department of Psychology University of Missouri–Columbia Columbia, Missouri

Jens Förster Department of Psychology University of Amsterdam Amsterdam, the Netherlands

Elliot T. Berkman Department of Psychology University of California–Los Angeles Los Angeles, California

Leda Cosmides Department of Psychology University of California– Santa Barbara Santa Barbara, California

Nathan A. Fox Department of Human Development University of Maryland College Park, Maryland

Gary G. Berntson Department of Psychology The Ohio State University Columbus, Ohio

Douglas Derryberry Department of Psychology Oregon State University Corvallis, Oregon

Yael E. Avivi Department of Psychology University of Miami Coral Gables, Florida

Ronald S. Friedman Department of Psychology University of Albany, State University of New York Albany, New York

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Cheryl A. Frye Department of Psychology State University of New York–Albany Albany, New York

E. Tory Higgins Department of Psychology Columbia University New York, New York

Philip A. Gable Department of Psychology Texas A&M University College Station, Texas

Bartley G. Hoebel Department of Psychology Princeton University Princeton, New Jersey

Shelly L. Gable Department of Psychology University of California– Santa Barbara Santa Barbara, California

Anne L. Hurst Department of Psychology College of William and Mary Williamsburg, Virginia

Seth Gitter Department of Psychology Florida State University Tallahassee, Florida H. Hill Goldsmith Department of Psychology University of Wisconsin–Madison Madison, Wisconsin Samuel D. Gosling Department of Psychology University of Texas–Austin Austin, Texas Takeshi Hamamura Department of Psychology University of British Columbia British Columbia, Canada Cindy Harmon-Jones Department of Psychology Texas A & M University College Station, Texas

Jean-Philippe Laurenceau Department of Psychology University of Delaware Newark, Delaware Joseph E. LeDoux Center for Neural Science New York University New York, New York

Carroll E. Izard Department of Psychology University of Delaware Newark, Delaware

Kathryn Lemery-Chalfant Department of Psychology Arizona State University Tempe, Arizona

Amanda C. Jones Department of Psychology University of Texas–Austin Austin, Texas

Ash Levitt Department of Psychology University of Missouri–Columbia Columbia, Missouri

Douglas T. Kenrick Department of Psychology Arizona State University Tempe, Arizona

Debra Lieberman Department of Psychology University of Hawaii Manoa, Hawaii

Sander L. Koole Department of Psychology and Education Vrije Universiteit Amsterdam, the Netherlands

E. J. Masicampo Department of Psychology Florida State University Tallahassee, Florida

Julius Kuhl Department of Psychology University of Osnabrück Lower Saxony, Germany

Eddie Harmon-Jones Department of Psychology Texas A & M University College Station, Texas

Peter J. Lang Department of Clinical and Health Psychology University of Florida Gainesville, Florida

Steven J. Heine Department of Psychology University of British Columbia British Columbia, Canada

Randy J. Larsen Department of Psychology Washington University in St. Louis Saint Louis, Missouri

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Amy Latimer School of Kinesiology and Health Studies Queens University Ontario, Canada

Joseph Moskal Department of Biomedical Engineering Northwestern University Evanston, Illinois Sadia Najmi Department of Psychology Harvard University Cambridge, Massachusetts Jaak Panksepp Department of Veterinary and Comparative Anatomy, Pharmacology, and Physiology Washington State University Pullman, Washington

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Carly Peterson Department of Psychology Texas A&M University College Station, Texas E. Ashby Plant Department of Psychology Florida State University Tallahassee, Florida Pedro Rada Laboratory of Behavioral Physiology University of Los Andes Merida, Venezuela

Aaron Sell Department of Psychology University of California– Santa Barbara Santa Barbara, California Meli S. Sheldon Department of Psychology University of Missouri–Columbia Columbia, Missouri

Dianne M. Tice Department of Psychology Florida State University Tallahassee, Florida John Tooby Department of Anthropology University of California–Santa Barbara Santa Barbara, California

Michelle N. Shiota Department of Psychology Arizona State University Tempe, Arizona

Donna J. Toufexis Department of Psychiatry and Behavioral Sciences Emory University Atlanta, Georgia

Bethany C. Reeb Department of Human Development University of Maryland College Park, Maryland

Carolin J. Showers Department of Psychology University of Oklahoma Norman, Oklahoma

Daniel M. Wegner Department of Psychology Harvard University Cambridge, Massachusetts

Marjorie Reed Department of Psychology Oregon State University Corvallis, Oregon

Regina M. Sullivan Department of Zoology University of Oklahoma Norman, Oklahoma

Ladd Wheeler Department of Psychology Macquarie University Sydney, New South Wales, Australia

Madeline E. Rhodes Department of Psychology State University of New York–Albany Albany, New York

Jerry Suls Department of Psychology University of Iowa Iowa City, Iowa

Ira J. Roseman Department of Psychology Rutgers University Camden, New Jersey

Daniel Sznycer Department of Psychology University of California Santa Barbara, California

Alexander J. Rothman Department of Psychology University of Minnesota Minneapolis, Minnesota

Amelia E. Talley Department of Psychology University of Missouri–Columbia Columbia, Missouri

Peter Salovey Department of Psychology Yale University New Haven, Connecticut

Maya Tamir Department of Psychology Boston College Chestnut Hill, Massachusetts

Abigail A. Scholer Department of Psychology Columbia University New York, New York

Todd M. Thrash Department of Psychology College of William and Mary Williamsburg, Virginia

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Donald A. Wilson Department of Zoology University of Oklahoma Norman, Oklahoma Jhon T. Wlaschin Department of Psychology University of Minnesota Minneapolis, Minnesota Eric Youngstrom Department of Psychology University of North Carolina– Chapel Hill Chapel Hill, North Carolina

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Part I Introduction

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Introduction and Overview and Avoidance 1 Approach Motivation Andrew J. Elliot CONTENTS History .......................................................................................................................................................4 Fundamental Role of Approach and Avoidance Motivation .....................................................................5 Definition and Conceptualization .............................................................................................................8 Terminological Considerations .................................................................................................................9 Overview of the Handbook of Approach and Avoidance Motivation .....................................................10 Acknowledgments ................................................................................................................................... 11 References ............................................................................................................................................... 11

The distinction between approach and avoidance motivation has a long and rich history in intellectual thought in general, and scientific psychology in particular. In accord with Lewin (1935), approach motivation may be defined as the energization of behavior by, or the direction of behavior toward, positive stimuli (objects, events, possibilities), whereas avoidance motivation may be defined as the energization of behavior by, or the direction of behavior away from, negative stimuli (objects, events, possibilities). Approach and avoidance concepts and constructs have been utilized across a diversity of scholarly disciplines, theoretical traditions, and empirical content areas. Attention to the approach–avoidance motivational distinction has not been constant over the years, but may be seen as waxing and waning at different periods. At present, there appears to be substantial interest in approach and avoidance motivation, but it is also the case that motivationally relevant theories, models, variables, and hypotheses continue to be espoused with little or no consideration of this fundamental distinction. In addition, when the approach–avoidance distinction is utilized in the contemporary literature it is rarely explicitly defined, and approach and avoidance motivation are often described and discussed using diverse terminology

that tends to obfuscate links between findings and frameworks. Accordingly, the broad aims of the Handbook of Approach and Avoidance Motivation are threefold. First, the handbook is designed to illustrate the importance and broad utility of the approach–avoidance motivational distinction. Second, it is designed to provide a ready resource for scholars interested in theoretical and empirical work in this area. Third, it is designed to reveal conceptual and empirical links and convergences across disciplines, research traditions, and levels of analysis that will, it is hoped, facilitate cross talk and cross-fertilization among researchers and theorists. In this introductory chapter, I begin by overviewing the history of the approach–avoidance distinction. I then proceed to explicate the fundamental role of approach and avoidance motivation in the functioning of organisms across the phylogenetic spectrum. Next, I return to the definition of approach and avoidance motivation offered above, and elaborate on several conceptual considerations inherent within this definition. I continue by discussing terminological issues pertaining to the approach–avoidance distinction, and then I close with a 3

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brief overview of the various sections that comprise the contents of the handbook.

HISTORY Distinguishing approach motivation from avoidance motivation may be considered one of the oldest ideas in the history of thought about the behavior of organisms. Scholars have made use of the approach–avoidance distinction for well over 2000 years. It first appeared in the writing of the ancient Greek philosopher Democritus of Abdera (460–370 B.C.E.). Democritus articulated an ethical hedonism in which the immediate pursuit of pleasure and avoidance of pain were prescribed as the guide for human action: “The best thing for man is to pass his life so to have as much joy and as little trouble as may be” (fragment 189, see Copleston, 1946, p. 125; see also Aristippus [435–356 B.C.E.] and Epicurus [342–270 B.C.E.]). Plato (427–327 B.C.E.) had Socrates (470–399 B.C.E.) espouse various hedonic notions in Protagoras and Phaedo, although it is unclear whether such positions should be attributed to Socrates or Plato himself. The eighteenth century British philosopher Jeremy Bentham was the first to clearly postulate a psychological hedonism, in addition to an ethical hedonism; this form of hedonism moved beyond a prescription of how we ought to behave to a proto-scientific description of how we actually do behave. This principle is directly stated at the beginning of Bentham’s Introduction to the Principles and Morals of Legislation: “Nature has placed mankind under the governance of two sovereign masters, pain and pleasure. It is for them alone to point out what we ought to do, as well as to determine what we shall do” (Bentham, 1779/1879, p. 1). Within the field of scientific psychology per se, the approach–avoidance distinction was attended to from the beginning. Wundt (1887), for example, in his monumental Principles of Physiological Psychology (Vol. 3), conceptualized pleasure and pain as unique psychic elements brought into consciousness by sensation, emotion, and cognition (Marshall, 1889). In his classic Principles of Psychology (Vol. 2), James (1890) portrayed pleasure and pain as “springs of action,” noting that pleasure is a “tremendous reinforcer” of behavior and pain a “tremendous inhibitor” of behavior (pp. 549–559). James even provided speculation on the neural mechanisms underlying “impulsive” and “inhibitory tendencies” (p. 550). Freud (1915) construed the procurement of pleasure and the avoidance of pain (i.e., unpleasure) as the basic motivational impetus underlying psychodynamic activity, and divided the superego into two parts—the ego ideal,

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representing what the person should do, and the conscience, representing what the person should not do (Freud, 1923). Thus, James and Freud moved beyond a general focus on pleasure and pain per se to a focus on the specific ways that approach and avoidance behavior are produced and regulated. In addition to these early pioneers, many prominent psychological theorists over the years have made use of the approach–avoidance distinction in their work. Thorndike (1911), in his “law of effect,” described how responses followed by satisfaction are more likely to recur and responses followed by discomfort are less likely to recur. Jung (1921) posited that a fundamental difference between extroverts and introverts is that extroverts exhibit an interest in moving toward social objects, whereas introverts exhibit an interest in moving away from social objects. Tolman (1925) contended that a complete description of behavior must include reference to the end (i.e., goal) toward which or away from which the organism is moving. Pavlov (1927) identified two types of reflexive responses to stimuli, an orienting response toward the stimulus and a defensive response away from the stimulus. Lewin (1935) posited that goal objects in the life space have positive valences that attract and negative valences that repel. Horney (1937) discussed different strategies that individuals use to cope with their basic anxiety, including “moving toward” and “moving away.” Skinner (1938, 1953) distinguished between reinforcers that strengthen responses and punishing stimuli that weaken responses, and differentiated positive reinforcement (the provision of a positive) from negative reinforcement (the removal of a negative). Murray (1938) distinguished between two types of psychological needs, “adient” (positive) needs that impel the organism toward other objects, and “abient” (negative) needs that impel the organism away from other objects. Hull (1943) proposed two classes of acquired drives, conditioned appetitive drives (e.g., involving food) and conditioned aversive drives (e.g., involving pain avoidance), and his mathematical theory of instrumental behavior included parameters representing the tendency to respond (reaction potential) and inhibit responding (inhibitory potential). Miller (1944) detailed various dynamic conflicts that can result from incompatible valences (e.g., being attracted to and repelled by the same goal object). Hebb (1949) posited that stimulation below a certain threshold leads to pleasure and approach behavior, whereas stimulation above the threshold leads to pain and avoidance behavior. Sullivan (1953) introduced the notion of self-personifications, including the good me and the bad me. Rotter (1954) proposed that individuals’

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Approach and Avoidance Motivation

expectancies and values are largely a function of their experiences with prior rewards and punishments. Maslow (1955) asserted that human beings have two basic sets of needs, deficit needs (e.g., safety) that involve striving to eliminate a negative-life situation and growth needs (i.e., self-actualization) that involve striving to attain a more positive-life situation. Cattell (1957) distinguished between the innate motives (ergs) of exploration (an appetitive motive) and escape to security (an aversive motive). Heider (1958) summarized the difference between “can” and “may” by stating that the former implies that if a person tries, he or she will succeed, whereas the latter implies that if a person tries he or she will not be punished. Mowrer (1960) differentiated between hoped for and feared states, and linked the presence and absence of these states to distinct emotions. Rogers (1961) stated that personal goals may either represent moving toward something positive or moving away from something negative. Erickson (1963) distinguished between basic trust and mistrust in articulating the crisis of the first psychosocial stage of development. Eysenck (1967) posited that introverts are “stimulus shy” due to high baseline levels of cortical arousal, whereas extraverts are “stimulus hungry” due to low baselines levels of cortical arousal. Bowlby (1969) proposed two distinct types of attachments, secure attachment that promotes challenge seeking and exploration, and insecure attachment that leads to caution and a preoccupation with safety and protection. The aforementioned is but a sampling of the prominent psychological theorists who have implemented approach–avoidance concepts or constructs in their work. This listing emphatically documents the historical significance of the approach–avoidance distinction; it not only shows that the distinction has a long history, but also that it has a broad history. Indeed, the approach–avoidance distinction has been utilized in all of the major theoretical approaches that have been employed to scientifically explain behavior, regardless of how these approaches might be characterized: psychodynamic (e.g., Freud), behaviorist (e.g., Skinner), and humanistic (e.g., Maslow); dispositional (e.g., Murray) and situational (e.g., Thorndike); biological (e.g., Eysenck), affective (e.g., Mowrer), cognitive (e.g., Heider), and social cognitive (e.g., Rotter). During the 1970s through the 1980s, many cognitive and social-cognitive theorists pitted cognitive against affective and motivational accounts of behavior. In this context, the approach–avoidance distinction was still utilized in theorizing to some degree, but in a much more limited way than in years past. It was with the acknowledgment in the 1990s that cognition, affect, and

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motivation are deeply intertwined, and need not be viewed as conceptual competitors, that motivational considerations in general, and the approach–avoidance distinction specifically, returned to prominence. This return to prominence is noteworthy, because use of the approach–avoidance distinction in the contemporary scene would appear to differ from prior use in two important ways. First, until recently, the approach– avoidance distinction had been widely utilized and applied without taking a step back to explicitly define and articulate the nature of approach and avoidance motivation. Thus, philosophers, theorists, and researchers over the years have incorporated the approach–avoidance distinction in many different ways in their work, but they have not clearly explicated the conceptual space represented by approach and avoidance motivation per se. Recent work has directly attended to this issue (Elliot, 1999, 2006; Elliot & Covington, 2001). Second, until recently, the approach–avoidance distinction has been used to address specific issues regarding motivation, without considering its broader potential as an explanatory tool. Prior work has focused on a diversity of specific issues—on hedonism as the ultimate energizer of activity; on the various appetitive and aversive mechanisms, needs, and motives that underlie observable action; on the different valence-based variables that serve to guide and direct behavior, etc. However, there has been little consideration of how the approach–avoidance distinction might be used to integrate various types and levels of analysis to construct a more detailed and sophisticated account of motivation. Recent work has moved in this direction (Cacioppo & Berntson, 1994; Carver & Scheier, 1998; Elliot & Church, 1997; Higgins, 1997; Lang, 1995).

FUNDAMENTAL ROLE OF APPROACH AND AVOIDANCE MOTIVATION The widespread use of the approach–avoidance distinction over the years undoubtedly reflects the fundamental role of approach and avoidance motivation in human functioning. Both approach and avoidance motivation are integral to successful adaptation; avoidance motivation facilitates surviving, while approach motivation facilitates thriving. This is the case with respect to physical and psychological adaptation alike (Elliot, 2006). Approach and avoidance motivation not only plays a central role in the functioning of humans, but also in the functioning of organisms across the phylogenetic spectrum. Tooby and Cosmides (1990) have argued that the decision to approach or withdraw has been the

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fundamental adaptive decision that organisms have had to make throughout their evolutionary past. To paraphrase Schneirla (1959), the high road of evolution has been littered with the remains of species that have failed to acquire one or more mechanisms for accurately determining the beneficial or harmful potential of environmental stimuli. As such, all animate life, from the singlecell amoeba upward, is equipped with at least some basic form of approach–avoidance mechanism that produces or regulates movement toward potentially beneficial stimuli and away from potentially harmful stimuli. In the amoeba, approach and avoidance motivation is obviously extremely rudimentary, representing approach and withdrawal tendencies “energized directly by protoplasmic processes set off by the stimulus” (Schneirla, 1959, p. 2). For example, a weak light will stimulate a local flow of protoplasm toward the light, often followed by a general movement in that direction, whereas an intense light will stimulate a local contraction of protoplasm, often followed by a general movement away from the light source. Schneirla (1959) argued that organisms at all levels of complexity possess approach-based mechanisms that evoke appetitive reactions and facilitate foodgetting, shelter-getting, and mating, and avoidance-based mechanisms that evoke withdrawal reactions and facilitate defense, huddling, flight, and protection, in general. He proposed that the sophistication of these mechanisms varies considerably across species, with those of protozoa and other invertebrates being rudimentary and rigid, and those of higher organisms being more advanced and flexible. Researchers have not only documented the existence of approach and avoidance mechanisms across phyla, but have also shown individual differences in approach and avoidance motivation within a variety of different species. Intraspecific differences in the tendency to approach or avoid novel stimuli have been documented in monkeys (Suomi, 1983), cats (Adamec, 1991), dogs (Goddard & Beilharz, 1985), wolves (MacDonald, 1983), cows (Fordyce, Goddard, & Seifert, 1982), goats (Lyons, Price, & Moberg, 1988), rats (Garcia-Sevilla, 1984), mice (Kagan, 1998), birds (Verbeek, Drent, & Wiepkema, 1994), snakes (Herzog & Burghardt, 1988), fish (Wilson, Coleman, Clark, & Biederman, 1993), and even some crustaceans (Wilson, Clark, Coleman, & Dearstyne, 1994). Perhaps most provocatively, some researchers have conducted factor-analytic studies seeking to demonstrate the presence of basic dimensions of “personality” in nonhumans. For instance, Budaev (1997) used factor analysis to examine the patterns underlying exploratory, predatory inspection, and schooling behavior in male guppies. Results

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revealed two primary orthogonal factors that the investigator interpreted in terms of approach and avoidance motivation: an approach system “governing exploration and social attraction” and a fear avoidance system “governing responses to aversive stimulation” (p. 399). Comparable results suggesting independent, approachand avoidance-based dimensions of “personality” have been obtained in factor-analytic studies of behavior with octopuses (Mather & Anderson, 1993), yellow-bellied marmots (Armitage, 1986), small-eared bushbabys (Watson & Ward, 1996), rhesus monkeys (StevensonHinde, Stillwell-Barnes, & Zunz, 1980), and hooded rats (Maier, Vandenhoff, & Crowne, 1988). It is not only just the organism’s ability to determine the adaptive significance of stimuli that is central to survival, but also the speed at which these determinations are made (Berntson, Boysen, & Cacioppo, 1993; Orians & Heerwagen, 1992). As such, all (surviving) organisms are hard-wired or “pre-programmed” to make immediate approach–avoidance responses to particular classes of stimuli (Zajonc, 1984, p. 122). Zajonc (1998) contends that “approach–avoidance discriminations” (p. 592) are the primary and most elemental reaction of organisms to environmental stimuli, the initial response on which all subsequent responses are based. This is nicely illustrated in the amoeba’s instantaneous, constitutionally ingrained approach or withdrawal response to light intensity, which is essentially a reflexive reaction to the light stimulus. Humans, like protozoa, exhibit immediate, constitutionally ingrained approach and avoidance responses to certain classes of stimuli. For example, humans possess many different unconditioned exteroceptive reflexes that are commonly classified as orienting (e.g., the salivary reflex) or defensive (e.g., pain withdrawal and startle; Graham, 1973; Pavlov, 1927; Sokolov, 1963) and that may be considered manifestations of approach and avoidance motivation, respectively (Dickinson & Dearing, 1979; Konorski, 1967). One such reflex that has attracted significant research attention is the blink component of the startle reflex. This blink reflex is an involuntary response to an intense stimulus such as a loud noise, a bright light, or an electric shock, and occurs within 30–50 ms of stimulus onset (Bradley & Vrana, 1993). It serves the defensive function of protecting the eye from injury, and acts as a behavioral interrupt that clears processors to deal with potential threats in the environment (Lang, 1995; Öhman, 1997). The magnitude and latency of this primitive reflex has been shown to vary as a function of the motivationally relevant state of the individual prior to stimulus onset. That is, the blink reflex is stronger and its

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latency is shorter when the startle stimulus is presented to persons in a negative state (e.g., viewing unpleasant materials) relative to a positive or neutral state (e.g., viewing pleasant or neutral materials; Lang, Bradley, & Cuthbert, 1990). An accumulating body of research indicates that people evaluate most if not all encountered stimuli on a good or bad dimension (Osgood, Suci, & Tannenbaum, 1957), and that they do so immediately, and without intention or awareness (Bargh, 1997; Zajonc, 1998). For example, in a set of studies on the “automatic evaluation effect,” Bargh, Chaiken, Raymond, and Hymes (1996) used a subliminal presentation technique to prime participants with positively or negatively valenced words prior to a task in which they pronounced other positively or negatively valenced words as rapidly as possible. The subliminal presentation of any positively valenced word facilitated the speed of pronunciation of any other positively valenced word presented (and likewise for pairs of negatively valenced words), thereby demonstrating that participants processed the valence of the subliminally presented words even though there was no instrumental reason for doing so (Fazio, Sanbonmatsu, Powell, & Kardes, 1986). Although it is possible that immediate good or bad evaluations represent a form of automatic cognitive processing (Fiske, 1982), several theorists have suggested that such evaluations actually take place independent of the transformation processes typically implicated in cognition (Kuhl, 1986; LeDoux, 1987; Zajonc, 1980). Recent research has yielded supportive evidence, suggesting that the neural circuitry involved in the evaluative (good or bad) processing of stimuli is at least partially divergent from that involved in the perceptual (identification and discrimination) processing of stimuli (Crites & Cacioppo, 1996; LeDoux, Sakaguchi, & Reis, 1984; Murphy & Zajonc, 1993; Shizgal, 1999). Thus, automatic good or bad evaluations may be a direct response to stimuli, unmediated by any higher order cognitive processes. Automatic evaluation is presumed to instantaneously evoke approach and withdrawal behavioral predispositions. Over the years, a number of theorists from the emotion (Arnold, 1960; Frijda, 1986; Lang, 1984; Lazarus, 1991), motivation (Corwin, 1921; Lewin, 1935; Mowrer, 1960; Young, 1959), and attitude (Bogardus, 1931; Doob, 1947; Osgood, 1953; Thurstone, 1931) literatures have posited that the positive or negative evaluation of a stimulus is inherently linked to a tendency to move toward or away from the stimulus, respectively. Empirical data support this proposition. In a set of reaction time experiments, Chen and Bargh (1999) had

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participants either pull a lever toward them (an approachbased flexor reaction) or push a lever away from them (an avoidance-based extensor reaction) as quickly as possible when a positively or negatively valenced stimulus word appeared. Results indicated that participants reacted more quickly for positive than negative words when they were instructed to pull the lever toward them (the approach response), and more quickly for negative than positive words when they were instructed to push the lever away from them (the avoidance response; Cacioppo, Priester, & Berntson, 1993; Förster, Higgins, & Idson, 1998; Solorz, 1960). These results were obtained even when no mention was made of the evaluative content of the stimuli and when participants were not instructed to evaluate the stimuli in any way, prompting Bargh and Chartrand (1999) to conclude that automatic evaluation results in a behavioral predisposition toward or away from the stimulus “in a matter of milliseconds” (p. 475). It is important to highlight that the action disposition associated with automatic evaluation is a predisposition, not an overt behavioral response per se. Positively and negatively evaluated stimuli produce a physiological and somatic preparedness for approaching and withdrawing (Arnold, 1960), but observable behavior may or may not correspond to this initial behavioral readiness (Lang, Bradley, & Cuthbert, 1997). Actually, in lower organisms, and in constitutionally ingrained responses in humans, evaluation does lead directly and invariably to observable approach or withdrawal behaviors. In much human behavior, however, behavioral predispositions represent an initial input that may be overridden by other inputs generated by other approach- and avoidance-based mechanisms or processes prior to an actual behavioral response being enacted. For example, the sight of a tasty dessert stimulus may automatically evoke an approach tendency at the physiological and somatic levels, but a more deliberate consideration of one’s ever expanding waistline may lead to the overt act of pushing one’s chair away from the dinner table. Thus, in predicting observable behavior, particularly for complex organisms such as humans, with their flexible and creative self-regulatory repertoire (e.g., delay of gratification, impulse control, goal setting), one must consider the operation of multiple levels of approach and avoidance motivation (Cacioppo & Berntson, 1994), both at the same level of representation (Miller, 1944) and in hierarchical fashion (Elliot & Church, 1997). Indeed, in human behavior, approach and avoidance mechanisms and processes are multifarious, operating across the neuraxis from rudimentary reflexes to vaunted cortical processes (Berntson et al., 1993; Elliot & Thrash, 2002).

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This prevalence of approach and avoidance mechanisms and processes bespeaks the central role of approach and avoidance motivation in survival and adaptation. In sum, approach and avoidance motivation is manifest in and fundamental to all organisms, from protozoa to human beings. The greater the complexity of the organism, the greater the number and complexity of the approach–avoidance mechanisms and processes involved in the production and regulation of behavior. Given the fundamental nature of approach and avoidance motivation, and its ubiquitous presence in biological and psychological functioning, it seems reasonable to consider the approach–avoidance distinction an organizing principle in the study motivation (Berntson et al., 1993). That is, the approach–avoidance distinction may be seen as a unifying thread that can be applied to most, if not all, motivational concepts and constructs. As such, this distinction holds tremendous integrative, interpretive, and generative potential. The approach–avoidance distinction is certainly not sufficient to account for motivation, but it is necessary, and its broad and deep application is likely to yield much theoretical fruit.

DEFINITION AND CONCEPTUALIZATION At the beginning of this chapter, I offered the following definition of approach and avoidance motivation: Approach motivation may be defined as the energization of behavior by, or the direction of behavior toward, positive stimuli (objects, events, possibilities), whereas avoidance motivation may be defined as the energization of behavior by, or the direction of behavior away from, negative stimuli (objects, events, possibilities). It may be helpful to elaborate on several aspects of this definition, given the fact that approach–avoidance motivation is rarely defined in explicit fashion. First, being a motivational distinction, approach–avoidance encompasses both the energization and direction of behavior. Energization refers to the initial activation, instigation, or “spring to action” (James, 1890, p. 555) that orients the organism in a general way (Elliot, 1997). This energization may be very rudimentary, as in the amoeba’s evolutionarily engrained orienting away from bright light, or may be more complex, as in the human being’s dispositional tendency to orient toward an achievement task as a function of past socialization in competence-relevant settings. Importantly, this use of energization does not presume that the organism is passive until instigated to action; on the contrary, the organism is viewed as perpetually active, with instigation functionally representing a shift from one form of orienting to another (Atkinson & Birch,

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1970). Direction herein refers to the guiding or channeling of behavior in a precise way. This guiding and channeling is typically in the service of an activated desire or concern (Elliot & Thrash, 2001). Second, inherent in the approach–avoidance distinction is the concept of physical or psychological movement. Positively evaluated stimuli are associated with an approach orientation to bring or keep the stimulus close to the organism (literally or figuratively), whereas negatively evaluated stimuli are associated with an avoidance orientation to push or keep the stimulus away from the organism (literally or figuratively). As noted earlier, although positively and negatively evaluated stimuli produce (at minimum) a physiological and somatic preparedness for physical movement toward or away from the stimuli, respectively (Arnold, 1960; Corwin, 1921), this preparedness may or may not be translated directly into overt behavior. In advanced organisms, initial approach or avoidance inclinations may even be overridden or channeled in the opposite direction of the initial inclination (Elliot & Church, 1997). Third, implicit in the aforementioned point is the notion that movement toward a positive stimulus and movement away from a negative stimulus each has two distinguishable forms. “Movement toward” can represent getting something positive that is currently absent or it can represent keeping something positive that is currently present (functionally, continuing toward). Likewise, “movement away” can represent keeping away from something negative that is currently absent (functionally, continuing away from) or it can represent getting away from something negative that is currently present (for a conceptual parallel, Herzberg, 1966). Thus, approach motivation not only encompasses promoting new positive situations, but also maintaining and sustaining existing positive situations, and avoidance motivation not only encompasses preventing new negative situations, but also escaping from and rectifying existing negative situations. Fourth, positive or negative valence is construed as the conceptual core of the approach–avoidance distinction. A stimulus is positively or negatively evaluated by the organism, and this produces inclinations and efforts to approach or avoid the stimulus. “Positive” and “negative” are presumed to take on somewhat different meanings in different contexts, including beneficial/harmful, liked/disliked, and desirable/undesirable. Research indicates that these dimensions are conceptually and empirically comparable to a high degree, although some empirical work suggests that they may be separable in certain instances (Berridge, 1999). At present, given their substantial comparability, it seems best to construe beneficial/harmful, liked/disliked,

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and desirable/undesirable as functionally equivalent dimensions that may be subsumed under the positive/negative rubric (i.e., in essence, the three dimensions are conceptualized as indicators of a positive or negative latent variable). Nevertheless, it is possible that subsequent research will establish a need to distinguish among these dimensions in defining the approach–avoidance distinction. Fifth, “stimuli” as used herein may represent concrete, observable objects/events/possibilities, or they may represent abstract, internally generated representations of objects/events/possibilities. Furthermore, stimuli are meant to connote an essentially limitless, idiographic array of focal objects/events/possibilities.

TERMINOLOGICAL CONSIDERATIONS Many different terms and labels have been used over the years to cover the basic conceptual space that is covered by the definition of approach and avoidance motivation offered herein. Each of the different designations tends to be associated with a somewhat different emphasis. Three of the most common of these designations are considered in the following, in addition to approach–avoidance. Hedonism (i.e., pleasure–pain). Hedonism has been conceptualized in many different ways in the philosophical and psychological literatures. In philosophy, the ancient Greeks, such as the Epicureans, used the term quite broadly to refer to seeking the pleasures and avoiding the pains of both the mind and the body, whereas the British empiricists used the term more narrowly to refer to the pleasures and pains of bodily sensation (Boring, 1950; Cofer & Appley, 1964). In psychology, hedonism has typically been defined in a narrow sense in terms of bodily sensation and experienced affect (Franken, 1994; Young, 1961). Rozin (1999) has recently proposed a more inclusive view of hedonism, defining pleasure as “a positive experienced state that we seek and that we try to maintain or enhance” and pain as “a negative experienced state that we avoid and that we try to reduce or eliminate” (p. 112). This more inclusive view of hedonism is more akin to the conceptualization of approach–avoidance motivation herein than is the normative view of hedonism in the psychological literature. Rozin’s definition remains narrower than that presented herein, however, in that he uses the term “experienced” to refer to conscious experience, whereas nonconscious and even reflexive processes are included under the approach–avoidance rubric in the present definition. Approach–withdrawal. The approach–withdrawal distinction was introduced to the psychological literature

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by Schneirla (1959), a comparative psychologist. Schneirla argued that motivational analyses should be grounded in overt behavioral actions, so that they are applicable to lower as well as higher organisms. Thus, he conceptualized approach and withdrawal motivation in terms of observable behavior toward stimuli and away from stimuli, respectively (i.e., approach–withdrawal motivation and observable physical movement were considered isomorphic). Davidson and colleagues (Davidson, 1992; Sutton & Davidson, 1997; Tomarken, Davidson, Wheeler, & Doss, 1992) currently utilize the approach–withdrawal distinction in broader fashion to refer to action tendencies as well as overt action per se. Approach and withdrawal tendencies are presumed to be grounded in differential cortical activation. Approach tendencies are linked to activation of the left prefrontal cortex, whereas withdrawal tendencies are linked to activation of the right prefrontal cortex. These approach–withdrawal tendencies are posited to be the foundational dimensions of emotional experience. The conceptualization of approach– avoidance proffered herein is similar to Davidson and colleagues’ conceptualization of approach–withdrawal, in that approach–avoidance refers to action tendencies as well as overt action per se. However, their approach– withdrawal distinction is narrower than the approach– avoidance distinction espoused herein, in that approach–withdrawal focuses on the issue of energization at the biological level, whereas approach–avoidance herein covers both energization and direction, and is applicable to biologically based and psychologically based processes across the neuraxis. Appetite–aversion. The “appetite–aversion” distinction was coined by Craig (1918), who conceptualized appetites and aversions in terms of internal states of agitation (i.e., energization) accompanied by a readiness to “consume” the “appeted” stimulus or “get rid of” the “disturbing” stimulus (pp. 93–94). Craig focused primarily on physiological instincts in his theorizing, and considered basic reflexive mechanisms to be outside the purview of his appetite–aversion analysis (as did Tolman (1932) who explicitly embraced Craig’s distinction). In the contemporary literature, Lang and colleagues (Lang, 1995; Lang, Bradley, & Cuthbert, 1997) utilize the appetite–aversion distinction in their analysis of emotion and reflexive behavior. Emotion is characterized as a motivationally tuned state of action readiness, and two basic brain systems are posited to underlie emotion: appetitive (consummatory) and aversive (defensive). Reflexive behaviors are also characterized in terms of the appetitive–aversive distinction. In both instances, appetitive is meant to connote consummatory and approach

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oriented, whereas aversive is meant to connote defensive and avoidance oriented. More complex, “tactical” behavior is also thought to be organized in terms of this appetitive–aversive distinction, but little detail is offered in this regard (interestingly, approach–avoidance terminology per se is utilized when “tactical” behavior is [briefly] discussed; Lang, 1995, p. 373). The conceptualization of approach–avoidance offered herein is similar to Lang and colleagues’ conceptualization of appetitive–aversive in that the approach–avoidance distinction is viewed as applicable to reflexive behavior. Indeed, given Lang and colleagues’ incorporation of “tactical” behavior under the appetitive–aversive rubric, the two distinctions under consideration primarily differ in terms of emphasis. Reflexive behavior has been the central focus of the appetitive–aversive distinction, whereas it is simply one of many levels under consideration in the approach– avoidance distinction). Approach–avoidance. The approach–avoidance distinction emerged from Kurt Lewin’s work on Field Theory, specifically his conceptualization of the forces that accompany positive and negative valences. Lewin (1935) posited that stimuli have positive or attracting properties, or negative or repelling properties (i.e., valences) that are linked directly to tendencies to approach or avoid the stimuli. These positive and negative valences usually emerge from the organism’s needs, meaning that approach and avoidance tendencies are typically activated in the service of need satisfaction. Working within a Lewinian framework, Miller (1944) helped popularize the approach–avoidance distinction with his systematic experimental research on approach–avoidance conflicts. In fact, it is not Lewin, but Miller (1937), as well as Hovland (1937) and Sears (1937), who first used the term approach–avoidance in print (in the published proceedings of an American Psychological Association symposium on conflict chaired by Clark Hull). Although, in most of Miller’s experiments, approach and avoidance were operationalized in terms of movement toward or away from an object in physical space, Miller (1944), in accord with Lewin, explicitly stated that approach and avoidance are to be understood dynamically and functionally, not spatially (Dollard & Miller, 1950). That is, the experimental work on “spatial approach or avoidance” behavior (Miller, 1944, p. 432) was designed to be a simple, concrete analog of more complex, abstract motivational processes. McClelland and colleagues (McClelland, 1951; McClelland, Atkinson, Clark, & Lowell, 1953) were also instrumental in establishing the approach– avoidance distinction. These theorists focused primarily on approach and avoidance motives, characterized as

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dispositional preferences for acquiring positive, hoped for experiences or states (e.g., the motive for success) or for avoiding negative, feared experiences or states (e.g., the motive to avoid failure). However, they also noted that the distinction between approach and avoidance motivation was applicable at the level of unlearned, reflexive mechanisms as well as motives (McClelland et al., 1953). Like Lewin (and Miller), McClelland and colleagues clearly conceptualized the approach–avoidance distinction in terms of underlying valence-based processes, rather than observable behavior per se. In sum, it seems that the best way to cover the conceptual space under consideration is in broad fashion, and in terms of underlying motivational mechanisms and processes rather than observable behavior per se. The term “hedonism” has tended to represent a rather narrow set of psychological phenomena (i.e., sensory or affective), and the approach–withdrawal designation has typically been linked to an emphasis on physical movement as a direct indicator of motivation. Both of these terminological options seem unnecessarily restrictive. The designations “appetitive–aversive” and “approach–avoidance” have been proffered and used in highly similar fashion in the literature. Both of these designations are broadly applicable to all levels and degrees of complexity of valence-based mechanisms and processes, from the simple, constitutionally engrained instigation of fixed behavior in the singlecelled amoeba to the highly complex, multiply determined, flexible regulation of the human being. Thus, from a conceptual standpoint, either of these options would suffice. Approach–avoidance has been selected herein because it is the more widely recognized of the two designations in the motivational literature, and because it is the easier of the two options to intuitively understand (particularly for the newcomer to the literature).

OVERVIEW OF THE HANDBOOK OF APPROACH AND AVOIDANCE MOTIVATION The present volume is designed as a broad overview of research and theory on approach and avoidance motivation. Given the breadth of applicability of the approach– avoidance distinction, the breadth of the coverage in the handbook is substantial, encompassing a multitude of different constructs, levels of analysis, and disciplines. This breadth of coverage bears testimony to the foundational and pervasive importance of the approach–avoidance distinction in motivational accounts of behavior. The scholars who have provided chapters to the handbook are widely recognized as outstanding contributors in their area of expertise. This is truly a stellar lineup,

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and they have, without exception, written excellent, cutting edge, insightful chapters that individually and corporately do justice to the topic of approach–avoidance motivation. The first part of the Handbook is comprised of a single introductory chapter that provides an overview of the approach–avoidance motivational distinction. The second part grounds approach–avoidance in neurophysiology and neurobiology, covering a broad range of topics that include brain systems and mechanisms, cortical asymmetry, cortex-reflex connections, subcortical processes, neurotransmitters, hormones, and olfaction. Part three shifts to a variety of topics relevant to different types and levels of analysis, including basic personality dispositions (including traits and temperaments) in both human and nonhuman animals, the genetic basis of basic dispositions, domain-specific (i.e., achievement and social) motives and goals, and situation-specific motivational states. Part four focuses on the evaluative processes that make approach and avoidance such an integral aspect of motivated behavior; topics include the evolutionary basis of evaluation, the immediacy and automaticity of evaluation, the structure of evaluation, and asymmetries in evaluative processes. The fifth part of the Handbook covers emotion and wellbeing, including the structure of emotions, the function of emotions, distinct emotional experience, the specific emotion of anger, and the general concept of psychological well-being. The sixth part focuses on cognition, specifically the topics of challenge and threat appraisal, mental control, orienting and attentional processes, and the framing of information. Part seven encompasses various topics relevant to the self, specifically, self-regulation, selfesteem and the self-concept, self-knowledge, and access to the self. The eighth and final part of the handbook covers the area of social context, including culture, stereotyping, social comparison, social exclusion, and last but certainly not least, sexual behavior. Clearly much ground is covered in the handbook; this breadth of coverage nicely illustrates the widespread influence of the simple but powerful approach–avoidance distinction. Those new to this area will undoubtedly be astounded by how a seemingly simple distinction can be so enduring and generative. I believe that those who are seasoned veterans working in this area will also find much to learn in the pages herein.

ACKNOWLEDGMENTS Preparation of this chapter was facilitated by a grant from the William T. Grant Foundation (Grant #2565).


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Sutton, S. K., & Davidson, R. J. (1997). Prefrontal brain asymmetry: A biological substrate of the behavioral approach and inhibition systems. Psychological Science, 8, 204–210. Thorndike, E. (1911). Animal Intelligence. New York: Macmillan. Thurstone, L. L. (1931). Measurement of social attitudes. Journal of Abnormal and Social Psychology, 26, 249–269. Tomarken, A. J., Davidson, R. J., Wheeler, R. E., & Doss, R. C. (1992). Individual differences in anterior brain asymmetry and fundamental dimensions of emotion. Journal of Personality and Social Psychology, 62, 676–687. Tooby, J., & Cosmides, L. (1990). The past explains the present: Emotional adaptions and the structure of ancestral environments. Ethology and sociobiology, 11, 375–424. Tolman, E. (1925). Behaviorism and purpose. Journal of Philosophy, 22, 35–41. Tolman, E. (1932). Purposive behavior in animals and men. New York: The Century. Verbeek, M., Drent, P., & Wiepkema, P. (1994). Consistent individual differences in early exploratory behavior of male great tits. Animal Behavior, 48, 1113–1121. Watson, S., & Ward, J. (1996). Temperament and problem solving in the small-eared bushbaby (Otolemur



garnettii). Journal of Comparative Psychology, 110, 377–385. Wilson, D., Clark, A., Coleman, K., & Dearstyne, T. (1994). Shyness and boldness in humans and other animals. Trends in Ecology and Evolution, 9, 442–446. Wilson, D., Coleman, K., Clark, A., & Biederman, L. (1993). Shy-bold continuum in pumpkinseed sunfish (Lepomis gibbosus): An ecological study of a psychological trait. Journal of Comparative Psychology, 107, 250–260. Wundt, W. (1887). Grundzüge der physiologishen psychologie, (3rd ed.), Leipzig: Engelmann. Young, P. (1959). The role of affective processes in learning and motivation. Psychological Review, 66, 104–125. Young, R. K. (1961). Motivation and emotion: A survey of the determinants of human and animal activity. New York: Wiley. Zajonc, R. B. (1980). Feeling and thinking: Preferences need no inferences. American Psychologist, 35, 151–175. Zajonc, R. B. (1984). On the primacy of affect. American Psychologist, 39, 117–123. Zajonc, R. B. (1998). Emotion. In D. Gilbert, S. Fiske, & G. Lindzey (Eds.), The handbook of social psychology, (4th ed., pp. 591–632). New York: McGraw-Hill.

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Part II Neurophysiology and Neurobiology

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Brain Systems and Mechanisms Processing 2 Emotional and Motivation: In Search of Brain Mechanisms Christopher K. Cain and Joseph E. LeDoux CONTENTS Developing a Framework ........................................................................................................................ 18 Tools for Studying Brain Mechanisms of Behavior ................................................................................19 Lesions ................................................................................................................................................19 Local Pharmacology...........................................................................................................................19 Genetic Manipulations .......................................................................................................................19 Neural Activity ...................................................................................................................................19 Avoidance Motivation .............................................................................................................................20 Behavioral Paradigms for Studying Avoidance Motivation ...............................................................20 Classical Fear Conditioning ..........................................................................................................20 Instrumental Conditioning and EFF Learning ..............................................................................21 Brain Mechanisms Related to Avoidance Motivation ........................................................................22 Classical Fear Conditioning ..........................................................................................................23 Escape From Fear ..........................................................................................................................25 Approach Motivation...............................................................................................................................26 Behavioral Paradigms Related to Approach Motivation ....................................................................26 Conditioned Approach ...................................................................................................................26 Conditioned Potentiation of Feeding .............................................................................................26 Pavlovian to Instrumental Transfer ...............................................................................................27 Brain Mechanisms Related to Approach Motivation .........................................................................27 Conditioned Approach ...................................................................................................................27 Conditioned Potentiation of Feeding .............................................................................................28 Pavlovian to Instrumental Transfer ...............................................................................................28 A Motive Circuit? ....................................................................................................................................28 Summary and Conclusion .......................................................................................................................30 References ...............................................................................................................................................30

Emotion and motivation are deeply intertwined (LeDoux, 2002b). The stimuli that trigger us to react emotionally also motivate us to act. In this chapter we discuss brain interactions between emotion and motivation in escape

behavior, a form of avoidance conditioning, using the vast base of knowledge that has been obtained about emotional processing through studies of fear conditioning. We next discuss appetitive conditioning and approach 17


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motivation in a similar fashion. We conclude with an integrated view of the brain mechanisms of avoidance and approach motivation. The final picture is far from complete, since much remains unknown. However, we hope to show that research on the brain mechanisms of avoidance and approach has solved different parts of similar puzzles. Considering the two together reveals a coherent view of the underlying circuitry and suggests a strategy for advancing our understanding of motivational processing by the brain.

DEVELOPING A FRAMEWORK How does a neuroscientist interested in the details of brain function approach the study of emotion and motivation? Consider the following scenario. A child at the playground encounters a dog. At first he freezes in his tracks, but after a few seconds he runs behind his mother for protection. If we want to understand this behavior we could ask him what he was feeling during the experience and why he behaved as he did. He may respond that he is afraid of dogs and ran away to avoid being bitten. Assuming that we could trust his verbal report, which we should not (Larsen & Fredrickson, 1999), it is still very difficult to study the brain mechanisms of human subjective experiences like feelings (emotion) and wants and needs (motivation). Imaging techniques like fMRI are rapidly advancing, but even this technique reveals little about the precise workings of neurons and molecules in the brain. The techniques required to study detailed mechanisms of brain function, discussed below, usually cannot be used with humans for ethical and practical reasons. Animal research allows for use of these techniques, but it is unlikely that human subjective experiences are the same in lower species (LeDoux, 2002c). Even if they were, procuring a verbal report from a rat is not possible. The strategy employed in our laboratory builds upon a distinction between emotions and feelings (Damasio, 1994; LeDoux, 1984). Emotions are states automatically elicited by significant stimuli. Stimuli associated with food, sexual reproduction, predatory defense, thermoregulation, and pain are some examples. Feelings, on the other hand, are cognitive representations of emotions. All animals have the capacity to detect and respond to significant stimuli independent of their higher cognitive capacities. For this reason, we focus on emotional responses and make no assumptions about conscious feelings that may accompany these responses, even though feelings may have an important impact on human behavior. The predatory defense, or fear, system has been a particularly useful model for exploring questions about



emotional processing. Stimuli associated with predators elicit defensive responses adaptive for the organism. By examining how the brain processes information about innate and learned fear stimuli, and how it generates specific defensive responses on the basis of this processing, the defense circuitry is being mapped. In this sense, emotion can be thought of as the process by which the brain computes the value of a stimulus for the purpose of responding adaptively. However, the same responses that are adaptive in some situations can become maladaptive when they are activated by stimuli that are not dangerous, or when activated in a recurring and prolonged way that exceeds the requirements of the situation. Returning to our example above, note that when the child encountered the fear-eliciting stimulus (the dog) he first froze in his tracks and then fled. This is a common theme with emotional behaviors. Emotional stimuli have the capacity to both elicit emotional reactions (such as freezing) and to enable emotional actions (such as flight), often in that order. Thus, the emotional processing of sensory information in the fear system elicits defensive reactions, and this processing also motivates active responses that minimize exposure to the threat. The former is usually referred to as fear, and the latter as escape or avoidance. In the introductory chapter of this book, Elliot (2006) defined avoidance motivation as “the energization of behavior by, or the direction of behavior away from, negative stimuli.” This is indeed a useful starting point. We would like to extend this view. We propose that “energization” occurs when the brain’s fear system is activated by a threatening stimulus. This energization is both general (nonspecific arousal systems, such as monoamine containing networks, are activated) and specific (fear responses, such as freezing behavior and associated visceral responses, are elicited). The “direction of behavior away from” the threatening stimulus also reflects the activation of the fear system. In this case, the fear system leads to the activation of motivational circuits that initiate goal-directed behavior. Using this framework we have investigated brain mechanisms mediating fear and avoidance motivation with two specific behavioral protocols: classical fear conditioning and instrumental escape from fear (EFF) learning. Classical fear conditioning studies have demonstrated how the brain mediates the learning of an emotional association between a neutral conditioned stimulus (CS) and an aversive unconditioned stimulus (US), and how the CS subsequently arouses the brain and elicits “passive” conditioned responses (CRs). EFF studies, on the other hand, are beginning to shed light on how the CS can then serve as a motivating factor to initiate active

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Emotional Processing and Motivation: In Search of Brain Mechanisms

responses that reduce exposure to the fear arousing stimulus.

TOOLS FOR STUDYING BRAIN MECHANISMS OF BEHAVIOR The field of neuroscience has a wide arsenal of tools available for studying the neural basis of behavior. Some of these are traditional techniques, such as the lesion method, whereas others have only emerged in recent years, such as the creation of genetically engineered animals that allow studies of the molecular basis of behavior. In order to facilitate the discussion of brain mechanisms later in the chapter, we give a brief summary of common techniques.

LESIONS Brain lesions have been widely used to investigate the functions of specific brain regions. In a typical learning experiment, a region of interest is damaged and behavior is assessed. Damage is usually induced by passing positive current through an electrode (electrolytic lesion) or by infusing a small volume of chemical into the region (excitotoxic lesion). The timing of the lesion relative to learning can further distinguish the brain region’s role in the learning and memory process. For instance, lesions before training can implicate a region in learning, while postlearning lesions can implicate a region in memory storage or recall mechanism (Rodrigues, Schafe, & LeDoux, 2004). Electrolytic lesions are perhaps the simplest technique and offer the greatest control over the spatial extent of damage; however, electrolytic lesions also destroy fibers of passage and cannot be used to firmly attribute function to cell bodies in the lesioned region (Koo, Han, & Kim, 2004). Excitotoxic lesions destroy cell bodies in the infused region and spare fibers of passage; however, controlling the extent of damage is difficult given the unpredictable diffusion patterns of infused liquids. “Disconnection” experiments are emerging as a clever and useful technique for studying the functional role of connections between two regions (LeDoux, Sakaguchi, Iwata, & Reis, 1986; Parkinson, Willoughby, Robbins, & Everitt, 2000b). In a classic disconnection experiment, asymmetrical unilateral lesions are produced leaving one intact nucleus type in each hemisphere of the brain. As long as unilateral lesions of either nucleus alone do not affect the behavior of interest, this technique implicates the interactivity of two nuclei in a brain process (Everitt & Robbins, 1992).


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LOCAL PHARMACOLOGY A related but less severe technique involves temporarily inactivating cells within a region prior to a particular phase of testing. This is achieved by infusing a chemical agent, via stereotaxically implanted cannulae, directly into a brain region. Muscimol, a GABAA-receptor agonist, is perhaps the most commonly used inactivating agent (Blair, Sotres-Bayon, Moita, & LeDoux, 2005). In addition to sparing transmission in fibers of passage, temporary inactivation preserves the integrity of the brain region for subsequent phases of testing and allows for greater temporal resolution. However, inactivation also has some drawbacks. For instance, it is difficult to control the diffusion of the chemical agent and to restrict inactivation to the region of interest. If nearby structures are necessary for some aspect of the task, then inactivation may prove difficult. Using a technique identical to inactivation, very small volumes of pharmacological agents can be infused into a specific brain region to implicate molecules in a particular behavior. The timing of the infusion relative to the stage of behavioral training can provide insight into whether a molecule in that region participates in learning, short-term memory (STM), long-term memory (LTM), or other nonspecific processes (Rodrigues et al., 2004). Of course, local pharmacology is also imperfect in that infused drugs can affect adjacent regions.

GENETIC MANIPULATIONS The use of genetic manipulations to investigate the role of brain site-specific molecules is rapidly advancing, but is still imperfect. Knockout and transgenic mice are very useful for implicating a specific molecule in brain processing, although the majority of these manipulations are global (whole brain), or at least affect large portions of the brain (e.g., forebrain specific knockouts), and present at birth (often resulting in unwanted compensation by other molecules). More recently, researchers have taken to directly infusing constructs to manipulate gene expression in a site- and time-specific manner. The early results are promising and such techniques are likely to be used more often in the future (Rumpel, LeDoux, Zador, & Malinow, 2005).

NEURAL ACTIVITY Rather than impairing a brain region to deduce its role in a particular behavioral process, it is also useful to record normal neural activity during the task. Multichannel

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single unit recordings have been widely and successfully used for this purpose (Schoenbaum, Setlow, & Ramus, 2003). Electrodes are chronically implanted allowing for the online recording of both field potentials and action potential activity in isolated neural units. By comparing spike frequency changes with different task phases or different behaviors one can begin to decipher whether neurons in a region participate in task-related sensory processes, motor processes, timing processes, or even plastic learning processes. Such techniques have been successfully used in the study of amygdala-dependent (Goosens & Maren, 2004) and striatum-dependent learning (Nicola, Yun, Wakabayashi, & Fields, 2004). One particularly useful aspect of single unit recording is that temporal components of recorded spike trains can encode an experience with a high degree of precision (Quirk, Armony, & LeDoux, 1997). Thus, spike timing information recorded from different structures during the same task can be used to track information flow through a particular circuit. Immediate early gene (IEG) expression is another method for mapping the neural circuitry related to specific behavioral tasks. Some common examples of IEGs used for mapping include cFOS, Arc, and Homer 1a. These genes are transcribed in response to heightened neural activity and have distinguishable patterns of mRNA expression. For instance, Arc expression can be seen in the nucleus 2–10 min after neural activity and dissipates by 20 min. Homer 1a, on the other hand, takes 25–30 min to be expressed in the nucleus after activation. Thus, one can distinguish between brain regions involved in specific behaviors by eliciting the behaviors with a 25 min separation and then examining differential IEG expression (Petrovich, Holland, & Gallagher, 2005). IEG expression studies can be a powerful tool for implicating brain regions in specific behaviors and may complement electrophysiological studies.

AVOIDANCE MOTIVATION The concept of avoidance motivation arose to explain why animals and people move away from, either physically or psychologically, certain environmental stimuli. Our natural inclination as introspective beings is to invoke some subjective state to explain why we, or other animals, avoid certain stimuli and situations. However, just as we defined emotions independent of conscious feelings, we also define motivations independent of conscious states. Motivations, in this view, reflect the activation, via emotional processing, of brain systems involved in goaldirected behavior. Avoidance motivation, specifically, can be defined in terms of brain processes that prevent



exposure or facilitate the removal of the organism from fear arousing stimuli. This is not to say that conscious factors never enter into motivation. But when we study motivation in rodents or other animals, it seems unnecessary, and in fact, counterproductive, to introduce conscious states as explanatory factors since the existence of consciousness in such creatures cannot be proven.

BEHAVIORAL PARADIGMS FOR STUDYING AVOIDANCE MOTIVATION The following paragraphs focus on two research areas that are commonly studied in relation to avoidance motivation: classical conditioning and instrumental escape conditioning. However, it is important to note that there are a wide range of behavioral paradigms that fall under the umbrella of “avoidance motivation.” For instance, animals will avoid situations that lead to the omission of reward (Papini, 2003) or the presentation of punishment (Bolles, 1967a). Interested readers are referred to the following works for further information regarding these, and other, avoidance behavioral paradigms (Brush, 1971; Denny, 1991; Reilly & Bornovalova, 2005). Classical Fear Conditioning Classical fear conditioning is a simple learning paradigm based on Pavlov’s seminal work with dogs (Pavlov, 1927). Fear conditioning has been intensely studied by psychologists and neuroscientists because of its simplicity and its relevance to human learning and anxiety (Blanchard & Blanchard, 1969b; Bolles & Fanselow, 1980; Davis, Walker, & Myers, 2003; Fanselow & Gale, 2003; LeDoux, 2000; Rescorla, 1988; Seligman, 1971). This focus has been fruitful, and we now have a good understanding of how the brain mediates this emotional behavior. In a typical fear conditioning experiment, rodents are presented with an emotionally neutral CS, often a tone, that is paired in time with an aversive footshock US. Prior to the pairing, subjects exhibit no defensive responses to the tone. After pairing, tone presentations elicit a cassette of defensive responses including freezing (Blanchard and Blanchard, 1969a), autonomic reactions (Schneiderman, Francis, Sampson, & Schwaber, 1974), neuroendocrine responses (Mason, Mangan, Brady, Conrad, & Rioch, 1961), and potentiation of somatic reflexes such as startle (Davis, 1986). Collectively these CS-elicited learned responses are referred to as conditioned fear responses. Fear responses elicited by the CS after pairing with the US indicate that associative learning took place during conditioning, provided that similar responses fail to occur when the CS and US are unpaired during training (Rescorla, 1967). Conditioned fear responses can last for

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the lifetime of the animal (Gale et al., 2004). Fear conditioning also establishes the CS as secondary incentive that can motivate avoidance behaviors (discussed below). Instrumental Conditioning and EFF Learning For many decades following Pavlov’s work, conditioned fear (Mowrer & Lamoreaux, 1946; Solomon & Wynne, 1954; Bolles, 1969) and its neural basis (Sarter & Markowitsch, 1985) were commonly studied with avoidance protocols. We focus here on signaled active avoidance, although there are many procedural variations on this theme, such as passive avoidance (Blanchard & Blanchard, 1970) and Sidman avoidance (Sidman, 1953). In a typical active avoidance experiment, rats are presented with toneshock pairings on one side of a two-compartment chamber. Movement to the opposite side terminates the tone and prevents the shock presentation. These avoidance responses (Ras) serve as the dependent measure of fear learning and animals exhibit Ras more frequently and with shorter latencies as training progresses. However, avoidance proved to be a difficult paradigm for the analysis and explanation of learning mechanisms. First, learning occurs on trials where the animal successfully avoids shock, and it was difficult to explain how absence of a US could reinforce a response. Second, researchers realized that avoidance was actually a complex learning process where animals first learned that the tone predicted shock, and then learned to escape the tone and prevent shock delivery. Two-factor theory arose hypothesizing that avoidance conditioning involves both classical fear conditioning and instrumental response conditioning (Miller, 1948; Mowrer, 1947). In the almost 80 years since the emergence of two-factor theory, researchers have heatedly debated the contents (i.e., S-S, S-R, or R-S), conditions (Pavlovian operations, instrumental operations, or both) and mechanisms (drives, perceptions, etc.) of avoidance conditioning. However, one idea was proposed early and remains a viable possibility today, escape from fear (EFF) (for review see Levis, 1989). EFF learning was proposed to explain how classical conditioning and instrumental conditioning could interact to mediate active avoidance. The basic idea is that classical conditioning first establishes fear of the CS. Then on later trials, active responding is reinforced by fear reduction associated with CS-termination. Another way to say this is that the response is instrumental in leading to the reinforcement: fear reduction. Formally, this sort of learning is called conditioned negative reinforcement of a stimulus–response association. Importantly, expression of EFF learning is also believed to be motivated by fear. As training progresses, escape responding is motivated by fear of the CS and reinforced by CS-termination. Thus, EFF learning may be an ideal paradigm for studying how


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fear processing can lead to the reinforcement and motivation of active instrumental responses. A major benefit of adopting this strategy is that the neural mechanisms of classical fear conditioning have largely been worked out giving us a firm foundation to examine aversive motivation and instrumental learning. Despite the promise and simplicity of EFF, it has itself been the subject of considerable controversy over the years (Bolles, 1970; Levis, 1989; McAllister & McAllister, 1991). The main reason is that some researchers have had trouble reliably reproducing EFF learning (independent of avoidance conditioning) in the laboratory. Many have reported successful EFF learning, but failures to obtain EFF learning are also common (see Cain & LeDoux, 2007 for a complete list of references) and may be underreported. We recently conducted an extensive behavioral examination of EFF, using rearing as the escape response, in order to address reasons for the controversy and to suggest procedural improvements (Cain & LeDoux, 2007). We found that EFF training led to a twofold increase in CSevoked rearing relative to yoked control animals (Figure 2.1A and B). This learning was long lasting (24 h) and response specific (no increase in other nonreinforced behaviors). Interestingly, successful EFF learning also resulted in a transition from passive freezing reactions to active escaping; rats that learned the EFF response showed no spontaneous recovery of freezing following the extinguishing CS presentations used for EFF training (Figure 2.1D). Importantly, expression of EFF learning was also motivated by fear of the CS; animals that went through EFF training did not rear differently than yoked controls until the CS was presented. Thus, our data lead us to conclude that instrumental escape responses can be reinforced by CS termination and be motivated by fear. Any discussion of emotional motivation would be incomplete without mention of drives and incentives. Hull’s drive theory (Hull, 1943) was devised to explain how new habits are learned and repeated. According to Hull, stimulus–response associations are formed because the stimulus evokes a drive, like hunger or pain, and the response results in reduction of that drive. Since not all motivating stimuli are innately motivating, studies on EFF learning expanded the notion of drive theory to include “acquired drives” (Miller, 1948). However, drive theory in its initial form was eventually replaced by incentive theory because of a number of problems. One such problem is that rats will work to obtain sweet-tasting saccharin even though it has no nutritive value and therefore cannot result in reduction of the hunger drive. Incentive theories discard hypothetical drive states and instead assume that external stimuli motivate behavior because they arouse emotion. Bolles (1967b) explained the difference by suggesting that

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FIGURE 2.1 Escape from fear (EFF) learning represents instrumental learning that is motivated by fear and reinforced by fear reduction. One day after Pavlovian tone-shock pairings, rats were presented with 25 tone-alone presentations in a novel context (EFF training, left). For paired-EFF rats, rearing during a tone presentation led to its immediate termination (response–reinforcement pairing). Paired-yoked rats received identical tone presentations independent of their behavior. One day after EFF training, rats were presented with a single, continuous 10 min tone presentation to assess long-term EFF memory (EFF test, right). Rearing and freezing were assessed during both phases. Paired-EFF rats showed a twofold increase in the EFF escape response (rearing) during the training and testing session compared to paired-yoked rats (A and B). Unpaired-EFF rats had no fear of the conditioned stimulus (CS) and did not acquire the EFF response (enhanced rearing). Successful acquisition of this active escape response was also associated with less passive freezing to the tone (C and D). Further analysis demonstrated that EFF learning was responsespecific and performance was motivated by fear (no difference in rearing in the absence of the CS; data not shown). From “Escape from fear: A detailed behavioral analysis of two atypical responses reinforced by CS-termination,” by C. K. Cain and J. E. LeDoux, 2007, Journal of Experimental Psychology: Animal Behavior Processes 33, p. 455. Adapted with permission.

“drives push while incentives pull.” For the purpose of studying brain mechanisms of emotion and motivation, we will assume that incentives do their work not by arousing subjective emotions, but rather by activating neuronal processing in specific brain regions. This activation reflects a brain state where performance of an instrumental response is a highly probable outcome.


BRAIN MECHANISMS RELATED TO AVOIDANCE MOTIVATION Using the tools outlined in “Tools for Studying Brain Mechanisms of Behavior” of this chapter, a great deal of progress has been made in understanding the brain mechanisms of avoidance motivation. Research on classical

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fear conditioning has been especially successful at delineating the anatomical, cellular, and molecular mechanisms of avoidance reactions (e.g., freezing). Although research regarding the brain mechanisms of instrumental escape or avoidance (fear-related actions) has lagged behind, we outline a strategy with the potential for rapid progress using our knowledge of fear conditioning mechanisms as a foundation. However, as we will discuss in “Approach Motivation,” findings from approach motivation research may provide an excellent guide for dissecting avoidance motivation at the systems level. Classical Fear Conditioning Neural circuits. Considerable evidence suggests that the amygdala is critical for learning, storage, and expression of fear conditioning (LeDoux, 2000; Pare, Quirk, & LeDoux, 2004). The amygdala is composed of a dozen or so nuclei (Pitkänen, Savander, & LeDoux, 1997). Fear conditioning research has focused primarily on three of these: the lateral nucleus (LA), central nucleus (CE), and basal nucleus (B). Neurons in the LA receive auditory (CS) and somatosensory (US) inputs from thalamic and cortical processing regions (LeDoux, 1990; Mascagni, McDonald, & Coleman, 1993; McDonald, 1998; Romanski, LeDoux, Clugnet, & Bordi, 1993). Tone signals arrive in the LA as early as 12 ms following stimulus onset and the same neurons receive shock inputs (Bordi & LeDoux, 1994a,b; Clugnet, LeDoux, & Morrison, 1990; Romanski et al., 1993). LA neurons in turn connect with CE both directly and indirectly via projections to B (Pare & Smith, 1998; Pitkänen et al., 1997). The LA appears to be critical for the acquisition and storage of fear conditioning. Both electrolytic and excitotoxic lesions of the LA prevent acquisition and expression of fear conditioning (Amorapanth, LeDoux, & Nader, 2000; Campeau & Davis, 1995; Gale et al., 2004; LeDoux, 1990). Further, temporary inactivation of the LA with muscimol prevents CS-elicited freezing when given before training or testing, but not if given immediately after training (Muller, Corodimas, Fridel, & LeDoux, 1997; Wilensky, Schafe, & LeDoux, 1999). CE, via its projections to the hypothalamus and brainstem (Bellgowan & Helmstetter, 1996; Davis, 1998; De Oca, DeCola, Maren, & Fanselow, 1998; LeDoux, Iwata, Cicchetti, & Reis, 1988), appears to mediate the expression of conditioned fear (Amorapanth et al., 2000; Goosens & Maren, 2001; Hitchcock, & Davis, 1986; Kapp, Whalen, Supple, & Pascoe, 1992; but see Koo et al., 2004). The role of B in fear conditioning is somewhat controversial at present. Pretraining lesions of B have no effect on learning or expression (Amorapanth


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et al.; Goosens & Maren, 2001; Nader, Majidishad, Amorapanth, & LeDoux, 2001; Sotres-Bayon, Bush, & LeDoux, 2004), but a recent study indicates that posttraining lesions impair expression of learning (AngladaFigueroa & Quirk, 2005). This suggests that B is not required for learning or expression of fear conditioning, but may participate in one or both of these processes under normal circumstances. Taken together, anatomic, lesion, and inactivation studies strongly suggest that LA participates in the learning and storage of fear conditioning while the B and CE participate at least in fear expression. Notably, LA manipulations that impair fear conditioning do not alter tone or shock sensitivity, the ability to freeze, or even nonassociative learning processes such as shock-induced sensitization (Fanselow & LeDoux, 1999). Thus, the LA appears to be selectively involved in associative learning about emotionally significant stimuli. Synaptic plasticity. Short latency ( BP /Cyou > 1/2: If WTR = 1/2, P takes action. If WTR = 1, P does not

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FIGURE 15.2 An actor’s welfare trade-off ratio (WTR) toward you can be inferred by observing how large a cost that individual is willing to impose on you for how small a benefit gained. The gray line represents a WTR of 1, meaning that the actor values your welfare as heavily as his or her own. The black dashed line represents a WTR of ½, meaning the actor values your welfare only half as much as his or her own. The area between these two lines represents the set of cost-imposing actions an actor would take if his or her WTR toward you were ½, but not if it were 1. Raising an individual’s WTR toward you allows you to avoid these costs.

it provides to P (BP)—that is, P will refrain when BP/Cyou < 1. But if P’s WTR toward you is ½, P values your welfare only half as much as his own; that is, P will take actions for which BP/Cyou > ½. This means there is a set of cost-imposing actions, ones for which ½ < BP/Cyou < 1, that P will take when his WTRyou = ½, but not when his WTRyou = 1 (see Figure 15.2). You will be spared more of these costs to the extent there is some way of raising P’s WTR toward you. But why should P raise his WTR toward you, when this reduces the set of self-beneficial actions that he will be willing to take? Humans, unlike most species, engage in many forms of cooperation: dyadic reciprocation (Cosmides & Tooby, 2005; Gurven, 2004; Trivers, 1971), coalitional (group) cooperation (Tooby et al., 2006), food sharing as a form of risk pooling (Kaplan & Hill, 1985), and deep engagement relationships (Tooby & Cosmides, 1996). If P does not raise his WTR toward you—that is, if he does not treat you better—then he may lose you as a cooperative partner. If you are a good and reliable reciprocator, for example, then P benefits from having you as a cooperative partner. If your motivational system is designed to make your level of cooperation contingent on how well P treats you, then P might be able to increase your level of cooperation by treating you better, by raising P’s own WTRyou. But P pays a price by increasing his WTRyou: A higher WTRyou means P will be sacrificing his own

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welfare more often for you, and refraining from a larger set of self-beneficial actions. So what price, in the form of a higher WTRyou, should P be willing to pay to maintain or increase your cooperation toward him? There is an equilibrium WTR value, at which the marginal increase in price P would pay, in the form of a higher WTRyou, is exactly offset by the marginal increase in benefits P would gain by doing so, through increased cooperation from you. If P’s WTR toward you is below this equilibrium value, the marginal decrease in your cooperation that this elicits will make P worse off than he could be. When this is true, there is the possibility of raising P’s WTR toward you. By threatening to lower your level of cooperation with P—or even withdraw it by switching to a partner who values your welfare more highly (i.e., whose WTR toward you is higher)—it should be possible to raise P’s WTRyou to a value closer to P’s equilibrium point. Another reason P might raise his WTR toward you is that you will inflict costs on him if he does not. Like most other species, humans sometimes use aggression to induce others to sacrifice their own welfare for the aggressor’s. Using variables such as the relative value of a resource to two contestants and their relative fighting ability, game theoretic models such as the Asymmetric War of Attrition (AWA) specify conditions under which a contestant should cede a resource or fight for it (Hammerstein & Parker, 1982; Maynard Smith, & Parker, 1976). The

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Internal Regulatory Variables and the Design of Human Motivation

AWA predicts that, if Y does not relinquish a resource, X will fight Y when v(X)/v(Y) > k(X)/k(Y), that is, when the relative value (v) of the resource to X exceeds the relative costs (k) that X will incur by fighting Y. More specifically, k(X) is the rate at which X will incur injuries if a fight between X and Y ensues, which is a function of their relative fighting ability. Behavior consistent with the AWA requires programs that compute one’s formidability relative to others, and use this information to adaptively regulate responses to resource conflict. For example, if you and person P value a resource equally and both of you know that P is more aggressively formidable than you are, the AWA predicts that P will try to take the resource and you will relinquish it rather than risk injury in a fight. This means that, all else equal, more formidable individuals will be more willing to initiate resource contests than less formidable ones, and less formidable individuals will defer to these demands. If cooperation (and so forth), is not an issue, then there is an equilibrium WTR value toward you, based on your formidability relative to P, where the benefits to P of getting or keeping a resource of value VP are exactly offset by the costs P will suffer by fighting you for it. If P’s current WTR toward you is below this equilibrium value, there is the possibility of raising it by threatening to aggress against P. Dominance hierarchies in species lacking cooperation are the result of such negotiations. In the absence of any contested resource, individual animals aggressively display toward one another, assessing who can hurt whom. Having determined this, injurious fights become unnecessary: Weaker individuals cede resources to stronger ones, whenever the relative value of the resource to the weaker one is less than the value of a regulatory variable expressing their relative formidability. The AWA, Hamilton’s rule, and reciprocal altruism theory each express how selection should shape an equilibrium WTR based on a single factor (formidability, genetic relatedness, or value as a reciprocator, respectively). But humans engage in cooperation as well as aggression, and we live in the presence of kin as well as nonkin. This should select for a welfare trade-off ratio estimator equipped with algorithms that compute equilibrium WTRs based on the values of several different regulatory variables: ones expressing an individual’s value as a reciprocator, coalition mate, sexual partner, and friend, as well as the kinship index associated with that individual and a variable expressing that individual’s formidability relative to one’s own. Indeed, your welfare trade-off ratio estimator should be designed by selection

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to compute two sets of WTRs: the WTRs that should regulate your behavior toward others, and the equilibrium WTRs that others should express toward you. If P knows that you will not respond by threatening to withdraw benefits or inflict costs, then P can benefit by having a WTR toward you that is lower than the equilibrium value would be if you were to respond. What can raise P’s WTRyou nearer to the equilibrium value is your ability to monitor P’s actions to see what WTRyou they express, and respond. Anger, we propose, is the activation of a response system designed to negotiate the value of the offending person’s WTR toward you. We call this proposal the recalibrational theory of anger (Sell, 2005; Sell, Tooby, & Cosmides, in prep. a, b).

ANGER AS A NEGOTIATION OVER WTR VALUES Social behavior publicly advertises WTRs. Given the ability to estimate the consequences of actions on welfare—the costs and benefits they impose on oneself and others—one can infer one person’s WTR toward another from his or her actions. For example, assume that you observe a person named Aaron taking an action that inflicts a cost of 4 (notional) units on you to gain a benefit of 1 unit for himself. From this, you can infer that Aaron’s WTRyou ≤ ¼. (BAaron/Cyou = ¼; Equation 15.1 means Aaron would take this action only if BAaron/Cyou ≥ WTRyou.) Most theories of anger recognize that humans typically get angry when someone imposes a cost on them; and, all else equal, the larger the cost, the more angry the person becomes. But the recalibrational theory of anger further predicts that being harmed will not be sufficient to trigger anger. If anger is the expression of a system designed to negotiate WTRs, then it should be triggered when the offending person’s action expresses a WTRyou that is too low—below what you feel entitled to or, more specifically, below what your WTR estimator has computed as the appropriate equilibrium value. (Thus, humans may become angry when they are benefited—but less than they feel entitled to.) This leads to a counterintuitive prediction: Holding the cost imposed constant, more anger will be triggered when the offending person imposed that cost to gain a small benefit than to gain a large one. Assume that your WTR estimator has computed, based on the nature of your relationship, that Aaron’s equilibrium WTR toward you should be ½. You then see him ruin your expensive scarf, imposing a cost of 4 units on you. According to the recalibrational framework, whether you become angry should depend on how much Aaron benefited by using your scarf. If the benefit he got

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was only 1 unit—let us say Aaron ruined your scarf by using it to wipe ketchup off his face—then this action expresses a WTRyou ≤ ¼. This is less than the equilibrium value of ½, and so should trigger anger. But if Aaron ruined your scarf while using it to make a tourniquet to stop blood spurting from his child’s arm, then the benefit he got was great—e.g., 24 units. This action should not trigger anger in you, despite the fact that it inflicts the same cost: In this case, Aaron’s action is still consistent with a WTRyou of ½. Indeed, the benefit to Aaron relative to the cost to you is consistent with Aaron having a WTR toward you as high as six (BAaron/Cyou = 24/4 = 6). This means that Aaron would have taken this action even if his WTRyou was very high—even if he valued your welfare almost six times as much as his own. The anger system should not be activated under such circumstances, because the events do not reveal a WTR that needs to be recalibrated. With these predictions in mind, we conducted experiments that held the cost imposed on the subject constant, while varying the size of the benefit the offending individual expected to gain by imposing it. Learning that the offending action was taken to procure a large monetary benefit made subjects less angry; learning that it was taken to procure a small one made them more angry (Sell, 2005; Sell, Tooby, & Cosmides, in prep. a). According to the recalibrational theory of anger, the program monitoring WTRs is activated when someone imposes a cost on you (or fails to provide an expected benefit). If the detection component inside the anger program infers that this person’s monitored WTRyou is below an estimate of the appropriate equilibrium value, then the anger system is triggered. The detection system sends an “anger signal” that regulates two downstream motivational systems as negotiative tools—one regulating cooperation, the other regulating aggression. The Anger Program Orchestrating Cooperation Assume, for this example, that Aaron is a cooperative partner of yours—a friend or colleague—and you observe him taking an action that imposes a large cost on you for a small benefit. Your detection system infers that this action expresses a WTRyou of BAaron/Cyou. This value is lower than the equilibrium value your welfare trade-off ratio estimator had computed as reasonable based on the benefits Aaron gains by your association, so your detection system sends asignal activating the anger program and its regulation of cooperation. This program structures arguments and other communicative acts according to a functional logic of anger, each of whose features is designed to solve a different recalibrational problem.

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Problem 1: Aaron may not realize that his action imposed a cost on anyone; alternatively, he may realize his action very likely imposed a cost on someone, but the fact that it imposed a cost on you may be something he did not realize or intend. Solution: The anger program activates two specific motivational goals: to tell Aaron that the offending action imposed a cost on you, and to find out if Aaron realized his action would have this consequence before taking it. (If he could not have known his action would impose a cost on you, it does not imply his WTRyou is too low; discovering this should deactivate your anger system.) Problem 2: Aaron may have misestimated the magnitudes of the cost imposed for benefit gained. Solution: The anger program activates the goal of recalibrating those estimates, motivating you to argue that the cost imposed on you was higher or the benefit Aaron gained was lower than he thinks. Problem 3: Aaron has underestimated your WTRAaron, resulting in an equilibrium WTRyou that is too low. (All else equal, Aaron—like everyone else—is better off associating with individuals whose WTR toward him is high rather than low, because such individuals will impose fewer costs on him and provide more benefits to him.) Solution: The anger program’s search engines scour episodic memory for examples of times when you sacrificed your welfare for his (i.e., incurred high costs to provide even small benefits), as these imply that your WTRAaron is high. Retrieval of these episodes will be accompanied by an intense desire to remind Aaron of these acts. Problem 4: Aaron has underestimated how much he benefits from having you as a cooperative partner, resulting in an equilibrium WTRyou that is too low. (This is different from Problem 3: Even if your WTR toward Aaron is low, you could be in a position to help and support him (at low cost to yourself), by virtue of your status, connections, or special skills.) Solution a: The anger program’s search engines scour your episodic memory for examples of times you helped Aaron, providing important benefits to him. Such episodes should be easily retrieved, and accompanied by an intense desire to remind Aaron of these acts. Solution b: The anger program activates a specific motivation: to threaten to withdraw cooperation, accompanied by the desire to vividly describe how this will cause Aaron to suffer. Aaron’s equilibrium WTRyou should increase if either response convinces him that the future benefits he will obtain from your association are high; Solution b

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adds the threat that he will be losing these future benefits if he does not treat you better. Trying to solve problems 1–4 will elicit an information exchange. Aaron might come to agree with you and apologize. On the recalibrational theory of anger, a sincere apology expresses the offending person’s willingness to place more weight on your welfare in the future, by recalibrating his WTRyou upwards or by recalibrating his misestimates of costs and benefits to self and to you. A sincere apology is a signal that the anger system’s recalibrational function has been accomplished, so it should deactivate the anger program, returning the cooperation system to normal mode and deactivating the aggression system. (In normal mode, the cooperation system motivates goals consistent with social exchange, providing help, and soliciting help; Cosmides & Tooby, 2005; Tooby & Cosmides, 1996.) Alternatively, Aaron might respond that your variables need recalibrating: that you are exaggerating the cost he imposed, underestimating the benefits he gained, attributing bad intentions when he had none, exaggerating how much you have helped him in the past (overestimating your value to him) and at what personal cost (overestimating your WTRAaron), or forgetting how often he has come through for you and at what personal cost (i.e., your WTRAaron is lower than he deserves, justifying his lower WTRyou). If you come to agree with his points, this too should deactivate your anger program because you will no longer see his action as expressing a WTRyou that is too low. A complete meeting of the minds on all points is unnecessary to dispel your anger: Adjustment of variables sufficient to indicate that Aaron’s WTRyou is not too low should be enough. But what if this does not happen? Problem 5: Aaron’s estimates of the costs and benefits associated with his action agree with yours, and so does his estimate of the appropriate equilibrium value for his WTRyou. But he believes you will not respond when his actions express a WTRyou below equilibrium. Solution: The anger program activates a specific motivation: to threaten to withdraw cooperation from Aaron. Demonstrating that you are monitoring his WTRyou and are willing to respond by downregulating your cooperation is a way of increasing his monitored WTRyou to nearer his equilibrium value. Problem 6: After all this, Aaron does not apologize; indeed, he indicates that he has no intention of raising his WTRyou. Solution: The anger program recalibrates the value of your equilibrium WTR Aaron, lowering it to reflect the fact that he places less weight on your welfare than you had

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expected. The functional product of this will be to downregulate your levels of cooperation toward Aaron, economizing on unrewarding social outlays. In cooperative relationships, lowering—or threatening to lower—your WTR toward someone has functional consequences: Threatening to lower it motivates reform in insufficient reciprocators; actually lowering it cuts losses with cheaters. Research testing for these specific anger responses as solutions to problems 1–7 is still in progress, but we have already confirmed a number of them, using vignette experiments and naturally occurring arguments collected from subjects. These experiments and results are reported in Sell (2005), Sell et al. (in prep. a), and Sznycer et al. (in prep.). The Anger Program Orchestrating Aggression Another way to negotiate WTRs is by threatening harm, so there are circumstances in which the anger program will regulate aggression. However, if aggression is used exploitatively inside a cooperative relationship, then the cooperative partner should avoid the exploiter (when possible), dissolving the relationship. Withdrawal of cooperation is a less expensive bargaining tool than aggression. In contrast, non-cooperators have no cooperation to threaten to withdraw. Hence, threats of aggression should be more common in noncooperative relationships, while threats of downregulating cooperation should be more common in cooperative ones. Threatening harm is a more effective tactic the more capable the threatener is of inflicting harm at low relative cost. Therefore, anger should more easily trigger aggression as a negotiative tool in more formidable individuals than in weaker ones. This effect should be particularly pronounced in men, because in humans, males are stronger and tend to pre-empt force as a social tool. Although absolute levels of aggression vary between cultures, within cultures women are far less likely than men to resolve conflicts by using physical force (Campbell, 2002; Daly & Wilson, 1988). Now, assume that circumstances force you and Aaron to interact, but you do not have a cooperative relationship. Moreover, Aaron’s WTRyou is low because he has a low estimate of your formidability relative to his. He communicates this to you and others through insults: comments impugning your willingness to fight, disparaging your strength, advertising a flippant disregard for your distress, and other forms of disrespect—claims or demonstrations that he can treat you badly without fear of harm from you. If his estimate of your formidability is correct, you may need to accept a low WTR from Aaron. If it is not correct,

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insults and actions expressing a low WTRyou should activate the anger system in its aggressive mode. When this happens, the anger program should motivate specific actions and goals, each designed to solve a recalibrational problem. For example: Problem 7: Aaron’s estimate of your relative ability to inflict costs on him—his formidability index with respect to you (FIyou)—is too low. Solution: The anger program activates a specific goal: to recalibrate the FIyou regulatory variable in Aaron’s brain. It should motivate actions that demonstrate your ability to harm him, displays such as chest thrusting, pushing, or breaking things. If these demonstrations are successful, they should raise Aaron’s FIyou and his WTRyou, because his WTR should be based, at least in part, on his assessment of your formidability (see discussion of the AWA, above) and that of your coalitional allies. (Your coalition-derived formidability should be registered by a distinct regulatory variable in Aaron’s motivational architecture, not merely by FIyou, which indexes your individual formidability.) Note that these displays can also serve a parallel function: to signal how much you value a resource, or how large a cost Aaron’s action imposed on you. That is, they can serve a communicative function as well, providing a solution to Problem 2 above (Aaron’s mis-estimate of costs imposed or benefits gained). In nonverbal animals, escalating displays and an unwillingness to back down are means used to signal how much one values a contested resource (Austad, 1983; Enquist & Leimar, 1987). Problem 8: Despite your displays, Aaron does not adjust his FIyou (and WTRyou) or his estimates of the costs imposed for benefits gained: He refuses to signal deference, submission, or respect. Indeed, he makes clear his belief that you will not respond with aggression when his actions express a monitored WTR below equilibrium. Solution: The anger program should activate a specific motivation: to threaten to harm Aaron. The harm can be physical or social. Threatening physical harm carries the risk that Aaron will consider it a bluff. Therefore, this motivation is more likely to be activated when you actually are more formidable than Aaron, or when external constraints would prevent a fight from actually breaking out (e.g., friends or authorities are present who will hold you back). Indeed, the logic of negotiation through the threat or actuality of inflicting costs is general, regardless of whether the costs are inflicted through violence, social manipulation, or other means. Different kinds of power

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have different effects, and so we expect them to be encoded by different regulatory variables (formidability being different from status, for example). When the anger program is orchestrating aggression, it should activate the motivation to escalate the displays and threats until one of you backs down. But what if neither of you backs down? Problem 9: Despite your threats, Aaron does not back down: The threats do not cause him to recalibrate his FIyou (and WTRyou) upwards. Solution: The anger program activates the goal of actually harming Aaron. This may lead to a fight, which will end when its informational function has been accomplished—that is, when it becomes clear that one of you can, in fact, inflict more injury on the other. The function of this escalation—from insults to threats to aggression—is to cause formidability-based WTR recalibration, not to kill, but on rare occasions people die from injuries incurred during this negotiation. Of the homicides that do occur, a large number result from the escalation of what police call a trivial altercation—a public confrontation between two men over face or respect (Daly & Wilson, 1988). Note two implications of this analysis of the role of aggression in negotiating WTRs. First, the anger program should be easier to trigger in people who are stronger (more formidable) because they can physically inflict more costs than weaker people can, enforcing a higher WTR toward themselves. Second, because they can inflict more injury at lower cost to themselves, aggressively formidable people should expect a higher equilibrium WTR from others, one where the benefits of not being harmed by the formidable person are exactly offset by the price of the higher WTR. All else equal, stronger, more formidable individuals should feel more entitled to deference and respect, more entitled to having other people’s actions take their interests into account. According to the recalibrational theory, anger is triggered by actions expressing a WTR below the equilibrium value the angered individual expected from others (based on an implicit computation of a power- or reciprocity-based equilibrium). This means that those who expect a higher WTR will be provoked by a larger set of actions than those who expect a lower WTR. For example, the set of actions between the two curves in Figure 15.2 should trigger anger in someone expecting a WTR of 1, but not in someone expecting a WTR of ½. If more aggressively formidable people expect a higher equilibrium WTR from others, then there is a set of cost-imposing actions that will trigger anger in them, but would not trigger anger in someone expecting a lower

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WTR. This leads to another surprising prediction that we have confirmed (Sell, 2005; Sell et al., in prep. b): Men who are physically stronger (as measured by lifting strength at the gym) are more prone to anger, feel more entitled to having their way, and have greater success resolving conflicts of interest in their favor. They have also been in more fights and believe more in the efficacy of aggression to settle conflicts. Interestingly, this belief in the efficacy of aggression reflects more than a rational assessment of their ability to win fights: It extends to international conflicts, where their personal strength could not possibly make a difference. We had predicted this in advance, on the grounds that modern humans think about conflicts between nation states with a mind designed for the ancestral world of hunter-gatherers. In that smaller world, a man’s personal strength would be an important factor contributing to the formidability of the small coalitions (two to five individuals) in which he takes part (Tooby et al., 2006). Approach Motivations in Anger A common way of conceptualizing approach–avoidance motivation is to view positive stimuli as eliciting approach and negative stimuli as eliciting avoidance (Elliot, 2006). But in anger, a very negative stimulus—someone who has placed too little weight on your welfare—elicits approach, not avoidance. Indeed, the motivation for “approach” when you are angry can be overwhelming—so much so that when circumstances prevent you from expressing your feelings to the person you are angry with, the sense of frustration can be intense. Nor is there a single way of characterizing approach in anger. When the anger program orchestrates cooperation, the approach response is to exchange information, argue, and, if necessary, withdraw cooperation, or even terminate the relationship and avoid the individual. When the anger program orchestrates aggression, the approach response is to demonstrate formidability, threaten harm, and, if necessary, actually injure the antagonist. “Approach” is a very rough way of characterizing behavioral responses. Like anger, foraging, courtship, and helping all involve approaching stimuli, yet the motivational systems regulating these activities have little in common with one another, and the approach behaviors they produce are unrecognizably different.

CONCLUSIONS We can only move toward or away from things, so “approach” and “avoidance” capture a lot of what we do in life. The great appeal of describing responses in this way is that it characterizes behavior at an abstract level,

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allowing generalizations that apply across many different concrete situations. What we have been trying to show, however, is that a satisfying level of abstraction can still be achieved while providing fine-grained descriptions of behavioral responses. The recalibrational theory of anger, for example, contains a fine-grained description of the specific content of arguments, yet these are described at an abstract level that applies to countless concrete situations (You inflicted [a large cost] on me! You did it on purpose! You did it for [a trivial benefit] for yourself! I’ve been so good to you! I’ve sacrificed for you! If you’re going to continue to treat me this way, I won’t treat you so well in the future!). The key to achieving abstract yet detailed characterizations of social motivations lies in taking an evolutionary and computational approach to motivation. Internal regulatory variables are by their nature abstract: They may use concrete situations as input—acts of sacrifice for welfare trade-off ratios, duration of coresidence, and observations of one’s own mother caring for an infant for kinship indexes—but they use these concrete situations to compute the magnitude of a variable, abstracted from those situations. These values are used by motivational systems, which activate abstract goals (make X suffer; put more weight on Y’s welfare) that get filled in with concrete content depending on the situation. Just as psychophysics allowed the principled study of perception, this framework opens a principled gateway into the scientific study of feeling—a previously intractable topic. According to this approach, conscious focus on a situation feeds new information through the architecture that triggers procedures designed to register or recalibrate the array of regulatory variables the new information is relevant to (Tooby & Cosmides, 2008). Next, signals of the significant changes in (some of) these variables are fed back into conscious awareness—presumably as a method to broadcast them to other programs they are relevant to. This cycle often appears to lead to chain reactions (as with grief, anger, and betrayal), where downstream programs are set off in their turn by receipt of further recalibrational information, triggering them then to broadcast their own contributions into conscious awareness. That is, the tapestry of felt experience that is directly elicited by the objects of awareness are, we think, annotations and evaluations about those objects in terms of changes in the internal regulatory variables relevant to them (that person is stronger than I thought; my sister is dead; this person was surprisingly kind to me; acacia beetles taste better than I thought). The demand for feeling computation often exceeds available bandwidth. When this happens, the individual spends time engaging in a particular form of behavior designed to maximize feeling

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computation, by suspending other activities that would distract from attention to the internal panorama of endogenous responses to new information. In short, feeling is a form of computation in which the values of regulatory variables are set, recalibrated, broadcast through the architecture, and output into awareness so that they can be fed into other programs designed to use them. Finally, models provided by evolutionary biology can help identify internal regulatory variables whose computational role in our evolved motivational architecture we might not otherwise suspect. Indeed, they provide us with the experimental guidance necessary for constructing abstract yet fine-grained maps of the responses our motivational systems were evolutionarily designed to produce.

ACKNOWLEDGMENTS We thank Howard Waldow and the NIH Director’s Pioneer Award (LC) for making this research possible.

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Evolution of Evaluative Processes II and Avoidance 16 Approach Motivation(s): An Evolutionary Perspective Douglas T. Kenrick and Michelle N. Shiota CONTENTS Evolutionary Perspective on Approach and Avoidance Motivation...................................................... 274 Functionality: What Are the Adaptive Purposes of Approach and Avoidance? .............................. 274 Domain-Specificity: Why Approach and Avoidance Strategies Vary ............................................. 275 Meaning of Domain-Specificity ..................................................................................................278 Summary .....................................................................................................................................279 Functional Trade-Offs in Approach and Avoidance Motivation ......................................................279 Punchline for Approach–Avoidance Motivation .........................................................................280 Research Adopting an Evolutionary Perspective on Approach and Avoidance....................................280 Same Target May Elicit Approach or Avoidance, Depending on the Goal......................................280 Activating Different Fundamental Motives Triggers Approach or Avoidance of the Same Target ............................................................................................................................281 Same Target May Elicit Simultaneous Approach and Avoidance Responses ..................................282 Emotions Facilitate Approaching or Avoiding Particular Stimuli, and Not Others ........................282 Implications of an Evolutionary Perspective: Future Directions for Research .....................................283 Specific Research Questions Suggested by the Evolutionary Perspective .......................................283 General Implications of an Evolutionary Approach for the Process of Research ............................283 Conclusion .............................................................................................................................................284 Acknowledgment ...................................................................................................................................285 References .............................................................................................................................................285 Consider the following: – The refreshments table at a party, loaded with meats, cheeses, potato chips, nuts, and desserts full of sugar and saturated fat; – A physically attractive member of your preferred sex; – An adorable kitten, mewing for attention; and – Your parents. Now consider this second list:

– A scorpion on the living room rug; – A full glass of rotten, smelly milk; – A driver who cuts you off on the freeway, making an obscene hand gesture; and – Your romantic partner, laughing with his or her extremely attractive ex. At first glance, all of the items on the first list are desirable, things or people we might want to approach, and those on the second list are undesirable, things or people we might want to avoid. At first, the utility of approach 273

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and avoidance in each case might seem obvious. However, closer examination of the lists challenges first impressions. First, our instinctive response to some of these situations can be quite alarming. For example, one might justifiably want to chase after the offending driver at high speed, return the hand gesture, and possibly ram into the back of his or her car. How can we explain the common impulse to do something so dangerous and foolish? A more subtle example lies in the cholesterol-laden refreshment table. Most humans find these kinds of foods extremely desirable in terms of taste; unfortunately, these foods are also strongly linked with many of the current major causes of death and disease in the developed world. On closer examination, the differences among items in each list also become more salient. For example, you might want to approach the refreshments table, the potential romantic partner, and your parents, but not (we hope) in exactly the same way. Similarly, the strategy appropriate to avoid a glass of rotten milk is quite different from one that will prevent your partner’s renewed interest in a former mate. From this perspective, the concepts of “approach” and “avoidance” are far from unidimensional. Yet a third issue emerges when we consider the context surrounding one’s experience of each item, including combinations of the items on the two lists. For example, your reaction to an attractive man or woman might depend, at least partly, on whether you are currently “spoken for” or not. If you are currently involved with someone else, you could still approach, but you might risk damaging your current relationship. Consider also the kitten walking toward a scorpion on the living room rug, preparing to play with it. You run toward the scorpion, push the kitten away, and step on the threat. Approach and avoidance are even more intertwined now—you have just physically moved toward the threat and distanced yourself from the desirable object, risking harm to yourself in the service of avoiding harm to a loved one.

EVOLUTIONARY PERSPECTIVE ON APPROACH AND AVOIDANCE MOTIVATION In this chapter, we contend that an evolutionary perspective on approach and avoidance motivation helps make sense of each of these complications. Our discussion will incorporate three key features of an evolutionary perspective on behavior: functionality, domain-specificity, and trade-offs. We will argue that approach and avoidance are most usefully conceptualized in terms of end

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states, rather than behaviors, and that many end-states people consistently approach and avoid are best understood in terms of their fitness implications in ancestral environments (Elliot, 2006). We will argue further that mechanisms of approach and avoidance are many and varied, differing in qualitative ways depending on the particular problem domain one currently confronts. Last, we will suggest that there are few cases of stimuli that are simply “approachable” or “avoidable.” An evolutionary perspective helps us to predict the “trade-offs” individuals will make in various situations, according to individual ecological factors, individual differences, and the actor’s developmental phase. Thus, an evolutionary perspective distinguishes between approach and avoidance at multiple levels of analysis (e.g., function, behavior), and offers more finely grained predictions about particular approach and avoidance behaviors in various situations. We will discuss the implications of this perspective for future research on approach and avoidance.

FUNCTIONALITY: WHAT ARE THE ADAPTIVE PURPOSES OF APPROACH AND AVOIDANCE? From an evolutionary perspective, the first question one asks about a general behavioral tendency is: How might this tendency have increased the chance that our ancestors would survive and reproduce, increasing their representation in the gene pool of the future? Most psychologists are functionalists at some level, but we often think about “function” in nonevolutionary terms. For example, psychologists often talk about motivations to feel good, avoid discomfort, raise self-esteem, or help make the world a better place. Such analyses emphasize function at the level of the pleasantness of immediate experience, or long-term sociological consequences. An evolutionary analysis also recognizes that feelings are functional, but goes one critical step further by asking what feels good when, and how might that have served to pass one’s genes on to future generations more successfully? (Alcock, 1993). From an evolutionary perspective, one begins with the presumption that any category of end-state that people reliably approach was likely associated with opportunities for enhancing inclusive fitness—the representation of your genes in future generations either through your own offspring, or those of your genetic relatives—in ancestral environments. These opportunities ultimately come down to a few simple categories: (1) obtaining food and water, and other survival essentials; (2) finding a mate or mates; and (3) nurturing offspring (and genetic relatives capable of reproducing), so they can reproduce in turn. Conversely,

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Approach and Avoidance Motivation(s): An Evolutionary Perspective

any category of end-states that people reliably avoid was presumably associated with threats to inclusive fitness, such as (1) danger of death or serious bodily harm that would interfere with reproduction; (2) loss of survival essentials; (3) loss of mating opportunities, including the loss of an existing mate through death, abandonment, or poaching; and (4) death of offspring (or genetic relatives capable of reproducing). In order to explain any speciestypical propensity to approach or avoid a category of targets, an evolutionary perspective links that propensity back to one or more of these proximal opportunities or threats. One could think about approach and avoidance as behavioral tropisms, literally movements toward desirable stimuli and away from undesirable stimuli. Simple living organisms are equipped with unconditional tropic responses, such as a plant’s tendency to grow toward light or to extend its roots toward water. In thinking about complex mobile organisms, however, it makes more sense to think of approach and avoidance in terms of strategies for attaining goals—sets of responses that increase the probability of a desired outcome, or decrease the probability of a negative outcome. Thinking in terms of goals makes it easier to see why one might functionally avoid some threat by moving toward its source (as in the case of the kitten and the scorpion), or why one might approach some opportunity by maintaining distance or temporarily moving in the opposite direction. According to an evolutionary perspective, functionality is defined in terms of adaptive outcomes (on average) in ancestral environments, which may or may not translate into functionality in any given current environment (Crawford, 1998). Consider the common automatic response to the rude driver mentioned at the beginning of the chapter—anger, sometimes to the point of pursuing the driver and making threatening gestures of one’s own. This is unlikely to produce any adaptive benefit, and on rare occasions, the outcome is highly maladaptive—an arrest for reckless driving, damage to your car, even death. Throughout most of our evolutionary history, however, angry displays at other people who wantonly insulted us or treated us unfairly would have served, on average, to ensure that one’s status within the group was not compromised, and status comes with serious fitness benefits in terms of food, territory, and mates. Our ancestors did not have frequent anonymous interactions with strangers, and the potential for a high speed auto accident or police intervention was not part of the picture then, so it does not get factored into our instinctive reactions. The impulse to chase someone down and let them know how angry you are is still there, however. Even in ancestral environments, such a response would have been

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adaptive if it resulted in average positive outcomes, even if it occasionally resulted in losses (demonstrating anger always carried a cost of reciprocal aggression, even before SUVs). However, such demonstrations are common (in humans and in other animals) because they presumably resulted in net benefits sufficient to balance the risks. Thus, an evolutionary perspective helps us to explain and predict a number of behavioral tendencies that seem absurd or even harmful in the present environment. Two key questions to ask, if one adopts an evolutionary perspective on approach–avoidance motivation, are (1) which categories of situations would our ancestors have needed to approach (i.e., recurrent opportunities) and (2) which would they have needed to avoid (i.e., recurrent threats), to reproduce more successfully on average?

DOMAIN-SPECIFICITY: WHY APPROACH AND AVOIDANCE STRATEGIES VARY From an evolutionary perspective, general motivations to “feel good” or “avoid feeling bad” are inadequate to solving the very different problems humans face in different domains. Different goals require different actions, as in the examples of approaching the food, the potential romantic partner, and one’s parents discussed earlier. Goals predict behavior better than available targets—the same target person may be approachable for some goals, but not for others. For example, it “feels better” to share material resources with one’s sibling as opposed to a stranger, but the reverse is true for sharing sexual favors (Ackerman, Kenrick, & Schaller, 2007; Lieberman, Tooby, & Cosmides, 2007). Evolutionary psychologists use the terms “domain-specificity” or “modularity” to indicate the presumption that evolved behavioral mechanisms are functionally and neurologically discrete (Tooby & Cosmides, 2005). Before researchers began to think about human behavior in evolutionary terms, it was presumed that there are an infinite and unconstrained number of possible approach or avoidance responses, contingent only on the idiosyncrasies of one’s particular learning history. One could learn to associate any stimulus with sensory pleasure or pain, and thus any stimulus could acquire the properties of a goal. For example, Rachman and Hodgson (1968) conducted a study that involved conditioning sexual arousal to a pair of knee-length boots, on the general assumption that sexual arousal could be conditioned to whatever random stimuli happened to be present during genital stimulation. On this view, the potential associations between specific characteristics of the environment

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and a sense of reward or punishment are unlimited. Not only can individual features of the environment become linked to reward or punishment, but interactions between multiple features can as well. Implications of this can be daunting to contemplate, as Cronbach (1975) observed: “Every second-order interaction is moderated by third order interactions, which in turn are moderated by higher order interactions. Once we attend to interactions, we enter a hall of mirrors that extends to infinity” (Cronbach, 1975, p. 119).

On entering any social situation, for example, one is presented with an overwhelming number of potentially important cues—there are several people, wearing different colored clothing and speaking with different accents, differing in height, standing or sitting, interacting with different people, and so on. If one has an unpleasant experience that “feels bad” in this situation, what can one learn from it? To avoid food in other people’s houses? To avoid people? To avoid people in red shirts? To avoid tall people? To avoid people with a certain accent, or those sitting down? Some of these cues may actually be relevant to the cause of the unpleasant experience. For example, if the people in red shirts are members of a competing sports team, it might in fact be a good marker of potential hostility. At the same time, the relevance of a given cue may depend on more or less transitory factors (the social event is a party at the home of an opposing team member, and the opposing team wears red), and many cues will

be useless in predicting future outcomes regardless of context. Trying to decode which of this myriad of cues is the one actually associated with some desired or aversive outcome would be completely overwhelming with no limitations or guidance. Thinking in evolutionary terms can help researchers discover a pathway out of this hall of mirrors (Kenrick, et al., 2002). Evolutionary reasoning—bolstered by neurophysiological evidence (Panksepp, 1982)—suggests a finite set of fundamental human goals, each linked to an adaptive problem posed by the environments in which ancestral humans lived. On the basis of several reviews of literature related to this question (Bugental, 2000; Buss, 1999; Fiske, 1992; Kenrick, Li, & Butner, 2003), we have suggested several key goals confronting humans living in social groups. For social mammals, these include alliance formation (getting along with other group members), self-protection (avoiding predation and conflict with other organisms who want the same resources), enhancing status (gaining preferential access to resources and mates), finding mates (choosing desirable mating partners), maintaining long-term mating bonds (hanging on to desirable partners), and offspring/kin care (contributing to the successful development of one’s own offspring and other close genetic relatives). Each of these goals involves different core opportunities (things to approach) and threats (things to avoid) (Schaller, Park, & Kenrick, 2007). We summarize these in Table 16.1; and also include distinct opportunities and threats in nonsocial contexts (e.g., finding edible food and

TABLE 16.1 Fundamental Goals and Associated Opportunities and Threats Goal Essential resource acquisition

Finding mate Maintain mate

Opportunities to Approach Food Water Shelter Parents and other adult caregivers (usually kin) Trusted nonkin (especially in groups) Sharing with alliance members Play (co-ordination, bonding with alliance members) Socially valued accomplishments Conspicuous resource display Connections with high-status group members High-fitness potential mates Fulfilling mate’s needs

Offspring/kin care

Fulfilling offspring/kin needs

Self-protection

Co-operative alliance formation Status enhancement

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Threats to Avoid Loss Stealing or cheating by conspecifics Predators Violent conspecifics Toxins Rejection Violation of group etiquette Failure on socially valued tasks Insults by group members Connections with low-status group members Same-sex competitors Illness or death of mate Sexual infidelity/mate-poaching Illness or death of offspring/kin

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avoiding toxins). Satisfying any one of these goals may facilitate others, or be facilitated by them. For example, forming social alliances may help one to acquire survival essentials such as food, and to protect oneself from threats from predators and out-group conspecifics. However, all of the goals ultimately come back to those listed earlier as fundamental, and the particular problems posed by the specific tasks of finding a mate, finding food, avoiding an enemy, and so on require different skills than those involved in finding a friend. We briefly consider each of these goals below, with particular attention to what people generally approach, and hope to avoid, in each larger goal. (1) Essential resource acquisition. Before even worrying about whether one is getting enough respect or affection, one needs to satisfy a number of basic bodily needs. Opportunities to acquire food and water are essential to attaining this goal, as is avoiding threats to these resources through loss, stealing, or other catastrophes. (2) Self-protection. Human beings are vulnerable to a wide range of threats to physical well-being. We can be attacked by predators, or by violent conspecifics who want our possessions or our territory. We can ingest potentially lethal toxins, including spoiled food. These threats must be avoided. Fortunately, we can also approach stimuli that provide opportunities for protection. At the simplest level, this includes safe shelter. However, protection is often offered by conspecifics, both close kin (especially relevant for young and vulnerable individuals, who rely on parents and other adult kin for protection), and trusted nonkin within one’s group. In the next section, we discuss the particular motivational system involved in forming and maintaining in-group alliances. There may, however, be distinct mechanisms involved in approaching groups of friends when one is concerned about threats (Taylor et al., 2000). Under these circumstances, for example, one might be inclined to prefer relatively larger aggregations of friends than might be desirable for a shared meal or a conversation in which intimate information is exchanged. (3) Co-operative alliance formation. Essential resource acquisition and self-protection can be accomplished by individuals, but humans accomplish these tasks far more effectively in coalitions marked by co-operation and mutual

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exchange of resources (Cosmides & Tooby, 1992; Eibl-Eibesfeldt, 1975; Hrdy, 1999; de Waal, 1996). On the approach side, this coalitional goal may be linked to motivations toward sharing and play with alliance members. On the avoidance side, one must avoid threats of rejection by the alliance, and behaviors that might lead to rejection (such as violation of group etiquette). (4) Status enhancement. For both sexes, there are tremendous fitness advantages to gaining and maintaining social status, including greater access to material resources and mating opportunities, and extended social alliances (de Waal, 1996; Fiske, 1991; Keltner, Gruenfeld, & Anderson, 2003). Because females use male status as a cue for mate selection, males are especially likely to be concerned with enhancement and potential loss of status (Buss, 1999; Kenrick & Luce, 2000). On the approach side, status enhancement can be achieved through socially valued accomplishments, through the conspicuous display of possessions, and through connections with those higher in the group hierarchy. This goal is also associated with a set of situations to avoid, including failing at socially valued tasks, being insulted or snubbed by other group members, and obvious relationships with those lower in the group hierarchy. (5) Finding mates. Access to high-quality mates is essential to reproductive success, so people are likely to selectively attend to features connoting reproductive viability, and to pursue those people. Because of inherent differences in amount and type of parental investment, males and females are likely to approach and avoid somewhat distinct sets of features in potential mates. For instance, women place more value on indications of status than do men (Kenrick, Sundie, Nicastle, & Stone, 2002; Li & Kenrick, 2006; Sadalla, Kenrick, & Vershure, 1987). Compared with women, men place more value on age and other indicators of fertility (Kenrick & Keefe, 1992). In addition, because females make a much greater investment than males in child-bearing, females are more likely than males to prefer partners interested in long-term commitment; the reverse is true for short-term encounters (Clark & Hatfield, 1989; Haselton & Buss, 2000; Kenrick, Sadalla, Groth, & Trost, 1990).

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Because biparental care requires a number of shared inputs from both parents, however, there are a number of features that both sexes seek in partners, such as co-operativeness (Li & Kenrick, 2006). Features associated with health and “good genes” are also considered attractive by both men and women (Gangestad & Simpson, 2000). On the avoidance side, both men and women must deter threats posed by same-sex competitors for mates, although men’s and women’s most dangerous rivals have somewhat different characteristics. Men are more concerned about competition from other men who are high in status, and women are more concerned about other women who display signs of fertility and physical attractiveness (Buunk, Massar, & Dijkstra, 2007; Gutierres, Kenrick, & Partch, 1999). (6) Maintain mate. Because human infants are helpless and slow to develop, their survival is enhanced by the presence and support of multiple adults, and both biological parents have the greatest investment in the child’s survival. Thus, long-term co-operative mating relationships would have been highly adaptive for our ancestors (Geary, 1998). Keeping a partner involves a distinct set of problems from finding a mate, however. Once a committed relationship is forged, demonstrations of one’s attractiveness likely become somewhat less important than demonstrations of one’s co-operativeness, generosity, and emotional stability. For this reason, it behooves one to approach opportunities to provide material support, emotional nurturance, and generally make sure one’s mate’s needs are fulfilled. One certainly needs to avoid any threats to the mate’s life and physical health, as well as signs of potential infidelity or mate poaching. (7) Offspring/kin care. The ultimate reason that human parents maintain long-term bonds is for offspring care. In 95% of other mammalian species, parental care is provided exclusively by the female without assistance from the male (Geary, 1998). Unlike other mammals, whose offspring are precocial and tend to be welldeveloped and somewhat mobile at birth, human offspring are altricial, or helpless at birth. In this way humans are more like a typical bird species than a typical mammalian species. Also like birds, humans have evolved a mating system that involves biparental care for their helpless offspring.

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The problems involved in caring for offspring are different from those involved in getting along with nonkin alliance members or mates. The usual rules of social exchange, for example, do not apply in relationships between children and their parents (Kenrick, Sundie, & Kurzban, in press). Instead, parents provide benefits for children with little or no expectation of reciprocation, all the while welcoming new opportunities to fulfill the offspings’ needs and protect them from harm. This is not to say that parental provisioning is noncontingent; factors such as the parent’s remaining reproductive potential, the number of other offspring, and the particular child’s health are all critical determinants of differential parental care (Daly & Wilson, 1998; Geary, 1998; Hrdy, 1999; Kenrick, Sundie, & Kurzban, in press). There are design features built into parents to ensure parental care, including the familiar mechanisms of bonding (Bowlby, 1979; Zeifman & Hazan, 1997). There are also design features built into the children, who come preequipped with attachment mechanisms designed to direct and exploit parental investment—by crying when they are alone, hungry, or in pain, and cooing and smiling when parental attention is adequately monopolized (Bowlby, 1979; EiblEibesfeldt, 1975). Besides investing directly in one’s offspring, humans live in familial groups, and often care for their siblings, nephews and nieces, and their grandchildren. Again, those investments are not noncontingent, but finely tuned to factors such as the existence of other more closely related children (Laham, Gonsalkorale, & von Hippel, 2005). Meaning of Domain-Specificity We have argued that human approach and avoidance motivations and their associated behaviors are largely domain-specific, rather than global. It is important to distinguish between “domain-specificity” in the sense of specific goal content from “domain-specificity” in the sense of input format—an evolutionary perspective implies the former, but not necessarily the latter (Barrett & Kurzban, 2006). Domain-specific mechanisms are attuned to particular arrangements of input cues, but can occasionally be triggered by stimulus arrays mimicking those cues. For example, other young mammals (puppies and kittens, for example) have many of the same features that trigger parental sympathy, such as large heads and eyes, as well as high pitched whimpering cries (EiblEibesfeldt, 1975). This is important in explaining both the situations in which some adaptation is clearly functional, and those in which a false alarm is likely. This distinction is also important in explaining why some modules can be content-general while still performing a fairly specific type of information processing, such as the module for

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working memory that briefly stores numbers, words, events, and information in a number of other formats. It is also important to note that although domainspecificity does imply some degree of modularity in brain processes, most modern evolutionary theorists do not rigidly accept all the criteria for a module that Fodor suggested 25 years ago (Barrett & Kurzban, 2006; Carruthers, 2005). Fodor’s (1983) criteria for modularity included domain-specificity, encapsulation, automaticity, inaccessibility to consciousness, speed, shallow inputs, neural localization, and specific breakdown patterns. As Barrett and Kurzban (2006) note in a recent review of the concept of modularity, the evidence accumulated in the intervening years suggests that not every domain-specific process meets each of the above criteria. For example, early views of mental modules presumed that each functional unit would be represented in a “spatial chunk” of brain tissue (Barrett & Kurzban, 2006, p. 641). Evidence suggests instead that functional units may in some cases be neural networks distributed across different parts of the brain. This leads to an asymmetry in the implications of fMRI findings: differing regions of activation for two processes suggests different modules, but activation of the same region for two processes does not necessarily imply a single module. Two possible solutions for this dilemma include (1) eventually increasing the spatial resolution of scanning, or, more likely; (2) applying new factor analytic techniques for examining networks of activation across the brain, rather than individual voxels or larger subregions of neural tissue (Alexander & Moeller, 1994; Moeller, Strother, Sidtis, & Rottenberg, 1987). Similarly, evidence suggests some degree of encapsulation in mental mechanisms—the existence of separate processes for handling different types of stimuli—but that encapsulation is incomplete. In the current understanding of psychological modularity, inputs from any given system can be sensitive to output from other systems. For example, simple memory processes for human faces are influenced by the perceiver’s emotional state, and the emotional state on the target’s face, although the modules for face recognition, emotion detection, and emotional experience are distinct (Ackerman et al., 2006; Becker, Kenrick, Neuberg, Blackwell, & Smith, 2007). Summary Very different rules apply to approaching different types of desirable opportunities relevant to different kinds of goals (food versus mates versus parents, for example). Likewise, different sets of rules apply to avoiding specific threats relevant to different kinds of goals (poisonous foods as opposed to mating rivals). Although much about

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modularity is yet to be understood, there is overwhelming evidence that a simple distinction between approach and avoidance systems is inadequate.

FUNCTIONAL TRADE-OFFS IN APPROACH AND AVOIDANCE MOTIVATION Recall the dilemma posed at the beginning of the chapter, of the individual deciding whether to approach an attractive potential partner, knowing that to do so threatens his or her relationship with an existing mate. Replace the kitten in the scorpion scenario with your own child and you have another dilemma—keep a safe distance from the threat, or approach the threat in the interests of protecting your offspring? Even the refreshment table poses a quandary. If you approach and heartily enjoy the food too often, you risk becoming less attractive to current or potential mates. All of these scenarios illustrate a third principle of evolutionary perspectives on approach and avoidance: few situations involve only a single goal, so trade-offs between opportunities and threats are inevitable. Because approach–avoid decisions typically involve such trade-offs, which strategy is most functional at any time depends on a number of situational details. Thus, evolved psychological mechanisms in approach and avoidance are more likely to provide “if-then” algorithms or decision rules, taking the broader environment into consideration, than stereotyped behaviors (Kenrick, Li, & Butner, 2003; Kenrick, 2006a). At a broad level of analysis, different ecological factors may lead to very different approach and avoidance strategies within a species. For example, humans may mate polyandrously (one female with multiple males) when resources are very scarce, as brothers will fare better if they share investment in a small number of offspring (Crook & Crook, 1988). Extreme polygyny (one male with multiple females) is found under conditions where resources are rich but variable, and there are steep social hierarchies, such that some families can accumulate much more than others. In such circumstances a female’s offspring may fare better if she mates polygynously with a member of a wealthy family than they would do if she mated monogamously with a poorer man. The circumstances predicting these variations in humans also predict variations in mating arrangements in bird species. One appealing aspect of evolutionary psychology is its links with other disciplines, particularly biology and anthropology. Evolutionary theorists taking a broad perspective on different species and different human societies have developed some useful theoretical tools for thinking about human behavior that would not necessarily arise from considering only the people living in a

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particular culture at a particular time. Life history theory is one broad set of concepts for considering how a particular species solves its particular problems of surviving and reproducing, and is particularly germane to the issue of trade-offs (Partridge & Harvey, 1988; Kenrick & Luce, 2000; Kaplan & Gangestad, 2005; Stearns, 1976). Lifehistory theorists begin with the presumption that organisms are involved in a struggle to acquire and efficiently allocate limited energy resources. All mammals, for example, must allocate resources to (a) somatic development, (b) mating effort, and (c) parenting effort. Allocation of resources to one category necessarily involves tradeoffs—searching for an additional mate means less time for parenting, feeding one’s own body means less resources for one’s offspring, and so on (Kaplan & Gangestad, 2005). One implication of life-history theory for our purposes is that the outcome of trade-off situations can be predicted by knowing the actor’s species and stage of life. Different species make very different allocations to the different life phases. For example, oak trees spend many years developing before they begin reproducing, but then they produce thousands of seeds, and continue reproducing for decades. Salmon spend 2 or 3 years developing, then reproduce in a single burst of reproductive effort, producing hundreds or thousands of eggs and then dying. Neither of these species devotes much effort to parenting. Elephants, on the other hand, are like oak trees in that they devote many years to somatic development and continue to reproduce for decades, but unlike oaks in that they have a very small number of offspring, and invest tremendous amounts of parental resources in each one. There are also variations within species in life-history strategies. In most vertebrates, for example, females and males have different life histories. Human females, for example, mature earlier than males, invest several years in choosing a mate, and necessarily invest very high amounts of resources in each offspring. Human males can in theory, and sometimes in practice, have many more offspring, and need not invest as much in each offspring. Punchline for Approach–Avoidance Motivation Given that there are trade-offs everywhere in nature, nothing is purely and simply approachable, or purely and simply avoidable. Approaching a desirable potential mate is likely to bring costs and risks, such as life-threatening competition with other suitors, or loss of a current relationship. Similarly, the obvious self-protection strategy of running away from a dangerous predator (avoidance) may also have associated opportunity costs, such as

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leaving one’s relatives at risk, or sacrificing valuable resources.

RESEARCH ADOPTING AN EVOLUTIONARY PERSPECTIVE ON APPROACH AND AVOIDANCE Our discussion thus far has suggested that the processes involved in approach and avoidance should vary in functional ways depending on what fundamental motivational domain is currently active, and depending on individual differences in key life-history factors that affect decision trade-offs. In this section, we will briefly review some research following from this perspective, considering some classic research as well as several recent research findings from our own labs.

SAME TARGET MAY ELICIT APPROACH OR AVOIDANCE, DEPENDING ON THE GOAL Social psychological models of close relationships traditionally involved a search for domain-general processes underlying all categories of intimacy. For example, reinforcement-affect theory (Clore & Byrne, 1974) posited that our feelings about a given target person were a function of the ratio of rewards to punishments that we had experienced in that person’s company. The result of a history of rewards associated with a target person would incline us to be attracted toward that person, and the model presumed that we were inclined to approach those to whom we were attracted. Traditional exchange-based models presumed a slightly different domain-general process underlying attraction toward another person, emphasizing the expected ratio of benefits to costs in interactions with that person as compared to available alternatives (Thibaut & Kelley, 1959; Walster, Walster, & Berscheid, 1978). In their traditional formulations, such models did not explicitly differentiate between different categories of intimate relationships, such as friends versus kin versus romantic partners, although they would have presumed that a greater frequency of interactions had the potential to yield a greater number of benefits. Considered in evolutionary context, the qualitative differences between approach responses in relationships with friends, mates, and close kin are more apparent. It is true that brothers and sisters have generally experienced a large number of rewarding interactions with one another, and people are especially likely to desire to affiliate with close kin throughout their lives (Daly, Salmon, & Wilson, 1997). Exchange relationships with kin tend to be biased

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in favorable ways (Ackerman et al., 2007). At the same time, the “positive affect” felt toward first-degree kin does not generally extend to the sexual domain. Instead, people asked to imagine romantic or sexual contact with their brothers or sisters report strongly negative affective reactions (Ackerman et al.; Lieberman et al., 2007). From an evolutionary perspective, it is generally presumed that this uniquely negative response to approaching kin for mating goals is linked to the potential dangers of combining harmful recessive genes. Although deleterious recessive genes are normally rare, the probability they will be shared by a brother and sister are high enough to make the costs of intra-familial mating outweigh the benefits (Lieberman et al., 2007; Van den Berghe, 1983). Another possible mechanism for preferring distant relatives as mates involves resistance to disease, which is decreased by mating with close relatives. Other species, not subject to human cultural norms, also disfavor sexual contact with close relatives, and will avoid mating with siblings (Lieberman et al.), even when they were not raised together. Aversion to incestuous mating does not seem to depend on cultural taboos against incest, but is instead linked to biological mechanisms operating outside human consciousness. Humans appear to rely on childhood coresidence as a cue of relatedness, triggering a mechanism evolved to prevent incest (Lieberman et al., 2007), even when cultural norms encourage those children to mate. In a massive social experiment, children on Israeli kibbutzim were raised in small groups of boys and girls born around the same time. There were no social norms discouraging romantic or sexual involvements between “pod-mates”, and such involvements were even encouraged. However, Shepher (1971) examined several thousand marriages among these individuals and found that, although the podmates became life-long friends, they rarely married one another. This finding is particularly interesting because of the wealth of data suggesting that people prefer to marry their neighbors (Bossard, 1932), and Israeli children were likely to marry others raised on the same commune, but not in the same pod. Similarly, the common practice in China of raising very young girls in the same household as their future husbands has been associated with low fertility and high marital dissatisfaction and dissolution, with greater problems found when the children had been raised together from an early age (Wolf, 1993).

ACTIVATING DIFFERENT FUNDAMENTAL MOTIVES TRIGGERS APPROACH OR AVOIDANCE OF THE SAME TARGET In a number of studies conducted with our colleagues, we have been activating different motivational states

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associated with the goals described in Table 16.1; and observing the consequences for cognitive and affective responses to various social situations (Griskevicius, Cialdini, & Kenrick, 2006a; Maner et al., 2005). The results of these experiments suggest that approach and avoidance inclinations toward a particular social stimulus can change dramatically, depending on the judge’s current motivational state. For instance, a person with an otherwise neutral facial expression may be perceived as feeling anger by judges who are themselves feeling fear, if the target is a male member of a discriminable outgroup (Maner et al., 2005; Schaller, Park, & Mueller, 2003). Other research suggests that people are quicker and more accurate in detecting facial expressions of anger on males than on females, and that this process reflects physiognomic features of the male face rather than culturally recognized signs of gender (Becker et al., 2007). This “functional projection” makes sense given that threats to physical safety are more likely to come from strange males than strange females. In another series of studies examining motivation-driven variations in approach and avoidance behaviors, participants were exposed to manipulations inducing either selfprotective or mating motivation (e.g., by reading scenarios involving being alone in a dark house at night and overhearing sounds of someone breaking in, as opposed to imagining a romantic encounter with an attractive and desirable person). After these inductions, participants encountered another judgment task in which they got information regarding the opinions of other group members. Results indicated that both men and women were more likely to conform to group opinion after self-protective goals had been primed than in a neutral prime condition. Activating mating motives, however, generally had opposite effects on male and female participants. Whereas females in a romantic frame of mind again conformed more (compared to a neutral control group), men did the opposite—actually going against group opinion (Griskevicius, Goldstein, Mortensen, Cialdini, & Kenrick, 2006b). These results fit precisely with two separate sets of evolution-based predictions about the adaptive functions of conformity and counter-conformity for achieving different goals. Under conditions of threat from potentially dangerous strangers, both men and women profit from group cohesion. On the other hand, there is a sex difference in the mating consequences of displaying independence from group opinion. Throughout the animal kingdom, males are generally more likely to compete with one another in an attempt to draw attention to their unique characteristics than are females. This difference is linked to differences in sexual selection and

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parental investment (Griskevicius et al., 2006a). The principle is well demonstrated by exceptions to the normal gender differences in life-history—when males contribute more to offspring than females do, as in phalaropes (a sandpiper-like bird), then females are more showy and competitive, and males are more selective.

SAME TARGET MAY ELICIT SIMULTANEOUS APPROACH AND AVOIDANCE RESPONSES In another series of studies, Ackerman and his colleagues (2006) found that the normal tendency for people to homogenize members of out-groups was erased if the outgroup members were males with angry facial expressions. This fits with the rationale we discussed above that angry males from outgroups are likely to pose a physical threat. Given this effect, we had expected to find that people pay particular attention to such individuals. However, findings from eye-tracking studies have tended to show the reverse—with participants looking at out-group males, and at angry faces, for less time than they look at other targets (Kenrick, Delton, Robertson, Becker, & Neuberg, 2007). Yet the same studies find higher-than-expected memory for those same targets. This disjunction between visual attention and later memory makes some functional sense—staring at an angry stranger is probably not something one wants to do, given that stares are themselves seen as threat gestures. At the same time, one does not want to forget potentially dangerous individuals, and so they seem to show the effects of emotional memory enhancement (Cahill, Prins, Weber, & McGaugh, 1994). A fascinating implication of this research is that not looking does not mean not attending. Other research from our labs has indicated an opposite disjunction between visual attention and subsequent cognitive processing. Although both sexes look at, encode, and later remember beautiful women, women look at handsome men, but do not remember them for more than a few seconds (Becker, Kenrick, Guerin, & Maner, 2005; Maner et al., 2003). The suppression effect for handsome male strangers seems less intuitively sensible at first, but does fit well with findings on women’s criteria for mate choice. Several evolutionary psychologists have provided evidence to suggest that male physical attractiveness is associated with so-called good genes (Gangestad, Thornhill, & Garver, 2002). Hence, it makes sense handsome men’s faces elicit initial attention from women. Consistently, we found more visual fixations for handsome men amongst women who are ovulating, who are unrestricted, or who are in a romantic frame of mind. However, even if a woman is interested in a short-term relationship, it is unlikely that that relationship will be

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with a man who has not stayed around long enough to pass several levels of initial screening. Before committing to a relationship with a man, women generally require additional information, including reliable information about the man’s social status or financial status (Buunk, Dijkstra, Fetchenhauer, & Kenrick, 2002; Kenrick, Sundie, Nicastle, & Stone, 2001; Li, Bailey, Kenrick, & Linsenmeier, 2002). Clark and Hatfield (1989) found in two studies conducted across two decades that not a single woman accepted an offer of a sexual liaison with a strange man, even though about half were willing to go on a date with him.

EMOTIONS FACILITATE APPROACHING OR AVOIDING PARTICULAR STIMULI, AND NOT OTHERS According to an evolutionary approach to emotion, emotions prioritize particular fundamental goals and activate motivations to approach specific opportunities and avoid specific threats (Frijda, 1986; Lazarus, 1991; Plutchik, 1980). For example, compassion highlights offspring/kin care goals and associated nurturant motives, whereas pride highlights status enhancement goals and motives to advertise achievements and resources (Keltner, Haidt, & Shiota, 2006). Neuroscience research does support the existence of a system broadly facilitating reward anticipation and acquisition (Ghitza, Fabbricatore, Prokopenko, Pawlak, & West, 2003; Knutson, Taylor, Kaufman, Peterson, & Glover, 2005). However, this system is likely to interact with other systems in mediating particular positive emotions and associated motivations (Young & Wang, 2004). Thus, an evolutionary perspective on approach and avoidance motivation strongly suggests the existence of neurologically discrete positive and negative emotions (Tooby & Cosmides, 2005). In one series of studies, we have considered how this approach might be relevant to consumer choices of various products. According to the affect infusion model (Forgas, 1995), people should learn to associate stimuli in the environment with their current mood state, such that an object or message encountered while one is in a positive mood will be “infused” with positive connotations but infused with negative connotations if encountered while one is in a negative mood. Previous studies of emotion and product attractiveness have supported this model, concluding that positive emotion generally enhances one’s perception of product attractiveness (Batra & Stayman, 1990; Edell & Burke, 1987). An evolutionary approach, however, would suggest that specific positive emotions, facilitating approach of opportunities relevant to different goals, would only affect perceived attractiveness of goal-relevant categories of products.

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Results reveal that, relative to a neutral condition, experimentally elicited pride increases the attractiveness of conspicuous, “public” items but not of inconspicuous household items of roughly the same value; contentment increases attractiveness of inconspicuous items but not conspicuous ones; and compassion has no effect on product attractiveness at all (Griskevicius, Shiota, & Nowlis, 2007). These findings suggest that positive emotions do not generally facilitate approach, but rather that they facilitate approaching objects that satisfy the specific goals activated by the emotion. Much about the extent of modularity in human emotion is still unknown. For example, it is unclear whether there are separate modular systems designed to deal with fears of predators, fears of violent conspecifics, and fears of social disapproval, or whether these are all mediated by the same circuitry (Öhman & Mineka, 2001). Similarly, it is unclear whether the disgust systems involved in responding to noxious food substances share some or all their underlying machinery with systems mediating moral disgust (Haidt, 2001). Still, an evolutionary approach provides guidance in developing hypotheses and research paradigms for these and similar questions.

IMPLICATIONS OF AN EVOLUTIONARY PERSPECTIVE: FUTURE DIRECTIONS FOR RESEARCH Adopting an evolutionary perspective on approach and avoidance raises a number of specific research questions. At the simplest level, it raises questions about the degree of modularity in the human mind. It seems functionally implausible that the same general mechanism is used for all forms of approach or for all forms of avoidance, and indeed there is evidence for this assumption (Garcia & Koelling, 1966; Sherry & Schacter, 1987; Wilcoxon, Dragoin, & Kral, 1972). Yet many questions remain about exactly how the mind works with regard to these processes. How many distinct approach and avoidance systems there are at the neurological level? How much sharing is there of subprograms between different modules? To what extent are these systems localized versus physically diffuse?

SPECIFIC RESEARCH QUESTIONS SUGGESTED BY THE EVOLUTIONARY PERSPECTIVE A particular, largely unexplored research area suggested by an evolutionary perspective on approach motivation is distinguishing among multiple, potentially discrete positive emotions (Shiota, Campos, Keltner, & Hertenstein,

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2004; Shiota, Keltner, & John, 2006). An evolutionary approach suggests the existence of discrete positive emotions that help us take advantage of specific kinds of opportunities in the environment, as well as discrete negative emotions that help us respond adaptively to different kinds of threats. Preliminary findings suggest that different positive emotions are associated with distinct facial and upper-body displays (Shiota, Campos, & Keltner, 2003; Tracy & Robins, 2004), and distinct effects on information processing (Griskevicius & Shiota, 2007), and that different positive emotion dispositions are differentially associated with several core personality processes (Shiota et al., 2006). Still, much research applying a discrete emotion perspective to positive emotion is yet to be done. We also reviewed the broad literature on life history strategies, which suggests that every decision made by every organism involves trade-offs between different potential allocations of effort, particularly between bodily development and health versus mating opportunities versus offspring care. That perspective suggested that there are reliable links between individual development and life-history allocations, and that those links are reliably mediated by ecological factors. Despite the power of this perspective in explaining the behavior of animals, very little research on humans has been elucidated by this perspective, and most of that research has been conducted by anthropologists. Psychological research techniques could be immensely helpful in understanding how people approach and avoid different survival, mating, and kin care opportunities at different phases of their lives, and how such processes are affected by ecological factors and individual differences (Gangestad & Simpson, 2000).

GENERAL IMPLICATIONS OF AN EVOLUTIONARY APPROACH FOR THE PROCESS OF RESEARCH An evolutionary approach to behavior has a number of distinct advantages. One of these is theoretical cohesiveness, in that adopting an explicitly evolutionary perspective helps us understand how proximate cognitive, affective, and behavioral processes make sense in light of general principles that apply across human cultures and across species. One common misconception is that the search for universal principles underlying diverse behavioral phenomena implies the absence of culture- or speciesspecific factors influencing behavior. Evolutionary theorists, whether they are studying humans or any other animal, are actually quite interested in the specifics characterizing that species, as well as in homologous processes. Evolutionary theorists studying human behavior are also interested in cultural variability as well as

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cultural constants (Ekman & Friesen, 1971; Gangestad, Haselton, & Buss, 2006; Kenrick, Nieuweboer, & Buunk, 2007; Norenzayan, Schaller, & Heine, 2006). At the same time, an evolutionary perspective counsels that the particulars of behavior within a given species or within a particular culture are not likely to be the products of general processes incompatible with the laws of natural selection (Kenrick, 2006b; Tooby & Cosmides, 2005). There are numerous examples of cultural variation in what is desirable or undesirable that are still consistent with explanations rooted in evolutionary mechanisms. Mating preferences offer an excellent example of this phenomenon. As we noted earlier, some societies, such as the modern United States, regard polygamy as undesirable, if not evil; other societies have regarded it as normative, if not a positive good. We also noted that variations in the acceptance and prevalence of polygyny as well as polyandry seem to vary across human societies according to some of the same conditions influencing their prevalence in other animal species (Crook & Crook, 1988). Consider another example, cultural variability in age preferences for mates. Because human females universally undergo menopause, and males continue to be able to have children into their later years, an evolutionary life-history model predicts a universal tendency for men, as they age, to prefer women relatively younger than themselves. This preference for relative youth is not presumed to follow from sex differences in social power or status, but from an attraction toward fertility cues. Teenage boys, for example, who have very little social status and power, report being attracted primarily to women several years older than themselves, though they do not believe those women are likely to reciprocate their interest (Kenrick, Gabrielidis, Keefe, & Cornelius, 1996). For very young men, it is older rather than younger women who are likely to manifest stronger fertility cues. However, men in their forties and fifties are attracted to women much younger than themselves, and this tendency appears to be universal (Kenrick & Keefe, 1992; Campos, Otta, & de Oliveira Siqueira, 2002). The Tiwi society might appear to be an exception to this pattern, in that men in their twenties all marry older widows (Hart & Pillig, 1960). On closer examination, however, Tiwi men are attracted to younger women, but powerful older men have managed to monopolize all the young brides for themselves. This polygynous society requires all females to be married, whether they are young children or widows. Older men bequeath their own daughters at birth to another older male to whom they owe a favor, including having previously received one of his daughters as a bride. Because the older men

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are not interested in widows, young men are free to marry them; by so doing they may elevate their position in society, and also curry future favors from the widow’s male relatives. Thus, Tiwi society represents a novel and unusual dynamic arrangement of norms that nevertheless reflects human nature. Men everywhere are attracted to relatively young, fertile females, men everywhere compete for power, and in many cases, men’s power is converted directly into a monopoly on desirable mates (Kenrick, Nieuweboer, & Buunk, 2007). Exactly how this plays out in a given society depends a great deal on the larger economic and social structure, but the principles are the same. Another misconception about evolutionary approaches, less prevalent but still persisting in some corners, is that evolutionary researchers search for particular cases in which an animal demonstrates a “human-like” behavior pattern, and then quickly jump to the conclusion that the two patterns are manifestations of homologous processes. Instead, good comparative research is attentive to the particular functional connections between adaptations and eliciting ecological factors, and generates hypotheses accordingly. For example, cats are among those species that are not responsive to the taste of sugar, whereas humans are among those species that are. Sweetness is a feature evolved to attract fruit-eating animals to plants at the time when the fruit is fully ripe, and when the plant can most benefit from seed dispersal. Thus, it would only be noticed by plant-eaters, and we might hypothesize than herbivores and omnivores, but not carnivores, would find the taste of sugar pleasant. Similarly, if the function of embarrassment/shame is to prevent aggression by group members after you have violated a social norm (Keltner & Buswell, 1997), then we should expect to see shame-like behavior in highly social mammals that live in “packs,” such as humans and dogs, but not in more solitary mammals such as cats.

CONCLUSION An evolutionary perspective suggests that there are multiple approach and avoidance systems at the functional and neurological levels, designed to deal with the unique problems regularly encountered by ancestral humans. Particular approach or avoidance mechanisms are likely to be triggered by functionally relevant factors in the immediate environment, and by chronic ecological factors in interaction with individual differences linked to gender, age, and other physical factors. An evolutionary perspective offers a strong theoretical foundation for empirical research on domain-specific approach and

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avoidance motivation, and although we have reviewed a number of empirical findings emerging from this perspective, much territory remains uncharted.

ACKNOWLEDGMENT The authors thank Vladas Griskevicius for his helpful comments on an earlier draft of this manuscript.

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Immediacy and Automaticity of Evaluation

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Evaluative Readiness: The Motivational Nature of Automatic Evaluation Melissa J. Ferguson and John A. Bargh

CONTENTS Notes on Terminology ...........................................................................................................................290 Attitude Versus Evaluation ...............................................................................................................290 Affect and Evaluation .......................................................................................................................290 Automatic Versus Implicit ................................................................................................................ 291 Notes on Measurement ..........................................................................................................................292 Evaluative Priming Paradigm...........................................................................................................292 Implicit Association Test ..................................................................................................................293 Motivational Nature of Automatic Evaluation ......................................................................................293 Automatic Evaluations and Currently Accessible, Conscious Goals ...............................................294 Automatic Evaluations and Currently Accessible, Nonconscious Goals .........................................296 Automatic Evaluations and Chronically Accessible Goals ..............................................................298 Motivation Nature of Automatic Versus Explicit Evaluations ..............................................................300 Conclusions ...........................................................................................................................................301 References .............................................................................................................................................301 The determinants and implications of people’s likes and dislikes for stimuli in their environment have been a central topic of study over the 100 years since empirical psychology began (Allport, 1935; Brown, 1998; Eagly & Chaiken, 1993; Higgins & Brendl, 1996; McGuire, 1969, 1985; Osgood, Suci, & Tannenbaum, 1957; Rosenberg, 1965; Tesser & Martin, 1996; Zajonc, 2000). Throughout most of this period, researchers have studied people’s likes and dislikes (i.e., attitudes, evaluations, preferences) by simply asking them to report them (Himmelfarb, 1993; Krosnick, Judd, & Wittenbrink, 2005). For example, a typical methodological strategy is to ask respondents to indicate on an 11-point scale how much they like a variety

of stimuli. In this way, researchers have typically examined how people’s explicitly (i.e., consciously, intentionally) generated evaluations predict their behavior across a range of circumstances, change after learning about new information or experiencing persuasive appeals, and compare to other people’s evaluations (for reviews see Albarracín, Johnson & Zanna, 2005; Eagly & Chaiken, 1993). This approach has yielded valuable insight into the questions of how, when, why, and to what effect people evaluate stimuli as good versus bad. Over the last two decades, however, there has been a remarkable shift in researchers’ assumptions about the ways in which people generate likes and dislikes in response 289

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to stimuli. A considerable amount of data now show that people’s evaluative processes are not limited or constrained to those times during which they are consciously and deliberately reflecting on a given stimulus. Instead, people evaluate the stimuli in their environment effortlessly, spontaneously, quickly, and often without realizing they have done so (Bargh, Chaiken, Govender, & Pratto, 1992; Fazio, 2001; Fazio, Sanbonmatsu, Powell, & Kardes, 1986; Greenwald, Klinger, & Liu, 1989; Greenwald, McGhee, & Schwartz, 1998; Zajonc, 1980). That is, on the mere perception of a stimulus, people invariably evaluate the stimulus in terms of being positive or negative, and they do so without being aware of it, intending to do so, or exerting any appreciable effort to do so (Bargh, 1994; for evidence of effortlessness, see Hermans, Crombez, & Eelen, 2000). For example, people are able to assess whether a facial expression is positive or negative on the basis of an exposure less than 10 ms in duration (Murphy & Zajonc, 1993; Niedenthal, 1990; Öhman, 1986), a time span almost 15 times shorter than the average human eye blink. Moreover, these immediate and effortless evaluations occur for a whole range of stimuli, including words, letters, pictures, drawings, people, faces, and even odors (for a review see Ferguson, 2007a; Musch & Klauer, 2003). These findings have demonstrated the phenomenon of automatic evaluation—evaluations that are unintentionally generated on the mere perception of the respective stimuli. The examination of such evaluations has consumed a sizable portion of attitude research over the last 20 years, and especially over the last 5 years. In this chapter, we consider the motivational basis of this mode of evaluation. We first review theory suggesting that motivations and goals should be expected to be closely related with one another. We then describe several lines of recent research that provide empirical support for the notion that automatic evaluations are contingent or conditional on current and chronic goals and motivations. But first, we need to lay the groundwork for these substantive sections with a discussion of the terminology and methodology that characterize this area of research.

NOTES ON TERMINOLOGY


White, 1956; Thurstone, 1931). However, they have more recently been defined simply as the evaluations associated with objects in memory (Fazio, 1986; Fazio, Chen, McDonel, & Sherman, 1982). In this way, attitude is virtually indistinguishable from evaluation, which is a less technical (i.e., academic) term referring simply to the assessment of whether a given stimulus is good or bad (Tesser & Martin, 1996). We use both of these terms freely throughout the chapter, while ascribing to the definition of an attitude as the evaluative information associated with a given object representation in memory. Another critical notion in the attitude literature is the concept of attitude object (Allport, 1935; Bargh et al., 1992; Fazio, 2001; Fazio et al., 1986; Sarnoff, 1960; Smith et al., 1956; Thurstone, 1931). This is a general term referring to any stimulus toward which a person holds an attitude, and includes any conceptual or perceptual stimulus that can be discriminated (Eagly & Chaiken, 1993; Thurstone, 1927). Even though most of the research in this area has examined automatic attitudes toward graspable, or physical, objects, such as people (e.g., blacks, elderly, women), animals (e.g., cockroach, puppy), and everyday objects (e.g., consumer products, trees), people also automatically evaluate more abstract concepts such as ideals, values, and goals (Ferguson, 2007b). It is also worthwhile to note that other theoretical constructs in social and cognitive psychology are related to people’s preferences even though they do not regularly show up in the attitude literature per se. For example, Damasio (1999) and colleagues have argued that people immediately and unintentionally generate somatic markers in response to stimuli. These somatic markers essentially denote the anticipated emotional reaction to the corresponding stimulus, a definition that is roughly equivalent to how attitudes have been conceptualized over the past two decades. In addition, behavioral economists as well as sociologists use the term tastes to refer to people’s preferences for stimuli. In economics, a person’s tastes are assumed to be based on the degree to which the corresponding objects or stimuli can bring enjoyment, satisfaction, utility, or happiness to that person, so that the economic concept of taste is essentially equivalent to the notions of preferences, likes and dislikes, evaluations, and attitudes.

ATTITUDE VERSUS EVALUATION Researchers have used a variety of terms to describe people’s likes and dislikes, the two most common being attitudes and evaluations. Attitudes have been traditionally defined as consisting of affective, cognitive, and behavioral reactions to stimuli (Albarracín et al., 2005; Allport, 1935; Doob, 1947; Eagly & Chaiken, 1993; Osgood et al., 1957; Sarnoff, 1960; Smith, Bruner, &

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AFFECT AND EVALUATION It is also useful to draw a distinction between evaluations and affective states, and we consider two points of discussion to this end. The first is whether evaluations necessarily involve affective processing in terms of the involvement of brain regions traditionally implicated in emotional and mood states (Davidson, Scherer, & Goldsmith, 2003). This

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Evaluative Readiness: The Motivational Nature of Automatic Evaluation

would at first glance seem to be true given that many researchers commonly assume that evaluations involve affective reactions (Albarracín et al., 2005; Clore & Schnall, 2005; Eagly & Chaiken, 2003; Forgas, 2003), as mentioned earlier. Also, some scholars consider an automatic evaluation to be the initial spark of an eventual, comprehensive affective or emotional state (Damasio, 1999; LeDoux, 1996). However, we should note that there is no research as of yet that convincingly demonstrates that the types of evaluations that we talk about here—those that are unintentionally and immediately generated in response to stimuli—necessarily depend on the brain and physiological systems typically characterized as affective. Future research will undoubtedly continue to address the extent to which automatic evaluations recruit those brain regions typically identified with affective experiences, as well as the circumstances under which this occurs. The second point of discussion regards the conceptual differences between evaluations and affect. For example, how are evaluations different from emotions? One classic distinction is that although both evaluations and emotional states occur in reaction to a particular stimulus or event, the latter are generally more durable, long lasting, and subjectively involving than the former (Tesser & Martin, 1996). Additionally, an evaluation is assumed to be a simple classification as positive versus negative, whereas emotions consist of shades of positive (e.g., elation, surprise) and negative (e.g., sadness, anger, anxiety) affect. Furthermore, emotional states are also classically defined as conscious experiences (Davidson et al., 2003), whereas evaluations, as mentioned previously, can occur nonconsciously. How might evaluations differ from mood states? Mood states are assumed to be less introspectively linked to any one stimulus, and are consciously felt (Davidson et al., 2003; though see Winkielman, Berridge, Wilbarger, 2005), diffuse, and somewhat persistent (i.e., not fleeting, lasting more than 5 min). In contrast, evaluations are generated in direct response to stimuli, and are usually fleeting. Yet, the line demarcating these theoretical constructs is not always sharp. In particular, especially if the nascent evidence for nonconscious mood states increases, the putative qualitative difference between a nonconscious evaluation of a given conceptual or perceptual stimulus, and a nonconscious mood state resulting from some incidental event, will become obscured.

AUTOMATIC VERSUS IMPLICIT In terms of the characteristic of automatic, we again consider two points of clarification. Firstly, although evaluations and attitudes are often referred to as automatic or implicit (e.g., automatic attitudes, automatic evaluations),

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the terms automatic and implicit refer to the measure rather than the construct being measured. This is an important distinction as the latter would suggest that there are two qualitatively different evaluations—those that are automatic and those that are not. Although this is a possibility, research concerning it is ongoing and not yet conclusive (Fazio & Olson, 2003; Hofmann, Gawronski, Gschwendner, Le, & Schmitt, 2005; Nosek, 2005; Wilson, Lindsey, & Schooler, 2000). The second point of clarification concerns the meaning of the terms automatic and implicit. The term automatic has been used to describe processes that unfold without the person’s awareness, intention, effort, or control (Bargh, 1994; Moors & De Houwer, 2006). However, a process does not need to meet all four of these criteria in order to be designated as automatic (very few do at the level of complexity typically of interest to social and motivational psychology), and in this way the term is not very specific. Therefore, it is useful when using the term to specify exactly what criteria are implied for a particular process (Bargh, 1989). With regard to the literature on evaluations, the term “automatic” usually refers to the fact that they can be generated without the person’s intention. Although some research has shown that evaluations can be generated without the person’s awareness of the stimuli themselves, most of the research employs measures in which the person is aware of the stimulus that is being evaluated but is unaware that their evaluation is being measured (for a review see Ferguson, 2007a). We use the term automatic in this chapter to refer to evaluations that are generated without the person’s intentions and usually without their awareness. We also offer the caution that the meaning of the term implicit as used in social psychology (Greenwald & Banaji, 1995) is somewhat different from how it is used in much of the cognitive science literature (De Houwer, 2005; Fazio & Olson, 2003). In cognitive psychology the term implicit refers to knowledge or memory that can influence processing but that cannot be introspectively identified, even when the person tries to do so. For example, a classic case of implicit priming is the influence of a previously studied word on word-fragment completion even when the respondent has no memory of encountering the word during the study phase (Roediger, 1990; Squire & Kandel, 1999; Tulving & Craik, 2000). In social psychology, however, the term implicit is often used to describe evaluations that are generated without the person intending to do so, even if that person would be able to identify her or his evaluation of a given stimulus if asked to do so. For example, people would probably be able to easily identify their evaluation of many of the stimuli that are presented in implicit attitude measures, and at least some of the time

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these intentional (explicit) evaluations will line up with their unintentional (implicit) ones (Nosek, 2005). We return to this issue of dissociation between implicit and explicit evaluations later in this chapter.

NOTES ON MEASUREMENT Throughout most of the last century of empirical psychology, researchers have measured people’s preferences in the straightforward manner of just asking for them. For example, in order to find out how much people like elderly people, they would ask people to circle a number on an 11-point scale with 1 indicating extreme disliking and 11 representing extreme liking. As Schwarz and Bohner (2001) and others have noted, this type of measurement is highly susceptible to a range of contextual factors, that is, factors that are unrelated to the attitude but that nevertheless influence how the person responds. These factors can include mood states, response biases, demand effects, and impression maintenance (for a review see Schwarz & Bohner, 2001). Because of these factors, it is difficult to precisely and accurately interpret the meaning of a respondent’s answer on an explicit attitude measure. One area of research where the difficulty of interpretation is especially clear is intergroup attitudes. Given societal norms for egalitarianism and fairness toward other (especially stigmatized) groups, people may feel social pressure to keep hidden any negative feelings and evaluations they may harbor about other groups of people (Dovidio, Mann, & Gaertner, 1989; Jones & Sigall, 1971; Katz & Hass, 1988; McConahay, 1986; Sears, 1988). This means that explicit measures of prejudice can underestimate the actual amount of prejudice the respondent holds toward others. To attempt to circumvent this problem, researchers began to develop indirect, and less obtrusive, and reactive measures of attitudes. For example, in the Bogus Pipeline research (Jones & Sigall, 1971), participants were hooked up to an apparatus that was supposed to be capable of detecting their attempts at deception. Given this possibility of detection, participants did admit to greater levels of prejudice when using this measure compared to other explicit, traditional measures of the kind described above. Although indirect (but explicit nonetheless) measures of this sort were an improvement, researchers continued to be interested in developing a method to assess a person’s unintended and nonconscious evaluative responses to stimuli. Given the covert nature of the implicit methodologies developed by cognitive psychologists, social psychological researchers began to modify them in order to address social psychological issues and phenomena.

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With regard to attitudes and evaluations, the two most common measures include the evaluative priming paradigm (Fazio et al., 1986) and the Implicit Association Test (Greenwald et al., 1998), among others (Brendl, Markman, & Messner, 2005; De Houwer, 2003; De Houwer & Eelen, 1998; Dovidio, Kawakami, Johnson, Johnson, & Howard, 1997; Koole, Dijksterhuis, & van Knippenberg, 2001; Niedenthal, 1990; Nosek & Banaji, 2001; Payne, Cheng, Govorun, & Stewart, 2005; von Hippel, Sekaquaptewa, & Vargas, 1997). These methods are summarized briefly in the next section.

EVALUATIVE PRIMING PARADIGM Sequential priming paradigms were originally developed by cognitive psychologists to assess the degree to which memory locations related to a given stimulus become activated automatically on perception of that stimulus (Logan, 1980; Meyer & Schvaneveldt, 1971; Neely, 1976, 1977; Posner & Snyder, 1975; Shiffrin & Schneider, 1977). In such a paradigm the “prime” stimulus of interest (e.g., butter) is presented on a computer screen for a fraction of a second and is followed by a “target” stimulus that is either related to it (bread) or not (chimney), and to which the participant must make some kind of response or judgment (e.g., lexical decision). The common finding is that people can respond significantly more quickly to the targets when they are preceded by related versus unrelated primes. This suggests that quickly following the perception of a given stimulus, such as butter, the knowledge that is semantically or lexically related to butter, such as bread, becomes automatically activated in memory. This activation makes bread more accessible in memory (i.e., more likely to be applied to incoming stimuli; Higgins, 1996), and thus facilitates the perception and assessment of it during the target response. A key finding from research using this paradigm is that related knowledge becomes activated without the perceiver’s intention, awareness, or control (Neely, 1977). Fazio and colleagues (Fazio et al., 1986; see also Fiske, 1982) applied this finding to the question of whether evaluative knowledge also becomes activated automatically on the perception of a stimulus. For example, does a positive evaluation (i.e., “good”) become activated as soon as someone reads the word puppy? To test this, the researchers developed an evaluative sequential priming paradigm in which primes that were either positive or negative were paired with targets that were either positive or negative but otherwise semantically unrelated to the primes. They found evidence for evaluative priming, such that people were faster at responding to the targets when they were

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preceded by evaluatively consistent versus inconsistent primes, even though the primes and targets were not otherwise related semantically. Since this first evidence was published, other researchers have replicated and extended the evaluative priming effect, and various alternatives have been offered concerning the underlying mechanisms of the effect (Castelli, Zogmaister, Smith, & Arcuri, 2004; Chaiken & Bargh, 1993; Fazio, 1993; Klauer & Musch, 2003; Klauer & Stern, 1992; Klinger, Burton, & Pitts, 2000; Wentura, 1999, 2000). Importantly, the evaluative priming paradigm can be used as a way to implicitly assess the evaluation of a prime stimulus simply by gauging whether the mere perception of the prime facilitates positive versus negative targets, compared to baseline responding to each kind of target (Fazio, Jackson, Dunton, & Williams, 1995; Ferguson, 2007b; Ferguson & Bargh, 2004; Wittenbrink, Judd, & Park, 1997, 2001). For example, it is possible to present pictures of members of a certain group as the prime stimuli and measure whether the perception of a face facilitates responding to positive versus negative targets (Fazio et al., 1995). In fact, this kind of paradigm is one of the two most popular measures of automatic evaluations. One important characteristic of this paradigm is that participants’ evaluations of the prime stimuli are assessed without their awareness, and participants are assumed to be unable to exert strategic control over the latency of their responses to the targets as a function of the nature of the primes.

The pairing of the categories would then be switched in the next task such that participants would have to press one key if the stimulus is elderly or negative, and another key if it is young or positive. The main analysis of these data consists of whether participants are faster at the first versus second sorting task. If they are faster on average at the second task, this implies that they have an easier time associating the elderly with negative things (and/or the young with positive things). The IAT has generated an incredible amount of research, spanning attitudes toward various groups, individuals, the self, and products (Greenwald & Farnham, 2000; Greenwald, Banaji, Rudman, Farnham, Nosek, & Mellott 2002; Jordan, Spencer, & Zanna, 2003; Marsh, Johnson, & Scott-Sheldon, 2001; Nosek, Banaji, & Greenwald, 2002). This task is implicit in nature because participants are not being asked to report their attitudes. Also, as in the evaluative priming task, the data from the IAT consist of the speed of participants’ responses. This means that it is very difficult for participants to manage or strategically conceal their underlying attitudes as this would require them to both detect differences in the speed with which they respond to targets across conditions, and to control their responses based on preconceived notions of appropriate responding. Moreover, also like the evaluative priming paradigm, the IAT demands quick responding and therefore does not give participants the necessary time to strategically edit their responses.

IMPLICIT ASSOCIATION TEST

MOTIVATIONAL NATURE OF AUTOMATIC EVALUATION

The other widely popular measure of automatic attitudes is the implicit association test (IAT; Greenwald et al., 1998). This paradigm also measures the degree to which people tend to associate a particular stimulus with positivity versus negativity, but does so in a different manner. In this case, participants are first asked to practice deciding on a computer whether a given stimulus belongs to one of two categories (e.g., young versus old people). For example, a word related to elderly people might appear on the screen and the respondent would have to press the key associated with elderly rather than the key associated with youth. In a second task, participants would have to judge each of a series of stimuli in terms of belonging to either positive or negative words (e.g., happy). In the next phase of the measure, participants would be asked to accomplish these sorting tasks simultaneously using two response keys. In this way, they would have to press one key if the stimulus that appears on the screen is either elderly or positive, and would have to press another key if the stimulus is either young or negative.

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What is the relationship between a person’s current goal pursuits and the automatic evaluations they make? To answer this question, first consider how researchers have understood the relationship between motivations and goals, on the one hand, and conscious or intentional evaluations on the other. Researchers across areas of psychology have long assumed a close correspondence between people’s preferences for stimuli and their motivations regarding those stimuli (Arnold, 1960; Bogardus, 1931; Chen & Bargh, 1999; Corwin, 1921; Doob, 1947; Frijda, 1986; Lang, 1984; Lazarus, 1991; Lewin, 1935; Mowrer, 1960; Osgood, 1953; Thurstone, 1931; Young, 1959). After all, one of the most fundamental axioms of motivation is the pleasure principle, or the notion that people approach things that make them feel good, and avoid those things that make them feel bad. As Bentham famously stated in 1789, “Nature has placed mankind under the governance of two sovereign masters: pain and pleasure. It is for them alone to point out what we ought

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to do, as well as to determine what we shall do.” Given that attitudes reflect the person’s assessment of whether the corresponding stimuli are good or bad, attitudes are therefore direct indications of our motivations toward those stimuli. But what about automatic (nonconscious and unintended) evaluations? Is the relationship between automatic evaluations and goals different in an interesting way from that between conscious evaluations and goals? Indeed, numerous researchers over the last couple of decades have argued just that: automatic, more than conscious, evaluations seem especially tied to people’s motivations because they facilitate people’s general goals of securing rewards and avoiding dangers and threatening stimuli (Chen & Bargh, 1999; Damasio, 1999; Duckworth, Bargh, Garcia, & Chaiken, 2002; Fazio, 1989; Ferguson & Bargh, 2002, 2004; Lang, Bradley, & Cuthbert, 1990; LeDoux, 1996; Öhman, 1986; Pratkanis, Breckler, & Greenwald, 1989; Roskos-Ewoldsen & Fazio, 1992; Smith et al., 1956). They do so by quickly providing needed and important information about the nature of the stimuli in a person’s environment. The nearly instantaneous delivery of this kind of relevant information can enable people to prepare to act and react to the objects in their surroundings in an adaptive, goal-consistent manner. Automatic evaluations are functional also because they direct people toward those stimuli that have the most goal-relevance for them. For instance, Roskos-Ewoldsen and Fazio (1992) presented participants with a series of displays of line drawings of everyday objects (e.g., elephant, bug, bike) for very brief amounts of time. Using recall paradigms, they found that participants automatically attended, visually, to those objects toward which they possessed strong, automatically activated attitudes. In this way, people are immediately alerted to those objects that hold the most potential for their goals, either in terms of reward or danger. There exists substantial research showing how automatically activated attitudes facilitate judgment and decision making, and serve as reliable, effective guides toward goal-relevant behavior (Fazio, 1989, 1990; Fazio & Williams, 1986; Petty & Krosnick, 1995). However, this conclusion regarding the motivational property of automatic evaluations is based on a single processing characteristic of how quickly they are generated, rather than anything about their content, or their relative intensity across situations. Does the content or intensity of automatic evaluations reflect anything about people’s current goals? If the way in which people automatically evaluate stimuli reflects something about their

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motivational stance toward the objects, then the content of automatic evaluations (i.e., good vs. bad) should fluctuate along with the person’s goals regarding the objects. That is, they should reflect what the person wants at the moment (Lewin, 1926). Positive automatic evaluations should emerge when the person currently possesses an approach stance toward the objects, and negative automatic evaluations should automatically emerge when the person holds an avoidant stance toward the objects. Moreover, there should be some correspondence between people’s chronic goals toward objects, and their automatic evaluations toward them. We now turn to several recent lines of empirical support for these propositions.

AUTOMATIC EVALUATIONS AND CURRENTLY ACCESSIBLE, CONSCIOUS GOALS Recently, several lines of research have examined whether a person’s currently accessible, conscious goals influence the way in which that person automatically evaluates the stimuli in their environment. Sherman, Presson, Chassin, Rose, and Koch (2003) examined the role of people’s goal to smoke and their automatic evaluations toward smoking paraphernalia (e.g., cigarettes). All participants were instructed to refrain from smoking before arriving at the lab. Whereas some participants were allowed to smoke for a few minutes before completing the experiment, others were not allowed to smoke. This manipulation ensured that some participants had the goal to smoke whereas others had just satisfied their need. All participants then completed a measure of their implicit evaluations, and the results showed that those who had the current need to smoke evaluated the smokingrelated stimuli as relatively more positive than those who had just fulfilled their need. These findings demonstrate that automatic evaluations seem to reflect the degree to which the perceiver currently wants to approach the respective stimuli. In another line of studies, we (Ferguson & Bargh, 2004) examined the goals of achievement, thirst, and athleticism. We wanted to test whether the desire for, versus fulfillment of, a variety of goals would dictate people’s immediate evaluations of stimuli related to those goals. In the first experiment, participants were asked to play a word game and they were told either that the game measured their verbal skills or that it was being developed for use in future research. They were instructed that in the game, they would earn a point for every word they could create out of a given set of letters, would earn extra points if the word was a noun, and still more points if the word was a noun that started with the letter “c.” They then

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played the game for about 5 min, and then completed a measure of their automatic evaluations. At that point, half of the participants believed that they were finished with the word game, whereas the other half of the participants believed that they were going to be playing a second round of the game after the computer task (i.e., the automatic evaluation measure). In this manner we manipulated whether the task goal was still active or “turned off” because the task and goal pursuit had been completed (Lewin, 1926). We then measured the participants’ automatic evaluations toward stimuli related to the game (e.g., points, achieve, nouns, c, create). The main finding was that the content of participants’ automatic evaluations toward game-related stimuli was a function of how much they cared about their performance in the game, and also whether they thought they would be playing the game again. Only those who thought that their verbal skills were being measured, and who believed that they would be playing again, produced positive automatic evaluations of the words. The findings from this experiment suggest that one’s current (rather than recently fulfilled) achievement goal can influence automatic evaluations both of stimuli that have recently been designated as goal-relevant (e.g., noun, c, game) as well as stimuli that are chronically relevant to achievement (e.g., achieve, win). Does the positivity of automatic evaluations depend on the extent to which a stimulus is related to the person’s current goal? For example, are stimuli that are strongly versus weakly related to a current goal automatically evaluated in a more positive way? This would suggest the prediction, on functional grounds, that those stimuli that are most able to fulfill a goal are immediately evaluated as the most desirable. Our second experiment tested this hypothesis. Participants were instructed to refrain from drinking anything for three hours before arriving at the experiment, and thus they were all thirsty. Participants were then asked to sample either a variety of bottled waters, or a variety of dry, salty, sourdough pretzels. Whereas the thirst of those who sampled the water was sated, it was exacerbated for those who had to sample the pretzels. In this way, the goal of quenching one’s thirst was recently fulfilled for some participants but was still active for the others. All participants then completed a measure of their automatic evaluations of stimuli varying in their relevance to the goal. Based on pretest data, the stimuli were strongly (e.g., water, juice, drinking), indirectly (e.g., glass, bottle), weakly (e.g., coffee, beer), or not at all (e.g., chair, window) relevant to the thirst goal. Those

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who were thirsty at the time of the measure gave automatic evaluations of the strongly relevant stimuli that were significantly more positive than their evaluations of the other stimuli, as well as significantly more positive than made by the nonthirsty participants. These findings demonstrate that automatic evaluations are prospective in that they reflect the upcoming or immediate utility of the stimuli, rather than only their recently experienced utility. Also, the results show that automatic evaluations are sensitive to the degree to which a certain stimulus can facilitate the perceiver’s current goal. A final question that we examined was whether participants’ automatic evaluations would be sensitive to the strength of the perceiver’s current goal. In this experiment, all participants were self-described athletes, in that they played athletics regularly and cared about their identity as an athlete. However, those who were varsity athletes cared more than those who were intramural (and nonvarsity) athletes. Participants were asked to describe either a recent failure or success in athletics, or were asked to describe their academic schedule. Based on selfcompletion theory (Wicklund & Gollwitzer, 1982), we expected that those who were asked to describe a recent athletic failure experience would be the most motivated to reclaim and reestablish their athletic identity, compared with those in the control condition and also compared to those who wrote about success. We then assessed participants’ automatic evaluations of stimuli that were either relevant to the athletic goal (e.g., agile, athletic) or irrelevant to the goal (e.g., chair, smart). The results showed that those who cared most about the goal—the varsity athletes—displayed the most positive automatic evaluations toward the goal-relevant stimuli, relative to the intramural athletes, and also compared to the goalirrelevant stimuli. Together, the findings of Sherman et al. (2003) and Ferguson and Bargh (2004) demonstrate that people’s currently accessible, conscious goals cause them to automatically evaluate the stimuli in their environment as a function of whether those stimuli can enable them to reach the goal. This suggests that automatic evaluations are motivational (and functional) in nature because they both provide information that is important to people’s goals quickly, and also because they reflect people’s current motivational priorities. In other words, the motivational nature of automatic evaluations goes beyond a single processing characteristic of the evaluations—the speed with which they are made—to their content and intensity within goal-relevant conditions. We now consider some implications and extensions of these findings.

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AUTOMATIC EVALUATIONS AND CURRENTLY ACCESSIBLE, NONCONSCIOUS GOALS The findings from the experiments described above suggest that automatic evaluations reflect the perceiver’s currently rather than recently active goals. Motivational influences on automatic evaluations are also moderated by the strength or importance of the goal to the individual, as well as by the relevance of the evaluated stimulus for reaching that goal. An important remaining question is whether the goal has to be pursued in a conscious, intentional, verbally reportable manner for these effects to occur. In each of the studies reviewed above, the participants were consciously induced into the goal state, and could easily have been knowingly and intentionally thinking about how they might want to fulfill it. For those in the Sherman et al. (2003) studies, the cigarette-deprived smokers could well have been thinking about how good a cigarette would taste. For those in the Ferguson and Bargh (2004) studies, the thirsty participants could have been thinking about several things: achieving and scoring points with nouns (Experiment 1), wanting some water (Experiment 2), or improving their athletic performance (Experiment 3). Thus, it remains possible that the effects of goals on the automatic evaluation of goal-relevant stimuli are contingent on the perceiver consciously thinking about those objects. Do goals influence automatic evaluations even when those goals are nonconsciously induced? There are several demonstrations now that goals can be activated from memory and influence behavior without the person’s awareness or intentions (Aarts, Gollwitzer, & Hassin, 2004; Bargh, 2007; Bargh, Gollwitzer, Lee-Chai, Barndollar, & Troetschel, 2001; Chartrand & Bargh, 1996; Fishbach, Friedman, & Kruglanski, 2003; Fitzsimons & Bargh, 2003; Shah, 2003; Shah, Kruglanski, & Friedman, 2002). For instance, the goal to attain high performance on a given task can be activated merely by reading words related to achievement, with positive effects on participants’ success and persistence on the assigned task (Bargh et al., 2001). Thus, one might expect other effects of a nonconsciously activated goal, such as on the individual’s immediate and spontaneous evaluations of the goal-relevant stimuli in their environment. If goals automatically influence how people evaluate the stimuli in their environment, then even a nonconsciously activated goal should lead to the kinds of motivational effects on evaluation as with the studies, described above, involving conscious goal pursuit. Another relevant question is whether such motivational influences on automatic evaluations are functional for

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the individual. We have been assuming here that if one’s currently active goal fosters positive automatic evaluations of goal-helpful stimuli, the probability of one’s attaining the goal will be enhanced. But is this actually the case? None of the experiments described so far have directly examined this question. One way to approach it would be to examine whether those participants who are the most skilled and successful in a goal domain are also the most likely to show the effects of goal activation on automatic evaluations. Thus, for example, when the goal of academic achievement has been activated in memory, those who are skilled in that domain should be the most likely to show more positive automatic (immediate, unintended) evaluations of the goal-friendly stimuli in that domain. Some very recent research has addressed these questions (Ferguson, 2007c). In one experiment, participants were nonconsciously induced into either an academic goal, a goal unrelated to academics (i.e., a social goal), or no goal. Participants completed a scrambled sentence task (Srull & Wyer, 1979) wherein they were asked to make grammatically correct sentences out of sets of five words each. Presented in some of the sentences were words related to the academic goal (e.g., study, school, smart) or to the social goal (e.g., friends, laughing, social), depending on the condition to which participants had been randomly assigned. In the control condition, none of the words in the sentences were related to the focal goals. This method has been used previously to activate a construct out of participants’ awareness, and indeed, none of the participants in this study reported any awareness of pursuing the primed goals. Once participants had been primed with a goal construct (or not), they completed a measure of their automatic evaluations of both words related to the academic goal (e.g., grades, graduation), and unrelated to the goal (e.g., chair, window). From the above considerations, it was predicted that those participants nonconsciously primed with an academic goal should automatically evaluate the academic stimuli as most positive, relative to the irrelevant stimuli; further, the academic goal-primed participants were predicted to evaluate the academic stimuli more positively than would those participants who had been primed with a goal unrelated to academics (the social goal condition) or no goal at all. The results supported these predictions. Those in the academic-goal condition automatically evaluated the academic stimuli as most positive, compared to the other relevant cells. It was further predicted that those who are most skilled in the academic domain should be the most likely to show these kinds of effects,

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and this too was confirmed: those participants with the highest grade point average (GPA) were the most likely to show the academic-goal priming effect on the automatic evaluation of academic-related stimuli. Taken together, this set of findings suggests that a goal can influence how people automatically evaluate the stimuli in their surroundings even when the goal has been activated and is operating nonconsciously. In addition, this effect seems to emerge particularly for those who are skilled in that goal domain, in harmony with the notion that motivational influences on evaluation are functional for the individual. The mere activation of the goal, even via minimal processing and awareness, is enough to change the way in which the perceiver sees and responds to the environment. In our view, this effect of active goals on evaluation is the affective equivalent of Bruner’s (1957) notion of “perceptual readiness,” in which active goals cause goalrelated mental representations to become more accessible or ready to be activated by relevant environmental stimuli. Just as we become, during goal pursuit, perceptually ready to see and hear goal-relevant objects and events in our environment, the recent research described above shows us to become “evaluatively ready” to positively evaluate and behaviorally approach those things that will facilitate the pursuit of the goal. Another interesting aspect of these findings is that those skilled people primed with the academic goal automatically evaluated the academic-related stimuli as more positive than those who had been primed with the social goal. Previous research suggests that when people skilled at a certain goal perceive a temptation (e.g., TV) that is deleterious to that goal, the skilled-goal increases in accessibility and strength (Fishbach et al., 2003). This work might suggest that those primed with a social goal should evaluate academic-related stimuli just as positively as those primed with the academic goal itself, and yet this did not happen. However, there is an important difference between distractions and temptations to a goal, on the one hand, and reminders of an equally important competing goal, on the other. In the social goal condition described above (Ferguson, 2007c), participants were not primed with social temptations—rather they were primed with the goal of being with friends, one of the most basic and fundamental goals in human nature (Baumeister & Leary, 1995; Brewer, 1991). Based on the above results, we would suggest that skilled people are not “blind” to the importance of other competing goals than the one at which they are skilled. Instead, their implicit readiness to approach that goal can be deactivated when it conflicts with another important goal that is currently active (see

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Morsella, 2005; Oettingen et al., 2006, for more on how such goal conflicts are resolved nonconsciously.). Although these findings suggest that nonconscious goals can influence automatic evaluations of goalrelevant stimuli in the environment, the effect seems limited to those stimuli that can help them achieve the goal. What about those stimuli that might distract or tempt the person away from the focal goal? Although it is surely helpful for a person’s currently accessible goal to render as positive those things that can enable the pursuit of that goal, it must also be functional for the goal to render as negative those things that might undermine or distract the pursuit of the focal goal. If such an effect emerged, it would provide support for a kind of “evaluative goal shielding” as discussed by Shah, Friedman, & Kruglanski (2002). That is, the focused pursuit of a given goal might be protected or enhanced by the negative automatic evaluation of distractions to that goal pursuit. This question was tested in another experiment (Ferguson, 2007c) in which participants were subliminally primed (or not) with the goal of academic achievement. They then completed an automatic evaluation measure of stimuli, some of which were temptations to the academic goal (e.g., TV) and some which were not. The results showed that those who were primed with the academic goal automatically evaluated the social temptations as more negative than the other stimuli; also, the academicprimed participants showed more negative automatic evaluations of the social temptations than did the nonprimed participants. Importantly, this effect emerged only for those with a high GPA (a marker of academic goal-skill), again showing the functional benefits of motivational influences on automatic evaluation. These preliminary findings suggest that even goals that are nonconsciously activated in memory can influence the way in which people automatically evaluate the stimuli in their environment. Thus, the empirical findings described above regarding the effect of conscious goal pursuit on evaluations (Ferguson & Bargh, 2004; Sherman et al., 2003) are not contingent on people intentionally thinking and deliberating about how they might accomplish that goal. Furthermore, these more recent findings (Ferguson, 2007c) extend the evaluative reach of currently (and nonconsciously) accessible goals to those stimuli that would undermine the pursuit of that primed goal, especially in the case of people who are skilled at pursuing that goal. We now consider the extent to which automatic evaluations are influenced by the person’s chronically accessible (latent) goals, even when these are not currently active.

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AUTOMATIC EVALUATIONS AND CHRONICALLY ACCESSIBLE GOALS Although the recent research described above suggests that people’s currently accessible goals can influence their automatic evaluations toward stimuli relevant to the goal, the motivational influence on evaluations may not be limited to those goals that are currently active. Surely people still automatically evaluate stimuli as good or bad even when those stimuli are unrelated to what the person is currently trying to accomplish. Indeed, it would seem dysfunctional to not do so (Chen & Bargh, 1999; Duckworth et al., 2002; Fazio, 1989; Ferguson & Bargh, 2002, 2004; Lang et al., 1990; LeDoux, 1996; Öhman, 1986; Pratkanis et al., 1989; Roskos-Ewoldsen & Fazio, 1992; Smith et al., 1956). We argue here that one’s automatic evaluation of stimuli should, on average, reflect the typical importance of that stimulus for someone’s goals. In this way, people may automatically evaluate puppies as relatively positive on average because they are typically always appealing (and nonthreatening), and cockroaches as relatively negative on average because they are typically always aversive and disgusting. This reasoning implies that just because an athlete’s automatic evaluation of agile becomes more positive when she or he is currently concerned with that goal, it should still be relatively more positive on average than for someone for whom the athletic goal is unimportant. In support of this claim, there is considerable evidence that people’s automatic evaluations toward a range of stimuli on average predict their approach versus avoidance behaviors toward those stimuli (Blair, 2002; Chen & Bargh, 1999; Dovidio, Kawakami, & Gaertner, 2002; Dovidio et al., 1997; Duckworth et al., 2002; Epley & Caruso, 2004; Fazio et al., 1995; Haidt, 2001, 2003; Kawakami & Dovidio, 2001; Lambert, Payne, Ramsey, & Shaffer, 2005; McConnell & Leibold, 2001; Nosek et al., 2002). Someone who displays a positive automatic attitude toward stereotypically black names, for instance, is more likely to display warmth and friendliness to black people compared with someone who displays a negative attitude toward the same group (for a review see Fazio & Olson, 2003). Automatic evaluations have been found to be particularly predictive of those behaviors that are spontaneous and difficult to control, more so than of obvious and overt behaviors (Blair, 2002; Dovidio et al., 2002; Dovidio et al.; Ferguson, 2007b; Kawakami & Dovidio, 2001). Overall, this body of research indicates that people’s automatic evaluations of stimuli are generally predictive of how they will tend to act toward those stimuli across time and situations. Because people’s

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approach and avoidance behaviors toward stimuli reflect their motivations toward those stimuli, automatic evaluations can be understood as reflections of motivations. Interestingly, almost the entire literature on the predictive validity of automatic evaluations has focused on people’s immediate evaluative responses to graspable stimuli, or those stimuli toward or away from one can physically move. For instance, almost all of the literature on how automatic evaluations toward groups predict behavior with group members has used stimuli such as group names, group labels, or faces of group members (Fazio & Olson, 2003). And yet, what about the more abstract values, goals, and ideals that undoubtedly predict people’s behavior across physical targets and situations? If automatic evaluations reflect the perceiver’s tendency to approach the respective stimuli, then automatic evaluations toward abstract goals, such as equality, should reflect the perceiver’s tendency to approach—or pursue—that goal. The more one immediately and unintentionally evaluates the word equality with positivity, the more that person should be expected, on average, to demonstrate egalitarian behavior toward others. How will such automatic evaluations of abstract concepts compare with what is known about how people evaluate concrete, graspable stimuli? The first thing to note is that the influence of any evaluation will depend on the accessibility of its referent (i.e., the respective attitude object). The more the referent is accessible in memory, the more its corresponding attitude should influence behavior toward that referent (Higgins, 1996). In addition, research also shows that the accessibility of abstract versus concrete memories fluctuates across circumstances (Trope & Liberman, 2003; Vallacher & Wegner, 1987; Wegner, Vallacher, Kiersted, & Dizadji, 1986). Thus, there is some reason to expect that automatic evaluations of abstract goals might sometimes be more influential on behavior than automatic evaluations toward concrete stimuli related to that goal. Ferguson (2007b) examined the above questions in a series of experiments. In the first of these, participants arrived at the lab and completed an automatic evaluation measure of stimuli related to the goal to be thin, and also provided their explicit attitudes toward the goal and the strength of their current desire to reach the goal. Participants were then contacted about a week later through e-mail, and asked to indicate how many times over the past week they had engaged in each of a variety of behaviors, and also how many times they planned to engage in those same behaviors during the upcoming week. Among the behaviors was “resisting tempting food”—a behavior that had been rated in a pilot study as

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the most effective way to meet the goal of being thin. The results showed that participants’ immediate, unintentional evaluations of the goal significantly predicted their reported successful goal pursuit, and did so above and beyond their explicit ratings of the desirability of the goal, and their explicit attitude toward the goal. What about automatic evaluations of the goal to be thin versus the tempting foods that need to be avoided in order to meet the goal? This comparison was examined in the next experiment. Participants arrived at the lab and indicated how often they regulated their intake of fattening foods. Then between 3 and 5 weeks later they came back to the lab and completed a measure of their automatic evaluations of the goal to be thin, as well as a variety of tempting foods related to the goal. The results showed that participants’ automatic evaluations of the goal significantly predicted their reported goal pursuit, while their automatic evaluations of the tempting foods did not. This set of findings indicates that automatic evaluations of goals are sometimes more predictive of goal pursuit than the concrete stimuli toward which goalrelevant behavior is directed. In the above two experiments, however, participants merely reported goal pursuit rather than demonstrated actual goal pursuit. To test whether automatic evaluations of the goal to be thin would predict how much of a tempting food one would eat, participants arrived at the lab and were told that they would sample and comment on products as part of a marketing study. They were assigned to taste either goal-relevant, fattening (cookies) or goalirrelevant, nonfattening (low-calorie mints) snacks. Right before they were asked to sample the food, they completed an automatic evaluation measure in which their evaluations toward the goal, as well as the goalrelevant target of behavior (cookies), were measured. The results showed that their automatic evaluations of the goal predicted their consumption of the goal-relevant snack, but not the goal irrelevant snack. Their automatic evaluations of the target of behavior (cookie) did not predict their consumption of the snack, however. Finally, in the last experiment, the participant’s automatic and explicit evaluations of an abstract goal, along with concrete stimuli related to that goal, were measured. Moreover, participants’ overt as well as subtle goal-relevant behaviors were assessed. In particular, participants’ automatic evaluations toward the goal of egalitarianism and a relatively more concrete target of egalitarian behavior— elderly people—were measured. Participants then provided their explicit attitudes toward the goal and the concrete goal-relevant stimulus. Finally, they were asked to express their support for a number of federal and state

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sponsored policies and programs. Included in this list of policies was Medicare, the federal program that provides financial assistance to elderly people. Previous research has suggested that subtle prejudice toward a group is related to decreased support for programs that target that group (Dovidio, Glick, & Rudman, 2005; Levy & Schlesinger, 2005; McConahay, 1983, 1986; Swim, Aiken, Hall, & Hunter, 1995), and thus it was expected that participants’ automatic evaluation of the goal of equality would predict their subtle prejudice toward the elderly, in terms of their support of Medicare. Participants also were explicitly asked to what extent a negative stereotypical trait of the elderly (i.e., rigidity) was true of elderly people in general; this constituted the blatant or overt indication of prejudice toward the elderly. It was expected that their automatic evaluation of the goal might be less effective at predicting this overt expression of prejudice, in line with previous research (Asendorpf, Banse, & Mücke, 2002; Devine, 1989; Dovidio et al., 1997, 2002; Egloff & Schmukle, 2002; Fazio, 1990; Wilson et al., 2000). Indeed, the results suggested that their automatic evaluations toward the goal predicted their subtle expression of prejudice but not their overt expression of prejudice. However, their explicit attitude toward the group did predict their overt expression of prejudice toward the group. The pattern of findings thus replicated the main result from the previous experiments that people’s automatic evaluations of a goal do seem to reliably predict their actual behavioral pursuit of that goal. Also, this may be particularly true for subtle versus blatant goal-relevant behaviors. This experiment also again suggests that automatic evaluations of goals can prove more predictive of goal pursuit than automatic evaluations of concrete stimuli related to the goal. Together, the results from this line of experiments suggest that automatic evaluations of goals may on average reflect the importance of the goals to the perceiver. But, when should such implicit evaluations out-predict more explicit motivations? Firstly, automatic evaluations should out-predict explicit motivations when it is difficult for the person to accurately introspect on how much they want to reach the goal. Note that it may be very easy for people to say whether they want, versus do not want, a particular goal, but it might be more difficult for them to precisely know just how much they want that goal. In such a case it may be that the degree of people’s unintentional, and immediately generated, positivity to words related to the goal ends up being a more accurate index of how much they, on average, pursue and want the goal. For example, the participants in the above research might

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have known that they cared about being egalitarian, but not been able to exactly pinpoint the degree of their commitment to the goal. Secondly, automatic evaluations of goals should also better predict actual goal pursuit behavior than should explicit ratings of the strength of those motivations when the particular goal is accompanied by normative social or impression management pressures to explicitly respond in a certain way. For instance, there is considerable social pressure to espouse and endorse the goal of being egalitarian, and it may be that people’s explicit commitment to this kind of goal is a poor reflection of how much they actually care about it. Again, in such a case it may be that people’s spontaneous evaluation of words related to equality ends up being a better indication of how likely they are to pursue that goal in future circumstances. When should automatic evaluations of goals out-predict automatic evaluations of more concrete stimuli? This question can essentially be translated into the question of when concrete versus abstract knowledge is likely to be most accessible in memory. There is a burgeoning literature on this topic, and researchers have identified a number of determinants, including temporal distance from an event being judged or evaluated (Trope & Liberman, 2003), the difficulty or familiarity of an action (Vallacher & Wegner, 1987), psychological distance (Trope & Liberman, 2003), spatial distance (Henderson, Fujita, Trope, & Liberman, 2006), and power (Smith & Trope, 2006). For example, Vallacher and Wegner (1987) argued that when an action is familiar, and when both concrete and abstract knowledge related to the action exists in memory, the abstract knowledge is likely to be more accessible in memory than the concrete knowledge. Thus, when a person is climbing a tree and is asked what he or she is doing, the person is likely to say something about having fun (an abstract answer) rather than about holding onto tree limbs and branches (a concrete answer). In other words, the why, or high level, knowledge tends to be more accessible than the how, or low level, knowledge. In such cases, the evaluative information that is associated with the abstract knowledge (e.g., goals) should also be more accessible, and thus more influential and predictive, than the evaluative information associated with the concrete knowledge. In the experiments described above (Ferguson, 2007b) in which people’s automatic evaluations of goals tended to be more predictive of their goal pursuit compared with their evaluations of relatively more concrete stimuli, it might have been the case that people were relatively familiar with those goal domains, and familiar with their strategies of

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goal pursuit and self-regulation. Thus, their abstract knowledge (including knowledge about goals and values) may simply have been more accessible than their knowledge about the particular concrete items and objects relevant to the goal. We now turn to a discussion of how automatic evaluations might be especially contingent on a person’s goals and motivations.

MOTIVATION NATURE OF AUTOMATIC VERSUS EXPLICIT EVALUATIONS Earlier in the chapter we discussed how automatic evaluations have been considered to be tied to motivations based on the speed with which they deliver important information to the perceiver. We argued that the motivational perspective of such evaluations can be considerably broadened in that automatic evaluations should actually reflect the content as well as intensity of the perceiver’s current and chronic goals. However, how does this characteristic of automatic evaluations compare with the operation of explicit evaluations? That is, whereas automatic evaluations are clearly more functional than explicit evaluations at least in terms of the speed with which they are generated, are they ever more reflective of people’s goals? On the one hand, people’s explicit evaluations can be clearly and directly reflective of what they want. People’s explicit evaluations of the stimuli in their surroundings do fluctuate with their current goals regarding those stimuli. In fact, people’s expressed desires for certain stimuli are often considered as a classic signature of a particular goal. When people (explicitly) express desire for food and drink, they are considered to have the goals of hunger and thirst, respectively (Cabanac, 1971). When people express their desire for meaningful relationships with others, they are understood as having the goal of belongingness. There is a long history in psychology of the tight connection between what people say they like and dislike, and what they say their goals and motivations are (Ajzen, 1991; Bandura, 1986; Cabanac, 1971; Deci & Ryan, 1985; Locke & Latham, 1990). However, on the other hand, as mentioned earlier, there are reasons why what people say they want does not always match up well with what they actually do in terms of motivational behavior (approach versus avoiding). Because people might not be able to always accurately introspect on the intensity of their goals, perhaps especially across situations, there may be times when their automatic evaluation of a goal is more predictive of their goal-relevant behavior, as we have discussed. Furthermore,

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because people might be reluctant to express their true inclination toward some goal (either to others or to themselves), their automatic (unintentional) evaluations of goals might at times be more accurate indications of how they will act in actual goal-relevant situations (this should be especially true under time pressure or in complex, information-rich environments). Finally, people may simply be unwilling to exert the control necessary to act in line with their expressed preferences. There is considerable empirical support in the self-regulation literature for the dissociation between what people say they like and dislike, and what they in fact do (for reviews see Baumeister & Vohs, 2004; Carver & Scheier, 1981, 1998; Loewenstein, 1996). People’s expressed preferences in domains of self-control and regulation are often at odds with how they actually behave. Moreover, there is also evidence for the dissociation between expressed preferences and behavior in recent research on automatic evaluations and goals. In the work by Ferguson and Bargh (2004), in the first experiment that examined the effect of the achievement goal on automatic evaluations, participants were also asked to indicate their explicit evaluations toward the stimuli. The results showed that whereas the goal and timing conditions influenced participants’ automatic evaluations as described earlier, they did not influence their explicit evaluations. This is some preliminary evidence that people may not always be able or perhaps willing to adjust their explicit evaluations toward their currently active goal, in line with our discussion here. Another line of evidence suggesting a possible dissociation between people’s explicit evaluations and their goal pursuit comes from the recent work on automatic evaluations of end-states (Ferguson, 2007b). In two experiments, people’s explicit attitudes toward the abstract end-states did not reliably predict their behavior relevant to the end-state. In one experiment, their explicit attitude toward the goal of being thin did not predict their pursuit of this goal over the following week. In the other experiment, participants’ explicit goal of equality did not predict their subtle expression of prejudice toward the elderly. In both cases, this disconnect may have emerged either because the participants were unable to introspect accurately on their desire for the goal, or were unwilling to do so. Future research is expected to continue to address the correspondence between people’s goals, and their automatic versus explicit attitudes, but at this juncture we argue that automatic evaluations may be especially reflective of, and therefore predictive of, people’s underlying motivations and goals.

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CONCLUSIONS In this chapter, we considered the motivational nature of automatic evaluations. We first considered the extent to which evaluations in general are closely tied to motivational behavior given the classic definitions of motivation and evaluations. We then reviewed recent research that examined questions relevant to this topic. Namely, we reviewed findings showing that a person’s currently accessible, conscious goal influences how that person automatically evaluates the stimuli in her or his environment: people evaluate as positive those stimuli that can help them achieve the goal. Additionally, a goal does not have to reside in conscious awareness in order for it to influence automatic evaluations. Nonconsciously induced goals also can influence the automatic evaluation both of stimuli that can help the activated goal, as well as stimuli that can harm the activated goal. Recent findings also suggest that the effect of goals on automatic evaluations is functional in that it seems to emerge most strongly for those who are skilled at the particular goal domain. We also speculated that automatic evaluations might be more closely tied to goals and motivations than are explicit attitudes, and considered some new findings relevant to this matter. Overall, the evidence supports concluding in favor of a strong and direct influence of motivational states on how people naturally and nonconsciously evaluate the objects, people, events, and even abstract concepts and issues that make up their psychological environment.

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Structure of Evaluation Functional Neuroarchitecture 18 The of Evaluative Processes Gary G. Berntson and John T. Cacioppo CONTENTS Functional Neuroarchitecture of Evaluative Processes.........................................................................307 Levels of Organization in the Nervous System .....................................................................................308 Neural Hierarchies ...........................................................................................................................308 Neural Heterarchies ..........................................................................................................................309 Re-Representation and Organization of Evaluative Substrates............................................................. 310 Lower Levels and Pre-Motivational Functions ................................................................................ 310 Intermediate Levels: Intake and Rejection Responses and Taste Hedonics .................................... 311 Higher Neural Levels and the Elaboration of Evaluative Processes ................................................ 311 Evaluative Space Model and the Neuroarchitecture of Evaluative Processes ...................................... 315 Fine Features of the Evaluative Space Model ....................................................................................... 316 Summary ............................................................................................................................................... 318 References ............................................................................................................................................. 318

FUNCTIONAL NEUROARCHITECTURE OF EVALUATIVE PROCESSES A fundamental computation performed by humans is the differentiation between hostile and hospitable stimuli. Survival depends on the ability to perform this computation and adapt one’s behavior accordingly. Evaluative processes refer to the operations supporting the computation, or set of computations, that are involved in the differentiation of hostile from hospitable stimuli. In this chapter, we review evidence that evaluative processes are fundamental to survival, are universal in humans and other animals, are manifest across the span of ontogeny as well as phylogeny, and represent multifarious computational operations, which differ predictably across levels of the neuraxis. Traditionally in psychology, this computation was conceived as a unitary operation or process, with the outcome including a positioning of the stimulus at a point along the dimension of valence (Osgood, Suci, & Tannenbaum,

1957). Allport (1935) went so far as to ascribe to this computation a mental representation, a neural locus, and a behavioral predisposition: “a mental and neural state of readiness, organized through experience, exerting a directive or dynamic influence upon the individual’s response to all objects and situations with which it is related.” This was said to promote acceptance of, approval of, support of, or approach toward hospitable stimuli, and that promote rejection of, disapproval of, opposition to, or withdrawal from hostile stimuli. Allport (1967) and Osgood et al. (1957) wrote about what today would fall under the rubric of explicit evaluative processes—computations that are amenable to self-awareness and self-report. In recent years, notions about the computations of stimulus hospitability or hostility have been expanded to include implicit as well as explicit evaluative processes (Greenwald et al., 2002). Implicit evaluative processes represent the positioning of the stimulus along the valence dimension that, 307

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although reliably measurable, is not easily amenable to self-awareness, self-report, or self-control. Implicit evaluative processes can also differ in the specific information that is activated, but they too are generally conceived as instantiated in a unitary computation in which the positioning of the stimulus along a valence dimension accords with the probability distribution of what the same or similar stimuli have turned out to be in the past history of the species and the individual. Evaluative processes are considerably more diverse than suggested by the simple implicit or explicit dichotomy. Evaluative processes encompass the broad range of operations and mechanisms that allow an organism to appraise the adaptive significance of stimuli or contexts, and to respond accordingly. Because of their critical survival functions, primitive (implicit) evaluative mechanisms have been highly conserved through evolution and more sophisticated; higher-level (explicit) evaluative processes have been hierarchically overlaid on these primitive substrates through evolution (Jackson, 1884/1958; MacLean, 1977, 1985). The influential 19th century neurologist, Jackson, noted that this entails the elaboration and “re-representation” of functions across levels of the neuraxis—from lower spinal systems to higher cortical association areas. This is echoed in MacLean’s concept of the triune brain and its reptilian, paleomammalian, and neomammalian components. This neuroarchitectural hierarchy underlies and constrains evaluative processes. The present chapter will consider the structural and functional organization of evaluative systems and the psychological and behavioral implications of the multiple levels of function in evaluative mechanisms. The terms level and multilevel have been used to distinguish between the levels of organization (e.g., the hierarchical organization in neural systems) as well as the levels of analysis or explanation (e.g., molecular, cellular, behavioral, social) at which a phenomenon can be explicated (Berntson & Cacioppo, 2004; Cacioppo & Tassinary, 1990; Cacioppo, Berntson, Sheridan, & McClintock, 2000; Larson et al., in press). These are not orthogonal dimensions, however, and multilevel approaches often encompass both. The present chapter will focus on the multilevel organization in evaluative systems, across levels of analysis.

LEVELS OF ORGANIZATION IN THE NERVOUS SYSTEM In his essay “Evolution and dissolution of the nervous system,” Jackson, emphasized the multilevel structure of

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brain organization and function (Jackson, 1884/1958). In contrast to the view that the evolutionary emergence of higher levels of the neuraxis come to replace or bypass lower-level organizations and functions, Jackson noted that evolution results in a progressive neurological layering, or multilevel re-representation of functions. The higher-level functional re-representations are characterized by elaborated networks with progressively greater flexibility and sophistication. But rather than replacing lower mechanisms, re-representative systems extensively interact with and depend upon lower substrates in a hierarchical-like fashion.

NEURAL HIERARCHIES Functional hierarchies are ubiquitous in neural systems. An example can be found in motor systems, which control somatic muscles of skeletal movement. As documented by early investigators, such as Sherrington (1906), basic somatomotor control is effected at the level of the spinal cord, with spinal reflexes representing the lowest central level in somatomotor control systems. Spinal reflex circuits are relatively simple and may be comprised of a single central synapse. The monosynaptic stretch reflex, exemplified by the knee jerk reflex to the physician’s rubber mallet, is one example. This reflex entails an afferent somatosensory link arising from muscle stretch receptors that synapse directly on the lower motor neurons controlling that muscle. This simple circuit (Figure 18.1) provides for a reflexive Stretch afferents

Motor efferents

Extensor muscle

Flexor muscle Inhibitory interneurons

(A) Monosynaptic stretch reflex

(B) Reciprocal innervation

FIGURE 18.1 (A) Stretch reflex. Basic parallel circuits of the flexor and extensor stretch reflex. (B) Reciprocal innervation, an example of Sherrington’s alliance of reflexes. Dotted lines represent inhibitory interneurons which achieve a level of reciprocal integration between flexor and extensor motor neuron pools.

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The Functional Neuroarchitecture of Evaluative Processes

contraction of the stretched muscle, which tends to compensate for the perturbing stretch. Stretch reflexes exist in all major classes of somatic muscles, including flexor muscles (which generally adduct or bring limbs toward the body) and extensor muscles (which generally abduct, or draw limbs away from the center of mass). Opponent flexor (e.g., biceps) and extensor (e.g., triceps) reflexes antagonize one another and promote opposite outcomes for the limb (flexion and extension, respectively). The basic neural circuits of these reflexes are independent and organized in parallel, and they have limited inputs and outputs, allowing for rapid, efficient processing (Sherrington, 1906). The cost of this efficiency, however, is that lower-level systems have limited integrative capacity. Moreover, they can be in conflict. Simultaneous stretch of both the flexor and extensor muscle may lead to a reflexive increase in muscle tension in both muscles, but because they are opposed in their actions, there may be no resultant limb movement. Greater levels of integration in motor systems are achieved by hierarchical circuits that promote coordination among the basic spinal reflexes—what Sherrington (1906) referred to as the alliance of reflexes. In our flexor and extensor example, this entails a collateral projection of the stretch receptor afferents onto inhibitory interneuron circuit elements, which in turn project to and inhibit the motor neuron for the opposing muscle. Stretching the flexor muscle, for example, results not only in activation of the flexor motor neurons (stretch reflex), but also inhibition of the opposing motor neurons via the inhibitory pathway illustrated in Figure 18.1B. This exemplifies a general principle of neural organization articulated by Sherrington (1906), the principle of reciprocal innervation, which stipulates that neural systems promote specific outcomes by activating the mechanisms for the target response while at the same time inhibiting opposing responses. Consider the fate of a hungry donkey sitting equidistant between two equivalent piles of hay to which it was equally attracted. Would the donkey starve, being unable to select from these equally attractive goals? Lore has it that the philosopher Burdan contemplated this issue (sometime referred to as the parable of Burdan’s ass). Burdan’s contemplation notwithstanding, the answer is no. This type of approach–approach conflict is readily resolved (Miller, 1951), as noise or random variations in orientation or the approach disposition toward one of the choices would be associated with inhibition of the opposing disposition, in accord with the principle of reciprocal innervation. This principle of organization is not limited

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to the motor domain, but manifests broadly in psychological and cognitive processes, including evaluative processes and conflicts. We will return to these issues below. Sherrington’s alliance of reflexes does not stop with reciprocal innervation. As hierarchical levels are layered on the motor control system, progressively higher levels receive a wider array of inputs, have greater circuit complexity and computation capacity, and can achieve a broader and more flexible range of outputs. At the highest levels, beyond the primary motor cortex, cerebral systems must process a tremendous amount of sensory information, integrate this information with associative networks, emotional and motivational substrates, and expectancies, in the contexts of strategic goals and tactical plans. This requirement for enhanced information processing can impose a processing bottleneck that necessitates a slower, more serial mode of processing and selective attentional mechanisms (Shiffrin & Schneider, 1984). Although it is these highest level systems that confer the greatest cognitive and behavioral capacity, they do not operate in isolation but depend upon and interact with lower levels in the hierarchy.

NEURAL HETERARCHIES Hierarchical dimensions of central nervous system organization can be demonstrated anatomically as well as functionally (Berntson, Boysen, & Cacioppo, 1993). The simple hierarchy depicted in Figure 18.2, however, belies the true complexity of neurobehavioral substrates, as long ascending and descending pathways can bypass intermediate levels of hierarchical organization and interconnect across widely separated neural levels. Cortical motor neurons project not only to intermediatelevel somatomotor networks, but also directly onto spinal motor neurons through long descending pathways (Edgley et al., 1997; Porter, 1987). The long ascending and descending pathways in neural hierarchies, together with the existence of lateral interactions among elements (such as those that underlie reciprocal innervation), yield what has been termed a heterarchical organization (Berntson et al., 1993; Berntson & Cacioppo, 2007). The outputs of a strict hierarchical system are coherent, as all levels are linked by intermediate regulatory levels, and all outputs are by fi nal common pathways. In a heterarchical organization, however, higher levels can directly access output mechanisms independent of intermediate levels. This organizational feature allows for concurrent expression of multiple re-representative systems, which can increase

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Broad, flexible

Heterarachial organization

Output repertoire

Integrative capacity Low

Restricted, rigid

Output1 Input1 Output2 Input2 Output3 Input3 Output4 Input4 Output5 Input5

Parallel, rapid

Processing mode

Hierarchical organization

High


Serial, slow, capacity-limited

310

Output1 Input1 Output2 Input2 Output3 Input3 Output4 Input4 Output5 Input5

FIGURE 18.2 Hierarchical and heterarchical organizations. A heterarchy differs from a hierarchy in the existence of long ascending and descending pathways that span intermediate levels. Properties of the levels in both classes of organizations lie along the illustrated continua of processing mode, integrative capacity, and output repertoire. Heterarchical organizations, however, have greater integrative capacity and output flexibility as the long ascending and descending projections provide inputs and outputs that are not constrained by intermediate levels.

behavioral complexity but can also lead to functional conflicts. By volitionally stiffening the leg, for example, higher-level systems can mask the stretch reflex and usurp control of motor neuron pools.

RE-REPRESENTATION AND ORGANIZATION OF EVALUATIVE SUBSTRATES LOWER LEVELS AND PRE-MOTIVATIONAL FUNCTIONS Paralleling the pattern for somatic motor control, adaptive and protective reflexes and mechanisms are organized at all levels of the neuraxis. The pain withdrawal reflex, for example, is organized at the level of the spinal cord and can be seen even after spinal transections that isolate the cord from higher brain systems. Pain withdrawal reflexes are protective reactions that arise from somatosensory afferents, carrying nociceptive signals, which anatomically link to flexor neuron pools by a multisynaptic spinal pathway. Through this spinal reflex circuit, noxious stimuli yield a protective flexor withdrawal response. Likely because of their adaptive value, pain withdrawal reflexes are among the earliest to develop and the most resistant to disruption. Although pain withdrawal reflexes at the level of the cord may not require the invocation of a construct of emotion or affect, they represent an important low level evaluative mechanism for escape from noxious stimuli. Moreover, despite their neural simplicity, these circuits can show operant conditioning of

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escape which can support not only escape from, but active avoidance of, pain stimuli (Grau et al., 2006). In contrast to the primitive avoidance system associated with flexor reflexes, separate mechanisms exist at the level of the cord for opposing extensor responses which promote engagement with the environmental stimuli. Reflexes such as the extensor reflex in response to nonpainful cutaneous stimulation of the palm or the sole of the foot contribute to postural, locomotory, and grasping responses that serve to engage the organism with the environment. As considered above, flexor and extensor reflexes are organized largely in parallel, as they control distinct motor neuron pools for opposing muscles. Nevertheless, they do interact. These lower reflex substrates are integrated by higher-level circuits, such as those that implement reciprocal innervation, which tends to reduce concurrent activation. They are also impacted by even higher systems that contribute to volitional actions and confer a greater degree of flexibility and control over flexor and extensor motor neuron pools and lower reflex substrates. Thus, we can volitionally contract both flexor and extensor muscles (e.g., in stiffening the arm) which can overcome the lower-level reciprocal innervation, and we are able to override or suppress flexor pain withdrawal reflexes (e.g., to remove a sliver from the finger). Beyond these neural interactions, there are simple mechanical constraints on the expression of activation of flexor and extensor muscles. For example, the biceps and the triceps

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muscles control the same joint, and yield opposite flexion and extension movements of the forearm. Flexion and extension movements are incompatible and cannot be expressed concurrently. Consequently, one might conceptualize the flexor–extensor movements along a bipolar continuum from maximal flexion to maximal extension. From a strictly behavioral standpoint, this may provide an accurate description of flexor and extensor movements, but it belies the fundamentally bivariate (although interacting) neural organizations that regulate flexor and extensor muscles, and it is inadequate in terms of mapping unequivocally onto underlying mechanisms.

INTERMEDIATE LEVELS: INTAKE AND REJECTION RESPONSES AND TASTE HEDONICS Systems for evaluative processes and approach–avoidance reactions are further elaborated at the level of the brainstem. Decerebrate organisms, with no neural tissue above the level of the brainstem, show highly organized escape, avoidance, and defensive behaviors in response to aversive stimuli as well as approach/ingestive responses to palatable tastes (Berntson et al., 1993; Berntson & Micco, 1976). As was the case for flexor and extensor reflexes of the spinal cord, the basic brainstem substrates for approach and avoidance appear to be distinct and at least partially independent (Berntson et al.; Berridge & Grill, 1984; Steiner, Glaser, Hawilo, & Berridge, 2001). An illustration of the organization of brainstem approach and avoidance systems comes from work on taste hedonics and intake and rejection responses in surgically decerebrated animals and tragic failures of neurodevelopmental cell migration in human anencephalic and hydranencephalic infants (for reviews see Berridge, 2004; Steiner et al., 2001). Both humans and other animals display stereotyped orofacial responses reflecting positive affective expression and ingestion (e.g., smiling, licking, swallowing) to palatable sweet solutions, and aversivelike facial expressions and ejection responses (e.g., gaping, tongue protrusion) to bitter or other unpalatable tastes. These responses emerge early in ontogeny and can be seen in both intact organisms and decerebrates, suggesting that these positive and negative hedonic reactions to gustatory stimuli reflect opposing patterns of approach and avoidance that are organized at brainstem levels and are highly conserved across ontogeny and phylogeny. The behavioral manifestations of these opposing intake and rejection responses might be interpreted to reflect a bipolar hedonic continuum extending from highly positive or ingestion, through neutral, and to highly negative or rejection. Additional findings, however, suggest that

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the gustatory approach and withdrawal systems are at least partially independent, and do not converge on a single hedonic integrator (Berridge & Grill, 1984). Although intake and rejection responses tend to oppose each other, they are not entirely incompatible. Increasing the concentration of a bitter adulterant in an otherwise positive sucrose solution, for example, can increase the probability of rejection responses without decreasing the probability of intake responses. Moreover, increasing the concentration of both sweet and bitter tastes was found to increase both intake and rejection responses (Berridge & Grill, 1984). Positive and negative responses in such cases may co-occur and display a rapid alternation. Consequently, equal taste preference, as measured by behavioral consumption, does not necessarily imply an equivalent hedonic state. This is not to suggest that there is no interaction between these approach and avoidance responses, there probably is, but it is clear that mixing positive and negative hedonic stimuli does not yield a middling hedonic state of indifference. Rather, gustatory approach and avoidance reactions appear to reflect, at least in part, the separate activations of positive and negative hedonic dimensions (Berridge & Grill, 1984). A single overt behavioral measure of intake and rejection, such as the quantity of consumption, might be adequately described along a continuum from total rejection to total consumption. As was the case with flexor and extensor responses, however, this bipolar description again belies the underlying bivariate structure of the basic hedonic mechanisms.

HIGHER NEURAL LEVELS AND THE ELABORATION OF EVALUATIVE PROCESSES The evaluative processes of brainstem origin are manifestations of what MacLean termed the reptilian brain, which was considered the evolutionarily conserved repository of primitive survival mechanisms associated with fight or flight (MacLean, 1985). It is not until the development of the paleomammalian brain (limbic system and archicortex) and the neomammalian brain (neocortex) that we see the full elaboration of evaluative processes (MacLean, 1985). As we have considered above, systems of the reptilian brain implement basic evaluative reactions, such as those associated with gustatory hedonics. The behavior of decerebrates, however, is largely reactive, stimulus-bound, and related to simple nonrelational dimensions of the environment. Although decerebrates will ingest palatable foods, they do not show typical goal seeking in the absence of food stimuli (Berntson et al., 1993; Berntson & Micco, 1976). They could be likened to be prisoners of the

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momentary environmental context. Although they can display associative learning and may develop dispositions based on prior experience, the manifestation of these dispositions again is largely controlled by the immediate external context. The behavioral repertoire of the decerebrate is rigid and stereotyped, lacking the variability, flexibility, and spontaneity of intact organisms. The reptilian brain is sensitive to hedonics and responds to rewards and punishments, in a fashion reminiscent of the early drive reduction models of motivation (Hull, 1952). The early drive theories focused largely on biological homeostatic needs, and had limited applicability to more complex human behavior and social and cognitive contributions to motivation. The emerging incentive-based theories were more comprehensive in emphasizing the importance of anticipatory processes, expectancies, goal-striving, and higher-level motivations in guiding thought and action (Bolles, 1967). It is these latter aspects of motivation that the reptilian brain seems to lack, likely because they depend importantly on structures and systems that evolved above the level of the brainstem. A general trend from lower to higher neuraxial levels of representation includes the gradient extending from simple circuits of limited dimensions and flexibility, with parallel automatic processing on the one hand, to more flexible systems comprised of complex networks of interacting systems supporting the integrative processing of more complex motivational phenomena. The latter entail multiple distributed networks for distinct but interacting aspects of evaluative processing that integrate perceptual, memorial, anticipatory, and affective functions. These systems integrate a vast amount of information and consequently may display a more serial controlled mode of processing, but one that supports the highest level of evaluative cognition. Because of the evolutionary elaboration and increasing complexity of higher-level evaluative substrates, basic approach and withdrawal systems are not as discrete as at lower neuraxial levels. Indeed, both dispositional systems depend on common processing substrates associated, for example, with perceptual, attentional, and associative networks. Moreover, both may utilize the same cognitive and motor systems to implement their outcomes (e.g., running toward a goal or away from a threat). In addition, distinct dimensions of evaluative systems may show progressive differentiation. At a spinal cord level, approach and withdrawal systems are hardwired into parallel circuits that have separate sensory inputs and motor (extensor and flexor) outputs. The extent of neural activity in these circuits offers an adequate characterization of the associated action disposition, so, as noted above,

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constructs such as arousal, motivation, or emotion generally need not be invoked for their explication. The complexity of higher circuits precludes this simplistic characterization. An example comes from recent work on the nucleus accumbens (nACC). The nACC has been long recognized as an important nodal point in rostral substrates for reward and positive hedonics. Virtually any stimulus or condition associated with pleasure, reward, or positive affect triggers dopamine release in the nACC, and administration of dopamine potentiating agents into this structure has been shown to be rewarding (Hoebel, Rada, Mark, & Pothos, 1999; Robinson & Berridge, 2003; Wise, 2006). Conversely, rewards and positive hedonic states are reduced by lesions of the nACC or pharmacological blockade of dopamine receptors in this structure (Hoebel et al., 1999; Robinson & Berridge, 2003; Wise, 2006). In addition to dopamine, endogenous opiate systems play an important potentiating role for positive affect in the nACC and the associated ventral pallidum (Pecina, Smith, & Berridge, 2006). At these higher levels of organization, however, positive affective processes are not as monolithic as spinal reflex approach and withdrawal systems. Berridge (1996) has drawn an important distinction between what he terms “wanting” (incentive salience, goal-striving) and “liking” (positive hedonic effect, reward) dimensions of motivation. These dimensions are differentiated not only behaviorally, but have a distinct anatomy and pharmacology within the nACC and ventral pallidum as well (Pecina, et al., 2006). Findings such as this illustrate the complexity of rostral evaluative networks, and caution against attempts to define a punctuate localization of positive and negative substrates at higher levels of the neuraxis. Despite these complexities, however, it is clear that higher positive and negative evaluative substrates continue to be at least partially separable. Higher-level approach and withdrawal systems are more distributed, and may share common circuits for perceptual, attentional, and memorial functions, but the affective mechanisms remain at least partially separable. At the most global organizational level, this is apparent in laterality of representations. Although the right hemisphere may have a greater overall affective representation than the left (Cacioppo & Gardner, 1999), considerable research indicates that the right hemisphere is preferentially involved in aversive or withdrawal motivation, whereas the left may be more involved in positive states. Positive emotional stimuli have been reported to induce greater left than right cortical activation whereas the opposite pattern is seen with negative stimuli (Canli, Desmond, Zhao, Glover, & Gabrieli, 1998; Davidson,

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1998, 2004; Lee et al., 2004; Nitschke, Sarinopoulos, Mackiewicz, Schaefer, & Davidson, 2006; Pizzagalli, Sherwood, Henriques, & Davidson, 2005). In addition, individual differences in affective disposition have been reported to be associated with corresponding lateral activation asymmetries, and left hemisphere lesions are more likely to result in depression and negative affective consequences (Davidson, 1998). Efferent outputs also evidence an asymmetrical representation that is consistent with this hemispheric laterality model. Right insula stimulation, for example, yields larger sympathetic cardiac activation than does the left, the latter being more likely to induce parasympathetic cardiac changes (Oppenheimer, 1993, 2006; Oppenheimer, Gelb, Girvin, & Hachinski, 1992). Similarly, somatic outputs including affective facial expressions and manual reaction times to positive and negative stimuli show lateral asymmetries consistent with a right hemisphere bias for negative affect and a left hemisphere bias for positive affect (Davidson, Shackman & Maxwell, 2004; Root, Wong, & Kinsbourne, 2006). This right hemisphere bias toward negative affect has been attributed to a right lateralize visceral/nociceptive projection system, which is in turn associated with a peripheral asymmetry in sympathetic autonomic control and visceral/nociceptive afferent signaling (Craig, 2005). The finding of laterality differences has not been universal as revealed by a meta-analytic study (Murphy, Nimmo-Smith, & Lawrence, 2003), although this should not be surprising in view of the complexity of affective processes and the wide variety of paradigms that may be tapping disparate aspects or dimensions of evaluative processes. Laterality differences, for example, may be more consistent with a distinction in (approach or withdrawal) action dispositions than with a simple positive versus negative emotion differentiation (Harmon-Jones, Vaughn, Mohr, Sigelman, & Harmon-Jones, 2004). In view of the complexity of rostral neural systems and of higher-level evaluative processes, we are less likely to find simple mappings between affective processes (psychological domain) and neural substrates (biological domain). Progress toward this goal will require interdisciplinary, multilevel analyses (Cacioppo et al., 2000), and such efforts are currently underway. One important outcome of these studies is the recognition of the need for finer grained analyses of neural circuits. As outlined above, the nACC is a structure that has been solidly established as a neural player in reward and positive incentives. Nevertheless, the nACC has been reported to also be activated in some negative states (Reynolds & Berridge, 2002, 2003). Although this has

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been suggested to question the separability of positive and negative evaluative substrates, a finer grained analysis of nACC systems yields a different picture. Although the nACC has an historical anatomical identity, it is actually comprised of multiple anatomically and functionally differentiated regions (Pecina et al., 2006; Zahm, 1999). Using local drug infusions, for example, Reynolds and Berridge (2002, 2003) report a rostrocaudal differentiation of nACC sites that trigger approach and feeding responses and avoidance and negative taste reactions, respectively. As was the case for intake and rejection responses at the level of the brainstem, this approach– avoidance dichotomy does not reflect a simple continuum extending from positive to negative. Activation of intermediate regions of the nACC were found to produce concurrent positive and negative reactions. Interactions between the positive and negative systems could be observed in some zones, for example, where activation resulted in a decrease in the aversive reactions to a bitter taste such as quinine (Pecina et al.). Importantly, these zones were not coextensive with those yielding an increase in positive hedonics, but appeared to constitute a separate inhibitory area. The nACC provides a rather clear example of the anatomical and functional differentiation of positive and negative forebrain evaluative systems, likely because of the distinct behavioral correlates (intake and rejection, approach and avoidance). With other emotional states, action dispositions may not simply map onto positive and negative affect. Anger, for example, may lead to withdrawal or to approach and attack. Moreover, because of the complexity of higher neuropsychological systems, a given anatomical structure or system may implement only a dimension or aspect of evaluative processes. An example is the amygdala, which has long been implicated in fear and negative affect (LeDoux, 2003; Phelps, 2006). Imaging studies have reported amygdala activation during emotion, especially with negative emotions (Critchley et al., 2005; Irwin et al., 1996; Lane, Fink, Chau, & Dolan, 1997; Norris, Chen, Zhu, Small, & Cacioppo, 2004; Sabatinelli, Bradley, Fitzsimmons, & Lang, 2005; Zald & Pardo, 1997). Amygdala activation is seen during fear conditioning (LaBar et al., 1998), and lesions of this structure have been reported to disrupt fear conditioning (Bechara et al., 1995; LaBar & Cabeza, 2006; LeDoux, 2003; Phelps, 2006) and the perception of potential danger (Bauman, Lavenex, Mason, Capitanio, & Amaral, 2004). Patients with amygdala damage have been reported to display less intense negative, compared to positive, emotions (Tranel, Gullickson, Koch, & Adolphs, 2006); to show deficits in episodic or

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(A) Amygdala lesion

(B) Contrast lesion

FIGURE 18.3 (A) Amygdala and control lesions. Bilateral lesion of the amygdala secondary to Herpes Simplex Encephalitis. Although only two of the six patients in the amygdala group had bilateral lesions, the lesions of this patient illustrate the range of completeness of unilateral damage to the amygdala in other patients. (B) Illustration of one of the smaller lesions in the lesion contrast group. Adapted from “Amygdala contributions to selective dimensions of emotion,” by G. G. Berntson, A. Bechara, H. Damasio, D. Tranel, & J. T. Cacioppo, 2007, Social, Cognitive & Affective Neuroscience, 2, p. 123.

autobiographical emotion-related memories (Buchanan, Tranel, & Adolphs, 2006; LaBar & Cabeza, 2006; Phelps, 2006; Phelps & LeDoux, 2005) and to evidence reduced emotional potentiation of memory (Cahill, Babinsky, Markowitsch, & McGaugh, 1995; McGaugh, 2004). These and other findings clearly implicate the amygdala in negative affective processes (Phelps, 2006; Phelps & LeDoux, 2005), although the precise role of this structure remains to be fully elucidated. Although the amygdala appears to have a predominant role in negative emotions, it has also been suggested to be important in appetitive conditioning and positive affect (Everitt, Cardinal, Parkinson, & Robbins, 2003; Hamann, Ely, Hoffman, & Kilts, 2002; Mather et al., 2004). Although this might be suggested to question the separability of positive and negative substrates, it is also possible that the amygdala codes some aspect or dimension of emotion, such as emotional intensity or arousal rather than, or in addition to, emotional valence (Adolphs, Russell, & Tranel, 1999; Anderson et al., 2003; Bauman et al., 2004; Glascher & Adolphs, 2003; Kensinger & Schacter, 2006; Winston, Gottfried, Kilner, & Dolan, 2005). We examined this question further, in a study of patients with amygdala damage and a clinical contrast

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group with lesions that spared the amygdala (Figure 18.3). A series of pictures from the International Affective Picture Series were presented and participants were instructed to rate the slides separately on positivity, negativity, and arousal. Slides were selected based on normative ratings to be highly positive, moderately positive, neutral, moderately negative, and highly negative, with corresponding positive and negative pictures matched on arousal. As illustrated in Figure 18.4, patients with amygdala lesions rated both the positive and negative valence of the pictures comparably to the lesion control group and to the normative sample from young adults. Clearly these amygdala patients were able to recognize and appropriately categorize the positive and negative features of the picture stimuli. They differed dramatically, however, on arousal ratings. Control patients and the normative group showed a progressive increase in arousal ratings for more positive stimuli as well as the more negative stimuli. Although the amygdala patients showed the typical increase in arousal for progressively more positive stimuli, they failed to show an arousal gradient to the negative stimuli (Figure 18.4). That is, the patient group was deficient selectively in the arousal dimension of evaluative judgments.

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FIGURE 18.4 Evaluative ratings. Mean (s.e.m.) arousal (A) and valence (B) ratings across stimulus categories, for patients with amygdala lesions (Amyg) compared to the clinical contrast group (Cnt) and a normative control data (Norm). All groups effectively discriminated the stimulus categories and applied valance ratings accordingly. All groups also displayed comparable arousal functions to positive stimuli, but the amygdala group showed diminished arousal selectively to the negative stimuli. Adapted from “Amygdala contributions to selective dimensions of emotion,” by G. G. Berntson, A. Bechara, H. Damasio, D. Tranel, & J. T. Cacioppo, 2007, Social, Cognitive & Affective Neuroscience, 2, p. 123.

EVALUATIVE SPACE MODEL AND THE NEUROARCHITECTURE OF EVALUATIVE PROCESSES The ultimate expression of neural representation is embodied in cerebral cortical systems. It is these cortical systems that provide for the most sophisticated sensory and perceptual analyses, access to associative networks, attentional focus, conversant awareness, strategic planning, response selection, and outcome monitoring. These processes are central to the strategic organization of behavior—for anticipatory planning, cognitive simulations, and counterfactual reasoning; the establishment of self-awareness, actual–ideal self-discrepancies, and social alliances; and for adaptive, flexible, and creative responses to challenge. Although these higher processes are often most salient in social psychology, in fact they ultimately derive from and interact with lower-level neural representations. As re-represented systems do not supplant lower systems, there is also the opportunity for interactions and conflicts among approach and avoidance systems and across levels of organization. Since Thurstone (1931) it has been common to consider affective states to extend along a bipolar continuum from positive to negative, or from happy to sad, or from liking to disliking, etc. (Russell & Carroll, 1999). On the basis of neural and behavioral evidence, however, Cacioppo and Berntson have argued that this is an overly restrictive

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model of affective structure, and have proposed a more comprehensive bivariate model of affect (Cacioppo & Berntson, 1994; Cacioppo, Gardner & Berntson, 1997; Cacioppo, Larsen, Smith & Berntson, 2004). As illustrated in Figure 18.5, the bivariate model is comprised of separate dimensions that correspond to the separable functional and neural substrates for positive and negative states, and can vary at least partially independently. This model subsumes the bipolar concept as the reciprocal axis, as illustrated in Figure 18.5. It offers a more comprehensive account of affective states, however, and permits a representation of concurrent activation of positive and negative dimensions, as in the concurrent activation of intake and rejection responses considered above (Reynolds & Berridge, 2002, 2003). Thus, among other advantages, the evaluative space model can account for states of ambivalence or mixed feelings and for the low correlation sometimes observed between positive and negative feelings. For example, good outcomes that could have been better (i.e., disappointing wins) and bad outcomes that could have been worse (i.e., relieving losses) are typically given middling ratings on bipolar emotion scales which can only represent positive and negative along a single dimension. The use of separate positive and negative rating scales, however, reveals that the affective state is characterized not so much by indifference as a concurrent (coactivated) mix of positive and negative reactions (Larsen, McGraw, Mellers, & Cacioppo, 2004).

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Negative gradient

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FIGURE 18.5 Evaluative space model. Bivariate evaluative space and its associated affective response surface. This surface represents the net disposition of an individual toward (+) or away from (−) the target stimulus. This disposition is expressed in relative units and the axis dimensions are in relative units of activation. The point on the surface overlying the left axis intersection represents a maximally positive disposition, and the point on the surface overlying the right axis intersection represents a maximally negative disposition. The two headed arrow (heavy line) illustrates the more limited bipolar model of affect, which can be represented by a single line. Each of the points overlying the dashed diagonal extending from the back to the front axis intersections represents a middling disposition. The nonreciprocal diagonal on the evaluative plane which represents different evaluative processes (e.g., neutral to ambivalence) yields the same middling expression on the affective response surface. Dashed lines (including the coactivity diagonal) represent isocontours on the evaluative plane, which depict many-to-one mappings between the affective response surface and the underlying evaluative space. These isocontours are illustrative rather than exhaustive. Inset: the activation functions depicted separately for positivity and negativity. Adapted from “Relationship between Attitudes and Evaluative Space,” a critical review, with emphasis on the separability of positive and negative substrates, by J. T. Cacioppo and G. G. Berntson, 1994, Psychological Bulletin, 115, pp. 401–423. Reprinted with permission.

This is not to suggest there are no interactions between positive and negative evaluative processes. One source of interaction arises from simple mechanical constraints associated, for example, with incompatible response

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dispositions. The extensor and flexor reflexes of the cord serve the distinct and opposing functions of approach and avoidance, and are embodied in distinct neural circuits, according to what has been termed the cardinal principle of evaluative bivalence (Berntson et al., 1993). Despite their distinct neurological identities, however, flexor and extensor reflexes may control the same joint (e.g., the biceps and triceps that flex and extend the forearm). The forearm cannot flex and extend at the same time, of course, as these movements are opposite and incompatible. Based simply on behavioral observation, one might appropriately characterize flexion and extension on a bipolar scale. This bipolar representation, however, belies the more fundamental bivariate neural organization underlying limb control. With more sophisticated measurement techniques (e.g., muscle action potentials or EMG measures), one can observe concurrent variations in flexor and extensor activity (e.g., in volitional stiffening of the arm) that reveal flexor and extensor muscle coactivation. This may occur with a net flexor movement, a net extensor movement, or even in the complete absence of movement. This is not the only source of interactions or constraints among flexor and extensor reflexes. As noted above, Sherrington’s alliance of reflexes promotes coordination and integration among opposing neural systems, so a pattern of reciprocal innervation tends to minimize opposing actions. What is important to note, however, is that dual, bivariate (e.g., positive vs. negative) interacting systems may have very different functional properties, operating characteristics, and range of outputs than a single bipolar mechanism with an obligatory reciprocal structure. Mutual interference, be it mechanical or neural, may promote a more reciprocal-looking function, but unless that interactions and functional correlations between the dual systems are precisely reciprocal and 1:1, the range of functional states of that system will extend beyond a bipolar dimension.

FINE FEATURES OF THE EVALUATIVE SPACE MODEL Higher evaluative mechanisms are not as strictly tied to a restricted set of motor outputs, but can achieve a wider array of behavioral responses (e.g., freezing, fleeing, or attacking in the face of threat). Behavioral dispositions arising from higher positive and negative evaluative processes may still evidence an output coupling, however, there may be final common pathways for behavioral output. The same response (e.g., walking) may be motivated by an approach disposition (walking toward a desired object) or an avoidance disposition (walking away

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from a feared object). One cannot walk toward and away from an object at the same time, however, even if approach and withdrawal dispositions are activated simultaneously. What may be seen under such conditions is a temporal vacillation between approach and withdrawal reactions, whether they be motor or cognitive (e.g., decision whether or not to buy a particular car). In a classical series of studies, Miller used a variety of measures of motivation disposition (e.g., strength of pull on a tether to approach a reward or to avoid a noxious stimulus) to study conflicts in animals (Miller, 1958, 1959, 1961). In one series of studies, Miller measured the approach disposition to a food reward as a function of the proximity of the animal to the goal box (Figure 18.6). He then measured the avoidance disposition away from an electrified grid in the goal box, also as a function of proximity. As illustrated in Figure 18.6, Miller generally observed that the slope of the avoidance gradient was steeper than that of the approach gradient, such that at remote distances the approach disposition was greater than the avoidance disposition, whereas the reverse was the case when the animal was close to the goal box. In accord with the bivariate model of evaluative processing, when the food reward and the electrified grid were presented simultaneously, Miller found that the net approach and avoidance disposition was a simple summation of the two dispositions. When the animal was far away from the goal, where the approach gradient was greater than the

Distance from goal

FIGURE 18.6 Miller’s approach–avoidance conflict. Approach (solid line) and avoidance (dashed line) strength as a function of distance from the goal. Goal items include food (positive incentive) and shock (negative incentive). The avoidance gradient has a steeper slope, and predominates proximate to the goal box (negativity bias), whereas at more remote loci, the approach gradient is higher than the avoidance gradient (positivity offset).

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avoidance gradient, the animal tended to approach the goal. As the animal approached, however, and the steeper avoidance gradient was now greater than the approach gradient, the animal moved away from the goal. This is what Miller referred to as a stable equilibrium, as the animals tended to stay around the middle region where the approach and avoidance gradients were equal (but imparted opposite approach and avoidance dispositions). The animals seemed far from neutral or indifferent, however, but tended to vacillate, sometimes moving toward the goal box, then turning and moving away as the avoidance gradient became greater than the approach gradient. How are these findings to be understood? The adaptive advantage of separable approach and avoidance substrates is that evolutionary pressures can adaptively sculpt these processes independently. Negative or threatening stimuli or conditions may pose a serious survival hazard, and selection pressures would likely favor the development and precedence of avoidance responses, especially when those stimuli are proximate. As noted above, this can be seen at the level of spinal reflexes, where the prepotency of flexor reflexes to noxious stimuli is readily apparent. This negativity bias can also be seen in higher evaluative processes. The magnitude of response to negative stimuli has been suggested to be generally larger than to positive stimuli (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001; Pratto & John, 1991). This can be seen in diverse attentional paradigms such as identification of negative versus positive emotional faces, and in event-related potential markers of the early stages of evaluative processing (Cacioppo et al., 2004; Öhman, Lundqvist, & Esteves, 2001). This negativity bias is reflected in the steeper slope of the negativity function of Figure 18.5. Although the negativity bias is firmly engrained at the level of flexor reflexes, and has been considered obligatory (Pratto & John, 1991), it may be subject to modulation by higher-level evaluative processes and the affective context (Smith et al., 2006). In addition to the negativity bias associated with the steeper slope of the avoidance gradient, Miller observed what has been termed a positivity offset, reflecting the greater height of approach gradient as one moves further away from the goal (see Figure 18.5, and the insert in Figure 18.6). This, too, may have adaptive value for the organism and may reflect a feature engrained through evolution. Avoiding danger may be more adaptively significant in the near term, when the threat is imminent, but exploration and approach behaviors are essential in acquiring food, water, and in establishing a cognitive map of the environment and its positive attributes. A net positive

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approach disposition, especially when threats are minimal or remote, would enhance the likelihood of survival. Although negative stimuli may be more attention grabbing, especially at close proximity and high arousal levels, event-related potential studies suggest that positive stimuli may receive greater preferential processing at lower levels of activation (Herbert, Kissler, Junghofer, Peyk, & Rockstroh, 2006). The positivity offset is also apparent in the mere exposure effect on attitude formation, where familiarity with a novel object tends to promote a positive attitude in the absence of explicit positive or negative manipulations (Zajonc, 1968). Although organisms may be naturally wary of unfamiliar stimuli, in the absence of negative outcomes, there results a shift toward a positive disposition to those stimuli (Robinson & Elias, 2005). The positivity offset is represented in Figure 18.5 by the higher intercept of the positivity function, despite its lower slope. It is important to note that Figure 18.5 depicts only one level of organization in the re-representative systems underlying evaluative processes. We have focused on the neomammalian representation in the evaluative space model, although evaluative processes have representations also at paleomammalian and reptilian brain levels. To fully conceptualize a heterarchical system an additional dimension would be needed to depict the separate evaluative space functions for different levels of organization. As discussed above for flexion and extension, the coupling between evaluative processes and behavioral outputs may differ across levels of organization. At the spinal level for example, flexion is associated with avoidance, whereas at a higher cognitive level, flexion may be associated with approach. The relations between central states and flexion and extension responses thus depend on what level is manifesting in behavioral control, and this may change over time and across contexts. Indeed, one of the important questions raised by the evaluative space model is how different levels interact and achieve expression in behavior. The importance of the evaluative space model is that it provides a quantitative model whereby such issues can be addressed.

SUMMARY Conceptualizations of social motivation grounded in solid evidence regarding genetic and neural organization and function have the potential to improve the veracity and precision of evaluative concepts and processes, generate new and testable behavioral hypotheses, and broaden the scope and impact of social psychological theories. We here summarize the evaluative space model, derived from evidence spanning three centuries of

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research on the heterarchical organization of the central nervous system and its implications for implicit and explicit processes underlying approach and withdrawal. This model illustrates the potential utility of neuroscientific perspectives for social psychological processes, and the broadened perspective that can arise from multilevel research and the integration of social psychology and neuroscience.

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Evaluation Asymmetry Approach and Avoidance 19 How Decisions Influence Attitude Formation and Change J. Richard Eiser and Russell H. Fazio CONTENTS Costs and Benefits .................................................................................................................................324 Decision Making, Uncertainty, and Risk ..............................................................................................325 Antecedents of Risk Acceptance and Aversion ....................................................................................326 A Fundamental Asymmetry..................................................................................................................327 Risk Aversion in the Standard Gamble .................................................................................................328 Attitude Learning Through Exploration ...............................................................................................328 Learning Asymmetry Depends on Approach–Avoidance ....................................................................330 Effects of Value Extremity .................................................................................................................... 331 Promotion Versus Prevention Focus and Gain–Loss Framing in BeanFest ......................................... 332 Socially Transmitted Attitudes and Indirect Experience ...................................................................... 332 The Generalization Asymmetry............................................................................................................ 333 Implications for Prejudice .....................................................................................................................334 Implications for Self-Evaluations and Happiness .................................................................................336 Concluding Remarks .............................................................................................................................338 References .............................................................................................................................................338

As Benjamin Franklin once remarked, in this world nothing can be said to be certain, except death and taxes—and, we might add, uncertainty. Uncertainty is not merely a fact of life, it is a challenge to the survival of all living creatures. With uncertainty comes risk—of damage, death, or deprivation, of failure to feed or reproduce. For us humans, not all decisions are so obviously a matter of life and death, but most if not all have consequences that may be construed as benefits or costs, as good or bad, as states of affairs to be attained or avoided. It is therefore vital to our happiness and well-being, if not our actual survival, that we learn to distinguish objects or activities that will provide us with benefits from those that will lead us to incur costs. This process

of learning constitutes attitude formation, since it results in us acquiring favorable attitudes toward objects associated with benefits and unfavorable attitudes toward objects associated with costs. In this chapter, we shall be concerned with how individuals acquire attitudes toward novel objects in contexts where such learning depends on their own behavior and specifically on their willingness to expose themselves to risk within an uncertain environment. We start by describing some of the factors that affect decision making under uncertainty, stressing in particular how different decision–outcome combinations vary in their diagnosticity, i.e., in their potential to confirm or disconfirm prior hypotheses and evaluative beliefs. 323

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We then apply these ideas to the issue of how individuals acquire attitudes toward novel objects through experience. We describe a phenomenon we term learning asymmetry, whereby individuals show fewer errors in their learning of bad objects than good objects. In other words, individuals rarely evaluate bad objects positively, but tend to evaluate a proportion of good objects negatively. The reason for this is that false-positive beliefs will lead to approach, and hence discovery that the objects approached are actually bad, whereas falsenegative beliefs may persist uncorrected since individuals fail to discover that some of the objects they have avoided are actually good. A series of experiments and simulations explore these processes in greater detail, and also consider the impact on attitude acquisition of socially communicated information about the attitude objects. We then consider the implications of these findings for positivity biases in self-conceptions and risk-averse decision making. In terms of how our chapter relates to others in this book, we regard attitudes as evaluative judgments. By virtue of their marking the valence of some object, issue or person, attitudes necessarily have action implications. Favorable attitudes provide a motivation to approach and unfavorable attitudes a motivation to avoid. Wherever favorable and unfavorable attitudes (or approach and avoidance motivations) coexist (Cacioppo & Berntson, 1994), this gives rise to uncertainty about what actions to perform. Furthermore, whereas approach and avoidance motivations can coexist to varying degrees, decisions to approach or avoid are mutually exclusive. We cannot both approach and avoid the same object at the same time. So the translation of attitudes and motivations into behavior involves a form of decision making, whether conscious or unconscious, under conditions of uncertainty with regard to costs and benefits. This in turn gives rise to two questions: first, how are decisions to approach or avoid guided by perceived costs and benefits? And second, how does the experience of costly and beneficial outcomes shape the formation of attitudes toward objects in our social environment?

COSTS AND BENEFITS Attempts to specify how costs and benefits relate to decision making have been traditionally dominated by economic rather than psychological theories. Furthermore, the purpose of much classical economic theory has been prescriptive (defining how a rational actor should decide) rather than descriptive (investigating how decisions are actually made). Yet it is precisely the introduction of costs

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and benefits that turns the problem of decision making under uncertainty into one of the motivations, and hence a more broadly psychological topic of study than one concerned simply with people’s cognitive ability to process ambiguous information. It goes without saying, or should, that we are motivated to make correct decisions and avoid errors. But, when decisions have consequences, not all errors are equally costly and not all correct decisions are equally beneficial. Furthermore, the steps required to avoid certain kinds of errors can themselves be costly or risky. This is a problem faced in a number of safety-critical industries: if there is no such thing as zero risk, how much effort and expenditure should be devoted to making an improbable risk even more remote? As Fischoff, Slovic, Lichtenstein, Read, and Combs (1978) once asked, “how safe is safe enough?” Evidently, there is no absolute right or wrong answer to this question. Nonetheless, there are ways to address it relatively systematically, provided we (or society) can agree on a common metric for balancing, say, the cost of extra safety procedures against that of the accident that may thereby be prevented. The difficulty is that this last calculation is often controversial (take the issue of nuclear accidents, or terrorist attacks, for example). Estimates of the precise likelihood of such events may be hotly disputed and many people would strongly resent the notion that consequences of disasters (e.g., numbers of lives lost) can be translated into some kind of crude monetary equivalent. Such calculations increasingly pervade public policy, for example where health economists are called upon to advise on the cost-effectiveness of different medical treatments so that scarce resources are used to maximum effect. The trouble is that, whereas it is relatively easy to measure (monetary) cost, measuring effectiveness is far more controversial and contains a large subjective element. The current approach is to rely on a derived measure termed Quality Adjusted Life Years (QALYs), essentially – how many more years of life will the treatment provide and what will be the gain in the patient’s quality-of-life during these years (Gold, Siegel, Russell, Weinstein, 1996)? Apart from methodological questions of how best to measure quality-of-life for different patient groups (Eiser, 2004), there are a host of essentially ethical questions hidden behind superficially technical calculations: Are all groups—for example, young and old, parents and childless—equally deserving (Nord, Pinto, Richardson, Menzel, & Ubel, 1999)? Is it better to concentrate resources on large benefits for a few, or small benefits for many (Dolan, 1998; Olsen, 2000)? Such difficulties arise most acutely when we are required to express preferences between things that are

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How Approach and Avoidance Decisions Influence Attitude Formation and Change

qualitatively very different, but undeniably many reallife choices are like this—balancing the enjoyment from a holiday or night out against the embarrassment of failing to complete a work assignment on time, the attractions of a new job in a different city against the distress of lost friendships. Since we cannot be in two places at once, or spend the same money twice, every choice has an opportunity cost—what we have to give up for what we choose to do. But even when we are comparing like with like, real-life decisions can still be difficult. The reason for this is simple but profound: we cannot always be sure what the consequences of our decisions will be.

DECISION MAKING, UNCERTAINTY, AND RISK Apart from death and taxes, another fact of life is that decisions cannot always be avoided or postponed, even if we are uncertain of the consequences. If we could predict consequences correctly and with certainty, there would be no risk, but in real life such conditions are rare. We need to make decisions on the basis of incomplete and imperfect data. How can we do this? One starting point for thinking about this question is the classic theory of perceptual discrimination, Signal Detection Theory (SDT) (Swets, 1973). The basic problem this theory addresses is that of describing the “discrimination performance” of a perceiver faced with the task of identifying whether or not a piece of stimulus information is evidence of a “signal” or merely “noise.” For instance, how does a radar operator tell the difference between a blip on a screen due to an approaching aircraft and one due to atmospheric disturbance? How reliably can a safety inspector (or even an automatic device such as a smoke detector) distinguish danger from safety? How well can a doctor diagnose a particular medical condition from a set of clinical symptoms? In all these dilemmas the decision maker is faced typically with a mass of different pieces of information, some relevant and others irrelevant. So a first question is how well the decision maker can process this accumulated information to derive some estimate of the likelihood that a signal is actually present. Within SDT, the extent to which such estimates are well-calibrated with actual probabilities is referred to as sensitivity or discrimination ability. Behaviorally, better discrimination ability will tend to be reflected in more accurate decisions and fewer errors. However, even well-calibrated decision makers, well-trained air-traffic controllers or physicians, can sometimes make mistakes, so a second question is how many such mistakes, or rather particular kinds of mistakes, matter.

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Although we can assume that correct responses will be more beneficial than incorrect ones, the extent to which this is so can vary considerably. Correct decisions can take the form of saying a signal is present when it is (hit) or saying that noise is mere noise (all clear). Incorrect decisions involve treating a signal as noise (miss) or noise as a signal (false alarm). Suppose, for example, the fire alarm sounds in the building where you work. It quite often sounds, since it is tested at least once a week, but this is not at its regular time. What do you do? Of course, you should leave the building. But then, a few minutes after you get outside, the alarm stops and you are told it had been set off accidentally by electricians doing some maintenance work, so you return to your desk. It was a false alarm, as a result of which you have wasted halfan-hour: a cost, to be sure, but a quite trivial one compared with staying in the building and perhaps losing one’s life if there really had been a fire. But the trouble is the more often alarms turn out to be false, the less ready you may be to react to them as real—the well known “cry wolf” problem. In other circumstances, however, false alarms can be more costly than misses. Gigerenzer (2002) recounts several examples where patients may be recommended to undergo aggressive and distressing medical treatments following unreliable diagnostic tests, or for conditions that are so slow to develop as to have no significant implications for (older) patients’ life-expectancy or quality-of-life if left untreated. An enduring contribution of SDT, and its major relevance to approach and avoidance motivation, is that it characterizes decision-making performance not merely in terms of overall accuracy, but also in terms of “criterion” or response bias. This refers to the tendency to give responses in one direction, for example, to say the signal is present, or that the patient has a specific condition. Depending where the criterion is set, some ambiguous pieces of information may be over interpreted as a signal (false alarm), and others wrongly discounted as noise (miss). Now, although the use of a particular criterion will increase the chance of particular kinds of errors, there is no absolute answer to the question of what the best criterion should be. If you change the criterion, you will decrease the chance of some kinds of errors but you will simultaneously increase the chance of others. So the choice of what criterion to adopt depends on the relative perceived costs and benefits of different outcomes resulting from correct and incorrect decisions. A minor difficulty in extending the SDT framework to more general issues of approach and avoidance motivation is that the terminology of signal versus noise implies a kind of “figure-ground” distinction between the

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detection of danger and safety. This is fair enough for contexts such as medical screening where the aim is correct detection of an abnormal condition. Conventionally, screening test results that indicate the presence of an abnormality are termed “positive” and those indicating an absence of disease are termed “negative.” Even within the medical context, this terminology is potentially confusing at least for some patients since, evidently, a positive test result is bad and a negative result good. When considering more general approach–avoidance situations, however, we may be equally concerned with the detection of good (safe, desirable, rewarding) objects as with detecting those that are bad (dangerous, undesirable, costly). Put differently, we may be just as concerned with identifying good objects to approach, as with identifying bad objects to avoid. Figure 19.1 illustrates the different decision–outcome combinations according to their conventional definitions, as well as how these might be applied to more general approach–avoidance decisions. A hit refers to correct detection of danger, a miss a failure to detect danger, and so on. Hits are conventionally termed “true-positives,” but for clarity we refer to these as instances of truepositive diagnosis to remind the reader of their medical usage. In an approach–avoidance context, treating a dangerous signal as dangerous (a hit) constitutes a case of “correct avoidance” whereas treating a dangerous signal as safe (a miss) constitutes a case of “incorrect approach.” As will soon become clear, we shall spend much time considering the processes that might lead to false alarms or instances of incorrect avoidance. Conventionally such responses would be termed false-positives, but we regard

this as somewhat confusing from the perspective of approach–avoidance motivation and attitude theory (since positive normally suggests a favorable attitude and a willingness to approach). In the following, therefore, we shall sometimes refer to false alarms as false-negative avoidance decisions (rather than false-positive diagnoses of danger), in that it is more intuitive to think of negative as reflecting an unfavorable evaluation.

ANTECEDENTS OF RISK ACCEPTANCE AND AVERSION A considerable literature has looked at the antecedents of people’s readiness, or reluctance, to engage in various forms of risk-taking. In many case, researchers have considered characteristics predictive of a predisposition to risk or caution as relatively stable personality traits that generalize across situations. Examples include Zuckerman’s (1994) research on sensation-seeking and Higgins’s (1998) notion of promotion and prevention regulatory focus. Such behavioral tendencies may possibly reflect underlying differences in temperament (Elliot & Thrash, 2002) or behavioral activation and inhibition systems (Gray, 1990). Social anthropologists have also attempted to identify subcultural types characterized by supposedly general orientations of acceptance or concern toward a range of societal and technological risks (Boholm, 1996; Douglas, 1986). In such cases, the antecedents of such predispositions and orientations are assumed to lie, at least partly, in the individual’s upbringing and experience of parental encouragement or discipline, and in experiences of autonomy or powerlessness

Action Avoid Treat as bad, dangerous

Approach Treat as good, safe

Object valence

FIGURE 19.1

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Bad, dangerous

True-positive diagnosis False-negative diagnosis Incorrect approach Correct avoidance Miss Hit

Good, safe

False-positive diagnosis True-negative diagnosis Correct approach Incorrect avoidance All clear False alarm

Decision–outcome combinations.

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within the political and economic system. Our own focus is narrower, but arguably more easily amenable to empirical investigation. We are concerned with how response biases toward greater risk acceptance (approach) or risk aversion (avoidance) may be shaped and reinforced by an individual’s experiences within a specific learning environment. Experiences can affect attitudes and motivations in several ways. A fair amount of work has looked at how individuals come to regard objects more positively or negatively, either as a function of mere familiarity (Zajonc, 1968, 1980) or through a process of associative learning based on the co-occurrence of novel objects with others of established valence (De Houwer, Thomas, & Baeyens. 2001; Olson & Fazio, 2001, 2002, 2006). Such learning can be characterized as “passive” in the sense that the relevant learning experiences to which individuals are exposed are independent of their own behavior. Put differently, information gain within this paradigm comes essentially risk-free. (Note that our concern here is with whether there are risks associated with information search per se, rather than with any risks associated with consequential changes in behavior, which of course could be either adaptive or maladaptive.) Our own focus is not on such passive learning, although it undoubtedly occurs, but instead on learning that is contingent on individuals’ active exploration of their environment. This links with a large literature on reinforcement learning (Sutton & Barto, 1998). The essential feature of reinforcement learning is that learners receive feedback as a consequence of their actions. For example, a rat that explores a given arm of a maze may receive a food pellet or an electric shock. Learners who perform different actions receive different feedback, but if no action is performed, no feedback is provided. Positive feedback (e.g., food) increases the likelihood of an action being repeated (hence, approach), whereas negative feedback (e.g., shock), decreases its likelihood (hence, avoidance)—the familiar “law of effect.” The slightly more subtle point is that the reinforcement learning paradigm is one in which the relation between action and learning experience is dynamic. Feedback is not only contingent on, but also shapes, the learner’s actions.

A FUNDAMENTAL ASYMMETRY Because of this dynamic relation, there is a fundamental asymmetry between approach and avoidance behaviors. At its simplest, approach behavior exposes the learner to potential feedback and learning experience whereas

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avoidance behavior generally does not. However, since such feedback could be either positive or negative, approach involves risk. Conversely, avoidance involves not merely escape from known danger, but a way of reducing uncertainty and hence, risk. Let us consider how this applies to the 2 × 2 matrix of decision–outcome combinations shown in Figure 19.1. If feedback is contingent on approach, learners should be unable to distinguish between false-negatives and true-negatives. In other words, learners should have no way of confirming or disconfirming the negative expectancies that led them to avoid a given object or action. More than 50 years ago, Solomon and Wynne (1954) established that avoidance behavior by animals is highly resistant to extinction. For instance, rats will continue to avoid an area of their cage where they have previously received an electric shock long after the reinforcement schedule has been changed so that the area can be safely visited. This again can be seen as a direct consequence of the dynamics of action and feedback: if the chosen action (avoidance) means that the rat never gets feedback that is inconsistent with prior negative expectancies, these expectancies will remain in force and lead to continued avoidance. Among humans, phobias, but also negative prejudices against out-groups, may reflect much the same process (as we shall discuss in more detail shortly). In such instances, adoption of a risk-averse response bias is likely to be self-sustaining. How might feedback affect learners’ ability to distinguish true- and false-positives? In a simple situation where feedback is immediate and unambiguous, discrimination should improve quickly. True positives should be rewarded and false-positives punished. (Shortly we shall describe an experimental paradigm that demonstrates this effect.) However, not all situations in real life are so clear cut. Physicians may often prescribe treatments on the basis of unreliable positive test results (as noted previously, positive means here that the disease is present, not that it is good news). If the patient’s condition then improves, then that can be taken to prove that both the diagnosis and prescription were correct, when actually the patient might have improved anyway, and possibly faster without the treatment. Similarly, if the patient’s condition worsens, that again just proves the correctness of the diagnosis and the seriousness of the medical condition that is resisting treatment. Likewise, many situations and systems can be relatively “forgiving” of unsafe behaviors (i.e., falsepositive “approaches”). Many unhealthy habits lead to illness, but often only after many years. Not all instances of unsafe sexual intercourse result in pregnancy or infection. Not all cases of unsafe driving lead to accidents. But every time someone appears to get away with doing

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something dangerous, their perception of the risk is likely to be lowered and, assuming the behavior is otherwise pleasurable or rewarding, the chance of them behaving the same way again will be increased. Once again, incomplete feedback (in this case, delayed or inconsistent punishment of false-positive risk-taking) can lead to selective interpretations of contingencies between decisions and outcomes that are biased in the direct of confirming prior beliefs.

RISK AVERSION IN THE STANDARD GAMBLE Before concluding this section, we need briefly to consider work involving a slightly different definition of “riskaversion.” This involves a procedure known to economists as the “standard gamble” where participants indicate their preferences between two options of the same expected value. An example would be: Option A: Winning $10 for sure. Option B: A 10% chance of winning $100, but a 90% chance of winning nothing. In terms of this paradigm, Option B is seen as “riskier” since the consequences are less certain. Preference for Option A is therefore defined as “risk averse.” The same problems can be rephrased in terms of chances of losing rather than winning, and this makes a big difference. According to Kahneman and Tversky’s (1979) prospect theory, when the problem is defined in terms of gains, participants tend to be risk averse, i.e., prefer Option A, but when it is defined in terms of losses, they tend to be risk-seeking, i.e., prefer Option B rather than accept a sure loss. What may underlie risk-averse and risk-seeking preferences within this paradigm? Interestingly, these too may reflect the learner’s history of feedback. March (1996) used computer simulation to argue that risk aversion for gains could be a direct product of learning experience, rather than any kind of personality trait or higher-order conscious process. In his simulations, the learning system was presented with two classes of objects, one of which (the “sure thing” option) always produced a moderate reward, and the other of which (the “risky” option) sometimes produced a much larger reward, but more often produced nothing (the reward magnitudes and probabilities being arranged so that the expected value associated with the two classes of objects was the same, as in the choice between Options A and B above). The learning system had to choose whether to approach or avoid these objects on the basis of its expectations developed over time. The

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learning algorithms used meant that these expectations were modified by experience of the value of individual objects, if and only if they were approached. March’s findings showed strong evidence for risk aversion for gains. The argument goes something like this. Whenever an object of the sure thing class is presented, it is consistently associated with a good outcome, and so approach is strongly reinforced. Before long, all sure thing objects will be approached. By contrast, most risky objects will produce no good outcome or reward at all, and so the tendency to approach these will be weakened. As a consequence, sure thing objects will be more likely to be approached and risky objects avoided. “Ah, but what about the fact that the two classes of objects have the same expected value?” (an economist might ask). “Should not the extra value of the occasional large rewards in the risky class compensate for their infrequency?” True, but this only applies if both classes are fully sampled. Once (as a function of the reinforcement process) the system starts differentially to approach the sure thing class and avoid the risky class, the chances are that it will never sample enough of the risky class to discover it contains a few high rewards. Unlike human participants in standard gamble experiments (or lottery players, perhaps), the learning system does not know that there is a jackpot out there, unless and until it finds it.

ATTITUDE LEARNING THROUGH EXPLORATION All of the above lines of research suggest that the outcomes experienced by individuals as a consequence of their decisions should be a major influence on attitude formation. At its simplest, we should come to hold favorable attitudes toward objects associated with positive outcomes and unfavorable attitudes toward objects associated with negative outcomes. Such attitudes are a source of approach and avoidance motivations, in that we should tend to approach positively valued objects toward which we hold favorable attitudes, and avoid negatively valued objects toward which we hold unfavorable attitudes. Approach and avoidance then, as explained, will in their turn influence the outcomes we experience. Although these ideas are relatively simple at a theoretical level, there has been little attempt to investigate them empirically in the context of human attitude formation. Part of the reason may simply be the practical difficulty of achieving experimental control over the outcomes

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individuals experience while also controlling for, or eliminating variation in, their prior attitudes. This appears to exclude the typical style of much attitude research, where individuals are asked to state their opinion on some real-life social issue, or express (implicitly or explicitly) their liking or disliking for an actual social group. For this reason, we sought to develop a new experimental paradigm within which individuals would be presented with novel objects about which they could have no prior preconceptions of their value, but where they could learn to identify some objects as “good” and others as “bad.” To this end, we devised a computer game (BeanFest) involving a virtual world filled with different kinds of “beans” (Fazio, Eiser, & Shook, 2004). These beans are presented visually on the computer screen, and their appearance varies along two dimensions: shape (round to oblong) and number of speckles. Participants are told that some of the beans they see will be good, and will provide them with energy if eaten, whereas others will be bad, and will lead to a loss of energy if eaten. For each bean presented, participants therefore have to decide if they want to “eat” or “not eat” it (i.e., approach or avoid). They are instructed that their survival or success in the game depends on them learning to identify which beans are good and should be eaten and which are bad and should be avoided. The critical feature of our (standard) procedure is that, if a bean is eaten, the participant receives consistent and immediate feedback

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about its true valence (in the form of a gain or loss of “energy” points), but if a bean is avoided, the participant receives no feedback whatsoever. We took particular care over the relationship between the valence of the beans and their visual attributes, so that the discrimination learning task could not be performed by focusing simply on one dimension and ignoring the other. There were 10 levels of each attribute, producing 100 possible attribute combinations, or stimulus patterns. However, participants only had to learn to discriminate between 36 of these. Of these 18 were good and 18 bad, and arranged in six separate clusters distributed across the 10 × 10 matrix shown in Figure 19.2. (In half the conditions, the valences were reversed from those shown, but this made no difference to the results to be described.) As can be seen, all beans within a single cluster or region had the same valence, thus enabling a form of generalization learning. (Participants were not shown the matrix, nor informed about the proportion of good and bad beans.) The basic procedure consisted first of a set of six practice trials involving one bean from each region. To ensure that they gained some preliminary idea of the beans and to familiarize themselves with the feedback procedure, participants were instructed to answer “Yes” to each of these when asked if they wanted to eat them. This was followed by a learning, or game, phase, consisting of three blocks of 36 trials, with each bean being presented once within each block. During this phase, participants

Speckles (Y) 10

Region 6 Region 5

9 8 7 6

Region 4

5

Region 3

4 3 2

Region 2

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1 Shape (X)

FIGURE 19.2

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1

2

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4

5

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7

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The BeanFest matrix. Regions 1, 3, and 5 comprise good beans; 2, 4, and 6, bad beans.

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could monitor the effects of their behavior on their total energy level via an “energy meter” on the screen. If they ate a good bean, a +10 appeared after “Effect of Bean.” If they ate a bad bean, −10 appeared in the same place. An additional feature included in the original version of the game was that, whatever they did, participants lost 1 energy unit or point on each trial, to simulate the idea that, if they never ate, they would eventually starve. Hence, another caption read “Energy Loss via Time” and took the value −1 on all trials. A third caption “Net Gain or Loss” was therefore followed by +9 whenever a good bean was eaten and −11 whenever a bad bean was eaten. If, however, the participant responded “No” when asked if they wanted to eat a bean, “Effect of Bean” remained blank, and a −1 was shown against the next two captions. In addition, participants could see their current energy level in numerical and visual analog form. In the original version of the game, their starting level was 100 units and they were told that, if the level dropped to 0, this symbolized “death.” (Variations in procedure across different versions of the game included removing the energy loss via time, and setting different starting levels.) When the game (the learning phase) reached its obvious conclusion, a final “test phase” began. At this point, the game was over. Hence, no energy meter was displayed. On each trial, a bean was presented and participants indicated whether they thought the bean was good or bad, i.e., whether it increased or decreased energy levels when eaten. The stimuli presented included both some from the original training set and others, not previously presented, from elsewhere in the 10 × 10 matrix. Responses to the former (original) beans were taken to provide a measure of participants’ discrimination learning. Given that the game itself had concluded, these responses are unaffected by participants’ current energy needs or consideration of the risk of a false-positive decision to “eat.” The latter (novel) beans were included to see if such learning generalized to other beans with similar visual features. In our first two experiments, we included only a selection of original and novel beans, but in subsequent experiments, the test phase involved presentation of all 100 possible patterns, i.e., all 36 of the original training set plus 64 novel beans. Our very first experiment (Experiment 1 of Fazio et al., 2004) yielded a number of clear and interesting effects. On average, participants were successful in learning. The mean phi coefficient relating the actual valence of the game beans to the participant’s classifications during the test phase was substantially better than chance. Indeed, over 50% of the participants were characterized by statistically significant phi coefficients. Moreover,

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these attitudes generalized to the novel beans. On the basis of Euclidean distances within the matrix, each novel bean could be classified as closer to a positive game bean, closer to a negative game bean, or equidistant. Responses to these novel beans were strongly affected by this proximity variable. Novel beans closer to a negative (i.e., more strongly resembling a negative game bean) were more likely to be classified as bad than were equidistant beans, and novel beans closer to a positive were the most likely to be classified as good. However, two intriguing valence asymmetries also emerged. The first we refer to as a learning asymmetry effect. Although classification of positive and negative game beans were both well above chance levels, identification of bad beans was more accurate than identification of good beans. Good beans were more likely to be wrongly categorized as bad than the reverse. Consideration of the novel beans revealed a generalization asymmetry effect as well: participants’ estimates of the valence of novel beans were biased toward the negative. Novel beans that were equidistant between a positive and a negative game bean were likely to be regarded as negative. Thus, resemblance to a known negative was weighted more heavily than resemblance to a known positive. Additional analyses showed this generalization asymmetry to be a phenomenon in and of itself, independent of the learning asymmetry. Although the generalization and learning asymmetries are strongly correlated across participants, the generalization asymmetry is apparent over and above the effects that the learning asymmetry itself has on generalization. In the next sections, we consider the mechanisms that underlie each of these valence asymmetries. We fi rst discuss the learning asymmetry and various experiments that have proven pivotal to our understanding of the forces that bring it about. We then consider what our research has revealed about the generalization asymmetry.

LEARNING ASYMMETRY DEPENDS ON APPROACH–AVOIDANCE Our explanation for the learning asymmetry effect follows directly from the earlier theoretical discussion. If feedback is contingent on approach (here, “eating”), then true-positive approach responses will be reinforced and false-positives corrected by gain and loss feedback, respectively. However, false-negative avoidance will remain uncorrected since no feedback is provided to such responses and hence participants will fail to distinguish reliably between true-negatives (bad beans) and

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false-negatives (good beans assumed to be bad). The consequence is that participants’ estimates of the valence of the stimuli will be predominantly negative. This argument rests on the assumption that learning asymmetry as assessed during the test phase reflects levels of avoidance versus approach during the learning phase, since these levels determine the feedback received. Direct evidence to support this assumption comes from the fact that the learning asymmetry was significantly negatively correlated with the overall amount of approach behavior during the learning (game) phase: the more participants chose to sample the beans, the more feedback they received and the better they became at identifying good as well as bad beans. Another way of establishing that the learning asymmetry effect arises from the dependence of feedback on approach is to remove the fundamental constraint of the game and provide feedback on every trial, irrespective of whether participants chose to eat a bean or not. This change was introduced in the “full feedback” condition of Fazio et al.’s (2004) Experiment 2, where, if participants chose to eat a bean, they were informed of the “Effect of Bean,” as before. However, if they chose not to eat, their energy level was unchanged, but they still received feedback alongside a caption reading “Effect Bean Would Have Had.” The consequence was an elimination of the learning asymmetry effect, the only condition in which this has been observed. This last finding is consistent with the conclusions of a series of computer simulations (Eiser, Fazio, Stafford, & Prescott, 2003) in which we trained a neural network to differentiate between “good” and “bad” input patterns corresponding to the beans in the BeanFest stimulus array. In the full feedback conditions, we employed the familiar backpropagation of error (“backprop”) learning algorithm (McClelland & Rumelhart, 1988). The way this algorithm operates is broadly as follows. When the network is presented with a given input (bean), it produces an output, corresponding to an estimate of the bean’s valence (how good or bad it is). This estimate is then compared with a target value, representing the correct output or true valence of the bean, and the “error,” i.e., discrepancy between the output and target value, is calculated. The connection weights (that govern how activation is fed forward from the input through a layer of “hidden” units to the output) are then modified to reduce this error so that the next time the same input is presented, the output should be closer to the target value. The consequence is that “learning” takes place both when the network selects an action equivalent to approach or eating a bean and when it selects an action equivalent to

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avoidance. In other words, regardless of whether the network approaches (eats) or avoids a given bean, it will be told whether the bean is good or bad, and so will be more likely to approach it next time it is presented if it is good, and less likely to approach it if it is bad. The simulations using the standard version of this algorithm produced perfect or near perfect learning of both good and bad beans, in other words, no learning asymmetry. In the contingent feedback conditions, however, we adapted the algorithm so that the connection weights were updated only if the network selected an action equivalent to approach (eating). In other words, learning only took place on trials where the network approached a bean to discover its valence, thus transforming the paradigm from one of supervised to reinforcement learning. The differences between the conditions were striking. Whereas the network continued to display perfect or near perfect learning of bad beans, it consistently failed to identify a proportion of the good beans, instead responding to them as though they were bad. In other words, we reproduced the learning asymmetry effect within an artificial learning system where, as in the human experiments, feedback depended on active exploration.

EFFECTS OF VALUE EXTREMITY Feedback in the BeanFest game not only provides information to participants, it also results in gains and losses. In the standard version of the game these gains and losses were symmetrical (+10 versus −10 points on each trial). But what would we expect if gains were stronger than losses, or vice versa? In terms of a reinforcement learning perspective, stronger positive reinforcements from eating a good bean should lead to more approach, whereas stronger punishments from eating a bad bean should lead to more avoidance. In terms of a more cognitive (SDT) decision perspective, greater gains from a good bean increase the benefits of a true-positive, and hence encourage adoption of a more risk-accepting (approach) response criterion, whereas greater losses from a bad bean increase the costs of a false-positive and hence should lead to more risk aversion. Either way, the predictions are the same. One of the experiments reported by Fazio et al. (2004) tested this specifically. In the extreme positive condition, the gains from each good bean remained at +10, but the costs of eating a bad bean were reduced to −2. Conversely, in the extreme negative condition, the costs of a bad bean remained at −10, but the gains from a good bean were only +2. As predicted, the extreme negative condition produced a dramatic decrease in approach behavior during the game, relative to the extreme positive condition.

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The test phase data showed the learning asymmetry effect, although statistically evident in both conditions, to be significantly greater in extreme negative condition. Moreover, a mediational analysis indicated that this effect of condition on the learning asymmetry was mediated by the differences in approach behavior produced by the extremity manipulation.

PROMOTION VERSUS PREVENTION FOCUS AND GAIN–LOSS FRAMING IN BEANFEST So far we have been describing structural factors within the BeanFest game that influence the learning asymmetry. But what of other cues or motivational factors that might trigger differential levels of approach and avoidance? According to Higgins (1998), individuals vary in the extent to which they generally interpret uncertain situations as offering the achievement of potential success and gain (“promotion focus”) and as requiring precautions against the occurrence of failure and loss (“prevention focus”). Although Higgins et al. (2001) suggest that such individual differences may have their roots in contrasting parenting practices, more experimental approaches have explored techniques for priming promotion- and prevention-focused interpretations of specific problems and situations that (as is the case with BeanFest) involve potential success and failure and gain and loss. There are close affinities here to the concept of “gain– loss framing” (Kahneman & Tversky, 1984), where preferences for different options can be affected by whether the same outcome is presented as a gain over a less desirable reference point (e.g., lives saved as a result of treatment) or a loss compared with a more desirable reference point (e.g., lives lost despite treatment). To this end we adopted a technique devised by Friedman and Foerster (2001) for priming approach and avoidance behavior through promotion and prevention cues. This involved participants tracing routes on visually presented mazes. In the promotion focus condition, these mazes were presented as involving an animal seeking food at the end point of the maze. In the prevention condition, these involved an animal escaping from a larger predator, with the end point of the maze being a safe refuge. Each participant completed three mazes (under the same focus), once before the BeanFest game and twice at intervals between blocks of the game. In addition, participants in the promotion focus condition started the game with 0 points and were told to try and get 100, whereas those in the prevention focus condition started with 100 points and were told to try to avoid dropping to 0, with no “energy loss via time.” (This

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manipulation of points targets had not been found to influence game behavior or learning by itself in a previous version of the experiment.) As predicted, promotion focus led to a significant reduction in the learning asymmetry, with more good beans and fewer bad beans being correctly identified, compared with the prevention focus condition. Mediational analysis indicated that this effect of focus on learning asymmetry was mediated by differences in approach behavior during the game, with promotion focus leading to more approach than prevention focus. These findings suggest that motivations triggered by promotion and prevention cues external to the BeanFest game itself may lead to greater risk acceptance or aversion, with consequent effects on attitude formation.

SOCIALLY TRANSMITTED ATTITUDES AND INDIRECT EXPERIENCE Our focus so far has been on how individuals acquire attitudes from their own experience, without any guidance for other people about what actions or objects should be approached or avoided. However, in many real-life contexts, our social interactions will be partly guided by socially transmitted attitudes, expectancies, encouragements, warnings, prejudices, and other kinds of information. Reliance on socially transmitted knowledge and experience is clearly functional in that it means that we do not have to discover everything for ourselves. The literature on social learning processes in personality and social development (Bandura, 1977; Mischel, 1973) is one of the many traditions of work that emphasize this theme. However, the implications of this for attitude formation have been relatively under-researched in comparison to topics such as the acquisition of behavioral and cultural norms. Even when the importance of socially transmitted expectancies for attitude–behavior relations has been more explicitly recognized, as with the inclusion of the subjective norm component in the theory of planned behavior (Ajzen, 1991), specific consideration of how such subjective norms have been acquired—and how this might combine with attitude formation processes more generally—has been largely lacking. What then might be the combined effect on attitude learning of participants’ own direct experience and evaluative information received indirectly from other people? Previous research has compared the effects of direct and indirect experience (indicating among other things that attitudes based on direct experience are more predictive of behavior, Fazio & Zanna, 1981, and more resistant to counter-persuasion, Wu & Shaffer, 1987). Here, though, we are not concerned with the relative effectiveness of

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direct and indirect experience for behavioral prediction so much as with how they might interact dynamically. Specifically, might socially transmitted information (indirect experience) guide individuals’ exploratory behavior and hence shape the direct experience on the basis of which individuals’ attitudes are formed? What happens when such direct experience confirms or disconfirms such expectations? A first attempt to address this question was made in Experiment 5 in Fazio et al. (2004). Before playing the BeanFest game, participants were told that the main focus of the experiment was on “how well people can learn across generations.” They would therefore be shown comments supposedly written by previous participants. These comments were presented to participants individually in folders, each containing two hand-written notes. One note was supposedly from a “first generation” player, the second from a “second generation” player who had been shown the first generation player’s note. The first player reported having been very successful and passed on the advice either to eat or avoid a specific class of beans (circular ones with few speckles, i.e., region 1 in Figure 19.2), whereas the second player reported having followed this advice and found it “very helpful.” Participants then played the game as in other conditions, either with the valences of the beans as in the original matrix shown in Figure 19.2, or with the valences reversed. This meant that the particular beans participants were advised to either eat or avoid were actually good (original matrix) or bad (reverse matrix). Our main interest was in the effect of misleading information, in conditions where participants were advised either to eat beans that turned out to be bad, or avoid beans that were actually good. The main finding was that participants were able to discount the former kind of advice, since by sampling the bad beans they discovered their true value. In the latter condition, however, they tended to follow the advice to avoid the beans in question and therefore failed to discover that they were in fact good. In other words, the impact of advice was mediated by participants’ own direct experience of the beans. In a sequel to this study (Eiser, Shook, & Fazio, 2007), we looked at the effects of advice that the set of beans taken as a whole (rather than just those in a single region) were predominantly good, and to be eaten, or bad and to be avoided. The same cover story of learning across generations was used, but this time participants only read the note from a first generation player, without corroboration from a second generation player. We anticipated that the former (good) advice would lead to a reduction in the learning asymmetry effect compared with the condition

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where participants were told most beans were bad. This was in fact the case, provided that participants did indeed start the game by following the advice they had been given; in other words, the effect of advice on learning was mediated by participants’ actual approach or avoidance behavior.

THE GENERALIZATION ASYMMETRY As noted earlier, participants in the BeanFest experiments show evidence of generalizing the attitudes that they develop toward the game beans to novel beans. The more closely a novel bean resembles a known positive (or negative), the more likely it is to be classified as positive (or negative). Despite this effect of resemblance, a strong asymmetry is also evident. It takes less resemblance to a negative to be declared negative than it takes resemblance to a positive to be declared positive. This generalization asymmetry has proven remarkably robust. It has been evident consistently across the various experiments that we have conducted. It has not been moderated to any significant degree by the manipulations that influenced the learning asymmetry. So, the generalization asymmetry was apparent regardless of whether feedback during the game was or was not contingent on approach behavior, regardless of whether positive or negative beans assumed more extreme values, and regardless of whether participants were induced to adopt a promotion or a prevention focus. Recent research by Shook, Fazio and Eiser (2007) provides the most extensive analysis of the generalization asymmetry to date. This investigation examined attitude generalization as a function of visual similarity to objects that varied from extremely positive to mildly positive to mildly negative to extremely negative. Instead of employing the standard matrix in which three regions are associated with a value of +10 and three with a value of −10, Shook et al. reduced the value of good beans in one of the three regions to +2 (while leaving the remainder at +10) and at the same time changing that of bad beans in one region only to −2 (while leaving the remainder at −10). Each bean, i.e., each cell of the matrix, was treated as the unit of analysis, with the average response to the bean across participants representing the presumed value of the bean. (Actually, four matrices, varying the location of the +2 and −2 regions, were included so as to unconfound value with specific visual characteristics.) Other things being equal, the more similar a novel bean was visually to a previously experienced game bean (i.e., the closer in the matrix), the more it was judged to share the same valence. As predicted, this tendency was

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even stronger for novel beans that more closely resembled previously experienced extreme negative beans than for those resembling (i.e., near in the matrix to) either extreme positive or mild negative beans. The extra potency of losses over gains was further evidenced by the fact that the tendency to rate novel beans similar to a mild negative (−2) bean as bad was of comparable strength to the tendency to rate novel beans similar to an extreme positive (+10) bean as good. Shook et al. conducted additional analyses to predict participants’ judgments of the novel beans from their individual responses to the original game beans (as distinct from the actual values of these game beans). The question addressed was whether any given novel bean would be judged as more similar in value to how those in the nearest region of original game beans were judged, or to those in the second nearest region of game beans (that would in fact be of opposite valence to the first). As expected, novel beans tended to be judged as more similar in value to the game beans in the nearer region than to those in the region slightly further away, but this effect of proximity was less marked when the nearer region was judged positive and the second region negative. This last finding is important in confirming that the generalization asymmetry is more than just a by-product of the learning asymmetry. In other words, one might expect some tendency for novel beans to be seen as predominantly negative just because participants typically succeed in identifying more negative than positive beans during the learning phase. In fact, this is what happens in the simulations reported by Eiser et al. (2003). The network’s “judgments” of the value of novel beans showed clear evidence of generalization on the basis of similarity, or proximity within the matrix, to the learnt values of the beans presented during the learning phase. In other words, if the network classified a training bean as bad (or good), it classified novel beans adjacent to it in the matrix similarly. There was a tendency for some novel beans adjacent to good training beans to be judged as bad, but only if the good training beans themselves were misclassified as bad. In other words, any tendency to predict novel beans to be bad rather than good in these simulations depends entirely on the learning asymmetry. This is not the case in the human experiments. The generalization asymmetry still is apparent after controlling for the learning asymmetry. Unlike the learning asymmetry, the generalization asymmetry does not depend on a structural mechanism involving the contingent relation between information gain and approach behavior (since it is found also under conditions of full feedback), nor is it purely a function of

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how well participants learn to differentiate the original stimuli. Instead, it appears to be an illustration of the frequently discussed proposition that negativity is more powerful than positivity (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001; Cacioppo, Gardner, & Bernston, 1997; Rozin & Royzman, 2001; Taylor, 1991). When judging a novel stimulus, perceivers weigh its negative features more heavily than its positive features. Another dramatic illustration of this negativity bias— this tendency to weigh the negative more heavily than the positive—was apparent in a recent study conducted by Eiser et al. (2007). The study focused on participants’ self-assessments after playing the BeanFest game. Participants provided evaluative ratings regarding the efficacy of the strategy with which they approached playing the game. A straightforward hypothesis would have been that participants would evaluate their own game strategy more positively both if it led to more positive reinforcements (true-positive approaches to good beans leading to a gain in points), and also to fewer negative reinforcements (false-positive approaches to bad beans leading to a loss in points). Interestingly, participants’ evaluations of their own strategy were strongly inversely related to the number of bad beans they approached, but not at all related to the number of good beans they approached. This is further evidence of how negative information looms larger than positive in its influence on evaluative judgment—in this case, with respect to self-assessments.

IMPLICATIONS FOR PREJUDICE We have described the findings from our BeanFest experiments in some detail, not because, obviously, we have any special interest in beans—real or virtual—but rather because we believe the processes underlying participants’ choices in this simple game may have wider relevance to people’s cognitions, feelings, and behavior in their real social environment. The starting point for any such extrapolation is a set of related ideas centering around the notion of uncertainty. We inevitably have incomplete knowledge of our physical and social environment, and because of this, every action we perform involves some element of risk. One way of reducing uncertainty and hence risk is by gaining more knowledge, but extra knowledge rarely if ever comes risk-free. To find out more about unfamiliar places, people, activities, etc., we have to be prepared to approach and engage with them and to allow our own happiness or unhappiness, gains or losses, to be affected by them in ways we can predict only imperfectly, if at all. So a trade-off has to be struck

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between the gains of new knowledge and experience on the one hand, and the effort, cost, and even danger of seeking such knowledge. This could be viewed as directly analogous to the issue of “energy budgets” in animal foraging (Bateson, 2002): will the energy expended in hunting or foraging be adequately compensated for by the energy gained from a new source of food? If animals fail to manage their energy budget efficiently, they will not survive, and for this simple reason we can assume that selection processes lead animals to be reasonably efficient in this respect, at least so long as the environment remains fairly stable. As humans, we still need to make trade-offs but the equations are far less well defined or deterministic, and the personal penalties for dysfunctional choices are often far less obvious or at least immediate. From a societal perspective, some of the most dysfunctional choices are those involving prejudice against an out-group. In particular, we can ask why negative attitudes and stereotypes persist in ways that are unsupported by evidence. This is clearly only one of the very many questions that could be asked, along with why certain out-groups historically have been the target of prejudice to a greater extent than others, why prejudiced beliefs involve particular kinds of stereotypic content and how these may be linked to broader ideologies, why prejudice may lead to discrimination, dehumanization, and extermination. The last thing we wish to appear to do is to trivialize these issues, or suggest that they can all be reduced to the structure of a simple computer game. Yet even so, we believe that there may be some continuity between the processes underlying the persistence of falsenegative avoidant tendencies and beliefs in our experiments and such real-world phenomena. The common link is that positive attitudes constitute a basis for motivation to approach, and negative attitudes a basis for motivation to avoid (Zajonc, 1998). To the extent that individuals can act out such motivations, they will interact with people they like and avoid interaction with people they dislike. The consequence of avoiding interaction is a lack of direct experience that might well disconfirm previous negative beliefs. Hence, false-negative avoidant tendencies and beliefs (prejudices) may well persist relatively unchallenged by experience. One might well ask where such positive and negative attitudes come from in the first place. If we take “the first place” to mean an individual’s earliest encounters with members of particular groups, these could well differ in the extent to which they are experienced as pleasant or unpleasant, reassuring or threatening. The relationship between attitudes and approach–avoidance behavior is

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essentially dynamic. As with all dynamic systems, we may witness an extreme sensitivity to differences in initial conditions (Eiser, 1994), so that small events can steer the social development of different individuals in directions of increasing divergence. Furthermore, as our experiments also show, socially transmitted beliefs, based supposedly on others’ experience, can have a similar effect in terms of steering approach or avoidance. Nor is such reliance on others’ opinions and advice irrational or unreasonable in the broader scheme of things. Reading consumer reports, travel guides, theater reviews, etc., can save us time, money, and disappointment, even if we also learn that we need to take some of these with a pinch of salt. When parents advise their children against accepting lifts from strange men, this is clearly sensible precautionary advice, even if not all strange men are molesters. The difficulty is being able to distinguish the types of advice that are reasonable and well-founded from those that are not. This difficulty is even greater when the advice or attitudes we receive from others leads to avoidance, and where the costs of avoidance (including falsenegative avoidance decisions) are affordable. Someone might take it into their head to avoid certain kinds of unfamiliar foods or ethnic cuisines—maybe they have been treated to horror stories of unhygienic practices or suspicious ingredients—but they are unlikely to starve as a consequence. Likewise, in many social contexts, individuals may neither have much opportunity nor feel any special need to form close friendships across ethnic, linguistic, or religious divides. Even without any perception of danger, it may simply be thought to involve more effort for no obvious gain. Similarity remains an important default cue for attraction (Berscheid & Walster, 1978). All this implies that many socially transmitted prejudices and negative attitudes may be assimilated in a relatively “mindless” (Langer, Blank, & Chanowitz, 1978) or uncritical way, and this may be especially the case where the target groups are ones with which the individual has only limited, if any, opportunity for direct interaction. When such interaction opportunities do arise, invalid negative prejudices diminish the likelihood that they will be pursued. Precisely such avoidance as a function of negative racial attitudes has been demonstrated in recent research. Towles-Schwen and Fazio (2003) observed a relation between automatically activated racial attitudes and participants’ expressed willingness to enter various situations involving interracial interaction. Plant and Devine (2003) likewise found that engagement in interracial interaction was inhibited by anticipated anxiety. The BeanFest findings illustrate what can happen when the relevant attitudes are unwarrantedly negative. The

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resulting avoidance behavior markedly reduces the chances of discovering the invalidity of the negative attitudes. Another set of questions relate to how prejudices might be overcome, especially through direct experience. If risk-averse avoidance of interaction with out-group members underlies the persistence of prejudice, then perhaps part of the answer is to increase the opportunities for such interaction. Such reasoning is the basis for the “contact hypothesis” that increased opportunity for intergroup contact can lead to an attenuation of prejudice (Deutsch & Collins, 1951; Pettigrew, 1997). However, most of the research evidence suggests that it is the quality of contact, in particular formation of interethnic friendships, rather than contact per se, that is important. This is consistent with our argument that increased approach does not automatically lead to a blanket increase in positive attitudes, but rather to more complete feedback. This then allows more accurate identification of positive attitude objects (i.e., more true-positive approaches), along with a more evidence-based avoidance of negative attitude objects (i.e., fewer false-positive approaches, or more true-negative avoidances). In less technical terms, this can lead to a more differentiated view of out-group members as individuals, with some of whom friendships are easier, and with others, less so.

IMPLICATIONS FOR SELF-EVALUATIONS AND HAPPINESS The reinforcements we receive from our social interactions not only lead us to hold positive and negative attitudes about other people, they critically affect the way we think about ourselves. If other people are nice to us, and show that they like us, then this surely “proves” that we are likable, and worth being nice to. Conversely, if people are nasty to us, and show they dislike us, then this just goes to show that we are nasty too, and do not deserve to be liked. A wide variety of studies suggest that our selfevaluations are related to how we believe others evaluate us (Bem, 1972; Fazio, 1987). Similarly, success can boost our self-esteem while failure or other negative life-events can damage it. If such failure persists, it can lead to depression. Naturally, there are individual differences in resilience to setbacks, and one moderating factor may be the extent to which success or failure is attributed internally to one’s own character, skill, or effort (or the lack of these), or externally to chance or the actions of others (Mullen & Riordan, 1988). However, such interactions need to be interpreted in context. Overall we are dealing with some powerful main effects: good events make us

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feel good and tend to raise our self-esteem, whereas bad events make us feel bad and tend to lower our self-esteem (Crocker & Wolfe, 2001). But here we confront an interesting paradox. Despite the fact that we are risk averse in many of our personal life-choices (implying that we see much of the world as beset with danger), and despite the fact that negative events typically appear to have a greater impact on social judgments than do positive events (Baumeister et al. 2001; Rozin & Royzman, 2001; Skowronski & Carlston, 1989), most of us describe ourselves as relatively happy, much of the time. Furthermore, if asked to compare ourselves with “average” others, we generally tend to rate ourselves, within the constraints of modesty, as more likely to experience success and less like to experience failure or mishaps such as illness or injury and as better on a wide variety of attributes (Alicke, Klotz, Breitenbecher, Yurak, & Vredenburg, 1995; Weinstein, 1980, 1982). Although the strength of such reported effects depends to some extent on the format in which such questions are asked (Eiser, Pahl, & Prins, 2001), the overall message still seems relatively clear: most of us, for much of the time, are relatively pleased with ourselves and with our lot in life. This tendency is all the more remarkable in the light of the fact that people can adapt surprisingly readily to changing life circumstances. In broad terms, we may overestimate the extent of any lasting changes to our happiness from positive and negative life-events (Wilson & Gilbert, 2003). Brickman, Coates, and Janoff-Bulman (1978) found that lottery winners reported little lasting gain in happiness. Likewise, the loss in well-being as a consequence of misfortune, injury, serious illness, or bereavement may be less severe in actual experience than in imagination (Lehman, Wortman, & Williams, 1987). But such homeostatic adaptive processes do not reduce everyone’s sense of happiness and well-being to “average.” On the contrary, on average most of us tend to see ourselves as somewhat happier than average (Diener & Diener, 1996). Although it is almost a truism that all social judgments (including judgments of our own happiness and wellbeing) are relative rather than absolute (Eiser & Stroebe, 1972), there is nothing fixed about the standards of comparison we use, and to which our judgments are relative. Most of the work of comparative or unrealistic optimism appears paradoxical in that it asks participants to compare themselves with an interpersonal standard or average. The finding that respondents, on average, rate themselves as somewhat above average suggests the operation of some kind of positivity bias, but this just pushes

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the question one step on. If we show a positivity bias in our self-appraisals, how has this come about? How does it reflect our personal history and experience of reinforcements? A possible answer is that, when we experience events as relatively positive or negative, we are not generally performing any interpersonal comparison (even if asked to do so), but rather comparing our experience with an intrapersonal or subjective standard. Still we are left with the question of why we mostly rate experiences as better than average, when our subjective standard may adapt to our personal distribution of good and bad events. But this is not such a difficult question to answer if we take account of how such subjective standards adapt to reflect the full distribution of our experiences. The classic theory of adaptation processes in social judgment is Helson’s (1947, 1964) adaptation-level theory, according to which all experiences are judged against a weighted average of all previous experiences along the relevant sensory continuum. Later research (see Eiser & Stroebe, 1972, for an early review) showed Helson’s formulation to be too simplistic. Among many other considerations, account needs to be taken of the shape (i.e., skewness) of the distribution of the stimulus events presented or experienced. According to Parducci (1963), a better prediction of an individual’s subjective average or adaptation-level can be derived from a combination of the midpoint between the extremes of the stimulus distribution and the median (a so-called range-frequency compromise). If the stimulus distribution is normal (or rectangular), the midpoint and median will coincide, and equal the arithmetic mean. However, if there is any skew, they will diverge. What has any of this to do with happiness? Well, Parducci (1984) offers an interesting and plausible speculation. Suppose most people’s distributions of life-events are positively skewed, i.e., characterized by relatively frequent events that are moderately positive, and rather fewer, but somewhat more extreme, negative events. If this is the case, then the midpoint of their distribution would be lower than their median and, since their adaptation-level (subjective average) lies between the midpoint and the median, the majority of events would be experienced as better than average. The result: happiness. This is a neat argument, but it raises an obvious question: why should most people’s experiences of life-events be distributed as Parducci suggests? We can offer an answer in two parts. First, the possibility that negative events are experienced as more extreme fits well with the broader evidence on the salience of negative information. Second, a predominance of moderately positive outcomes

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follows directly from the general tendency for risk-averse decision making, where individuals approach familiar objects they are confident are good, thus obtaining a satisfactory return of true-positives, while avoiding objects about whose valence they are less certain, thus minimizing the number of false-positive approaches, or nasty surprises, even at the price of missing out on available rewards of which they are unaware (false-negative avoidances). Any general statements of this kind need obviously to be hedged around with a number of caveats. One of the most obvious is that the argument rests on the assumption that we can mostly avoid bad things happening to us, in other words, that conditions allow our approach and avoidance motivations to carry forward into approach and avoidance behaviors. Risk aversion is only functional if risks can indeed be avoided. If they cannot, the consequence is not happiness but a kind of learnt helplessness (Alloy, Abramson, & Francis, 1999; Seligman, 1975). For individuals deprived of free choice in oppressive lifecircumstances or abusive relationships, positive outcomes may be the exception, and negative outcomes the norm. Another is that there is huge variation in the kinds of experiences that different individuals find pleasant and unpleasant. One person’s fear may be another’s excitement, one person’s boredom another’s mellow relaxation. The origins of such differences lie far beyond the scope of the present chapter, but do not affect our basic argument insofar as we assume that it will be individuals’ personal evaluations of different outcomes that guide their approach–avoidance behavior. A more general limitation is that there are many other aspects of feedback other than mere valence that may affect the processes described. Although our experimental situation fits within a general reinforcement learning paradigm, the more general literature on reinforcement learning emphasizes the importance of several parameters of reinforcement schedules beyond those we have manipulated. Note that, in BeanFest, every good bean is good, and every bad bean is bad, on every occasion they are presented and sampled. We have not explored the subtleties of partial reinforcement, variable interval or ratio schedules, or other such variations that were studied intensively in the animal learning literature for most of the last century. Our narrower focus reflects the limitations of our own efforts rather than any dismissal of the lessons that might be drawn from this wider literature. Nonetheless, we are struck by how few of these lessons have been drawn by social psychologists in general, and attitude theorists in particular.

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CONCLUDING REMARKS Like all contributors to this volume, we regard the distinction between approach and avoidance motivations as fundamental to psychological theory across many different areas. Our own focus has been on how such motivations interface with attitude processes as studied by social psychologists. Relating attitudes and motivations to each other immediately draws attention to the behavioral implications of attitudes. For the best part of 70 years or more, researchers have been concerned about such implications, but mainly from the perspective of how well attitude predicts behavior. We have argued for a more dynamic view of this relationship. Attitudes may motivate approach and avoidance, but approach and avoidance in their turn shape the experiences on which our attitudes are based. One of the simplest to state, but at the same time most startling and profound, challenges for attitude theory is the fact that different individuals can disagree in their evaluations of the same attitude object or issue, and sometimes violently. It is almost a truism that such differences in attitude reflect different selective perceptions of the issue, but what gives rise to such selectivity? We hope we have demonstrated that part of the answer can lie in the divergent experiences, and hence learning histories, that arise from different levels of risk acceptance, exploration, and hence discovery associated with approach and avoidance under conditions of uncertainty.

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Part V Emotion and Well-Being

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Structure of Emotions and Emotivations: 20 Motivations Approach, Avoidance, and Other Tendencies in Motivated and Emotional Behavior Ira J. Roseman CONTENTS Motivations and Emotions: Why Do We Need Them (Both)? ..............................................................344 What Is Motivation? .........................................................................................................................344 What Is an Emotion? ........................................................................................................................345 Similarities Between Motivations and Emotions .............................................................................345 Differences Between Motivations and Emotions .............................................................................345 Motivations as Specific Purpose Mechanisms; Emotions as General Purpose Mechanisms ...................................................................................................................346 Motivations as Relatively Deliberative; Emotions as Relatively Impulsive ................................346 Emotions Preempt Motivations ...................................................................................................346 Relationships Between Motivations and Emotions ..........................................................................347 Functions of Motivations and Emotions...........................................................................................348 Determinants of Motivated and Emotional Behavior..................................................................348 Alternative Determinants ............................................................................................................350 Why Incorporate Both Motivations and Emotions Into Theories of Behavior? ..............................350 Two Types of Motivation and Emotions ............................................................................................... 351 Two Types of Motivation .................................................................................................................. 351 Two Types of Emotions (When Emotions Are Motivations) ........................................................... 352 What Is Approached or Avoided in Motivated and Emotional Behavior? ....................................... 352 Why Have Two Types of Motivation and Emotions? ....................................................................... 352 Discrete Emotions: Beyond Two Types ............................................................................................ 353 There Is More to Emotions Than Positive and Negative ............................................................. 353 Only Degrees of Positive Versus Negative Affect and Arousal?................................................. 353 Specifying Emotion Response Syndromes and Strategies ...............................................................354 Emotion Families .............................................................................................................................356 More to Emotions Than Approach and Avoidance .......................................................................... 358 Why Do Emotions Prompt More Than Approach and Avoidance? ............................................ 358

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Approach Versus Avoidance Motivation as a Determinant of Specific Emotions ........................... 359 Reward-Maximizing Versus Punishment-Minimizing Motivation as a Determinant of Joy-and-Sadness Versus Relief-and-Distress ............................................................................... 359 Summary ............................................................................................................................................... 361 References ............................................................................................................................................. 361

The concepts of motivation and emotion have been used across cultures and historical time periods to help explain human behavior. But motivation and emotion often are assigned to do similar theoretical work: accounting for the energy of behavior, that is, determining whether or not any action will occur and/or the magnitude or intensity of action (e.g., Hull, 1943; Lindsley, 1951). Motivation and emotion are usually also held to influence the direction of behavior: determining which particular behaviors will occur. But determining direction is not as unique a function of these variables, given that situational, learning history, and cognitive factors are also held to influence behavior specificity. Perhaps in part because both variable types can account for the energization of action, during some periods in the history of psychology either motivation or emotion—but not both—has played relatively dominant roles in the mainstream of psychological theorizing. For example, from the 1920s through the 1950s, motivational or motive-like constructs such as instinct, drive, and reinforcement were much discussed and emotion got relatively short shrift; from the 1960s through the present, emotion became more dominant and there has been correspondingly less theoretical and research interest in motivation (though interest in motivational constructs seems to have been rising since the 1980s; see, e.g., Sorrentino & Higgins, 1986). But while motivation and emotion may perform similar functions in psychological theories, and a number of theories do not distinguish between them (e.g., Murray, 1938; Plutchik, 1962), it is also true that different properties have been ascribed to motivational and emotional constructs, and some theoretical systems include both types of variables (e.g., as described below). In this chapter I will examine the general similarities, differences, and relationships between motivations and emotions, and also consider whether there are different types of motivations and emotions which have different types of effects upon behavior.

MOTIVATIONS AND EMOTIONS: WHY DO WE NEED THEM (BOTH)? What is a motive? What is an emotion? How are the two alike, and how do they differ? These are simple, straightforward questions, but they do not currently have simple,

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straightforward answers. Theorists disagree, at least to some extent, about how motivation should be defined, and disagree profoundly about the nature of emotion.

WHAT IS MOTIVATION? Kleinginna and Kleinginna (1981a,b) reviewed many definitions of both motivation and emotion, and proposed what they hoped might be integrative conceptualizations. They suggested (1981b, p. 272) that the term motivation refers to internal mechanisms that proximally energize behavior and give it direction (facilitating some actions while inhibiting others). In the introductory chapter to this volume, Elliot also identifies motivational processes as energizing and directing behavior, either toward positive stimuli or away from negative stimuli. A broader definition was adopted in Madsen’s (1968, 1974) review of more than 40 motivation theories: motivation was defined as encompassing “all variables which arouse, sustain, and direct behavior” (1968, p. 46; see also Reeve, 2005). However, Cofer and Appley (1964), in their classic volume Motivation: Theory and Research, argued that a definition of motivation which encompasses all internal and external causes of behavior is too broad. Nonmotivational causes of behavior, in their view, include externally applied force (such as a shove), the simple physical structure of an organism, and existing habits. They suggest that motivation might be postulated based on any or all of the following properties: “that behavior occurs at all, that a variety of responses is facilitated by some operation (like deprivation of food), that responses vary in vigor, that behavior has direction, that certain kinds of subsequent event may strengthen (and other kinds may weaken) a behavioral sequence” (p. 13). If we combine 1. Kleinginna and Kleinginna’s (1981b) conception of motivation as an internal state that serves to energize and direct behavior, 2. Cofer and Appley’s distinction between merely caused versus motivated behavior, and their motivational properties of

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Motivations and Emotivations

a. Facilitation of varied responses and b. Strengthening or weakening of behavioral sequences by subsequent events, and 3. Elliot’s emphasis on approach and avoidance, we may arrive at a conception of motivated action as behavior that can be described as at least partly determined by its consequences (e.g., increasing positive stimuli or decreasing negative stimuli)—that is, behavior which seems goal directed (for other conceptualizations of motivation in terms of goal-directed action, see Gollwitzer & Bargh, 1996). I use the phrase “described as” (rather than actually) determined by its consequences, because future states cannot cause present behavior. Instead, some current state or process that is consequence-related (such as an expectation of future goal attainment or a process which repeatedly compares current states to fixed or variable set points or ranges) is causing motivated behavior, so that behavior is facilitated until the current representation or state corresponds more closely to a target set point or range, or less closely to an unsatisfactory set point or range (referred to by Carver & Scheier, 1998, as goals and antigoals respectively). For example, eating is motivated behavior which can be described (in part) as directed toward keeping levels of glucose, lipids, and the hormone ghrelin within target ranges (see Carlson, 2007, for a digestible summary). A motivation, then, is an internal state that produces behavior which can be described as moving toward desirable reference values or away from undesirable reference values.

WHAT IS AN EMOTION? Kleinginna and Kleinginna (1981a) suggested emotion be defined as “a complex set of interactions among subjective and objective factors, mediated by neural/hormonal systems, which can: (a) give rise to affective experiences such as feelings of arousal, pleasure/displeasure; (b) generate cognitive processes such as emotionally relevant perceptual effects, appraisals, labeling processes; (c) activate widespread physiological adjustments to the arousing conditions; and (d) lead to behavior that is often, but not always, expressive, goal-directed, and adaptive” (p. 355). Similarly, in their introduction to the recent Handbook of Affective Sciences, Davidson, Scherer, and Goldsmith (2003) define emotion as “a relatively brief episode of coordinated brain, autonomic, and behavioral changes that facilitate a response to an external or internal event of significance to the organism” (p. xiii). Building on Averill’s (1980) conception of emotion as a syndrome of responses (none of which must occur in every

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instance of the emotion), I have defined emotions as syndromes of “(a) phenomenology (thoughts and feeling qualities); (b) physiology (neural, chemical, and other physical responses in the brain and body); (c) expressions (signals of emotion state, such as facial, vocal, and postural responses); (d) behaviors (action tendencies or readinesses); and (e) emotivations (emotional motivations, conceptualized as characteristic goals that people want to attain when the emotion is experienced)” (Roseman, 2001, p. 75).

SIMILARITIES BETWEEN MOTIVATIONS AND EMOTIONS According to these definitions, motivations and emotions have a number of similarities. Both are internal states or processes (and thus may be able to account for individual differences in response to the same event or situation). Both are used to explain the energy and direction of behavior. Both may lead to goal-directed action.

DIFFERENCES BETWEEN MOTIVATIONS AND EMOTIONS Although motivations and emotions may have a number of similar properties, there are some internal states that tend to be conceptualized chiefly as motivations and others that are more typically identified as emotions. For example, hunger, thirst, sexual desire, and need for achievement have typically been seen as motivations; whereas joy, sadness, fear, and anger are typically regarded as emotions. These and a number of other prototypical motivations and emotions are shown in Table 20.1. The fair amount of consensus, at least on these exemplars, suggests that some differentiation of the two classes may be possible. A number of authors have written about differences between motivations (instincts, drives, needs, motives,

TABLE 20.1 Some States Typically Regarded either as Motivations or as Emotions Motivations Hunger Thirst Sexual drive Competence motivation Need for achievement Need for approval Need for power Cognitive dissonance Need for cognition

Emotions Joy (or happiness) Sadness Fear Anger Love Disgust Shame Pride Distress

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desires, goals, etc., depending on the terminology of the day) and emotions. I will discuss especially the formulations of affect theory pioneer Silvan Tomkins. Motivations as Specific Purpose Mechanisms; Emotions as General Purpose Mechanisms Tomkins (1970) proposed that compared to motives (“drives”), emotions (“affects”) are more general with regard to “object” (p. 105). By this he meant that motives are activated by specific conditions, and direct behavior toward specific ends. For example, hunger is characteristically activated by food deprivation (and its biochemical and visceral consequences), thirst by water deprivation, and need for affiliation by the absence of desired social interaction; and these motives direct behavior specifically toward food, water, and social contact (one cannot generally satisfy one motive with the object of another). In contrast, emotions can be produced by contingencies applicable to any motive. For example, attaining food or water or companionship or any current goal can elicit happiness; a threat to having food or water or companionship or any desired state can elicit fear; and another person’s interference with attainment of any motive can elicit anger (see Scherer, 1988, for examples of the range of events that can elicit joy, sadness, fear, and anger). Motivations as Relatively Deliberative; Emotions as Relatively Impulsive If motivated behavior can be described as influenced by its consequences, then it may be regarded as instrumental or goal-directed. Goal-directed action has been said to have the property of equifinality (Heider, 1958; Tesser, Martin, & Cornell, 1996)—a variety of means may be employed to approach a desired end or avoid one that is undesired. Insofar as cognitive processing influences enactment of particular motivated behaviors, goal-directed action may be described as relatively deliberative. For example, according to Expectancy-Value models of motivation (see Feather, 1982), a person may assess whether or not to take a particular action, or which of several possible actions to take, based on expected consequences (Ajzen, 1991; Atkinson, 1964; Gollwitzer, 1996). Note that such “deliberation” may occur without awareness, as when people unconsciously choose particular words to convey an intended meaning, or decide how to turn the steering wheel to stay on the road while driving (Bargh & Barndollar, 1996); or it may have occurred previously and merely be recalled or activated in a current situation, and as when people have previously decided what foods they will eat if hungry at breakfast time (cf. Ajzen, 2002); or it

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may be based on nonconscious beliefs or expectations, as when an implicit belief that ability is malleable leads to persistence in the face of failure (Dweck, 1999) or when a new person’s resemblance to someone known triggers an unconscious expectation of acceptance or rejection and influences social approach or avoidance (Andersen, Reznik, & Glassman, 2005; Lewicki, 1985). In contrast, much emotional behavior seems relatively impulsive (though I will also argue below for the existence of some deliberative emotional behavior). It seems we often do not plan how to enact our joy, sadness, fear, or anger to the same extent that we plan how to satisfy our hunger, social, or achievement needs (e.g., choosing which foods to eat, which people to approach, or which career goals to pursue). Particular emotions are linked to readinesses or tendencies to engage in particular actions, such as freezing in fear, yelling in anger, and doing nothing in sadness (Frijda, 1986; Lazarus, 1991; Roseman, Wiest, & Swartz, 1994). Many emotion researchers have commented on the feeling of relative compulsion that accompanies much emotional behavior. For example, Frijda (1986) described emotions as having “the character of urges or impulses” that “clamor for attention and for execution” (p. 78). For a recent similar perspective, see Strack and Deutsch (2005) who distinguish between reflective and impulsive motivational systems, with the latter often triggered by positive or negative affect. Emotions Preempt Motivations The main distinction between motivations and emotions mentioned by Tomkins (1970) is that emotions typically take precedence over motivations. Tomkins argued that sexual drive, for example, which was accorded such importance in Freudian theory, is easily disrupted by emotions such as anxiety or shame. Many other examples could be cited. Research indicates that when afraid: infants reduce exploratory behavior (see Kobak, 1999), adults reduce achievement striving (Birney, Burdick, & Teevan, 1969), and rats reduce eating (e.g., when a predator may be present; Fanselow & Lester, 1988). Although mild sadness may facilitate eating and socializing, intense sadness (as in grief or a major depressive episode) more often results in loss of appetite, loss of libido, a reduction in socializing, and loss of interest in activities formerly pursued (American Psychiatric Association, 2000; World Health Organization, 2007). Frustration caused by preventing children from playing with attractive toys was observed to lead to aggressive play which destroyed the very toys that had been sought (Klein, 1982, discussing the findings of Barker, Dembo, & Lewin, 1941). Even positive emotions such as joy, which can increase eating,

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sexual behavior, and social motivation, may reduce sustained pursuit of any of these or other specific motives, replacing it with “free activation” (Frijda, 1986), which involves increased distractibility (as in manic episodes, which are typically characterized by elevated mood; see American Psychiatric Association, 2000) and responsiveness to whatever features of a stimulus situation seem likely to sustain good mood or reward (Isen, 2000; Roseman, Swartz, Newman, & Nichols, 2007). Note that the primary contention here is that emotions preempt pursuit of nonemotional motivations, rather than eliminating those motivations. But I am not suggesting that emotions result in an absence of goal pursuit. Instead I will argue below that each emotion engenders its own (emotion-specific) motivation, which tends to take precedence over nonemotional motivations, such as those listed in Table 20.1. Nor do emotions of any strength preempt all nonemotional motivation, as shown by instances in which emotions are regulated in order to achieve social, sexual, or achievement goals (see Gross, 1999). Rather, it may be proposed that emotions tend to preempt nonemotional motivations of comparable (or lesser) strength.

RELATIONSHIPS BETWEEN MOTIVATIONS AND EMOTIONS At the influential Loyola Symposium on Feelings and Emotions, Leeper (1970) proposed that motives are related to emotions in two ways. First, emotions are perceptions of what a person “regards as the most significant realities in his life” (p. 164). This suggests that emotions result in part from motives. Many contemporary emotion theorists make similar claims. For example, I have proposed (Roseman, 1984, 2001) that positive and negative emotions are produced by perceptions about the consistency versus inconsistency of situations with a person’s current motives. Scherer (1984, 2001) views positive versus negative emotions as produced by goal-conducive versus goal-obstructive evaluations, as well as by intrinsically pleasant and unpleasant events. Frijda (1986, 2007) regards emotions as responses to match and mismatch of events with an individual’s “concerns.” Lazarus (1991, 2001) viewed emotions as arising in part from appraisals of goal-congruence versus incongruence; the dimension is “motivational congruence” in Smith and Kirby’s (2001) theory. Research supporting this claim indicates that emotions indeed result in part from motives: an emotion is caused by having some motive (goal, preference, etc.), and perceiving that a stimulus or event has implications for attainment of that motive (e.g., Roseman, 1991; Roseman & Evdokas, 2004; van Reekum et al., 2004).

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Second, according to Leeper, emotions are motives. That is, emotions motivate behavior, giving it energy and direction. This perspective is explicitly or implicitly endorsed by a number of motivation theorists (e.g., Brown, 1961; Murray, 1938; Weiner, 1985) and most emotion theorists (e.g., Frijda, 1986; Izard, 1991; Lazarus, 1991; Plutchik, 1980). But many of the latter see emotions as causes of behavior, rather than as motivators which establish goals to guide action. This fits with the view, discussed above, that emotions prompt impulsive behavior rather than planful instrumental action. However, there is reason to believe that emotional processes can also engender goals that guide behavior, just as do hunger, thirst, need for achievement, and other motivations. For example, fear may motivate a person to engage in a variety of behaviors (e.g., freezing, hiding, fleeing, calling for help, and defensive aggression) that move the person away from some danger and toward safety (cf. Plutchik, 1980). Anger may motivate a person to engage in a variety of aggressive actions (behaviors intended to hurt someone), such as hitting, criticizing, taunting, thwarting, giving the silent treatment, and so forth (Berkowitz, 1999; Underwood, 2003). Love may motivate a person to engage in a variety of behaviors that increase interpersonal closeness, such as physical proximity maintenance, caregiving, and initiating sexual contact (Shaver, Morgan, & Wu, 1996). In accord with this view, research participants recalling experiences of: fear, say that they wanted to get to safety; anger, say that they wanted to hurt someone; and love, say that they wanted to be close to someone—more than do participants recalling experiences of other emotions (Roseman et al., 1994, 2007). Indeed, unless we recognize that emotions involve action toward a goal, it is difficult to adequately understand (a) what the different behaviors that may be enacted when feeling a particular emotion have in common (e.g., in anger, yelling at someone and giving the silent treatment may have extremely different surface properties but serve the same goal—hurting the target in some way, for example, making the target feel bad) and (b) sequences of emotional behaviors, in which one behavior (e.g., the silent treatment) fails to attain an emotion’s goal (making the target feel bad) and is then replaced by another behavior (e.g., criticizing or thwarting). Thus I am proposing (cf. Roseman et al., 1994) that emotional behavior is organized at two levels: the level of action readiness patterns, in which particular emotions are linked to particular actions (given particular stimulus conditions); and the level of emotivational goals, in which particular emotions are linked to emotion-specific goals (which can organize a wider variety of behaviors aiming to achieve those goals).

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FUNCTIONS OF MOTIVATIONS AND EMOTIONS Why might an organism have two systems—motivational and emotional—for energizing and directing behavior? I suggested above that motivational processes are often more deliberative than emotions, selecting among alternative actions those that are relatively likely to increase motive attainment in light of situational conditions and outcome expectancies; whereas emotional processes are often more impulsive, involving greater reliance on relatively prespecified, evolution-tested patterns of action readiness. Behavior organized by emotivational goals occupies a middle ground: an emotion urges the adoption of its more general emotion-related goal (e.g., hurting another person, when feeling anger) instead of a more specific motivational goal (e.g., gaining approval; maintaining a friendship), but there is flexibility in selecting the particular actions that aim to achieve that goal (e.g., criticizing; thwarting; refusing to interact with the person). Together with behavior that is neither motivated nor emotional, this set of processes provides organisms with multiple behavior control systems suitable for situations that differ in the need for rapid action. That is, affectively neutral states would seem to exert the least constraint on action, permitting an infinite range of behaviors that might be initiated or sorted through in a temporally unlimited manner. Motivations allow for relatively flexible action, with behaviors that can be generated or selected at least partly based on their potential to advance current goals and block antigoals. Comparatively, emotivational goals reduce flexibility in goal selection—decreasing response time by increasing focus on a particular general purpose goal (such as getting to safety) in place of more time-consuming processing of multiple specific purpose goals. Emotional action tendencies and readinesses further constrain the set of behaviors that are likely to be initiated, with the smaller number of action options permitting even faster response. Thus the motivation system allows for relatively flexible behavior when conditions permit, and the emotion system allows for more preprogrammed behavior when faster action is needed. This formulation fits conceptions of emotions as “emergency” responses (Cannon, 1932) or “coping mechanisms” (Lazarus & Folkman, 1984). As such, it may seem most suited to negative emotions (Fredrickson, 1998) such as fear and anger. Faced with an immediate threat, it may be vital to have in the behavioral repertoire preorganized readinesses for responses such as flight and fight to cope quickly with the crisis (see, e.g., LeDoux, 1996; Tooby & Cosmides, 1990). But the framework can be extended to encompass positive emotions as well, if we recognize the existence

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of time-limited opportunities that should be seized before they slip away (Roseman et al., 2007). One example is the appearance of another person who is appraised as having the potential to greatly enhance motive fulfillment (e.g., as a potential mate, caregiver, close friend, or other important relationship partner). The positive emotion of love (what Shaver et al., 1996, call “surge love”) may be the emotional response to such a stimulus, involving readiness for behaviors that form, maintain, and strengthen relationships. Similarly if the emotion of pride is a response to positive outcomes caused by the self (Roseman, 1991; Stipek, 1995) and engenders readiness for culturally syntonic self-display and self-assertion, it may serve to seize an opportunity (for acquiring social standing, dominance, resources, etc.) at a moment in time when those behaviors are most likely to meet with success, insofar as other people can see or be shown evidence of the self-caused positive outcomes (Roseman et al., 2007). Overall, then, positive and negative emotions provide ways for organisms to seize opportunities and cope with crises, by engendering time-tested patterns of action readiness when there may not be time to more deliberatively consider the relative advantages, disadvantages, and potential consequences of particular behaviors or behavior alternatives. Determinants of Motivated and Emotional Behavior What factors influence whether action is governed primarily by nonaffective processes, by motivations, by emotivational goals, or by emotional action tendencies? As shown in Table 20.2, two possible determinants are motive-relevance and actual or potential change in motiverelevance perceived in a situation. According to Table 20.2, if a situation lacks relevance to all active motives—for example, because no motives are active at a given time, or the person perceives that action would have no impact on progress toward active goals or preferences (cf. Bandura, 1997)—behavior would be neither motivated nor emotional. Behavior may nonetheless occur (organisms may be active even when not motivated or emotional), but it would lack goal-directedness, persistence, and felt compulsion to act. In contrast, in situations perceived as relevant to active motives, behavior may be under motivational control—flexibly directed toward wanted states or activities and away from unwanted ones. However, insofar as situations are not just motive-relevant, but involve actual or potential changes in motive-relevant events, emotion(s) may be generated (and the larger the changes, the more intense the emotions). If the changes are relatively large, emotions (joy, fear, anger, etc.) are likely to be relatively intense (as compared to

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TABLE 20.2 Some Determinants of Behavior Control by Nonaffective and Affective Processes Eliciting Condition

Processes Governing Behavior

Lack of relevance to active motives (e.g., no active motives or no possible effect on active motives) Motive-relevance (not unmodifiable match or mismatch with actively wanted or unwanted states or activities) Relatively large actual or potential change in motive-relevant events

Nonaffective (e.g., situational or cognitive) determinants

Emotivational goals

Very large actual or potential change in motive-relevant events

Emotional readinesses and action tendencies

Motivational goals and preferences

Note: As discussed by Izard (2000), the term affect is used by some psychologists to refer only to emotions, and by other psychologists to encompass both motivations and emotions. It is used here in the latter sense. This table does not attempt to list all determinants of motivational and emotional processes, but focuses instead on hypothesized differential determinants (e.g., it omits the importance and the imminence of desired and undesired states, which appear to influence the intensity of both motivation and emotion).

motives such as hunger, sex, need for achievement, etc.), and emotivational goals (e.g., sustaining a situation in joy, getting to safety in fear, getting revenge in anger) would increasingly come to govern action in place of the original motivational goals and preferences (which may remain active, but become increasingly subordinate as emotions get more and more intense). If changes in motive-relevant events are very large, emotion intensity would increase still further and the flexible pursuit of emotivational goals increasingly give way to behavior dominated by emotionspecific action readinesses and tendencies. As an example, consider a student taking a college course. If the course lacks relevance to the student’s current motives, she would be neither motivated nor emotional about her course performance (but may still take the course, e.g., because instructed to do so, or in accord with familial models or scripts). If the course is perceived as motive-relevant (e.g., to a desire to progress, or do well, or not do poorly) but relatively little actual or potential change in a motive-relevant outcome is envisioned, the student’s behavior would be motivated (show persistent, goal-directed effort, e.g., in reading course material) but not particularly emotional. If a relatively large change from prior or expected outcome is imagined or perceived (e.g., a final exam is announced, and the student thinks about the prospect of doing significantly better or significantly worse than she otherwise might do), she would have an emotional response (e.g., hope or fear), and her behavior would be correspondingly guided by the emotivational goal of her emotion (e.g., making the envisioned outcome happen, or getting to safety) to the relative exclusion of other goals (either emotivational goal could be pursued by focused studying or by other means, such as seeking assistance or engaging in self-handicapping). If a

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great change is envisioned, our student may feel intense emotion (e.g., hope or fear) and her behavior may be dominated by the action readinesses or tendencies of her emotion (e.g., in hope, eager anticipation, such as fantasies of success and its sequelae, and excited, preoccupied waiting or approach behavior; in fear, tense vigilance, such as watching out for and thinking about the potential for failure, and aroused passive or active avoidance behavior, e.g., periods of paralysis, thoughts of bailing out, and frantic studying or dropping the course). The theory just outlined posits an adaptive matching between the conditions requiring organismic response (the degree of actual or potential change in motive-relevant events) and the functional characteristics of the behavior control system mobilized to govern action (in particular, the latencies of response that are characteristic of the different systems). As the immediate implications for active motives increase in magnitude, one moves from nonaffective to motivational to emotivational to emotional behavior, and action becomes more and more focused and constrained. The fewer the behavioral options generated, the smaller the need for cognitive involvement in selecting among options, and thus the more rapid a response can be. A number of other theorists have suggested that change or rate of change is a key determinant of emotion activation or intensity. For example, Frijda (1988, 2007) posits a Law of Change: “Emotions are elicited not so much by the presence of favorable or unfavorable conditions but by actual or expected changes in favorable or unfavorable conditions” (Frijda, 2007, p. 10), and contends that the greater the change, the stronger the subsequent emotion. Carver and Scheier (e.g., 1998) have proposed that emotion is generated by the rate of progress toward goals

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or away from antigoals, in comparison to a desired rate; larger differences from this “reference rate” are held to produce more intense emotions. In comparison, motivational processes may not require change, or any particular degree or threshold amount of change. For example, hunger may be generated when glucose or fatty acids in the blood are below target levels, or when ghrelin levels are high; and thirst when blood flow to the heart or kidneys is too low (Carlson, 2007). These hunger- and thirst-generating mechanisms appear to be at least partly dependent on levels rather than changes in the monitored substances, as it is possible to be chronically hungry or thirsty. For example, patients with Prader– Willi Syndrome have chronically high levels of ghrelin and continual hunger (DelParigi et al., 2002). Similarly, achievement striving and persistence may be engendered by dispositionally high competence perceptions and mastery or “performance-approach” goals (Elliot, 1997). However, motivational processes may also be affected by change, as when hunger is triggered by the smell of food (Carlson, 2007), thirst by changes in osmotic pressure (Liedtke et al., 2000), and achievement motivation by perceived progress toward goals (Schunk, 2003). Yet consistent with the hypothesized influence of change on emotion, it is possible that significant or large changes in degree of fulfillment of these motives simultaneously generate emotions such as excitement (Tomkins, 1979), distress (Brunner, 1993), or joy (Summerfield & Green, 1986). Alternative Determinants It is also possible that, contrary to Table 20.2, change is not required for emotion initiation, and that the key determinant of emotional dominance over motivation is degree of match or mismatch with current goals or antigoals, which is then reflected in emotion intensity. As Frijda (1988, 2007) observes, many instances in which an absence of change reduces emotional intensity may be cases of habituation or “adaptation,” (Helson, 1964) in which desires or expectations shift as a function of current state (e.g., we get used to an increased salary and set our sights higher; thus we cease to be happy not because change is required for happiness, but because a new level of aspiration makes our current state no longer match what we desire). Frijda also notes some cases—all of negative emotions, which leads him to posit a Law of Hedonic Asymmetry—in which it seems that people do not adapt but rather feel continued or increasing negative affect in response to unchanging aversive states. Among the examples given are irritations, such as noise (Frederick & Loewenstein, 1999), and chronic intractable pain.

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One could come up with explanations for these apparent exceptions to the Law of Change: the cited studies examined intermittent rather than constant noise, perhaps preventing adaptation; over time one might increasingly want either noise or chronic pain to cease, thus accounting for intensification; and, as Frederick and Loewenstein (1999) point out, in degenerative diseases, chronic pain worsens over time, reducing adaptation. But it may also be possible to explain apparent change or rate of change effects as special cases of match or mismatch with a positive or negative reference state. For example, in Carver and Scheier’s (1998) theory, people are said to have a desired rate of change. Perhaps that rate should be taken as their goal—the frame of reference from which degree of goal match and mismatch should be calculated. Suppose that as the size of match or mismatch with reference states increases, emotions increase faster in intensity than do motivations. If so, as the size of match or mismatch grows, behavior might come first under increasing control of motivations, then emotivational goals, and then emotional action readinesses and tendencies. If this were the case, greater match or mismatch with reference states might be what produces increasingly constrained behavior, and the functional rationale would be that greater match or mismatch makes faster action advantageous (in order to more quickly respond to states that are more undesired or desired).

WHY INCORPORATE BOTH MOTIVATIONS AND EMOTIONS INTO THEORIES OF BEHAVIOR? If motivations and emotions have significant similarities, and both provide energy and direction to behavior, why should both constructs be included in our theories? In accord with the above discussion, one answer to this question is that motivations and emotions also seem to have different empirically observable characteristic properties (narrow vs. broad initiating conditions, relatively deliberative vs. impulsive influence on behavior, and subordinate vs. preemptive tendencies). There may be other distinguishing characteristics as well. For example, a number of emotions seem to have expressive properties that most motivations lack, such as distinctive pan-cultural facial displays (Darwin, 1872/ 1965; Ekman, 1999; Izard, 1971), vocal patterns (Scherer, Johnstone, & Klasmeyer, 2003), and postures (Darwin, 1872/1965; Tracy & Robins, 2004). By signaling an organism’s emotional state, and readiness for emotional behaviors such as attack (e.g., in anger), flight (e.g., in fear), submission (e.g., in shame), and assertion (e.g., in

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pride), emotional expressions may serve as preprogrammed social coping mechanisms which rapidly and relatively effortlessly help individual organisms (Levenson, 1999), and groups or species of organisms (Keltner & Haidt, 1999), deal with opportunities and crises by exerting influence on other organisms. For example, expressions of anger may serve as threat displays that deter conspecifics—and sometimes other species—from a course of action (see, e.g., Fessler, 2006). Postural expressions of fear may elicit fear in conspecifics, facilitating flight (de Gelder, Snyder, Greve, Gerard, & Hadjikhani, 2004). Such rapid, effortless signaling may be more important under the conditions of significant change held to generate emotions, than under the less potentially urgent circumstances that generate motivational processes. The primary brain circuitry of motivations and emotions may also differ. For example, Berridge and his colleagues (e.g., Berridge, 2004) distinguish motivational “wanting” sites in the nucleus accumbens (which are dopaminergic and influence working for food) from emotional “liking” sites in particular areas of the accumbens shell and ventral pallidum (which respond to opioids and influence facial responses to pleasant tastes). In short, both motivations and emotions are needed to adequately describe and explain behavior. Motivation constructs (along with either expectancies, or comparisons of existing and potential states to reference states) are needed to describe and account for much behavior that occurs under normal circumstances: behavior that is goal-directed, persistent, and tailored to specific situations. Emotion constructs are needed to describe and account for the relatively impulsive deployment of a limited number of general purpose strategies and responses that have evolved (along with quick appraisals of basic cross-situational dimensions that nondeliberatively predict which emotion strategies are likely to be most successful in which types of situations) to deal with crises and potentially time-limited opportunities. To return to our earlier example, motivational constructs (such as need for achievement or competence motivation) are needed to adequately explain why some college students devote persistent daily effort to attending lectures and reading and studying course material (despite fatigue, obstacles to comprehension, the easy availability of sensory and social pleasures, etc.). Emotional constructs (such as hope, fear, and guilt) are needed to adequately explain why various equally motivated students respond to an impending final exam with not only studying but also eagerness, anticipatory fantasies, and excited effort; or tense watching out for signs of approaching failure and periods of paralysis; or ruminative self-reproach.

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In arguing for inclusion of both motivation and emotion in models of behavior, I am not alone. For example, all theories claiming that emotions result from appraisals of events in terms of motives, goals, or concerns (e.g., Carver & Scheier, 1998; Frijda, 1986; Lazarus, 1991; Roseman, 2001; Scherer, 2001; Smith & Kirby, 2001) implicitly if not explicitly encompass both types of variables. So do all theories which regard emotions as a distinct subtype or manifestation of motivations, or attempt to distinguish their properties (e.g., Buck, 1985; Tomkins, 1970). But fewer theories attempt to encompass both motivations and emotions as distinct yet roughly coequal determinants of action, and that is what is being advocated here.

TWO TYPES OF MOTIVATION AND EMOTIONS TWO TYPES OF MOTIVATION In the introductory chapter of this volume, Elliot traces the history of a distinction between approach and avoidance motivations for over two thousand years (see also Elliot, 1999). As Elliot shows, some version of the distinction can be found in descriptive and prescriptive philosophical accounts of human action, and is present in very many theories proposed by psychologists. The contributions to this volume reflect the continuing relevance of the distinction across many subfields of psychology. Elliot’s introductory chapter also discusses alternative conceptualizations of the approach versus avoidance distinction, including the terms appetitive versus motivation relevant to aversive, which he regards as covering roughly the same conceptual ground. In my model of emotioneliciting appraisals (Roseman, 1984), I have used the latter distinction to refer to motivation relevant to statesto-be-attained versus states-to-be-prevented. The term “appetitive” was meant to incorporate the seeking aspect of appetitive behavior (to approach or maximize some states), without necessarily limiting what is sought to objects, such as food, which would subsequently be consumed or engaged with in a consummatory manner (Craig, 1918; cf. Lang, 1995). “Aversive” refers to motivations that avoid or minimize other states. In our empirical research, the meaning has best been captured by distinguishing between wanting to “get or keep” versus “get rid of or avoid” something (Roseman, Antoniou, & Jose, 1996). This phrasing indicates that the positive and negative reference states which guide motivated behavior may or may not be currently present in a situation.

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TWO TYPES OF EMOTIONS (WHEN EMOTIONS ARE MOTIVATIONS) In emotion theory and research, positive versus negative emotion is a perpetual and central theme (Tolman, 1923; Tomkins, 1962, 1963; Watson & Tellegen, 1985). Although some theorists have challenged the classification of emotions into positive and negative groups or question the basis for the classification (Kristjánsson, 2003; Solomon & Stone, 2002), most analyses recognize positive versus negative emotion as a fundamental and important distinction. While emotions may be categorized as positive versus negative according to their putative adaptive value (e.g., healthful vs. harmful, as discussed by Solomon & Stone, 2002), or people’s attitude toward emotions (approving vs. disapproving of their experience or expression; see, e.g., Tsai, Knutson, & Fung, 2006), the most widely recognized version of the distinction is in terms of subjective feeling quality (e.g., Barrett, Mesquita, Ochsner, & Gross, 2007; Wundt, 1904). Emotions such as joy, love, and pride feel pleasant, and emotions such as sadness, fear, and shame feel unpleasant. This division is immediately apparent when research participants are asked to sort emotions into groups (Shaver, Schwartz, Kirson, & O’Connor, 1987), or make similarity judgments among emotion words (Russell, 1980) or faces (Abelson & Sermat, 1962). It is also apparent when participants rate the emotions of others (Roseman, 1991) or their own ongoing experience of emotions (Barrett, 2006b). Positive emotions tend to covary, at least to some extent; so do negative emotions. The hedonic quality of positive versus negative emotions enables them to also serve as motives—people may behave to experience more of positive emotions generally (Tomkins, 1987), or particular positive emotions such as joy, love, or pride (e.g., Atkinson, 1964; Tennov, 1979), or less of negative emotions generally (Taylor, 1991; Tomkins, 1987), or particular negative emotions such as panic, disappointment, or regret (Barlow, 1988; van Dijk, Zeelenberg, & van der Pligt, 2003; Zeelenberg, Beattie, van der Pligt, & de Vries, 1996).

WHAT IS APPROACHED OR AVOIDED IN MOTIVATED AND EMOTIONAL BEHAVIOR? How should we characterize that which people want to get or keep in appetitive (approach) motivation and get rid of or avoid in aversive (avoidance) motivation? Although some theories have focused primarily on the maximization of positive emotions and minimization of negative emotions (e.g., Tomkins, 1970, claimed that nonemotional motives

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require emotional “amplification” to affect behavior), it does not seem that emotions are in fact the only motivators. Nor must pleasure and pain be involved in motivating action. At least at low to moderate levels of motive intensity, people seem to regulate many different processes or parameters (e.g., perceptual constancies, speech production, self-verification), at least somewhat independently of the happiness or sadness, or pleasure or pain, it makes them feel. To give another example: people seek accurate understanding not just because it makes them feel joy, or pleasure, or even competence, but seemingly for its own sake (Chaiken, Liberman, & Eagly, 1989; Heider, 1958). We also seek to categorize stimuli, to evaluate stimuli, and to correct for bias, often without conscious awareness (Glaser & Kihlstrom, 2005; Petty & Wegener, 1993). To encompass a very wide variety of approached versus avoided states and activities, it would seem that a very general formulation of the regulated entities must be offered. One candidate is rewards versus punishments (Gray, 1987; Gray & McNaughton, 2000). A possible advantage of this conceptualization is its potential linkage to distinct brain systems, such as those that mediate appetitive versus aversive information processing, (e.g., nucleus accumbens, ventral pallidum, and paraventricular nucleus of the hypothalamus vs. central amygdala and bed nucleus of the stria terminalis, as described by Cacioppo, Larsen, Smith, & Berntson, 2004).

WHY HAVE TWO TYPES OF MOTIVATION AND EMOTIONS? The existence of appetitive versus aversive motivational systems and positive versus negative emotions may provide an important mechanism for prioritizing action. At comparable levels of affective strength, higher priority may be given to aversive (avoidance) motives and negative emotions as compared with appetitive (approach) motives and positive emotions (cf. Carver, 2003; Maslow, 1955). Indeed there is considerable evidence of such prioritization (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001; Taylor, 1991). For example, as discussed by Baumeister et al. (2001), most people (83%, according to a study of wagering by Atthowe, 1960) try harder to avoid losses than to obtain comparable gains (see also Kahneman & Tversky, 1984); the effects of punishment and negative reinforcers on behavior are generally stronger than the effects of reward and comparable positive reinforcers (Constantini & Hoving, 1973); and people report more often trying to get out of bad moods than to get into or prolong good moods (Baumeister, Heatherton, & Tice, 1994).

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Moreover, differentiation of importance or urgency may provide a functional explanation for the evolution of two motivational systems, and the assignment of particular regulated parameters to one system or the other in the process of natural selection. For example, sexual motivation seems predominantly to involve appetitive motivation and pleasure seeking (e.g., van Furth, Wolterink, & van Ree, 1995); and though people may seek to eat particular foods in order to get pleasant tastes, eating as a response to prolonged food deprivation involves aversive motivation (reduction of unpleasant feelings of hunger; see Ashton, 2002). Perhaps this is because reproduction, while ultimately essential for the continuation of the species, is less time urgent than satisfying basic nutritional needs. Similarly, the need to cope with crises that is signaled by negative emotion seems more urgent than the need to seize opportunities that is signaled by positive emotions. As Elliot (2006) put it, avoidance goals are concerned with survival, and approach goals with thriving. Or to state it another way, if one doesn’t reproduce or seize an opportunity today, one can try again tomorrow; but if one doesn’t survive today, there will be no further opportunities (cf. Baumeister et al., 2001, p. 358). Note that the “bad is stronger than good” principle (Baumeister et al., 2001) does not itself require two different systems of motivation or emotion. Organisms could have only approach (appetitive) goals, and respond with higher priority to departures from the goals than to progress toward them. More attention and effort could be mobilized toward avoiding losses than achieving gains, and to minimizing losses that occurred (Taylor, 1991), even if the gains and losses were only of desired objects or states. Instead, the existence of two motivational systems (with favorable and unfavorable outcomes possible in each) suggests some nonredundant functions, such as a more differentiated prioritization or action control system. I will consider further the utility of having four possible outcomes (improvement or worsening with respect to approach or avoidance motivation) in discussing motivation-linked emotions, below.

DISCRETE EMOTIONS: BEYOND TWO TYPES There Is More to Emotions Than Positive and Negative Most theories of emotion, from ancient (Aristotle, 1966/350 BC; Galen [see Irwin, 1947]) to classical (Descartes, 1649/1968, Spinoza, 1677/2000) to modern (Izard, 1991; Oatley & Johnson-Laird, 1987; Plutchik,

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1980; Tomkins, 1962, 1963), including theories and taxonomies generated in other cultures (Hejmadi, Davidson, & Rozin, 2000; Romney, Moore, & Rusch, 1997), maintain that there are more varieties of emotion than just positive and negative. For example, Ekman (1992) argued that there are at least seven different emotions, based on evidence of pan-cultural facial displays for happiness, sadness, fear, anger, disgust, surprise, and contempt (according to Keltner, Ekman, Gonzaga, & Beer, 2003, there is now some evidence of expressions for embarrassment, shame, amusement, sympathy, and love as well). Panksepp (1998, p. 88), citing neuroanatomical and neurochemical evidence, also identified seven emotional systems: play (joy), panic, fear, rage, seeking, care, and lust. Frijda (1986, p. 88) distinguished 17 different patterns of “action readiness” and on this basis listed 17 emotions. de Rivera (1977), citing distinctive patterns of phenomenology, posited 48 emotions. Citing evidence of distinctive profiles of phenomenology, physiology, expression, action tendencies, and goals, as well as antecedent appraisals, I have proposed a system encompassing 17 emotions: 16 positive- or negative-valenced emotions, and the neutral-valenced emotion of surprise (Roseman, 2001). There is also clearly disagreement about which states should be regarded as emotions (Ortony & Turner, 1990), although some of these can be understood as differences in terminology (e.g., what Panksepp, 1998, refers to as the “seeking” emotion system may correspond to hope in other emotion theories, e.g., Lazarus, 1991; Roseman, 2001). The more important disagreements would seem to be based in part on different definitions of emotions and thus different criteria for identifying and distinguishing between putative emotion states (e.g., phenomenological conceptualizations suggest more emotions than do universal expressive displays). Only Degrees of Positive Versus Negative Affect and Arousal? In recent years, James A. Russell and Lisa Feldman Barrett (Barrett, 2006a; Russell, 2003; Russell & Barrett, 1999) have led a challenge to the discrete emotion perspective, citing the variability of responses observable across instances of the same emotion, such as anger; and low correlations among the different responses proposed to constitute an emotion (e.g., subjective, physiological, facial, and behavioral responses). Russell and Barrett contend that what appear to lay persons and many emotion theorists as different emotions are really cultural or linguistic categories arbitrarily imposed on a simpler, dimensional affective reality (cf. Russell, 1980; Russell & Mehrabian, 1977). They claim that joy, sadness, fear,

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anger, and so forth correspond principally to particular combinations of valence and arousal. In my view, some variability in responses across instances of an emotion and relatively low correlations among different emotion components are empirical realities (see, e.g., Cacioppo, Berntson, Larsen, Poehlmann, & Ito, 2000). But there are good reasons to expect such variability, and ways to explain it systematically. (a) As discussed above, at least when emotion intensity is not extremely high, emotivational goals may tailor emotional behavior toward responses seen as effective in specific situations (e.g., in fear, seeking safety by concealment or by calling for help). (b) Emotion regulation may alter or control emotions or their individual component responses (as when people suppress anger or mask facial displays of disgust to conform to social norms; see, e.g., Ekman, 1972; Gross, Richards, & John, 2006). (c) Other nonemotional processes may compete with emotions to influence physiology, expression, behavior, and phenomenology. For example, depending on the situation one was in, talking could alter facial expression; task demands (e.g., filling out a questionnaire vs. running on a treadmill) would affect heart rate and blood pressure; and nonemotional motives (such as keeping a job, or caring for an interaction partner) could constrain or shape behavior (e.g., the likelihood and form of angry attack). The critique of discrete emotions is also empirically inadequate because it fails to account for relationships between particular emotions and particular responses that do exist. For example, Russell (2003) and Barrett (2006a) simply do not explain why the same facial and vocal expressions (e.g., smiling and laughter with happiness, downturned lips and weeping with sadness) would be associated with the same emotion concepts and similar eliciting conditions (e.g., reunions vs. separation from loved others) across all human cultures (Boucher & Brandt, 1981; Ekman, 1972; Izard, 1971; Keltner et al., 2003); or why such expressions are found in children born blind or even blind, deaf, and retarded (e.g., Charlesworth, 1970; Dumas, 1932; Eibl-Eibesfeldt, 1970, 1972; Mistschenka, 1933; as reviewed in Collier, 1985). Existing relationships between subjectively experienced emotions and behaviors are also not adequately explained. For example, although people do not necessarily attack when feeling angry, and can attack when feeling fear or other emotions, aggression is more likely when feeling anger than when feeling no emotion, and more likely when feeling anger than when feeling other emotions, such as happiness, sadness, fear, surprise, or love (Berkowitz, 1999; Consedine, Strongman, & Magai, 2003; Roseman et al., 1994; Scherer & Wallbott, 1994).

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Similarly, freezing is more likely when feeling fear than when feeling anger, sadness, joy, disgust, or other emotions (Bracha, 2004; Gray & McNaughton, 2000). Nor can the various emotions differentiated by discrete emotions theorists and researchers be adequately accounted for simply by combinations of valence and arousal. Fear and anger, both high arousal negative emotions in dimensional accounts, differ significantly in characteristic facial expression (e.g., brows raised, lips stretched vs. brows lowered and squarish lips), physiology (e.g., pallor vs. flushing), behavior (as just described), and subsequent effects (see, e.g., Demaree, Everhart, Youngstrom, & Harrison, 2005; Ekman & Friesen, 1975; Lerner & Keltner, 2000; Mackie, Devos, & Smith, 2000). As discussed above, the valence of emotions is an important dimension of variation. This hedonic characteristic divides emotions into positive versus negative groups which then have in common that they are sought versus avoided. But though there may be few cases of invariance, there are many documented significant relationships between particular emotions and particular emotional responses. Neither a two-group analysis of emotions (positive vs. negative) nor a two-dimensional model is sufficient to account for them.

SPECIFYING EMOTION RESPONSE SYNDROMES AND STRATEGIES Based in part on prior emotion theories and empirical studies (e.g., Davitz, 1969; Izard, 1977), my students, colleagues, and I have developed many specific hypotheses about relationships between particular emotions and particular phenomenology, behaviors, and emotivational goals; and have conducted four studies to test these a priori hypotheses (Fischer & Roseman, 2007; Roseman, 2002; Roseman et al., 1994; Roseman et al., 2007). The studies ask participants to recall intense experiences of particular emotions, and answer questions about what they thought, felt, felt like doing, actually did, and wanted in the experiences that they described. Some results are shown in Table 20.3. In these studies we found some responses that differentiated each of the 17 emotions in the model of the emotion system that I have proposed (Roseman, 2001). A number of these relationships have also been found in studies by other investigators (e.g., Consedine et al., 2003; Scherer & Wallbott, 1994; Shaver et al., 1987; see Roseman et al., 1994, 2007, for examples). Perhaps most relevant to the present chapter was the support found for specific emotivational goals for many emotions (e.g., in joy, wanting to make an experience last

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TABLE 20.3 Some Responses Found to Differentiate Particular Emotions as Predicted Emotion

Responses

Surprise

Feel yourself breathe in suddenly Think that what was happening was unexpected Remain motionless Want to figure out what was going on

Hope

Think that you could be optimistic about the future Feel like planning for the futurea Want to approach something Want what you were thinking of to happen

Joy

Feel a sense of lightness in your movements Feel like jumping up and down Celebrate Want to make the experience last longer

Relief

Feel tension leaving your body Think that the worst was over Rest Want to get on to something else

Affection

Feel warm all over Think that you belonged with someone Feel like holding someone Want to be close to someone

Pride

Feel more powerful Think that you had accomplished something Assert yourself Want to seek recognition

Fear

Feel your heart pounding Think of how bad things could get Feel like running away Want to get to a safe place

Sadness

Feel a lump in your throat Think about what you were missing Feel like doing nothing Want to be comforted

Distress

Think that you did not know what to do to make things less upsetting

Frustration

Feel impatient

Feel like moving away from something Think about an obstacle that was in your way Want to overcome some obstacle Disgust

Think that something was offensive

(Interpersonal) Dislike

Think of something in another person that you didn’t want to be around

Wrinkle your nose Feel like avoiding interactions with someone (Continued)

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TABLE 20.3 (continued) Some Responses Found to Differentiate Particular Emotions as Predicted Emotion

Responses Minimize your contact with someone Want to be far away from someone

Anger

Feel ready to explode Criticize the other person Want to hurt someone

Contempt

Feel revolted by another person Think that someone was unworthy of respect Feel like saying something unflattering about another person Want another person to be rejected by your group

Regret

Think of what a mistake you made Feel like correcting your mistake

Guilt

Think that you were in the wrong Feel like offering an apology Scold yourself for something Want to make up for what you did wrong

Shame

Feel small Feel like hiding your face Blush

Note: Based on data from Fischer and Roseman (2007); Roseman (2002), Roseman et al. (2007); Roseman et al. (1994). a

Response was only marginally different from other emotions tested.

longer; in fear, wanting to get to safety; in anger, wanting to hurt someone; in love, wanting to be close to someone). These findings indicate that there is more to emotions than approach and avoidance (or appetitive and aversive) goals. Rather, it seems that a component of each emotion is a distinctive goal (or goals) that people feeling the emotion want to pursue. Indeed people may seek to pursue emotivational goals even if they are not aware of their emotion (e.g., wanting to hurt someone even though one is not aware of being angry) or not aware of the goal itself (see Carver, Ganellen, Froming, & Chambers, 1983). Hypothesized phenomenological, expressive, behavioral, and emotivational responses for each emotion in the proposed model are shown in the boxes in Figure 20.1. Proceeding outward, from an emotion box to its borders around the chart, shows the combinations of appraisals proposed to elicit each of the emotions (see Roseman, 2001, for a full discussion). Examination of the emotion syndromes shown in Figure 20.1 suggests they are not made up of unrelated responses that just happen to be part of one emotion rather

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than another. Instead, the various responses characteristic of a particular emotion seem related to and supportive of each other, forming a “package” of responses (Keltner et al., 2003) that constitutes a “strategy” for coping with a particular type of situation (cf. Lazarus, 1991). Like “reproductive strategies,” emotion strategies are not consciously formulated and pursued by individuals, but are organizing principles of emotional response likely to have been shaped by evolution. For example, as shown in Figure 20.1, in response to unexpectedness (Reisenzein, 2000), the emotion of surprise implements a response strategy of suspending action and processing information in order to adjust to the disconfirmed expectancy. Proposed strategies for other emotions are shown in angle brackets at the bottom of each box in the chart.

EMOTION FAMILIES Below surprise, the strategies of the other emotions shown in Figure 20.1 form four main groups or “emotion families.” Each family contains distinct but related

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Positive emotions

Negative emotions

Motive-consistent

Motive-inconsistent

Appetitive motive

Aversive motive

(Circumstancecaused)

Uncertain

Certain

Aversive motive

Surprise PHE: unexpectedness; stunned EXP: brows raised, arched; eyes wide; mouth open, oval; gasp BEH: interrupt, take in information EMV: understand <suspend movement>

## Unexpected

## Not unexpected

Appetitive motive

Hope PHE: potential; eager EXP: brows raised, eyes widened, focused BEH: anticipate, approach EMV: get closer, make happen <prepare to move toward or to stop moving away from it>

Fear PHE: danger; cold, heart pounding EXP: brows raised, straight; eyes wide, lips drawn back BEH: vigilance, inhibition or flight (run) EMV: get to safety, prevent <prepare to move away from or to stop moving toward it>

Joy PHE: attainment; vivid, light EXP: smile BEH: jump (move), act (do) EMV: sustain <move toward it>

Sadness PHE: missing; lethargy, throat lump EXP: weep BEH: inaction EMV: recover <stop moving toward it>

Distress PHE: harm; agitated EXP: cry out BEH: move away, leave EMV: terminate, get out <move away from it>

Frustration PHE: obstacle; tense EXP: brows lowered BEH: exert effort EMV: overcome <move against it>

Disgust PHE: repulsiveness; nausea EXP: wrinkled nose BEH: vomit EMV: expel, remove <move it away from you>

Relief PHE: amelioration; calming EXP: exhalation, sigh BEH: rest, relax EMV: return to normal <stop moving away from it>

Low control potential

Hope Uncertain

Joy

Relief

High control potential

Certain

Other-caused Uncertain Certain

Uncertain

Love PHE: appreciation; warm, drawn to someone EXP: sustained relaxed eye contact BEH: touch, hold EMV: attach <move toward other>

Certain

Self-caused Uncertain Certain

Uncertain Certain

Pride PHE: accomplishment; big, powerful EXP: head raised, erect posture BEH: exhibit, assert EMV: recognition, dominance <move toward self>

Dislike PHE: disapproval; cool EXP: refuse eye contact BEH: decrease attention to EMV: dissociate <move away from other> Anger PHE: injustice; explosive EXP: brows lowered, teeth bared BEH: hit, criticize EMV: hurt <move against other>


Contempt PHE: other unworthy; revulsion EXP: sneer BEH: look down on, reject EMV: exclude <move other away>

Regret PHE: mistake; sick, sinking EXP: eyes closed; lips stretched, pressed together BEH: do over, do differently EMV: correct, improve <move away from self> Guilt PHE: transgression; heavy EXP: shift gaze BEH: reproach, punish self EMV: redress <move against self> Instrumental problem

Shame PHE: self unworthy; small EXP: blush, avoid gaze, head low BEH: withdraw EMV: get self out of sight <move self away>




Intrinsic problem

FIGURE 20.1 Structural model of the emotion system. Emotion components: PHE = phenomenological; EXP = expressive; BEH = behavioral; EMV = emotivational goal. Strategies integrating the response components for each emotion are given in angle brackets. Appraisal combinations eliciting each emotion are shown in unshaded areas around the borders of the chart. Adapted from “A model of appraisal in the emotion system: Integrating theory, research, and applications” by I. J. Roseman, in Appraisal Processes in Emotion (pp. 70–71) by K. R. Scherer, A. Schorr, & T. Johnstone (Eds.), 2001, New York: Oxford University Press. By permission of Oxford University Press.

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strategies whose members cope either with motiverelevant events in general, or with events caused by other people, or with events caused by the self. The five positive emotions in Figure 20.1 form a family of “contacting” emotions, which increase proximity to and/or interaction with impersonal, interpersonal, or intrapersonal stimuli. The response strategy of joy involves increased contact with rewarding stimuli via “movement toward” them, increasing interaction with them. Relief reduces “movement away” from stimuli— increasing contact via relaxation and decreased defensive responding. Hope increases contact by preparing to move toward or to stop moving away from stimuli. The preparation involves a focusing of attention, anticipation, and if possible, action to produce desired outcomes. Love moves one person toward another (or others), increasing interpersonal closeness, and forming, maintaining, or strengthening interpersonal bonds. Pride moves one toward oneself, in the sense of bringing one’s behavior closer to one’s own identity and self-conceptions, and promoting selfexpression and self-assertion. Distress, sadness, fear, interpersonal dislike, and regret form a family of “distancing” emotions, which increase distance from impersonal, interpersonal, or intrapersonal stimuli, thus reducing contact and/or interaction with them. Distress actively moves one away from stimuli. Sadness reduces movement toward them. Fear, like hope, is conceptualized as a ‘remote coping’ response, which prepares a person to move away from or to stop moving toward a stimulus. The vigilance that is characteristic of fear is the counterpart to hope’s anticipation—watching out for danger and prompting freezing and/or preparation for flight. The responses of interpersonal dislike move one away from other persons, increasing social distance, for example, by minimizing interaction and connection with them. Regret involves moving away from oneself, in the sense of distancing one’s future behavior from what one has done previously (e.g., a regretted course of action). Disgust, contempt, and shame form a family of “rejection” emotions. Unlike the distancing emotions, which move the self away from something, rejection emotions move something away from the self. The coping strategy of disgust is to get less of something offensive by moving it out of or away from the self. In contempt, another person is moved away from the self, in a type of rejection that is specialized for interpersonal relationships. This social rejection involves looking down on someone and seeking to have the contemptible person rejected by one’s in-group and excluded from social interactions. In shame the self is moved away, hidden, withdrawn, and excluded from social interactions.

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Finally, frustration, anger, and guilt constitute a family of attack emotions, which move against objects and events in general, against other persons, or against the self. The coping strategy of frustration (which in this conceptualization corresponds to what Smith & Lazarus, 1990, called the emotion of “challenge/determination”) moves against something to try to force a change in its state or behavior. It often involves an increased exertion of effort (Amsel, 1992), for example, to overcome an obstacle. In anger, effortful movement against is organized into an interpersonal attack, in which there is an attempt to get revenge, hurt the other person in some way, make the target feel bad. This type of attack is specialized to deal with other sentient beings, who can be hurt (e.g., by feeling pain, or censure, or thwarting of their goals). In guilt, one moves against the self, for example, by self-reproach or by offering an apology or reparation (incurring a social or material cost to redress a negative outcome one has caused).

MORE TO EMOTIONS THAN APPROACH AND AVOIDANCE The existence of contacting, distancing, rejection, and attack emotion families reveals that even when emotions are grouped according to the kind of coping strategies they represent, distinguishing between approach and avoidance classes still provides an insufficient or incomplete description of emotional behavior. Positive and negative emotions, as valenced states, are indeed themselves approached and avoided, or maximized and minimized. However in the emotion system there are at least three distinct minimization processes: distancing, rejection, and attack. Distancing emotions cope with motive-inconsistent events by accommodating to them, moving away from them. But rejection and attack emotions cope with motive-inconsistent events by contending with them (Arnold, 1960), attempting to change the environment by actively moving stimuli away from the self or by attacking them. Why Do Emotions Prompt More Than Approach and Avoidance? The model offered in the first part of this chapter proposed that whereas motivated behavior may be generated by any degree of match or mismatch between a current situation and an actively wanted or unwanted state, emotional behavior is elicited by significant changes in such match or mismatch (or alternatively, by relatively large match or mismatch with reference states). Thus motivations guide behavior under relatively normal circumstances when an organism can utilize specific purpose behaviors, including behaviors acquired through

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instrumental learning, to approach desired states or avoid undesired states in ways tailored to the requirements of specific situations. For human beings, in the absence of great change in motive-relevant events, there is more likely to be time to consider particular actions and alternatives, assess their expected consequences in the particular situation at hand, and select an action partly informed by such assessments. In contrast, greater changes are likely to necessitate more rapid response, and I have described emotional behavior as often less planful and deliberative, and more preprogrammed and impulsive than motivated behavior. Moreover, I have argued that emotions typically take precedence over nonemotional motives, which is functionally adaptive because of the greater urgency of their eliciting conditions. These contrasts between motivation and emotion may provide an explanation for why there are more varieties of emotion (contacting, distancing, rejection, and attack) than varieties of motives (approach and avoidance). Specifying only that something should be done to approach or avoid particular conditions (i.e., establishing goals or antigoals to guide behavior) may be sufficient if action is not needed urgently. But in the face of the larger changes that can create crises and time-limited opportunities, the more constrained action control that is characteristic of emotion, which permits faster response, may be advantageous. More constrained guidance of behavior would seem especially important when dealing with the motiveinconsistent events that cause negative emotions. As shown in Figure 20.1, the distancing emotions (fear, sadness, distress, interpersonal dislike, regret) accommodate to stimuli (moving away, increasing distance from them) in situations appraised as low in control potential. Being constrained to move away is relatively likely to be helpful in such situations, reducing negative outcomes while conserving resources. If instead, an organism attempted to contend with stimuli (tried to change or get rid of them) when control potential is low, the effort is likely to be futile. In contrast, when control potential is high, accommodating to stimuli may well result in a less than optimal adaptation. Contending with stimuli (e.g., getting rid of something rather than getting used to it; changing a person’s behavior rather than avoiding the person on a continuing basis) may lead to better outcomes, especially in the medium and long term. According to Figure 20.1, the attack emotions (frustration, anger, and guilt) contend with motive-inconsistent stimuli by moving against them, when it is perceived that control potential is relatively high, and the problem is instrumental (a goal blockage). These are situations in which an urge to attack (a problem, another person, or the self) is most likely to be useful: the

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person feeling the emotion is relatively powerful, and if the target is not intrinsically negative but merely blocking a goal, an attack may succeed in forcing some change. However if a problem is intrinsic to an object, event, or person, attacking it cannot succeed in forcing it to change, even if the person reacting to the problem is relatively powerful. According to Figure 20.1, in such situations a rejection emotion (disgust, contempt, or shame) is elicited, which urges a person to move the emotionproducing stimulus away from the self. Such active rejection of a stimulus (moving it away or getting rid of it) may minimize its impact on one’s outcomes and be the best one can do in this type of situation (Fischer & Roseman, 2007).

APPROACH VERSUS AVOIDANCE MOTIVATION AS A DETERMINANT OF SPECIFIC EMOTIONS Most of the motivation-plus-cognition theories of emotion, and many other theories, implicitly or explicitly maintain that events related to any motive can give rise to an emotion. For example, as discussed above, many theories claim that happiness can be produced by fulfillment of any motive (hunger, thirst, sexual drive, need for achievement, etc.), fear by a threat to any motive, and anger by another person’s interference with any motive. A few theories claim that there are linkages between particular motives or types of motives and particular emotions. For example, Lazarus (1991) proposed that anger results in part from events incongruent with the goal of preserving or enhancing self- or social-esteem (a view similar to that of Aristotle, 1966/350 B.C., who claimed that anger results specifically from unjustified “slights”), guilt from incongruence with moral goals, and shame from incongruence with goals involving living up to an “ego ideal.” However, other authors disagree with the motive-emotion linkages proposed by Lazarus, citing cases of anger in response to any physically or psychologically aversive event, such as pain, heat, frustration, and so forth (Berkowitz, 1998) especially if other people caused or were responsible for it (Roseman, 1991; Scherer, 1993; Smith & Kirby, 2004); and guilt in response to selfcaused outcomes that may be unrelated to morality, such as going off a diet or not preparing sufficiently for an exam (Roseman, 2001; cf. Frijda, 1993).

REWARD-MAXIMIZING VERSUS PUNISHMENT-MINIMIZING MOTIVATION AS A DETERMINANT OF JOY-AND-SADNESS VERSUS RELIEF-AND-DISTRESS I have proposed (Roseman, 2001; see Figure 20.1) that consistency and inconsistency of certain events with

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reward-related versus punishment-related motives are likely to produce different emotions. The precise claims are that consistency with a reward-maximizing motive (“getting something that you want”) gives rise to joy; inconsistency with a reward-maximizing motive (not getting something that you want) gives rise to sadness; consistency with a punishment-minimizing motive (not getting something you don’t want) gives rise to relief; and inconsistency with a punishment-minimizing motive (getting something you don’t want) gives rise to distress. These hypotheses have been supported, for example, when measuring appraisals in recalled emotion experiences (Roseman et al. 1996; Roseman, Spindel, & Jose, 1990), and (for joy and relief) in research manipulating appraisals and measuring emotions (Roseman & Evdokas, 2004). Similar proposals have been made by other theorists. In the model proposed by Higgins (e.g., 1987, 1997), having a “promotion focus” (a concern with aspirations and accomplishments) makes a person likely to experience “cheerfulness” emotions (e.g., happiness, satisfaction) if a positive outcome is present, and “dejection emotions” (e.g., disappointment, dissatisfaction, sadness) if a positive outcome is absent. In contrast, a “prevention focus” (a concern with responsibilities and safety) makes one likely to experience “quiescence” emotions (e.g., relaxed, secure) if a negative outcome is absent, and “agitation” emotions (e.g., uneasy, threatened, afraid) if a negative outcome is present. Support for Higgins’ formulation has been obtained in a number of studies. For example, Higgins, Shah, and Friedman (1997) found that in individuals with more of a promotion orientation, congruence between the person’s actual and ideal self was associated with more cheerfulness emotions, and discrepancy between actual and ideal self was associated with more dejection emotions. In individuals with more of a prevention orientation, congruence between actual and ideal self was associated with more quiescence emotions, and discrepancy between actual and ideal self was associated with greater agitation emotions. Higgins et al. (1997) also found that inducing promotion focus led to greater change on a continuum from dejection to cheerfulness, whereas inducing prevention focus led to greater change on a continuum from agitation to quiescence. Carver and Scheier (1998, p. 165) proposed that “discrepancy-reducing meta systems” (analogous to approach motivation) produce “elation/joy” if discrepancy reduction is occurring faster than a person’s (minimum) desired rate, and “depression” if discrepancy reduction is slower than desired. For “discrepancy-enlarging systems” (analogous to avoidance motivation), progress (away from

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undesired states) that is above an individual’s standard is hypothesized to produce relief, and progress that is below standard is hypothesized to produce anxiety. Among the support cited for these relationships is a connection between the failure to attain incentives and depression, and between threat and anxiety (Ahrens & Haaga, 1993; Wickless & Kirsch, 1988; cited in Carver, 2003). While there are differences among these three theories in formulation of the motivational distinction (rewardmaximizing vs. punishment-minimizing; promotionfocus vs. prevention-focus; discrepancy-reducing vs. discrepancy-enlarging), and in the specific associated emotions (joy vs. cheerfulness vs. elation/joy; relief vs. quiescence; sadness vs. dejection vs. depression; distress vs. agitation vs. anxiety), all three posit similar relationships between approach- versus avoidance-like motivational orientations and specific emotions. Why might such relationships exist? According to Figure 20.1, the negative emotion of distress increases distance between a person and a stimulus by moving the person away from the stimulus (i.e., via attempts to escape from the unwanted state). This active movement away in distress seems appropriate when dealing with high priority crises (those arising from punishment-minimizing motives). The positive emotion of relief allows increased contact with a stimulus by stopping the distancing. According to Figure 20.1, the positive emotion of joy increases contact with a stimulus by actively moving a person toward it, and increasing interaction with it; the negative emotion of sadness allows increased distance by reducing this movement toward something. The active movement toward stimuli in joy seems appropriate when dealing with rewards (lower in priority than aversive states); and the passive failure to pursue incentives in sadness seems appropriate for lower priority situations (stimuli that need not be urgently pursued). If punishment-minimizing motives are those with greater urgency, then the responses of related emotions might well have priority: the movement away in distress would have priority over movement toward in joy. Distress would also have greater power to influence behavior than sadness. Some data cited by Baumeister et al. (2001) are consistent with this formulation. For example, as discussed above, Baumeister et al. (1994) found that attempts to get out of bad moods were more frequently reported than attempts to get into or maintain good moods. Also, Major, Zubek, Cooper, Cozzarelli, and Richards (1997) found that negative affectivity but not positive affectivity influenced distress. Leith and Baumeister (1996) reported that, unlike low-arousal negative moods such as sadness, high-arousal

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negative moods led research participants to “curtail information processing and make snap decisions” (Baumeister et al., 2001, p. 334). These findings are consistent with the depiction of distress as a more powerful, higher priority emotion than sadness. That is, it may be adaptive to have a lower priority emotion (sadness) which prompts us to cease pursuit of rewards; and a higher priority emotion (distress) which demands, more loudly, persistently, and actively, that we maintain efforts to escape from punishing events. Thus two types and four degrees of prioritization are provided by this system, with priority-appropriate responses specified for each one: negative over positive emotions, and within these classes, avoidance-linked (distancing-related) over approach-linked (contactingrelated) emotions.

SUMMARY In this chapter I have argued that an adequate account of behavior must include both motivations and emotions, which energize and direct behavior under different conditions and in different ways. I proposed that relatively small changes of adaptive significance can give rise to motivational processes, which are relatively planful, deliberative, and specific-purpose responses, tailored to the specific situations in which they occur. Larger changes of adaptive significance give rise to emotional processes, which take precedence over comparable strength or weaker motives. If changes are only moderately large, emotion-specific emotivational goals tend to replace motivational goals in guiding behavior. Very large changes produce less deliberative, more impulsive, more preprogrammed general purpose emotional behaviors, governed more by stimuluscontingent patterns of action readiness. In agreement with the theoretical framework of this volume, the model I proposed recognizes the two basic varieties of motivational processes that have been labeled approach and avoidance motivation. As positive and negative emotions have hedonic valence, they also serve as motives, states to be maximized and minimized respectively. I next discussed the nature of emotions as syndromes of response that form coping strategies. Different positive emotions constitute distinct ways of coping with different types of opportunities, while different negative emotions are distinct ways of coping with different types of crises. I described a model consisting of 16 positive and negative emotions plus surprise (which is a neutral-valenced emotional reaction to unexpectedness). The positive and negative emotions can be grouped into four families— contacting, distancing, rejection, and attack emotions,

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which move toward a stimulus, move away from a stimulus, move a stimulus away from the self, or move against a stimulus. Specific emotions apply each family’s strategy either to objects and events in general (including distinct reactive and preparatory coping strategies), to other people, or to the self. Thus the emotion system cannot be adequately described just in terms of appetitive and aversive or approach and avoidance processes. Behavior guidance mechanisms beyond approach and avoidance, such as attack and rejection, must be recognized; and the specific varieties of contacting, distancing, rejection, and attack strategies that are specialized to deal with impersonal, interpersonal, and intrapersonal opportunities and crises (i.e., the individual discrete emotions shown in Figure 20.1) also appear to have distinctive properties that are worthy of attention. Finally, I discussed causation of the specific emotions of joy and sadness (by success and failure, respectively, in maximizing reward) and relief and distress (by success and failure in minimizing punishment), as proposed in my model of appraisal and emotion; discussed two other theories that make similar claims, and some evidence supporting these theories; and considered why, from a functional perspective, having different emotions related to appetitive (approach) and aversive (avoidance) motives might make adaptive sense.

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Function of Emotions of Emotions and 21 Functions Emotion-Related Dysfunction Eric Youngstrom and Carroll E. Izard CONTENTS Functionalist Perspective on Emotions .................................................................................................368 Emotions as Evolved Capacity: Three Levels of Analysis ...............................................................368 Functions of Emotions ......................................................................................................................368 Specialization ..............................................................................................................................369 Rapid Appraisal ...........................................................................................................................369 Rapid Response............................................................................................................................369 Survival Fitness ................................................................................................................................370 Reproductive Fitness and Sexual Selection ...................................................................................... 371 Affiliation .................................................................................................................................... 371 Competition ................................................................................................................................. 371 Runaway.......................................................................................................................................372 Approach, Avoidance, and Sex ....................................................................................................372 Social and Interpersonal Functions: Building, Maintaining, and Changing Networks ...................373 Intrapersonal Functions: Sculpting the Self ..................................................................................... 374 Runaway Software: Emotions, Memes, and Culture ........................................................................ 374 Emotion-Related Dysfunction ............................................................................................................... 376 Models of Emotion and Psychopathology ........................................................................................ 376 Conflict as Normative Development ............................................................................................ 376 Too Much of a Good Thing (Statistical Models of Extremity).................................................... 376 Dysfunction as Transaction: Right Feelings, But at the Wrong Place and Time ........................ 376 Mutation—Fractures in an Otherwise Good System ..................................................................377 Sneaky Value Added (Subtle or Counterintuitive Adaptive Value).............................................377 Approach and Avoidance Emotional Models of Psychopathology: Behavioral Inhibition System and Behavioral Activation System .......................................................................................378 Conclusion .............................................................................................................................................380 References ............................................................................................................................................. 381 The goal of this chapter is to review the function and dysfunction of emotions within an overarching framework of approach and avoidance. The discussion of emotions will adopt an explicitly functionalist perspective, as described in the first section. The function of emotions and emotionrelated dysfunction are addressed in the second and third

sections. Whereas most prior evolutionary treatments of the functionality of emotions have concentrated on the survival value of emotions, our discussion also adds the element of reproductive advantage. We will argue that much of the function and dysfunction of emotions in human culture has been affected by sexual selection as 367

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well as survival pressures. Finally, and perhaps most provocatively, we explore the idea of memetic replication with regard to emotion. We argue that emotions offer a powerful ally for the propagation of memes, and hopefully will offer some provocative ideas about the plasticity with which both culture and self are developing.

FUNCTIONALIST PERSPECTIVE ON EMOTIONS The word “emotion” is used every day in conversation, with a naïve, folk-psychology definition that is readily intuited. However, it proves exceedingly difficult to define what an emotion is in precise technical terms (Solomon, 2000). Consistent with a large body of prior work, we define an emotion as a system that involves and organizes many different processes and levels of analysis (Izard, 1991; Lazarus, 1991). Emotions connect sensory perceptions with very rapid appraisals of the valence and importance of the percepts. The appraisals are connected to physiological responses and cognitive processes, and these in turn are often connected to behavioral outputs. One of the hallmarks of emotions as systems is that there is some looseness in the connections between the different levels or processes. It is possible to have emotions without explicit cognitive involvement or behavioral output, for example. However, the stronger the emotional experience, the greater the entrainment of these different processes and levels of analyses (Cacioppo & Berntson, 1999).

EMOTIONS AS EVOLVED CAPACITY: THREE LEVELS OF ANALYSIS Why develop emotions? What problems of fitness do emotions help solve from the perspective of natural selection? Many functionalist models of emotion explicitly theorize that emotions are an evolved capacity of biological organisms (Cosmides & Tooby, 2000; Plutchik, 1980, 1993). On the basis of this conceptualization, emotions evolved because they increased the “fitness” of organisms. Most discussions of emotion have emphasized the role of emotions in enhancing fitness in terms of survival (Darwin, 1872/1965; Izard, 1972, 1991; Lazarus, 1991). Less frequently discussed is the fact that emotions can also improve the fitness of an organism by contributing to success in sexual reproduction. Dawkins’ (1989) discussion of the “selfish gene” as the appropriate level of analysis for biological evolution is informative in this regard. The ultimate determinant of genetic fitness is how many copies of a gene that pass on to subsequent generations, and not whether a particular organism survives. An organism acts as a vehicle carrying the genes until the organism is able to

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reproduce. Both survival and reproductive success are gates through which the stream of genes must pass in order to flow into subsequent generations. Although less often studied, it seems likely that emotions can play a large role in terms of influencing reproductive success. This opens the possibility of emotions being subject to sexual selection pressures as well as survival selection pressures, with the consequence that emotional systems might evolve in ways that are not evident when viewed through the lens of survival fitness (Miller, 2000; Ridley, 1993). A third level of selection might also be fruitful to consider in the context of the functionality of emotions. Dawkins (1989) pointed out that the process of natural selection could operate on “replicant” units besides biological genes, and he speculated that behaviors might offer another potential form of replicant. Specifically, he coined the term “meme” to refer to a unit of behavior (including cognition) that could be copied and reproduced by other agents. Memes could be words, concepts, objects (such as clothes, or clothing fashions), or processes (such as tool-making, or making a pun). Other authors have subsequently elaborated on the concept of meme as a unit of selection among ideas and behaviors (Aunger, 2002; Blackmore, 1999; Distin, 2004). It is possible for memes to propagate because they are “infectious” ideas, apart from their relationship to biological, survival, or reproductive fitness. We will explore the role of emotions in an approach and avoidance framework, moving through the three different forms of selection: survival selection, sexual selection, and memetic selection.

FUNCTIONS OF EMOTIONS Emotions are not the only behavioral response system observed in nature. Operant conditioning appears to be possible without having sufficient neural circuitry to have even a rudimentary affective system. Protozoa can approach food and attempt to avoid dangerous environmental stimuli such as extreme heat or toxic chemicals—but it does not seem appropriate to interpret the avoidance as an indicator of fear. Organisms as neurologically simple as planaria (flatworms) can be conditioned by the application of aversive stimuli, suggesting that approach and avoidance represent some of the most fundamental motivational systems for organisms (Elliot, 2006; Zechmeister & Nyberg, 1982). This is not surprising given the value that approach and avoidance can have in navigating fundamental threats to survival. But why have selection processes further elaborated the basic dimensions of approach and avoidance into more complex emotion systems? And why have emotions not been selected against once cognition develops? The fictional Vulcans of Star Trek found it highly illogical that emotions would persist once cognition became sufficiently

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Functions of Emotions and Emotion-Related Dysfunction

developed. To them it seemed evident that rational analysis would produce consistent survival and social advantages compared to emotional responses. Specialization Emotions represent an opportunity for more nuanced response than offered by the blunt tools of undifferentiated approach and avoidance. The difference between shyness, fright, and terror is not just a matter of degree of avoidance (Izard, 1992). Similarly, although episodes of anger and enthusiasm might represent comparable degrees of approach motivation, these emotions are triggered by highly different environmental cues, and they galvanize extremely discrepant behavioral responses (Carver, 2004; Davidson, Ekman, Saron, Senulis, & Friesen, 1990; Izard, 1992). Emotions also offer a more flexible system of interpreting environmental stimuli and organizing responses than is possible with instincts or other stereotypic behaviors that are triggered by innate releasing mechanisms (Cosmides & Tooby, 2000). Rapid Appraisal Emotions also provide a more rapid system for response and appraisal than offered by cognition (LeDoux, 1992). Contrary to the Vulcans’ perception, emotions maintain a survival advantage even after cognitive capacity has emerged, because they afford more rapid appraisal and response. At a neuropsychological level, the “deep structures” of emotional circuitry (brainstem, amygdala, hypothalamus) receive sensory input before it reaches the cortex—the seat of cognition (Panksepp, 2000). Cognitive processes at the cortical level then further interpret the now emotionally charged and filtered perceptions, and they can direct a behavioral response (LeDoux & Phelps, 2000). Cognition can also influence or regulate emotion by means of reciprocal inputs into the prefrontal cortex, which functional imaging studies indicate is one of the main areas involved in emotion regulation (Phan, Wager, Taylor, & Liberzon, 2002). However, there are also projections from the amygdala and proximal structures that can organize behavioral responses without cortical input. The subcortical pathway can function without any cortical input, to the point that it remains intact even if the cortex is physically removed (LeDoux, 1992; LeDoux & Phelps, 2000). The subcortical pathway also processes information more rapidly than the cortically mediated system, enabling more rapid responses. As has been pointed out by other emotion theorists, emotions also have the advantage of avoiding a “paralysis of analysis” in everyday tasks (Cosmides & Tooby, 2000). Mild emotional responses guide us through mundane choices almost effortlessly. What do we want for

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breakfast? Which tie or blouse should we wear? Emotional appraisals gently guide us along. A purely cognitive analysis could bog down into careful investigation of the nutritional value of different breakfast alternatives, or the time involved in their preparation, or their economic costs. Emotions similarly navigate most social interactions in a precognitive fashion, analyzing nonverbal cues and only involving cognition after the fact or when unusually complex situations are encountered. Emotions may be a form of “fast and frugal” heuristic, offering a rapid algorithm for processing information (Gigerenzer & Goldstein, 1996; Todd & Gigerenzer, 2000). In fact, a productive line of research and modeling has developed by trying to “reverse engineer” how people process information and make decisions (Arkes & Ayton, 1999; Todd & Gigerenzer, 2000). Although people (and animals) clearly are not fitting regression equations or Bayesian models in their heads to interpret data (Arkes, 1991), they are able to handle huge volumes of information and make decisions that often closely approximate complicated statistical procedures in terms of their accuracy (Todd & Gigerenzer, 2000). Emotions provide a constellation of services that facilitate decision making that is not only fast, but also frugal—enabling decisive choices on the basis of relatively few data points. Emotions accomplish this frugality by filtering data for cues that are salient to survival, reproductive, or social needs, and then concentrating attention preferentially on these cues. Emotions also augment the retrieval of relevant experience through mechanisms such as mood-congruent recall enhancement. Conversely, emotions also weight the encoding of memories. The experience of intense fear can provoke learning that is stamped by the amygdala to create an impression that lasts a lifetime (Orr, Pitman, Lasko, & Herz, 1993; Shin et al., 1997). Rapid Response An additional benefit of emotions, as opposed to the fast and frugal heuristics generated by cognitive scientists or Vulcans, is that they also organize and motivate rapid behavioral responses. Subcortical systems make us jump away at the sight of a snake, while the Vulcan’s cortical response systems are still trying to decide whether the reptile is a poisonous or harmless. The rapidity of response is not just a matter of more rapid appraisal. The emotional circuitry also can innervate simple automatic avoidance behaviors and energize fairly complicated behaviors without waiting for the frontal cortex to assess different strategies and decide on a best course. Once fear circuitry captures control, perceptual frames shift so that other environmental stimuli are reappraised in a search for hiding places, viable escape routes, or sources of aid (Cosmides & Tooby, 2000). Although the Vulcan is still

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cataloging the evidence for different risks and options, any emotional being will have decided whether the threat appears to be a false alarm (and begin de-escalating the emotional cascade), a minor nuisance (triggering relief or annoyance responses), a manageable challenge (perhaps triggering an angry approach response), an avoidable danger (leading to a hiding or flight response), or an unavoidable threat (unleashing a volley of defensive aggression). Once the Vulcan decides on an appropriate course of action, he or she then must act without the benefit of the cascade of physiological changes that emotions have set in motion. For humans, adrenaline, changes in heart rate, changes in blood flow (leaving the digestive system and viscera, and flooding to the peripheral musculature; Tomaka, Blascovich, Kibler, & Ernst, 1997), and other physiological changes all prepare the organism for vigorous action to increase or preserve its fitness. Although emotions probably developed as “natural kinds” in evolution (Panksepp, 2000), there evidently is a great deal of flexibility in the physiological responses (Cacioppo & Berntson, 1999) and behavioral acts associated with an emotion, allowing complexity that enhances fitness at the same time as it frustrates researchers.

SURVIVAL FITNESS Approach and avoidance represent the most fundamental impulses relevant to an organism’s survival (Elliot, 2006; Schneirla, 1959). Approach orients and motivates effort towards acquiring food and shelter. Avoidance monitors for threats and then actively impels organisms away from them. More subtly, avoidance-related emotions might promote survival by averting conflict with other animals within the same social group. Displays of submission, and inhibition of aggression displays, play an important role in preventing or terminating violent behavior that might otherwise injure animals. Darwin observed this in the behavior of wolves as well as primates, and other ethologists have subsequently confirmed and extended documentation of these displays across species as well as across human cultures. Similarly, approach-oriented emotions play a crucial role in survival fitness by providing motivation for organisms to seek food, to challenge competitors for food, or to organize other effortful behaviors in the pursuit of survival goals (Elliot, 2006). Emotions evolved increasingly complex elaborations on the two basic themes of approach and avoidance. Panksepp has described three broad categories of emotions, with the lowest being “reflexive affects” including approach-related systems such as gustatory pleasure or lust; and avoidance-related circuitry such as gustatory

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disgust or pain (Panksepp, 2000). The second category is what Panksepp terms the “Blue-Ribbon, Grade-A Emotions,” relying on circuitry situated in the mid-level of the brain with sensory, motor, and cortical connections that enable functioning as “sensory-motor emotional command” systems. On the approach side, these emotions include joy, affection, and interest, as well as (less intuitively) anger. On the avoidance side, emotions would include fear, sadness, shyness, and the like. Panksepp, like Darwin and others, believes that both the category 1 and category 2 emotions are present in fairly homologous fashion, and involve similar brain circuitry, in mammals. These loosely correspond with what others have described as “discrete emotions,” with some specificity in neural circuitry (Phan et al., 2002) as well as behaviors such as facial displays (Ekman, 1994; Ekman & Friesen, 1971; Izard, 1971, 1994). The third and most elaborated category is the “higher sentiments,” which have markedly greater involvement of the forebrain. In Panksepp’s view, these emotions involve creating blends of lower category emotions with more cognitive inputs. Some of these may follow channelization suggested by neural architecture, resulting in an emotion that is archetypal or universally experienced in a way that could be conceptualized as being a “discrete emotion” (Izard, 1972, 1992). Other such “higher sentiments” might be highly determined by cultural specifics or individual learning history, and might lead to behaviors such as artistic expression that clearly have an affective component, but without necessarily being reducible to a single emotion (Izard, 1992). At its most fundamental level, approach is the function of the “seeking system,” or the ascending medial forebrain bundle dopamine system (Panksepp, 2000). Activation of this system accompanies the urge for animals to explore their environment, learning about the rewards in their surroundings through trial and error. Panksepp argues that the seeking system does not directly encode pleasure or reward status. It is possible that the discrete emotion of interest or excitement is related to this seeking system, to the extent that interest or excitement is activating but only secondarily showing a positive hedonic valence. Enjoyment and joy also reflect positive, approachoriented emotions. These emotions more strongly involve positive valenced encoding, and in mammals may be more tied to social cues. Panksepp has described the importance of play in mammals, and posited an evolved “play system” in the brain. Observers of humans and animals note that play appears important in developing skills (such as hunting or courtship), promoting self-efficacy, and determining social dominance (Boulton & Smith, 1995; Wilson, 1980).

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On the avoidance side, emotions play a powerful role in organizing perceptions of threats and responding rapidly. The fear system is the prototype for avoidance. There are some evolutionarily prepared fears that are innate or at least more easily learned, including fears of snakes, of heights, and of open spaces (Mineka, Davidson, Cook, & Keir, 1984). There are also fears of social rejection or defeat that can be expressed in humans as avoidant behavior in the form of shyness (Kagan, 1997b) or social phobia (Kagan, 1997a). It is also possible for fear to be learned readily via classical conditioning, creating a wide range of generalized fear associations that can be as unique as an individual’s learning experience (Zechmeister & Nyberg, 1982).

REPRODUCTIVE FITNESS AND SEXUAL SELECTION A second major way that emotions contribute to genetic fitness is by means of sexual selection. For genes to propagate, the organism carrying the genes must not only survive, but also reproduce. Reproduction is an affectively laden enterprise, with the emotions becoming more complex and flexible with the evolution of social groups and cognitive abilities. Affiliation At the most basic level, there appears to be an evolved circuitry for “lust,” motivating mate selection, courtship, and copulatory behaviors. Interestingly, the lust systems appear to involve different architecture and neurotransmitters for male versus female animals (Becker, Breedlove, & Crews, 1992; Crenshaw & Goldberg, 1996). The female lust system is more dependent on oxytocin (versus vasopressin in males); and oxytocin plays a major role in the neurocircuitry of caregiving, including behaviors such as grooming and nursing, and affects related to attachment (Petersen, Caldwell, Jirikowski, & Insel, 1992). In more social mammals, these emotions of caring, bonding, and love motivate the parent to protect the offspring, and the offspring to remain close to the parent. This proximity promotes survival, particularly during the much-prolonged infancy and childhood linked to the sudden evolutionary increase in human cranial size (Konner, 1981); but then attachment-related behaviors are recruited and used as part of the repertoire for courtship and assortative mating (Stevens, 1982). Competition Humans as a species have relatively few offspring, which require a substantial investment of time and energy to survive to reproductive maturity. From a genetic perspective,

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genes favoring nurturing behavior and some degree of parental investment in the offspring would promote both survival and later reproductive success for persons carrying those genes. At the same time, there is a genetic pressure for “choosiness.” The costs of pregnancy and parenthood to a female are high (Buss, 1994). Women genetically predisposed to be selective about partners are more likely to be able to choose partners with desirable genes (for physical health, cognitive capacity, or attractive personality). They also are more likely to be able to marshal resources in support of themselves and their children, by demanding greater displays of fidelity and paternal investment, and also by mating with more powerful members of the social group (Ellis, 1995). Males also want to mate with the most desirable partners that they can, but the much lower costs invested in contributing sperm versus the minimal maternal contribution from ovum to weaning (let alone the more extended maternal investments typically made in humans) create an evolutionary pressure suggesting that at least some males would explore Casanova-like strategies of pursuing as many partners as possible, and others would be tempted to wander (Buss, 1995b). Interestingly, there is evidence for “social Machiavellianism” in female primates, too, where they may seek to partner with a good provider, but then have opportunistic liaisons with other partners with different desirable genetic attributes (Ellis, 1995; Ridley, 1993). The details of sexual selection are fascinating, and any attempt at detailed treatment would derail the course of the present chapter. The central point for our purposes is that sexual selection is not simply a matter of pursuing or attracting a partner. There is a crucial component of selecting the “right” partner, which introduces a huge element of competition into the process. The competition includes intra-sex contests to capture the attention of the most attractive suitor, or to win access to the most desired partner. Sexual selection can focus on attributes and preferentially select for them, independently of their survival advantage. In fact, if the advantage in terms of sexual preference outweighs the risks in terms of survival, then it is possible for sexual selection to result in heritable changes that actually handicap the survival of the carrier (Zahavi, 1991). The classic example is the male peacock’s tail; but the argument has been made that any attribute that shows rapid evolutionary change in the absence of clear survival advantages might be a good candidate for sexual selection (Miller, 2000). Sexual selection is also unusual compared to survival selection in that it has greater freedom in terms of what attributes it can seize upon, and also how rapidly it can

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drive changes. The rapid inflation of the size of the human brain might be attributable to sexual selection (Miller, 2000; Ridley, 1993). Sexual selection also would provide a mechanism for selecting persons more capable of emotion regulation, and more nuanced displays of emotion expression. Runaway Competition also can lead to an “arms race” between the sexes, where sexual selection drives change at a pace that is much more rapid than survival selection would produce (Ridley, 1993). The sexual selection argument for brain development hinges on the idea that humans would preferentially choose mates who were more intelligent, articulate, charming, and clever. People possessing these attributes would be more likely to mate at all, more likely to have multiple partners, and more likely to have their offspring survive to reproductive maturity (by virtue of the indirect effect of other desirable genes, as well as via the environmental benefits that come with having higher-status parents) and achieve their own reproductive successes. A consequence of this would be that genes for larger brains and more skillful emotion expression and regulation would become more common in the gene pool. This sort of sexual selection could lead to a “runaway” escalation in the attributes targeted for selection. Take for example the ability to use behaviors from the caregiving emotional repertoire. The first human ancestors able to invoke these behaviors as part of courtship instead of only during caregiving would have held an enormous advantage. Females able to express these emotions and behaviors during courtship would be demonstrating their capacity to be a good mother. Males showing similar behaviors would be displaying a capacity for exceptional paternal involvement. As these individuals achieved greater reproductive success, their genes would become more common. However, the very success of the genes would in time mean that most of the population would eventually possess the beneficial genes, and what had been the jewel in the crown of fitness indicators now has become commonplace. This creates circumstances favoring the selection of individuals who happen to possess even more extreme degrees of the attribute, creating a positive feedback loop that leads to extremely rapid, “runaway” change in the sexually selected attributes (Miller, 2000; Ridley, 1993). In the realm of emotions, sexual selection in humans appears to have produced a runaway process where the point of departure was the mammalian emotional toolbox. Sexual selection took these basic emotion processes and then favored those who could employ these emotions

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more flexibly in the service of courtship and reproduction. The pressure to demonstrate greater facility with emotions and social relationships may have contributed to the development of verbal expression, language, and cognitive development (Miller, 2000). In turn, these created a more complex social environment for more sophisticated displays of emotion. This feedback loop has literally exploded into the staggering array of behaviors ranging from gossip to dance to romantic poetry and the many forms of music. What chance would a Vulcan have against a human competitor in the dating game? A human could use emotions to size up the competition quickly, almost intuitively, and concentrate her efforts on the best matches while the Vulcan was still cataloging the features of the first person encountered. And once the Vulcans had identified a promising candidate some hours later, their dry catalog of the logical advantages of partnership would not be heard over the pulses of a samba that the emotional competitors were dancing. Approach, Avoidance, and Sex From the perspective of sexual competition, emotions would be extremely valuable in multiple ways. Approach emotions are crucial in identifying potential partners, as well as motivating courtship behaviors. In many cultures, the experience of romantic love is an emotional state that verges on religious ecstasy or hypomania (Johnson, 1983). There is a narrowing of attention onto the desired person, a sense of extreme well-being when connected with that person, a feeling of grandiosity about the relationship, and often marked increases in energy and decreased need for sleep. Feelings of lust can motivate extreme effort in animals; humans in love can display the same intensity with greater nuance. Approach emotions such as anger are also invaluable in navigating intra-sex competition. Without anger, it would be difficult for suitors to motivate their best performances, and few would be as willing to risk the losses—of social standing or physical injury— potentially accompanying the pursuit of a desired partner (Buss, 1995a). Anger also energizes assertive behaviors to ward off perceived competitors. People have a tendency to overestimate the attractiveness of competitors, which motivates greater effort to present oneself in the best light possible (Hill, 2006). Avoidance emotions would also be crucial in rapidly evaluating complex social situations and deciding which potential partners to reject. It makes evolutionary sense to avoid pursuing partners who are too far above or below oneself in terms of desirability, given the investment involved in actually raising a child, and the limited number of children that humans have (relative to other

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animals). Avoiding pursuit of partners who are “out of reach” also makes sense if the courtship is going to consume resources without much likely return on the investment, or if there are competitors who are likely to impose costs (either physical injury or social derogation) if the person enters the fray (Buss, 1994). Avoidance emotions like shyness would help to shield people from exposure to the risks of direct competition. Shyness also supports a strategy of waiting to see which potential partners are motivated enough to continue to pursue even without immediate displays of receptivity. In other words, shyness might be an evolutionary tactic for helping separate serious partners from more casual suitors (Miller, 2000). If this hypothesis is correct, then it would make evolutionary sense for shyness to be more commonly expressed in women than men, because biological factors would favor women concentrating on the quality instead of quantity of partners (Buss, 1994). Consistent with this hypothesis, shyness appears more common in females (Kessler, 1998; Youngstrom & Green, 2003), and it also appears more socially handicapping in males when present (Snyder, Smith, Augelli, & Ingram, 1985). Other avoidance emotions would be valuable in rejecting unwanted partners. The sense of disgust one feels on a bad blind date is not due to a biologically toxic effect, but instead reflects an emotion that initially developed for the purpose of avoiding poisons being recruited to guide avoidance behaviors in a complex social situation. Displays of social disgust or contempt will terminate flirtation far more quickly and thoroughly than any factual enumeration about the reasons for incompatibility. Sadness acting as an avoidance emotion is crucial for motivating withdrawal from situations where the relationship is damaged or lost, preventing further losses and providing space for recovery. Conversely, strategies for regulating sadness can lead to social exchanges that elicit empathic responding and social support (Izard, 1991; Izard & Ackerman, 2000). The importance of emotions to our ancestors’ sexual success is written across our bodies as well as our brains. The eyes and the muscles immediately around them are central to the facial expression of most emotions (Ekman, 1993; Izard, 1971; Izard, 1990). Humans, unlike other primates, have evolved very white scleras that make the eyes more visible. The greater contrast between the eye and the rest of the face makes it easier to discern emotion expressions, and also to divine where the other person is directing their attention. Both of these become increasingly valuable in complex social groups (The Economist, 2006). Humans have also become attuned to nonverbal cues about emotional and physical traits. Women are able

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to look at facial photographs of unfamiliar males and make judgments that correlate highly with the men’s assayed testosterone levels, or their attitudes towards children (indexed by the men’s performance on a picture sorting task)—both with correlations around .6 (Roney, Hanson, Durante, & Maestripieri, 2006). Women also appear to have an advantage in terms of recognizing facial expressions of emotion, consistent with both attachment promotion and threat sensitivity fitness models of emotion (Hampson, van Anders, & Mullin, 2006).

SOCIAL AND INTERPERSONAL FUNCTIONS: BUILDING, MAINTAINING, AND CHANGING NETWORKS Implicit in the discussion above are some of the ways that emotions influence social and interpersonal functions. Recent neuroimaging data indicate that social situations trigger emotions differently and engage distinct brain regions as compared with nonsocial stimuli (Britton et al., 2006). Approach and avoidance emotions are constantly alert to social cues. At the survival level, these include cues about whether a person is a friend or foe (Hampson et al., 2006). Far more attacks and deaths have resulted from intraspecies violence than from encounters with poisonous animals or other predators for most of humanity’s recent evolutionary history. Humans appear to have gotten particularly good at recognizing expressions of anger in others, especially in dominant males, for just this reason (Allan & Gilbert, 2002). Approach and avoidance may also work in an opponent process to help people quickly gauge the perceived controllability of social situations and their dominance or social status within the group. Dominance has important consequences in terms of social interactions, access to resources, and assortative mating. Approach emotions would help drive efforts to climb the social ladder, often through play (Panksepp, 2000), but sometimes in more serious confrontations. Avoidance emotions become vital to de-escalate conflicts and have the loser retreat before sustaining serious injury (Wilson, 1980). Avoidance emotions such as sadness and submissiveness displays also may help people to remain in the social group by advertising that they are no longer challenging the victor’s status (Allan & Gilbert, 1997; Gilbert & Allan, 1998). Studies of conflict in families suggest that an additional layer of meaning may have developed for emotional interactions beyond the surface content of the exchange. Emotional conflicts often involve deeper issues pertaining to intimacy or power within a relationship. If the conflict is about power, then winning or losing the argument matters a great deal to the participants, precisely because

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social dominance is at stake. However, if the conflict is about intimacy, then the content does not appear to be important; nor does “winning” matter as much. Instead, the intensity of the conflict communicates important information about the perceived importance of the relationship (Emery, 1992). It is our closest friends and lovers who can provoke the greatest extremes of emotional response. When we are able to discuss the strengths and weaknesses of a relationship with Vulcan-like dispassion, then the flame has gone out. On the basis of this model, even avoidance emotions can communicate important information about intimacy. Paradoxically, the profoundness of the sadness or pain at the rupture of a relationship reveals the importance of the intimacy. Finally, much recent work emphasizes the value of positive, approach-oriented emotions for “broadening” awareness and “building” social networks (Fredrickson, 1998). Research with couples indicates that stable relationships tend to have partners expressing five times as many positive, approach emotions towards each other as negative emotions, including both anger and avoidant emotions (Gottman, 1994). “Stonewalling,” an extreme form of withdrawal, also appears to be a particularly toxic pattern of interaction found in relationships that are close to dissolution (Gottman, 1994).


Mathews, 1990). Mood congruent biases in perception and memory continue to color learning history (Mogg, Bradley, Williams, & Mathews, 1993). Even as cognitive abilities develop, our thoughts work on percepts tinted by emotion, and we compare our experiences with memories selected for relevance based on our emotional state. Finally, besides providing scaffolding for organizing our interpretations and reactions to experiences, approach and avoidance also represent foundational dimensions for individual differences in motivation for behavior. Out of this cycle of experience, memory, and reinforcement grow temperamental styles (Kagan, 1997a). With continued cognitive development and experience, temperamental tendencies become personality traits. Genetic differences contribute to propensities for personality to grow in certain directions, but learning history can shift the course, although many environments will contribute to the self-reinforcing tendency of emotion systems. This process of development has been described as the formation of “affective-cognitive structures,” or “emotion schemas,” (Izard, 2007), a terminology that nicely captures the composite and interactive nature of emotion and cognition as components of personality (Izard, Libero, Putnam, & Haynes, 1993).

RUNAWAY SOFTWARE: EMOTIONS, MEMES, AND CULTURE INTRAPERSONAL FUNCTIONS: SCULPTING THE SELF Approach and avoidance emotions also play a fundamental role in shaping the development of personality, individual differences, and a person’s self-identity (Elliot, 2006; Elliot, Gable, & Mapes, 2006). General tendencies towards behavioral activation and inhibition have a genetic component (Loehlin, 1992). These dispositional tendencies begin influencing temperament in infancy (Kagan, 1997b). People with lower activation thresholds for approach emotions are more likely to have higher activity levels. People with lower thresholds for avoidance emotions will have greater sensitivity to cues of threat, and are more likely to be shy and withdrawn as toddlers. These emotions continue to filter perceptions of experiences, fundamentally altering the perceived developmental environment. These emotion tendencies also change the transactions that the person has with peers and adults. Even in the same classroom, the experiences of a shy, anxious child versus a curious and energetic one are radically different. In addition to changing the perceptions, emotional responses, and behaviors elicited by significant others in the environment, approach and avoidance emotions also shift the valence and weight of recalled memories (Mogg &

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Many researchers are beginning to think about ideas or behaviors as being something that can replicate and either become more common or extinguish, in a manner analogous to genetic replication (Blackmore, 1999). Just as the Earth provided a primordial soup that allowed amino acids to develop, and from which emerged DNA with self-replicating capabilities; so genetic evolution created increasingly complicated nervous systems until the capacity for imitative learning emerged and became sufficiently developed to create a new environment where memes could replicate and compete (Jablonka & Lamb, 2005). The concept is appealing on multiple levels. Viewed in this way, culture cannot be fully explained by a biological reductionism. Instead, culture and perhaps consciousness are emergent properties that only become possible when the underlying architecture is sufficiently rich and complex, but then begin to interact in a way that is at least partially independent of the architecture (Dennett, 1991). Another analogy could be made to computers. Initially they were calculators, hardwired for specific computations and purposes—analogous to the biologically reflexive responses, or instinctive innate releasing mechanisms and stereotypical responses. As computers become more

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powerful, it became possible to shift more functions into “software” instead of hardwired circuits. Software allowed the same computer to be used for different purposes, and much more flexibly. As memory capacity increased even further, software became more complicated (and less stable). The current world of Internet browsers, shared applications, cookies, spyware, and viruses represents a state of development where software often propagates across computers without conscious knowledge of the user, and it also can result in unpredictable behavior (Aunger, 2002). One of the points of this analogy is that because both culture and software operate at an emergent level, it is not possible to make deterministic predictions about them based on the underlying architecture. Scientists cannot look at a functional image of a person’s brain and know what languages they speak, nor what they will choose for lunch, any more than we could look at the motherboard of a computer and tell whether it is currently running a word processor or an Internet browser, or both at the same time. A converse implication is that there are still constraints on the operation of the system based on the underlying architecture. Software no longer runs if there is physical damage to the memory or hard drive, just as culture or consciousness may cease to function if there is damage to the underlying brain. More subtly, the underlying architecture imposes some limits and creates probabilistic influences on the emergent systems. In terms of culture and consciousness, we cannot react to colors outside the spectrum that is visible to our optic system, or to tastes (even of toxins) not discernible by our gustatory system. Our brain must impose order on a jumble of sensory information, analogous to processing millions of web search “hits” every minute. The algorithms our brains use to rank the sensory “hits” were developed and optimized by our evolutionary history and its legacy in our nervous system. Put another way, our search and ranking algorithms for navigating our environment are more emotional than rational. Our emotional nature shapes the playing field on which memes compete. Not all memes have emotional content, but the memes that do are at a considerable advantage in terms of grabbing attention, getting “chosen” for long-term memory, and getting shared with others. In terms of practical benefits, the contributions of theoretical physics objectively far outweigh pop culture, but apparently that is not the over-riding factor in the popularity of memes among emotional beings. Consider the number of people who could recite the three laws of thermodynamics versus humming a few bars of Michael Jackson’s song “Thriller,” which sold more than 59 million copies worldwide.

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The environment occupied by memes has also changed with extreme rapidity. Some animals show evidence of vicarious learning of simple behaviors—arguably the protean form of memes. The development of language not only created a larger number of potential memes, but also increased their complexity and the number of people who could be exposed to the meme. The printed word further changed the memetic environment: (1) memes preserved in writing could last much longer, like spores or cryogenic freezing for biological replicants; (2) written memes could be exposed to much larger audiences; and (3) writing itself became another evolutionary niche that memes could occupy. The rise of mass media further increased the bandwidth through which memes could be broadcast, and also added the possibility of sound and color being attached to the memes—some of the secret weapons that “Thriller” used to out-propagate the Laws of Thermodynamics. The Internet and computer games represent another quantum advance in the changes to the memetic environment. The Internet makes possible communication with literally hundreds of millions of people, and it now combines the durability of the printed word with the sensory appeal of sound, color, and animated motion. The result is a much larger audience exposed to memes, as well as accelerated competition. At present, virtual reality is available to a much smaller audience, but goes a step further than the typical Internet download in terms of sensory stimulation. The latest generation of videogames (e.g., X-Box, Playstation 3, Wii) are arguably the most widely distributed virtual reality systems. Even a cursory examination of the content shows that our choice of topics on the Internet and in games is driven by evolved emotional preferences. It does not flatter our species that more people will play “First Person Shooter” games such as Doom than will visit the Louvre, but these preferences make evolutionary “sense” given the greater importance that survival or sexual competition had as compared to aesthetic appreciation for the bulk of our evolutionary history. Aesthetics became a growth stock in the human market only once sexual selection focused on it, and artistic sensibility became a way of advertising fitness to potential mates (Miller, 2000). What is fascinating about the Internet and virtual reality from an emotional perspective is that these media allow for activities that are based on evolved preferences for rewards, without the same potential costs that were present for most of our evolutionary history. An interesting parallel can be made to diet. For 2 million years, sugar, fat, and salt were present only in trace quantities in most available foodstuffs. Our taste preferences and drives evolved to

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provide motivation sufficient to incur the necessary costs to spend a day gathering nuts, or to brave hunting down a large mammal. Suddenly, in the evolutionary eye-blink of the last 10,000 years, the agricultural and industrial revolutions have changed our environment so that there is a profligacy of nutrients compared to the strength of our urges to consume them (Konner, 1985). We have sufficient motivation to spend a day foraging, impelling us impulsively to grab a Snickers bar at the checkout line; sufficient drive to hunt a mastodon guiding our choices at a drive-through fast food restaurant. A McDonald’s Big Mac caters to our evolved preferences for fat and salt. Our choices of violent, sexual, or thrill-seeking content paint a similarly unflattering portrait of the legacy of our evolutionary environment on our choices of memes. Horror films, sad songs, elegiac poetry—all of these serve no obvious biological function in terms of survival or sexual selection. Instead, these are “junk food of the mind”—things that achieve their popularity by pandering to evolved preferences for approach and avoidance. The bottom line is that, in the emergent world of consciousness and culture, not all memes are emotional. But the memes that carry an emotional charge are at a tremendous advantage, with the billows of approach and avoidance adding wind to the meme’s sails at the moments of perception, attention, interpretation, and action. It is a substantial competitive edge, and the consequences of these probabilistic preferences are writ large across our popular culture. Supermarket tabloids provide a clearer window onto our evolutionary memetic legacy than do college textbooks or doctoral dissertations, even though the latter represent higher accomplishments by highly evolved minds.

EMOTION-RELATED DYSFUNCTION Psychopathology presents one of the fundamental challenges to a functionalist approach to emotions. If emotions served an evolutionary purpose, why do emotions feature so prominently in pathological conditions? How could a good thing turn so bad? And how could an adaptive system that improves survival and sexual fitness go so wrong so often? Mental disturbances that involve severe emotional dysregulation are not a freakish oddity. Instead, emotional imbalance is the mainstay of psychopathology, to the point that scholars can argue that emotional dysfunction is the core construct of almost all mental illness (Bradley, 2000).

MODELS OF EMOTION AND PSYCHOPATHOLOGY There are a variety of models that offer different explanations of the role of emotions in psychopathology.

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Conflict as Normative Development To some degree, conflict is an unavoidable part of maturation. Children and adolescents change roles and test the boundaries of relationships with authority figures and peers as they grow and master new skills (Emery, 1992). Approach emotions will motivate limit-testing behavior. Avoidance emotions will de-escalate conflict and promote periods of stability where the status quo of relationships and authority are maintained. Although parents, teachers, and sometimes youths will seek mental health services for these sorts of developmental conflicts, typically these do not represent psychopathology or emotion dysfunction so much as the inevitable bumps and scrapes of growing up. Too Much of a Good Thing (Statistical Models of Extremity) A related model of psychopathology would be the statistical extremity definition. Anger might serve an adaptive function on average, and there are individual differences in the tendency to activate or express anger. At the extremes of the distribution, there will be those who are extremely likely (or unlikely) to express anger. Persons in the top 5% of tendency to show hostility are likely to experience more adverse interpersonal interactions, as are people who are similarly reticent or incapable of showing anger. At either extreme, individual differences in anger could increase the likelihood of the person experiencing the “harmful dysfunction” that is considered a hallmark of psychopathology (Wakefield, 1997). Extremes in the tendency to experience other emotions are also likely to be associated with, and might even be a causal mechanism for, psychopathology. Extreme shyness appears linked with social phobia and perhaps other forms of anxiety (Heiser, Turner, & Beidel, 2003). Extremely low levels of positive affect (anhedonia) are implicated in depression (Clark & Watson, 1991). An important caveat is that statistical extremity need not signify an underlying genotypic extremity. Environmental factors play a large role in dulling or honing the edges of emotional expression. Traumatic events can have profound consequences on later emotional development (Porter, 1998), and cultural factors also do much to potentiate or mitigate emotional extremes. Dysfunction as Transaction: Right Feelings, But at the Wrong Place and Time Developmental models of psychopathology often focus on the transaction between the person and the environment (Chess & Thomas, 1989; Kazdin & Kagan, 1994). The same behavior might be adaptive on the playground, but

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inappropriate in the classroom; or behavior that is frighteningly disinhibited in the view of one parent might be within tolerable limits for another. Changes in the environment, precipitated by shifts in culture or technology, might alter perceptions of what is adaptive versus counterproductive, much as changes in food production have shifted our dietary environment away from the Paleolithic larder of our origins. The human emotional repertoire evolved primarily under circumstances where social groups might include up to a few dozen individuals, all of whom knew each other, and with a strong pressure for xenophobia towards strangers (Konner, 1981). Our emotional systems are likely to be stressed by the density and complexity of social relationships in postagricultural or postindustrial societies. At the same time, technology has magnified the consequences of emotional expression. Evolved anger responses to perceived social challenges among primates in the modern phenomenon of “road rage,” and evolved jealousy responses to perceived infidelity turn lethal when a gun is added to the equation. Within mental health, the transactional argument has received its fullest expression in the realm of attentiondeficit/hyperactivity disorder, which psychiatry argues is a medical illness (American Psychiatric Association, 2001), but which others interpret as pathologizing individual differences in temperament that are within normal limits (Carey, 1998). A similar debate is now occurring with pediatric bipolar disorder, which some believe is a biological entity, and opponents argue is another example of “disease mongering” (Healy, 2006), or attempts to pathologize normal emotional experiences so as to increase the demand for medical services to treat the “problem” (Heath, 2006; Scott, 2006). An advantage of transactional models is that they can account for psychopathology even when adaptively evolved emotion systems appear to be intact. It is not that the emotion system is damaged or categorically dysfunctional. Instead, adaptive emotions can become linked to maladaptive learning histories, cognitions, or social environments in “emotion schemas” (Izard, in press). A drawback of transactional models is that they do not draw sharp boundaries around a condition to delineate pathology. Instead of yielding a clear definition, transactional models imply that pathology is “negotiable,” and can be changed by modifying the behavior, the setting, or both. This fuzziness appeared anathema to common sense, “medical model” definitions of pathology. However, current understanding of gene–environment interactions is demonstrating that genetic polymorphisms transact with the environment in complicated ways, such that a particular nutrient or caregiving environment might be essential

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to one subgroup, and toxic or irrelevant to another. Transactional models also provide a convenient solution for the puzzle of how emotions could be adaptive yet bound so tightly to psychopathology. The riddle is resolved if the environment where the emotion is problematic differs substantially from the context where the emotion system originally evolved to be adaptive. Mutation—Fractures in an Otherwise Good System A fourth model of emotion and psychopathology would concentrate on harmful mutations as an explanation of dysfunction in the emotional system. Examples can be found of single gene mutations or chromosomal deletions that result in severe emotional dysregulation, such as Williams syndrome—with its associated hyper-sociality and lack of fear of strangers, or Huntington’s chorea— a single-gene trinucleotide repeat expansion that is associated with anxiety, depression, or extreme aggression. However, these mutations tend to be rare (affecting only 1 in 7,500 births for Williams syndrome, and up to 8 per 100,000 births for Huntington’s chorea). Given the extreme social and reproductive consequences of such dysregulation of the emotion systems, it is unlikely that these mutations would persist long in a population unless their deleterious effects appeared well after reproductive maturity (as is typically the case with Huntington’s chorea), or perhaps if lower doses of the mutation were associated with positive effects. The beneficial effect of low doses has been demonstrated with Sickle cell disease, where carriers with one copy of the recessive allele show enhanced resistance to malaria. More speculatively, there is evidence that low doses of bipolar disorder, in the form of mild illness or in the presumed loading of unaffected family members, are associated with increased creativity and productivity (Jamison, 1993; Simeonova, Chang, Strong, & Ketter, 2005). On the basis of this argument, mutations that increased approachoriented emotions might provide advantages in moderate doses, though sometimes becoming deleterious in extreme concentrations. Sneaky Value Added (Subtle or Counterintuitive Adaptive Value) A final model for emotions and psychopathology hypothesizes subtle or indirect benefits sufficient to outweigh the costs to the replicating unit. There are multiple variations on this theme that have been proposed. Depression, which clearly involves short-term costs for the individual, may yield important social benefits by allowing the person to remain a member of the community in spite of setbacks or losses (Gilbert & Allan, 1998; Plutchik, 1993), or it

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might benefit the individual by preventing the wasteful expenditure of energy and resources in pursuit of a failed cause (Izard, 1992). By shifting the focus from the organism to the gene, kinship selection models become plausible, whereby emotions might have evolutionary advantage even though the person expressing them may not have offspring of their own. Another provocative model is that sexual selection pressure drove the elaboration of the human brain as a marker of reproductive fitness, making it consume a disproportionate amount of energy and involve the expression of a disproportionate number of genes precisely because mental health status would then provide a quick and accurate method of sampling the genetic and developmental history of the organism (Miller, 2000). In this view, paying attention to emotional functioning becomes an excellent way of gauging not just mental health, but also reproductive and survival fitness more generally, precisely because so many things could go wrong with the emotion systems due to harmful mutations, poor environment, or acute trauma. Healthy displays of emotion are like the “miner’s canary” whose sensitivity provides warning of accumulated toxins. A third, and perhaps more disturbing, possibility arises if memes are considered as the unit of replication. From a memetic view, psychopathology could be an extremely effective way of propagating memes, even though the organism suffers harmful dysfunction, or the genes fail to propagate. Van Gogh was severely unhappy, dying childless of suicide; but his artwork has retained iconic status, with pieces auctioning for millions of dollars, and literally millions of reproductions of paintings such as “Starry Night” continuing to sell around the world. The cliché of the tortured artists suffering for their work might hold some truth viewed from a memetic level. Doses of approach and avoidance emotion that would be toxic at the interpersonal level and counterproductive from a genetic point of view may actually contribute to memetic success. Phenomena such as suicide contagion in schools, or suicide bombing, propagate memes widely and often indelibly on the minds exposed to them. A less violent example, albeit equally challenging at the genetic level of explanation, would be the popularity of celibacy within many organized religions. If it is possible for memetic selection to occur independently of the biological adaptiveness of the idea or behavior (and self-immolation presents the most extreme philosophical example of this scenario), then psychopathology becomes much easier to explain within an adaptive framework. The behavior becomes adaptive from the perspective of the meme, regardless of the consequences to the carrier, much as

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inducing a terminal cough is adaptive from the perspective of the pathogen for influenza or pneumonic plague. If the memetic model is correct, then there are important implications in terms of mental health. Recent policies of minimizing the publicity around suicides or terrorist attacks may help curb the spread of the memes of risk for these behaviors. Avoiding glamorization of violence or suicide also helps decrease replication by avoiding associations with “popular” memes that could accelerate the spread of linked memes. In other words, avoiding associations with sex, social status, or other emotionally provocative cues would decrease the spread of the meme. The more that a meme can co-opt evolved emotion systems, the easier it is for the meme to be perceived, remembered, and replicated in “copy-cat” behaviors (Aunger, 2002).

APPROACH AND AVOIDANCE EMOTIONAL MODELS OF PSYCHOPATHOLOGY: BEHAVIORAL INHIBITION SYSTEM AND BEHAVIORAL ACTIVATION SYSTEM A dimensional framework has already been elaborated for understanding psychopathology in terms of approach and avoidance. Gray focused on neuroanatomical models and described three major motivational systems: The Behavioral Activation System (BAS), the Behavioral Inhibition System (BIS), and the Fight/Flight System (FFS) (Gray, 1985; Gray & McNaughton, 1996). Gray’s model specifies neural circuitry and behavioral outputs for each of these systems. Others have developed questionnaires and behavior checklists to assess human behaviors, emotions, and personality traits that correlated with BAS and BIS (Carver & White, 1994; Depue & Iacono, 1989). BAS is the “gas pedal” that orients attention and impels the organism towards cues of reward, galvanizing approach behavior. BIS is the “brake pedal” that is attuned to cues of threat, inhibits approach, and potentially motivates avoidance. Data from multiple levels of analysis from imaging, psychophysiology, and factor analyses of questionnaires all indicate that BAS and BIS are separate systems, not opposite ends of a bipolar continuum (Beauchaine, 2001; Corr, 2001; Matthews & Gilliland, 1999). The interesting implication of this is that it is possible for an individual to experience any combination of activation of these two systems, including intense activation of both at the same time. Multiple investigators have applied the BIS and BAS constructs to psychopathology, including extensive work by Quay with children and adolescents (Quay, 1985, 1993), and Fowles’ review with adult psychopathology (Fowles, 1994). As the BIS and BAS constructs have also extended into personality research and social psychology, points of

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High approach (High BAS) Pure mania Mixed mania Psychopathy/ conduct disorder Hypomania Attention-deficit/ hyperactivity disorder Low avoidance (Low BIS)

Generalized anxiety

Depression

High avoidance (High BIS)

Anxiousdepression

Low approach (Low BAS)

FIGURE 21.1

Relationship of clinical disorders to dysregulation of approach and avoidance systems.

overlap have become evident (Elliot & Thrash, 2002). Approach is roughly isomorphic with BAS, which also has a strong overlap with “positive affect” in the TellegenWatson model of affect (Watson & Tellegen, 1985), or with positive-valence plus high activation in other dimensional models of affect, or the high energy pole of Thayer’s energy-tension model (Thayer, 2001). Avoidance corresponds well with BIS, which overlaps with “negative affect” in the Tellegen-Watson model. Figure 21.1 illustrates where many common forms of psychopathology fall in terms of dysregulated approach and avoidance. Overactivity of the BIS (potentially due to low activation threshold, or due to exaggerated responsiveness of the BIS to threat, or due to longer latency to recovery once triggered) is associated with more negative affect, especially fear and worry. Chronic activation is correlated with trait neuroticism at the personality level, and with anxiety disorders at the acute pathology level (Matthews & Gilliland, 1999). Interestingly, high BIS activation (or high negative affect in the “Tripartite Model” of depression and anxiety) is most strongly linked to generalized anxiety disorder (and possibly separation anxiety in youths) (Chorpita, Albano, & Barlow, 1998), but not so tightly to phobias, which may often involve a strong disgust reaction instead (Watson, 2000). BIS deficits are thought to be associated with conditions such as attention-deficit/hyperactivity disorder (ADHD), where low BIS results in impulsivity due to failure to

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inhibit behavior (Quay, 1997). Low BIS is also expected to contribute to the development of antisocial behavior (clinically diagnosed as conduct disorder or antisocial personality disorder in DSM parlance, and sometimes conceptualized as “psychopathy” in research) due to the lack of inhibition and also perhaps due to a failure to learn rapidly in response to punishment (Quay, 1993). Inadequate levels of avoidance motivation clearly are a risk factor for disinhibited, externalizing psychopathology. Dysregulation of the approach system (i.e., BAS) also conveys marked risk for emotional and behavioral problems. High levels of BAS may contribute to “reward dominance,” where the urge to obtain a goal overrides any cues for inhibition (Fowles & Dindo, 2006; Quay, 1993). The combination of high BAS and low BIS predisposes an individual to antisocial behavior, as they focus only on rewards and not potential negative consequences for actions. Low BAS is an important component of major depression. Although depression also tends to involve high levels of negative affect (the nonspecific or shared component of both anxiety and depression), the more distinctive feature of depression is the lack of positive affect, energy, and motivation (Clark & Watson, 1991). Clinically, this manifests in symptoms of sadness (the opposite of happiness in dimensional models of state affect), loss of interest in activities, anergia or fatigue, and anhedonia. Less obviously, low trait BAS due to a high activation

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threshold might be a risk factor for substance use and other sensation-seeking behaviors (the hypo-arousal hypothesis; Zuckerman, 1999). The combination of approach and avoidance, or BAS and BIS, can also be fruitfully applied to the construct of bipolar disorder. Previously known as “manic depression,” bipolar disorder is an illness that can present any of a variety of mood states, including major or minor depression, euthymia (or mood within normal limits), hypomania, mania, or mixed states that combine manic and depressed symptoms in the same episode (American Psychiatric Association, 2001; Kraepelin, 1921). This dizzying range of clinical states can be challenging to recognize and categorize correctly. It is much more simple and elegant to conceptualize the illness as involving fluctuations in the BIS and BAS symptoms. High BAS activation and BIS suppression would characterize a pure, uncomplicated manic state with elevated mood, increased energy, and goal directed activity. Hypomania would involve more moderate amounts of BAS hyperactivation. Depressed states would entail very low BAS (resulting in the anergia and anhedonia of depression), with high levels of BIS adding the anxious, tense negative affectivity also often seen in depression. High BAS and BIS activation during the same episode would create a “mixed state,” involving the high energy of mania with the negativity, tension, and anxiety of depression (Depue & Lenzenweger, 2001). Recent work in bipolar disorder has found good evidence for the BAS dysregulation component in particular, with the interesting findings that successes and positive life events can be destabilizing for people prone to mania (Johnson, 2005), and that mania may be associated with distinct cognitive and perceptual biases from depression (Reilly-Harrington, Alloy, Fresco, & Whitehouse, 1999). It is important to note that although an approach and avoidance framework provides a parsimonious unifying framework that fits a broad variety of disorders, it does not provide a complete fit for all pathology. For example, approach and avoidance are not likely to be the primary dimensions contributing to eating disorders, obsessivecompulsive disorder, pervasive developmental disorders, or tic disorders—even though all of these typically include some degree of anxiety (Bradley, 2000). Approach and avoidance will also not be the salient dimensions for mental retardation or learning disabilities. Even acknowledging these limitations, the explanatory power of approach and avoidance in the realm of psychopathology is impressive. Not only do these dimensions figure prominently in multiple disorders, but they also facilitate integration of personality, emotional,

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behavioral, psychophysiological, and neural aspects of functioning. The involvement of these two dimensions in multiple disorders also provides a plausible explanation for the high rates of psychiatric comorbidity observed in both epidemiological and clinical samples. Purportedly distinct disorders may be sharing a common underlying mechanism, such as BIS or BAS dysregulation (Caron & Rutter, 1991).

CONCLUSION Organisms with appropriately calibrated emotional responses are more likely to survive and to reproduce. Discrete emotions can be organized to a large degree within a two-dimensional framework of approach and avoidance. However, discrete emotions evolved because they offered more differentiated ways of optimally addressing adaptational events. Emotions rapidly process a wealth of information, carefully attuned to cues of goals to approach or threats to avoid. Much of the information processing is happening precognitively, appraising nonverbal behavior and details that would be difficult to articulate consciously. Human intelligence and culture introduced new levels of flexibility and complexity. Behavior is no longer driven by instinct and the stereotypic responses to innate releasing mechanisms, nor is it always led by emotion. Individuals developed the capacity to regulate emotions, and as social environments became more complex, it became possible and often beneficial to mask emotions or to feign emotional states different than what was actually felt. With the development of meta-emotional capacities, it became possible to recruit and blend emotions for other purposes, rather than primarily experiencing them as a response to the environment. Positive, approach-oriented emotions serve a crucial role in “broadening and building” social networks and cementing significant relationships. Negative, approach-oriented emotions such as anger and contempt serve to motivate action, to assert oneself or attempt to climb in social rank, and to defend that rank. Negative, avoidance-oriented emotions serve to not only avoid threats to survival, but also to help define social outgroups (promoting affiliation within a group), and also facilitate assortative mating. Dawkins’ concept of memes as replicable units of behavior offers a speculative but intriguing way of thinking about culture and ideas, and explaining behavior. The behavior or idea itself becomes the new unit of replication (not the selfish biological gene), and this change in type of replicant creates a new arena for adaptive events to select among myriad memes. Memes that have an

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attached “charge” in terms of approach or avoidance have a tremendous advantage for increasing their chances of propagation. Such charged memes are more likely to be appraised as important by evolved emotion systems, and thus are more likely to capture cognitive attention and to motivate behaviors (including the re-expression of the meme). Other memes, lacking a direct association with approach and avoidance, may be able to replicate by virtue of other features, but they operate at a distinct disadvantage. Future functionalist views of emotions may want to consider how emotions contribute to survival, sexual, and memetic adaptation, and to consider how other domains (such as attachment or culture) are influenced by these processes. The emergent properties to our neurocognitive and our social systems add fascinating complexity. Although approach and avoidance systems initially evolved to facilitate survival, these dimensions were both conserved and elaborated in the service of sexual selection, and may now be reciprocally influencing memetic selection. Approach and avoidance are tools that now are often being turned to new purposes loosely linked, if at all, to their biological origins.

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Solomon, R. C. (2000). The philosophy of emotions. In M. Lewis & J. M. Haviland-Jones (Eds.), Handbook of emotions (2nd ed., pp. 3–15). New York: Guilford Press. Stevens, A. (1982). Archetypes: A natural history of the self. New York: Quill. Thayer, R. E. (2001). Calm energy: How people regulate mood with food and exercise. New York: Oxford University Press. Todd, P. M., & Gigerenzer, G. (2000). Precis of simple heuristics that make us smart. The Behavioral and Brain Sciences, 23, 727–741; discussion 742–780. Tomaka, J., Blascovich, J., Kibler, J., & Ernst, J. M. (1997). Cognitive and physiological antecedents of threat and challenge appraisal. Journal of Personality and Social Psychology, 73, 63–72. Wakefield, J. C. (1997). When is development disordered? Developmental psychopathology and the harmful dysfunction analysis of mental disorder. Development and Psychopathology, 9, 269–290. Watson, D. (2000). Mood and temperament. New York: Guilford Press.

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Watson, D., & Tellegen, A. (1985). Toward a consensual structure of mood. Psychological Bulletin, 98, 219–235. Wilson, E. O. (1980). Sociobiology: The abridged edition. Cambridge, MA: Harvard University Press. Youngstrom, E. A., & Green, K. W. (2003). Reliability generalization of the self-report of emotions across gender, ethnicity, age, and socioeconomic status when using the Differential Emotions Scale. Educational and Psychological Measurement, 63, (Special Issue: Reliability Generalization), 279–295. Zahavi, A. (1991). On the definition of sexual selection, Fisher’s model, and the evolution of waste and of signals in general. Animal Behaviour, 42, 501–503. Zechmeister, E. B., & Nyberg, S. E. (1982). Human Memory: An Introduction to Research and Theory. Monterey, CA: Brooks/Cole Publishing Co. Zuckerman, M. (1999). Vulnerability to psychopathology: A biosocial model. Washington, DC: American Psychological Association.

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Distinct Emotional Experience Avoidance, 22 Approach, and Emotional Experiences Charles S. Carver, Yael E. Avivi, and Jean-Philippe Laurenceau CONTENTS Feedback, Action, and Affect................................................................................................................386 Action ...............................................................................................................................................386 Affect ................................................................................................................................................387 Research Support..............................................................................................................................387 Action Consequences of Affect ........................................................................................................388 Affects Linked to Approach and to Avoidance ................................................................................389 Approach and Avoidance Sensitivities ..................................................................................................389 Issues in Conceptualizing Affect ..........................................................................................................390 Approach-Related Negative Affect ..................................................................................................390 Avoidance-Related Positive Affect ................................................................................................... 391 Relationship-Specific Approach and Avoidance ...................................................................................392 Velocity and Distinct Contributions of Approach and Avoidance ...................................................392 Relationship-Specific Functions? .....................................................................................................393 Closing Comment ..................................................................................................................................394 References .............................................................................................................................................394

Over the past two and a half decades, a broad principle has reemerged with renewed vigor in mainstream psychology. The principle is that two distinct classes of action tendencies serve as the building blocks from which complex behavior arises. Sometimes these are discussed simply as action tendencies: approach and avoidance (or withdrawal). Sometimes they are discussed in terms of the corresponding motivational tendencies: appetitive and aversive. In either case, the argument is that these two sets of tendencies are components, from which grows the complexity of human behavior (Davidson 1998). The reemergence of this principle as a central theme is reflected throughout this volume. The idea that complex behavior reduces to approach and avoidance tendencies is not new, of course. It is implicit, for example, in the two facets of the Freudian

superego. The ego ideal represents desired behaviors, to which the person aspires. The conscience represents behaviors that are forbidden and to be avoided. The idea of approach and avoidance as the building blocks of behavior is not generally attributed to Freud, however. It is more often linked to the writings of Miller and Dollard (1941; Miller, 1944), who viewed approach and avoidance tendencies in terms of gradients. The premise that these two tendencies are building blocks also led, during that period, to the idea that the two tendencies are managed by different structures in the nervous system (Konorski, 1948; Miller, 1944; Schneirla, 1959). In the past 25 years or so, similar themes have gradually reemerged, in a family of theories with roots in neuropsychology, psychopathology, animal conditioning, and psychopharmacology. The theories that make up this 385

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family generally hold that appetitive motivation and approach behaviors are managed by what is variously termed a behavioral activation system (Fowles, 1980; Cloninger, 1987), behavioral approach system (Gray, 1981, 1987, 1990, 1994a,b), behavioral engagement system (Depue, Krauss, & Spoont, 1987), or behavioral facilitation system (Depue & Collins, 1999). Aversive motivation and withdrawal or avoidance behavior are said to be managed by a system that has been called a behavioral inhibition system (Cloninger, 1987; Gray, 1981, 1987, 1990, 1994b) or a withdrawal system (Davidson, 1984, 1988, 1995, 1998). These two broad systems are believed to have partially distinct neural substrates and to exert distinct influences on action. This family of theories is very influential today.

FEEDBACK, ACTION, AND AFFECT The authors of this chapter became interested in approach and avoidance processes by somewhat circuitous paths. The first author has long been broadly interested in the structure of “behavior-in-general.” The second and third authors have been interested primarily in close relationships and some of the factors that contribute to their ongoing dynamics and their success or lack of success. For somewhat separate reasons, we have all come to find ourselves thinking about motivational tendencies to approach and to avoid. For many years the first author has explored a view of the person as a complex organization of self-regulating feedback loops (Carver & Scheier, 1990, 1998, 1999), which is yet another set of ideas with a considerable history (MacKay, 1966; Powers, 1973). Most people who are only vaguely familiar with the concept of a feedback loop probably associate it with descriptions of electromechanical or electronic devices. Those who have passing familiarity with the application of the concept to living systems (but not much more than that) probably think of its application to physiological systems such as those that maintain homeostatic control over blood pressure, body temperature, and so on. The viewpoint that Carver and Scheier have explored over a considerable period is that the structural elements that underlie homeostasis also underlie attempts to attain desired goals.

ACTION In this view, goal pursuit entails having a goal, assessing where one presently stands with respect to that goal, and taking steps to reduce any discrepancy sensed between the present state and the desired state (the goal). These are the functional elements of a discrepancy reducing feedback loop. The operation of the loop is continuous

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and iterative; the process repeats as needed, until there is a match between what is and what was intended. This model can be applied to motor-control goals such as reaching and grasping; it can also be applied to goals that are more abstract (e.g., being honest, being productive, forming a strong relationship). It can be applied to goals that are static; it can also be applied to goals that are moving and evolving targets (e.g., developing a research career, having a sound marriage, raising children to hold the right kind of personal values). Discrepancy reducing feedback processes are essentially approach processes. They represent one kind of meta-theoretical framework for understanding the regulation of actions that involve approach. Although discrepancy reducing loops are the most commonly discussed feedback process, there is also a second kind: discrepancy enlarging loops. These loops act to increase distance from comparison values. The comparison values in this case might be thought of as “antigoals,” values that the system tries not to embody. An intuitive example is a feared or disliked possible self (Markus & Nurius, 1986; Ogilvie, 1987). A discrepancy enlarging loop compares present conditions to the undesired state (the antigoal) and tries to increase the discrepancy between the two. These processes thus create avoidance, escape, or withdrawal. These two kinds of feedback processes differ both in the direction of the resultant effect on behavior (i.e., approach versus avoid) and also in how “directive” they are. That is, discrepancy reducing systems have a particular value as a target. They continue to home in on the target, even if the target is moving. In contrast, discrepancy enlarging systems have no specific aim. Their function is to create distance from the antigoal. Getting away is getting away, no matter what direction the escape happens to take. In living systems, however, the functioning of a discrepancy enlarging process is generally constrained in some way by a discrepancy reducing process. What may begin as purely avoidance often leads a bit later to approach. Thus, an avoidance loop acts to increase distance from the antigoal; at some point an incentive becomes identified and an approach loop begins to engage. Once this happens, the person is simultaneously trying to avoid the antigoal and approach the goal (assuming that both loops remain active). Thus, many cases of active avoidance of a threat also involve approach of an incentive. An example of active avoidance plus approach is the “ought self” (Higgins, 1996). The ought self is a goal to approach, but the person approaches it in order to escape from a source of disapproval. Thus, for example, Higgins and Tykocinski (1992) found that people whose sense of self was dominated by discrepancies between actual self and ought self were focused on the avoidance of negative

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Approach, Avoidance, and Emotional Experiences

occurrences. In contrast, people whose sense of self was dominated by discrepancies between actual self and their ideals were more likely to be striving for affirmative goals. Other research suggests that persons approach the ought self in order to avoid the feared (Carver, Lawrence, & Scheier, 1999). Avoidance blended with approach is also represented in Ryan and Deci’s (1999) concept of introjected values. Introjected values are goals that people try to attain and conform to. However, they try to attain these positive goals in order to avoid feelings of blame or guilt. Thus, although approach is involved, the first and most basic motive in these cases is an avoidance motive: the desire to avoid punishment or self-punishment. Approach and avoidance motives sometimes overlap in achievement-related behavior, as well. This is reflected, for example, in Elliot and Church’s (1997) hierarchical model of achievement motivation (for review see Elliot, 2006). People with a strong motive to avoid failure are energized at the core by an avoidance process. Yet sometimes this leads to the engagement in approach processes. Thus, these individuals prevent themselves from failing by actively pursuing success.

AFFECT Feedback functions can exist in many different forms. Carver and Scheier (1990, 1998) have also used the feedback principle to make an argument about processes that underlie affect. Affect refers to the subjective experience of valence, the experience of positivity or negativity arising from a particular experience (Russell & Carroll, 1999). In many ways affect is the heart of emotion, though the term emotion often incorporates connotations of physiological changes that frequently accompany hedonic experiences. The Carver and Scheier argument was that the subjective experience of affect reflects the error signal (the detection of a discrepancy) in a layer of feedback systems that exists in parallel to the systems that manage action. The function of the second layer is to monitor, and ultimately influence, how well the first layer (the organization of behavioral loops) is doing at moving the person toward desired goals and away from threats. The affect-related loop has the same structural elements as the behavioral loop, but it has a different kind of reference value. Carver and Scheier suggested that the affect loop has as its criterion a rate of progress occurring in the behavioral loop. The criterion rate is compared to the sensed rate of progress of the behavior system, and the result (the “error” between the two) is experienced as affect. Behavioral discrepancies can exist in numerous ways. For example, when reaching for an object, one may reach

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too high, too low, too far to the right, too far to the left, not far enough from one’s body, etc. A loop that monitors rate, however, can in principle detect only two sorts of discrepancies. The sensed rate can be above the criterion or below the criterion. If the rate of goal-related progress is below the criterion, the second system’s error signal is experienced as negative affect. If the rate is exactly at the criterion, the person is affect-free, because the error signal is zero. If the rate exceeds the criterion, the error signal is experienced as positive affect. In essence, this theory holds that positive feelings mean that you are doing better at something than you need to (or expect to), and negative feelings mean that you are doing worse than you need to (or expect to; for broader discussion see Carver, 2003; Carver & Scheier, 1998, chapters 8 and 9). This view on affect rejects the idea that affect arises purely from attainment of a goal per se. Instead, it emphasizes the idea that progress toward goals across time is computed continuously while the person is engaged in goal-directed behavior. This position allows for the existence of affect to exist while the person is on the way to goals. Indeed, it allows for continually varying hedonic experiences (negative to positive and back and forth again), while the goal-directed behavior plays out over time.

RESEARCH SUPPORT There is now at least a modest accumulation of evidence to support the idea that affect follows this rate or velocity function. For example, Hsee and Abelson (1991), who came to this hypothesis independently of Carver and Scheier (1990), presented laboratory participants with hypothetical scenarios depicting a desirable outcome, in this case improvement in class standing. They held constant the amount of change (a shift from 30th to 70th percentile), and varied the amount of time in which it occurs. The outcome of interest was levels of satisfaction or dissatisfaction with the outcome displayed. Participants expressed more satisfaction when improving to a high outcome than when having a constant high outcome; they expressed more satisfaction after reaching a given outcome at a fast velocity than after reaching the same outcome at a slow velocity; and they expressed more satisfaction after a change involving a high velocity over a short distance than after a change involving a lower velocity over a greater distance. All of these effects appear to indicate the involvement of a velocity function in affect. Negative changes in this research showed a similar link between velocity and affective potency. That is, participants were more satisfied with a constant low salary

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than with a salary that dropped from higher to the same low level; they were less dissatisfied after slow drops than after fast drops; and they were less dissatisfied after an extended, gradual drop than after a small, fast drop. The velocity effect was also replicated in a study in which participants watched a graphic simulation of changes in the price of a hypothetical stock. Participants preferred a fast velocity when the outcome was improving and a slow one when the outcome was declining. Lawrence, Carver, and Scheier (2002) tested the velocity effect in personal experience, rather than hypothetical situations. They manipulated participants’ perceptions of progress toward an actual goal. Participants engaged in a task that was disguised as measure of social intuition. In reality, the task was simply an opportunity to provide false feedback of doing well or doing poorly. Participants received performance feedback after each of six 10-trial blocks. All received the same final total score: 50% accuracy. However, for some people, scores increased over blocks; for other people, scores decreased over blocks; and for other people, scores were stable across blocks. Increases in rate of perceived success over time predicted positive changes in mood; decreases in perceived success over time predicted negative changes in mood. Thus, mood change related to changes in how well things were going. Indeed, it is noteworthy that the total number of successes experienced by people with downward trajectories by the time of the mood rating was greater than the total number of successes experienced by people with upward trajectories. Yet the mood of the former was worse than the mood of the latter. Presumably this was due to the difference in trajectories. Another study bearing on the velocity hypothesis was conducted by Brunstein (1993). In it, undergraduates reported subjective well-being over the several months of an academic term, as a function of various goal-related perceptions, including goal progress. At the beginning of the semester, participants listed six long-term goals. At subsequent assessments (4, 10, and 14 weeks later), participants rated progress toward these goals and their subjective well-being. Perceived progress at each assessment was positively and strongly correlated with concurrent well-being. Greater progress was additionally related to greater subsequent well-being. A later study refined this picture, by taking into account individual differences in participants’ motive dispositions and how those dispositions related to participants’ goals (Brunstein, Schultheiss, & Grässmann, 1998). In this study, participants’ goals were separated into those that were congruent with their dominant motives and those that were incongruent with those

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motives. Greater progress toward motive-congruent goals related to better emotional well-being, as one might expect. However, having greater progress toward goals that did not fit with the person’s core motives did not relate to better emotional well-being. Results that are conceptually similar to all of these emerged from a study of female fibromyalgia patients (Affleck et al., 1998). Patients made reports of their progress on social-interpersonal goals from one day to another. These daily ratings of progress toward social goals were positively associated with increases in positive mood and decreases in negative mood, controlling for that day’s levels of pain and fatigue.

ACTION CONSEQUENCES OF AFFECT Let us return to the idea that affect reflects the error signal in a feedback loop. If this were so, then affect would be a signal to adjust one’s rate of progress. That is, if the input function of the affect loop is a sensed rate of progress in action, the output function must be a change in rate of that action. Thus, the affect loop has a direct influence on what occurs in the action loop. This view thus implies a natural link between affect and action, a theme that is very congruent with contemporary views of emotion (Frijda, 1986, 1988). Negative feelings imply a rate that is too low. Consistent with theory, the first response to negative feelings usually is to try harder. If trying harder (or trying “smarter”) does increase progress, the result is that the negative feeling goes away. Some increases in rate output are straightforward. If you are lagging behind at something, you may be able to speed up. Sometimes the changes are less straightforward. The rates of many “behaviors” are defined not by a pace of physical action but in terms of choices among potential actions, or entire programs of action. For example, increasing your rate of progress on a project at work may mean choosing to spend a weekend working rather than going to the beach. Increasing your rate of being kind means choosing to do an action that reflects that value when an opportunity arises. Thus, adjustment in rate must often be translated into other terms, such as concentration, or allocation of time and effort. For negative feelings, this principle seems completely intuitive. What this view predicts for positive feelings, however, is counterintuitive to many people. In this view, positive feelings arise when things are going better than they need to. This view argues that people who exceed the criterion rate of progress (who have positive feelings) will ease back on subsequent effort in this domain. They are likely to

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“coast” a little (cf. Frijda, 1994, p. 113)—not necessarily stop, but ease back such that subsequent rate of progress returns to the criterion. Although this hypothesis is interesting, it has not been much studied, and it is not addressed further here (see Carver, 2003, for further discussion). The existence of two feedback systems functioning in concert with one another turns out to be quite common in an application of feedback concepts that is quite different from the one now under discussion. This other application is the literature of control engineering (Clark, 1996). Engineers have long since found that having two feedback systems working together—one controlling position, one controlling velocity—permits the device in which they are embedded to respond in a way that is both quick and stable (i.e., prevents overshoots and oscillations). The combination of quickness and stability in responding is valuable in the kinds of devices that engineers deal with, but its value is not limited to such devices. A person with very reactive emotions is prone to overreact, and oscillate behaviorally. A person who is emotionally unreactive is slow to respond even to events where there is great urgency. A person whose reactions are between the two extremes responds quickly but without undue overreaction and oscillation. For biological entities, being able to respond quickly yet accurately confers an adaptive advantage. This combination of quick and stable responding may be a consequence of having both behavior-managing and affect-managing control systems. Affect causes responses to be quicker (because this control system is time sensitive) and as long as the affective system is not over-responsive, the responses are also stable. It is also of interest that the behavioral responses that are presumed to be linked to the affects would also lead ultimately to reduction of the affects. Thus, the affect system seems to be, in a very basic sense, a self-regulating system (cf. Campos, Frankel, & Camras, 2004).

AFFECTS LINKED TO APPROACH AND TO AVOIDANCE Recall our starting point: the idea that there exist both approach and avoidance behavioral systems. Presumably both approach and avoidance can give rise to the experience of affects. The Carver and Scheier (1990, 1998) view holds that positive affect results from doing well and negative affect from doing poorly. Certainly it is possible to do either well or poorly at either approach or avoidance. But doing well at moving toward a desired goal is not precisely the same experience as is doing well at moving away from a threat (see also Elliot & Sheldon, 1997). Doing poorly at attaining a desired end is not the same experience as is doing poorly at escaping a punishment.

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Relying in part on insights from Higgins and his collaborators (reviewed, for example, in Higgins, 1996, 1997), Carver and Scheier (1998) argued that affective experiences can be organized along two bipolar dimensions. One dimension is generated by affect loops that concern approach behavior. It includes elation at one end (when things are going very well) and despair and despondency (when things are going very poorly) at the other end. The second dimension is generated by affect loops that concern avoidance. This dimension includes fear at one end (when things are going poorly) and relief and serenity at the other end (when things are going very well; Roseman, 1984, has expressed a similar view; see also Frijda, 1986, 1988; Ortony, Clore, & Collins, 1988). This is not the same argument as underlies other depictions involving two dimensions of affect. The best known dual-dimensional model is known by the terms positive and negative affect, or positive and negative activation (Cacioppo, Gardner, & Berntson, 1999; Watson, Wiese, Vaidya, & Tellegen, 1999). That theoretical view argues for two unipolar dimensions, one of which is grounded in approach, the other in avoidance. The Carver and Scheier view, in contrast, argues for two bipolar dimensions. This difference, which may at first seem subtle and minor, is in fact quite important. This issue is addressed in greater detail a bit later on.

APPROACH AND AVOIDANCE SENSITIVITIES Having noticed the general resemblance between two kinds of feedback loops (discrepancy reducing and discrepancy enlarging) and two classes of motives (appetitive and aversive), Carver and Scheier and some of their colleagues became interested in how deeply intertwined these two sets of ideas might be. Gray (1981, 1987, 1990, 1994a,b), Fowles (1980), and a number of others (Depue & Iacono, 1989), had pointed to the potential importance of individual differences in the functioning of appetitive and aversive motivational systems. One obvious path for study, then, was individual differences. It seems reasonable to suggest that people vary in the sensitivity or the strength of these broad motivational systems. Some people by nature are readily engaged in active pursuit of whatever incentives arise (e.g., an upcoming social event, an unexpected opportunity for professional gain); others are less drawn to them. Some people by nature are vigilant to the possibility of threats or dangers in the environment (e.g., criticism or punishment for mistakes, dimly lit parking lots); others are less responsive to this sort of cue. If the neurobiological systems that manage approach and avoidance are independent in

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their sensitivities, then individual differences in responsiveness to incentive and threat will also be independent, yielding all combinations of highs and lows. Drawing on the literature pertaining to this family of biobehavioral theories, Carver and White (1994) devised a set of self-report measures that they called the BIS/BAS scales. These scales reflect the self-rated sensitivity of the behavioral approach system and behavioral inhibition (or withdrawal) system. In their initial validation research, Carver and White found that people higher in BAS sensitivity (but not BIS sensitivity) reported larger increases in happiness in response to a rewarding outcome. They also found that people higher in BIS sensitivity (but not BAS sensitivity) reported larger increases in anxiety in response to a threat. These findings were exactly as would be expected from the biological models of appetitive and aversive motives from which the scales were designed. That is, a person with a highly sensitive approach system should experience more positive affect than a person with a less sensitive approach system, given cues of reward, but this variable should not influence responses to cues of threat. In the same way, a person with a highly sensitive avoidance system should experience more anxiety than a person with a less sensitive avoidance system, given cues of threat, but this variable should not influence responses to cues of reward. The BIS/BAS scales have proven useful for a wide variety of potential research applications. They have, for example, been used to examine views of personality in which approach and avoidance are considered to be the driving forces behind the trait dimensions of extraversion and neuroticism (Carver, Sutton, & Scheier, 2000; Carver & White, 1994; Elliot & Thrash, 2002; Zelenski & Larsen, 1999). They have also been linked to several aspects of psychopathology (Johnson & Carver, 2006; Johnson, Turner, & Iwata, 2003; Meyer, Johnson, & Carver, 1999; Meyer, Johnson, & Winters, 2001).

ISSUES IN CONCEPTUALIZING AFFECT A particularly interesting application of the BIS/BAS scales is the use of them to investigate whether a given phenomenon pertains to approach or to avoidance. A measure of BAS and BIS sensitivities would seem to represent a very useful methodological tool for such investigations. BAS and BIS sensitivities can be assessed and then related (separately) to any behavioral or experiential phenomenon that might be of interest. If the phenomenon actually derives from functioning of the avoidance system, it should relate to individual differences in BIS

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sensitivity. If the phenomenon actually derives from functioning of the approach system, it should relate to individual differences in BAS sensitivity. Thus, individual differences can be used to shed light on broad principles about general phenomena (cf. Underwood, 1975).

APPROACH-RELATED NEGATIVE AFFECT This strategy has been used to examine the roots of two negative affects about which there has been disagreement: sadness and anger (Carver, 2004). As noted earlier, disagreements exist about the dimensionality of affect. One widely held view is that there is a dimension of positive affect and a separate dimension of negative affect. Each of these dimensions is unipolar, ranging from absence of that affect to intense experience of that affect. This view has a number of theoretical sources. For example, Gray (1981, 1990, 1994b) held that the BIS is engaged by cues of punishment and by cues of frustrative nonreward. He thus saw BIS as responsible for negative feelings in response to either of these sorts of cue. Similarly, he held that BAS is engaged by cues of reward or of escape from (or avoidance of) punishment. He thus saw BAS as responsible for positive feelings in response to such cues. Gray’s view thus was one in which each system is responsible for affect of one hedonic tone (positive for BAS, negative for BIS). A similar position has long been taken by Watson, Tellegen, and their colleagues, first with respect to moods (Watson & Tellegen, 1985) and more recently with respect to affects with more focused origins (Watson et al., 1999). In recent years this viewpoint has increasingly pointed to neurobiological theories of motivation and action (Davidson, 1998; Fowles, 1993; Gray, 1994a) that appear to provide a conceptual basis for why these dimensions are fundamental (Watson et al.). That is, each dimension is now linked explicitly to a category of motives: appetitive and aversive. Other theorists in personality and social psychology and related areas have also taken similar positions (Cacioppo et al., 1999; Lang, Bradley, & Cuthbert, 1998). In contrast to this position, the Carver and Scheier (1998) analysis, described earlier, assumes two bipolar dimensions. More specifically, Carver and Scheier argued that certain negative affects arise when an approach process is doing poorly at attaining its goals. The affects in question are sadness, frustration, and anger. If this were so, it should follow that the intensity of those negative affects under conditions that normatively evoke them would relate to individual differences in BAS sensitivity. Specifically, greater BAS sensitivity should lead to greater intensity of these affects. If, however, all negative affects

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have their roots in the BIS, that should not happen. Instead, stronger experiences of those negative affects should all relate instead to greater BIS sensitivities. It is of particular importance here that all items of the BAS scales focus on affective and behavioral responses to the presence of incentive cues. More specifically, BASrelated items describe positive emotional and behavioral reactions to three aspects of the possibility of obtaining incentives (being motivated to seek them, being persistent in pursuit of them, and having positive feelings when obtaining them). No BAS item refers in any way to an adverse event, nor is there any hint of negative affect in the content of any BAS item. The opposite is true of BIS items. Each references a threatening event, and assesses emotional responsiveness to the threat. On the basis of the semantic content of the items, then, there should be a bias toward linking of BIS items to reports of adverse affective experiences. These competing theories were tested in three studies (Carver, 2004). In Study 1, participants were led to believe that by performing well at a laboratory task they could obtain bonus credits toward a course requirement. However, they were all caused to perform at a level that failed to yield the bonus credits. Under these conditions of frustrative nonreward, reports of being sad and frustrated related significantly and positively to Fun seeking, a BAS scale. They did not relate significantly to the BIS scale. In Study 2, participants imagined themselves in three hypothetical scenarios. All were written to be anger-eliciting and also potentially anxiety-eliciting at the same time. Reports of the feeling that would be experienced in those situations were aggregated into those pertaining to anger and those pertaining to nervousness. Nervousness related positively to BIS sensitivity, as would be expected

Affect:

Blissful

on the basis of all of the theories under study. In contrast, anger related positively to Reward responsiveness, a BAS scale, but only weakly to BIS. In Study 3, conducted within two weeks of the terrorist attacks of September 2001, participants were asked to report their feelings about the events of that day. Levels of fear related positively to BIS sensitivity, as expected. Greater anger related to greater Reward responsiveness and Drive, both BAS scales. It appears from these results, and others reviewed in that article, that certain negative affects do indeed relate to inadequacy of approach. These findings are not consistent with a view in which all negative affects relate to a dimension of avoidance motivation. Clearly anger and sadness are different from each other, and a theoretical model that places both of them on the same dimension should also be clear about their relationship to each other and to the approach function more generally. It has been argued that a key issue here is a variable that has not been considered thus far in this chapter: the extent of the person’s confidence of being able to bring the desired rate back to the criterion (Figure 22.1; see Carver, 2004, for detail). Anger appears to be aimed at regaining lost ground. Implicit in that affect is a degree of confidence of being able to regain that ground. Sadness appears to imply that the effort seems pointless, the opportunity lost, the reward gone. Yet, despite these very real differences, it seems possible to relate both of these qualities to the function of approaching (or failing to approach) desired ends.

AVOIDANCE-RELATED POSITIVE AFFECT Most work that compares these two dimensional positions to each other has examined negative affects that

Happy

Delighted

Eager

Frustrated Angry

Dejected Sad

Despondent

Extent of engagement or effort

Above

Criterion

Below

FIGURE 22.1 Hypothesized approach-related affects as a function of doing well versus doing poorly compared to criterion velocity. A second (vertical) dimension indicates the degree of behavioral engagement posited to be associated with affects at different degrees of departure from neutral. Adapted from “Negative affects deriving from the behavioral approach system,” by C. S. Carver, 2004, Emotion, 4, p. 3.

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Carver and Scheier argued should relate to approach. However, there is at least a little information concerning the other prediction that differs between the theories: that some positive affects should relate to an avoidance motivational tendency. One such affect is relief. Relief is a positive affect that occurs when a threat is removed. The removal of a threat would seem to be an indication that avoidance of the threat is going very well. Recall that Gray (1990, 1994b) held that BAS is engaged both by cues of reward and by cues of escape from (or avoidance of) punishment. The latter is the circumstance that should induce relief. In contrast, the Carver and Scheier (1998) model holds that relief should occur when avoidance is going well—as when a threat disappears. These contrasting predictions have now been tested in two studies (Carver, in press). Participants in both studies were asked to imagine themselves in hypothetical scenarios, some of which were written to be relief-eliciting. Participants then rated how they would feel in those situations, along several dimensions, including relief. These ratings then were related to participants’ BIS/BAS scores obtained previously. In both studies, greater relief was related most strongly to greater BIS sensitivity. Relations with BAS scales were mixed. Greater relief related to greater Reward responsiveness but also to lower Fun seeking. These results appear to offer at least some support for the existence of a bipolar affective dimension relating to avoidance.

RELATIONSHIP-SPECIFIC APPROACH AND AVOIDANCE Given these arguments—separate approach and avoidance functions, separate affective consequences of doing well and doing poorly at approach and avoidance—how far can they be extended? One emerging frontier for extending all of these themes is the domain of social and intimate relationships (Gable, 2006). The experience of emotion is certainly a core element in the functioning of such relationships (Berscheid, 1983). Given the arguments outlined earlier in this chapter, we would expect approach and avoidance processes to play separate roles in how such relationships are experienced. We would also expect the roles to differ from one another in important ways. Let us consider close relationships, in particular, from this view. What goals do people have in close relationships? One relationship goal that has been noted repeatedly in the literature is intimacy (Peplau & Gordon, 1985; Reis, 1990; Reis, Senchak, & Solomon, 1985), the feeling of connectedness with another person (Laurenceau, Rivera, Schaffer, & Pietromonaco, 2004). Many regard

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this connection as a universal human need (Baumeister & Leary, 1995; Ryan & Deci, 2000). People in romantic relationships try to maintain desired levels of intimacy, by self-disclosing to their partner and by conveying a sense understanding and responsiveness toward their partner (Laurenceau, Barrett, & Pietromonaco, 1998; Laurenceau, Barrett, & Rovine, 2005; Reis & Shaver, 1988). The goal of intimacy is sufficiently important that it presumably is always active at some level in the minds of people who are in romantic relationships, thereby influencing their experiences (Fitzsimons & Bargh, 2003). Not all reference values that pertain to close relationships are desired conditions, however. Some are conditions to avoid—threats rather than incentives. An obvious threat in relationships is conflict, or interpersonal pain (Simpson, Oriña, & Ickes, 2003). Guerrero and Andersen (2000) suggested that each person has a level of relationship conflict that is intolerable, and that this represents a feared state to avoid. Indeed, conflict is so salient a factor in relationships that it is often taken as the main indicator of relationship functioning (Fincham & Beach, 1999). Although conflict and (loss of) intimacy are related, they are not simply opposite ends of a single dimension. Intimacy is an incentive; conflict is a threat. In the same way, people have social motives that are broader than those that pertain to intimate relationships per se (Elliot, Gable, & Mapes, 2006; Gable, 2006). People have the desire to affiliate with other people and the desire to avoid rejection from others. The former is an approach motive, the latter is an avoidance motive. These motives pertain to social relations with friends and acquaintances, as well as with intimate others. As we shift our attention here from the more general conceptual statement on approach and avoidance to the context of relationships, at least three issues arise. One of them is whether the velocity principle pertains to the relationship domain. A second issue is whether approach and avoidance motives relate to distinct affective experiences in the relationship domain, as they do in other domains. A third issue is whether approach and avoidance tendencies in relationships differ in any important way from more general tendencies toward approach and avoidance. At least some information is presently available pertaining to each of these issues.

VELOCITY AND DISTINCT CONTRIBUTIONS OF APPROACH AND AVOIDANCE Let us consider first the velocity principle. The velocity idea has been applied to the relationship context in several places. For example, Baumeister and Bratslavsky

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(1999) reviewed indirect evidence suggesting that rapid increases in intimacy relate to positive emotions such as passion. They suggested that passion is a function of the rate of change in intimacy over time. Thus, passion should not derive only from the current level of intimacy, but from the rate with which intimacy changes. The notion of rapid change in intimacy has been similarly discussed in terms of self-expansion (Aron & Aron, 1986; Aron, Norman, & Aron, 2001), with rapid expansion yielding the feelings associated with falling in love. Several studies have produced evidence that bears fairly directly on this issue. For example, Karney and Frye (2002) found that married couples evaluate their happiness, or their satisfaction with the relationship, more on the basis of perceptions of recent improvements than from perceptions of the quality of the relationship at that particular time. Karney and Bradbury (1997) also found that decreasing satisfaction over time (compared to low initial satisfaction) predicted dissolution of relationships over a period of 4 years. Another recent study investigated romantic partners using a daily diary methodology (Laurenceau, Troy, & Carver, 2005). Participants used electronic devices to record perceived levels of, and perceived changes in, both intimacy and conflict twice daily over 10 consecutive days. Perceived increases in intimacy related to positive affect (passion and excitement) above and beyond perceptions of current intimacy (which also related to positive affect), among both male and female partners. Perceived increases in conflict related to anxious affect above and beyond perceptions of current conflict (which also related to anxiety), but only among males. These findings pertaining to perceptions of change are consistent with the velocity principle. The findings from this study also indicated that the approach and avoidance tendencies made distinct contributions to participants’ affective experiences in the relationship. That is, it was only perceptions of increased intimacy (i.e., approach of a desired state) that related to positive, intimacy-related emotions. Perceptions of conflict played no role in those emotions. The complementary pattern occurred for feelings of anxiety. It was only perceptions of increased conflict (i.e., avoidance going poorly) that related to anxiety. Perceptions concerning intimacy played no role in that emotion. Another project that bears on the velocity principle (though not the separation of approach and avoidance) was reported by Avivi, Laurenceau, and Carver (2007). This research examined one sample of dating couples in a cross-sectional design and followed a second sample of committed romantic couples in a longitudinal design. As

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in the Laurenceau, Troy, and Carver (2005) project, participants rated their perceptions of progress toward goals. In this case, however, it was the perception of progress toward goals that were perceived as being shared by both members of the couple. These perceptions of goal progress again related to a relationship-related outcome: in this case, perceptions of the relationship’s quality.

RELATIONSHIP-SPECIFIC FUNCTIONS? Another issue that arises when shifting the focus to the domain of close relationships is whether there is something special about this class of goals. When Carver and White (1994) developed their measure of the sensitivity of people’s approach and avoidance systems, they intentionally created a very general measure. It was intended to apply to all sorts of incentive and threat situations. At that point, it had not occurred to them that there might be reasons for distinguishing among behavioral domains. However, neurobiological evidence suggests that there may be social incentive and threat systems, which are partially overlapping but also partially separate from the more general appetitive and aversive systems (Depue & Morrone-Strupinksy, 2005; Panksepp, 1998). Thus, there may be individual differences in specialized sensitivities to incentives and threats within the domain of intimate relationships. The global BIS/BAS scales do not focus on close relationships as specific sources of incentives and threats. As a result, they may lack sensitivity in predicting behaviors and outcomes that are relationshipspecific. If these theoretical ideas have any substance, what would be needed is a more focused measure of incentive and threat sensitivities, aimed specifically at close relationships. At least two groups of researchers have begun to address this issue. Elliot et al. (2006) developed a measure intended to assess social approach and avoidance goals in friendships. They found that higher levels of the desire for affiliation predicts greater adoption of friendship-related approach goals, and that higher levels of fear of rejection predicts greater adoption of friendshiprelated avoidance goals. The holding of those goals, in turn, predicted subjective well-being and physical symptoms. Adoption of approach goals led to greater subjective well-being, and adoption of avoidance goals led to greater levels of physical symptoms. In another project, Kleinman, Kaczynski, Laurenceau, and Carver (2007) developed a set of self-report scales intended to measure relationship-specific incentive and threat sensitivities. They called this measure the RAp/ RAv scales (standing for relationship approach and

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relationship avoidance). The focus of this measure is somewhat different from that of Elliot et al. in two respects. First, the Kleinman et al. (2007) scales target intimate relations in particular, whereas the Elliot et al. scales target friendships. Second, the RAp/RAv scales are aimed at assessing sensitivities of postulated focused incentive and threat systems, whereas the Elliot et al. measure assesses the holding of goals (though they also supplemented that measure with measures of motives for affiliation and fear of rejection in some research). It remains to be seen whether the two new measures will prove to differ from each other in their focus of convenience, or will instead overlap in their prediction of relevant outcomes. The RAp/RAv items were modeled on the items of the BIS/BAS scales, but each new item refers explicitly to the respondent’s close relationship. The new scales have a reasonably sound factor structure, and there is also evidence of convergent and discriminant validity (Kleinman et al., 2007). Kleinman et al. (2007, Study 4) have also used these scales to predict the affective reactions of newlyweds after they engaged in two relationship-focused tasks. The first task was a pair of 12-min conversations about each of two topics identified by the couple as being sources of marital conflict. The second task was a conversation about the couple’s positive feelings for each other. The outcomes of interest were the levels of anxiety reported after the conflict task and positive affect reported after the positive task (both adjusted for the respective baseline affect). Among wives, RAp scores related to greater positive affect after the positive conversation task and did not relate to anxiety after the conflict conversation task. RAv scores related to greater anxiety after the conflict task and did not relate to positive affect after the positive task. Of particular interest, this pattern of associations remained, even after controlling for BIS and BAS scales. Among husbands, the results were somewhat less clearcut. Husbands’ RAp scores predicted positive affect after the positive conversation. Contrary to prediction, however, husbands’ RAv scores did not significantly predict anxiety after the conflict conversation, after controlling for baseline affect. Again, these relationships remained unchanged after controlling for the BIS and BAS scales. Initial investigations thus suggest the potential usefulness of the RAp/RAv scales in predicting relationshiprelated outcomes. Moreover, these scales predicted the outcomes even when taking into account global incentive and threat sensitivity, in the form of the BIS/BAS scales. Thus, this research suggests that there may be considerable merit in distinguishing global approach and avoidance

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sensitivities from more focused approach and avoidance sensitivities. Many questions about this latter issue remain to be examined. For example, this pattern of results may simply represent a specific case of a more general principle concerning the breadth versus narrowness of psychological constructs. That is, attitudes and expectancies typically predict other outcomes better if they are at the same level of abstraction as the other outcome than if they are not. In the same way, a measure of sensitivities to relationship incentives and threats may be better predictors of relationship outcomes than a measure of broader sensitivities purely because it is at the right level of specificity. Alternatively, it may be the case that there is something unique about relationship functioning, which gives it a kind of privileged status in the neurobiology of behavior and emotion (cf. Carter, 1998; Young & Wang, 2004). These are issues that will take time to sort out.

CLOSING COMMENT It seems clear that approach and avoidance functions are deeply embedded in the nature of human personality (Zuckerman, 2005). It also seems clear that these functions—each of which in itself is fairly simple—can lead to great complexity. In this chapter we have described multiple ways in which these functions have emerged in our own thinking and research efforts. As noted earlier, our interest in these functions as building blocks of behavior arose as a function of our interest in other constructs. Yet pursuit of those other constructs led us to undertake a closer consideration of approach and avoidance. We believe that these conceptual principles are extremely useful as organizing themes for theory development, and that they thus will continue to be central figures in psychology for a good long time.

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Anger and Approach–Avoidance 23 Anger Motivation Eddie Harmon-Jones, Carly Peterson, Philip A. Gable, and Cindy Harmon-Jones CONTENTS Anger as an Emotion .............................................................................................................................400 Causes of Anger ....................................................................................................................................400 Reinforcement Approaches ..............................................................................................................400 Cognitive Appraisal Approaches......................................................................................................401 Motivational Components of Anger: Subjective and Behavioral Evidence ..........................................402 Motivational Components of Anger: Asymmetrical Frontal Cortical Activity ....................................404 Baseline EEG and Individual Differences .......................................................................................404 Baseline EEG and Responses to Emotion-Eliciting Stimuli ............................................................404 EEG Activity During Emotional Situations .....................................................................................405 Explanations of the Asymmetrical Frontal Brain Activity and Emotion Relationship ...................405 Subjective Feelings Associated With Anger .........................................................................................408 Relationship to Other Emotional Experiences .................................................................................409 Conclusion .............................................................................................................................................409 Acknowledgment ................................................................................................................................... 410 References ............................................................................................................................................. 410

“Anger is a great force. If you control it, it can be transmuted into a power which can move the whole world.”— William Shenstone (Scottish Writer, 1714–1763) “Anger and jealousy can no more bear to lose sight of their objects than love.”—George Eliot (English Writer, 1819–1880)

Contemporary theories of motivation and emotion assume that positive emotions are associated with approach motivation and that negative emotions are associated with withdrawal motivation. For instance, Watson and colleagues wrote, “…accumulating evidence suggests that the self-report NA [negative affect] dimension represents the subjective component of the withdrawal-oriented BIS… In contrast, variations in self-rated PA [positive affect] reflect

the operation of the BFS [behavioral facilitation system]” (italicized information added; Watson, Wiese, Vaidya, & Tellegen, 1999, p. 830). These and similar theories (Lang, 1995) have been very influential in contemporary psychology and have led to important advances in understanding basic processes involved in emotion and motivation, the physiological and neural underpinnings of emotion and motivation, and disorders of emotion and motivation. At the same time, the assumption that positive emotions are always associated with approach motivation and that negative emotions are always associated with withdrawal motivation can be misleading. For the emotions of fear and disgust, the assumption that these negative affects are exclusively associated with avoidance motivation is tenable. Both fear and disgust 399

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impel the organism to flee from the source of the threat. In contrast, anger violates the association of negative affect and avoidance motivation. Instead of motivating avoidance, anger often motivates approach, causing the organism to go toward the threat. Less research has been conducted on anger than on other negative affects by scientists who study emotion. However, past research by scientists who study aggression and other behavioral phenomena has suggested that anger may be associated with approach rather than avoidance motivation. In this chapter, we will review the evidence on the motivational functions of anger.

ANGER AS AN EMOTION Emotions can be considered processes that involve involuntary action readiness (Frijda, 1986). Basic emotions, such as anger, provide organisms with relatively complex and biologically prepared behavioral potentials that assist in coping with major challenges to their welfare (Panksepp, 1998). However, for organisms with larger, more complex brains, these inherited behavioral potentials only suggest ways of behaving. Emotions can be regulated and thus may not directly affect behavior. Thus, while humans may possess the same emotional instincts as lower animals, we are not as controlled by the dictates of emotions and thus we have more choices (Panksepp, 1994). An emotion is not a “thing” but is best considered a complex process that is made up of basic processes such as feelings of pleasure or displeasure, facial expression components, particular appraisals, and particular action plans and activation states (Frijda, 1993). Anger is a relatively unpleasant feeling, and is described using words like annoyed, angry, and enraged, which in our view, express differences in intensity (cf., Lewis [1993]; however, suggested that rage and anger are qualitatively different). When left uncontrolled or uninhibited, its facial expression involves the muscles of the brow moving inward and downward, thus “creating a frown and a foreboding appearance around the eyes, which seem to be fixed in a hard stare toward the object of anger. The nostrils dilate and the wings of the nose flare out. The lips are opened and drawn back in a rectangle-like shape, revealing clenched teeth. Often the face flushes red” (Izard, 1977, p. 330). Because humans are taught to control anger and its expression, the expressions of anger vary considerably from one person to another. In this chapter, we will review recent research and theoretical advances in the study of basic processes involved in anger. We will focus our review on the causes of anger,

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its subjective feeling and motivational components, and some of its neural components. In doing so, we will consider all of the component processes typically involved in anger—its feelings, appraisals (under causes), action plans and activation states (under motivation), and physiology. However, we will not review the literature on angry facial expressions, as it is beyond the scope of this chapter (for a review, see Russell & Fernández-Dols, 1997).

CAUSES OF ANGER Anger is often thought to result from physical or psychological restraint or from interference with goal-directed activity (Darwin, 1872; Izard, 1977; Lewis, 1993). This action-oriented approach to understanding the cause of anger is consistent with postulations advanced by other major theoretical perspectives.

REINFORCEMENT APPROACHES Neo-behaviorists suggested that the actual or signaled arrival or termination of pleasant or unpleasant events (positive or negative reinforcers) was the primary cause of emotions (Mowrer, 1960). Gray (1987) extended these ideas by including stimulus omissions and interactions with individuals’ resources, such as ability to deal with events (see also, Rolls, 1999). According to these models, angry emotions (like frustration, anger, and rage) occur as a result of the omission of a positive reinforcer or the termination of a positive reinforcer. Along these lines, Lewis (1993) proposed that the thwarting of a goal-directed action is an unlearned cause of anger. In one experiment, after 2- to 8-month-old infants were conditioned to move one of their arms in order to see a picture of another baby’s smiling face, the infants were exposed to an extinction phase in which the arm movement no longer revealed the happy picture. This “frustrating” event caused the majority of the infants to exhibit anger-like facial expressions (Lewis, Alessandri, Sullivan, 1990). Similarly, in considering the causes of anger, Berkowitz (1989) extended the original frustration-aggression model (Dollard, Doob, Miller, Mowrer, & Sears, 1939) with a cognitive neo-associative model of anger and aggression. According to this model, any unpleasant situation, including pain, discomfort, frustration, or social stress, provokes negative affect. This negative affect is associated with fight and flight motivation. The individual’s prior experiences have formed associations that provide cues relating to the present situation. If these cues lead him or her to desire primarily to escape, then the flight system is activated and the person experiences mostly fear. If the cues

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Anger and Approach–Avoidance Motivation

lead him or her to desire to attack, then the fight system is activated and he or she experiences mostly anger.

COGNITIVE APPRAISAL APPROACHES The other main theoretical approach aimed at understanding the causes of anger is the cognitive approach taken by appraisal theorists. These theorists propose that emotions are caused by an individual’s appraisal of a situation. All appraisal theorists agree that anger is evoked in negatively appraised situations. However, negatively appraised situations are associated with all of the emotions considered to be negative, including fear, sadness, and anger. Therefore, appraisal theorists have sought the necessary conditions required in order to cause anger, rather than a different negative emotion, to be evoked. Anger-evoking situations are often described as situations where the individual’s goals are blocked. To clarify what is meant by “goals,” some theorists state that the instigating circumstance must be evaluated as personally significant in some way, so that it has goal relevance, if there is to be an angry reaction (Lazarus, 1991). Goals are defined very broadly by some researchers, including not only consciously sought goals, but also basic needs. One condition that has been proposed as necessary for anger to occur is an appraisal of “other-blame,” that is, an assessment by the individual that someone or something has wrongly caused the negative situation to occur (Lazarus, 1991; Ortony, Clore, & Collins, 1988). Another condition proposed to cause anger is an appraisal that the negative event was wrong, unfair, or improper (Shaver, Schwartz, Kirson, & O’Connor, 1987; Frijda, Kuipers, & ter Schure, 1989; Roseman, 1991). Lazarus proposed that, in order for anger to occur, the individual must perceive a threat against self-esteem (Lazarus, 1991). Another characteristic that appraisal theorists have proposed as necessary for anger is an appraisal of high coping potential in the negative situation. By this, they mean that individuals become angry when they believe that they have a high likelihood of being able to rectify the negative situation and to prevent the undesired consequences (Lazarus, 1991; Stein & Levine, 1989). In negative situations where the individual appraises low coping potential, by contrast, these theorists propose that sadness, fear, or anxiety are experienced instead of anger. The idea that anger results from an appraisal that the situation is (a) negative, (b) threatens self-esteem, (c) is caused by others, and (d) is one that we expect to be able to rectify has intuitive appeal. That is, many of us can easily recall instances where we experienced anger and it seemed that the anger resulted from such appraisals.

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However, our intuitions may be wrong. Indeed, the appraisal literature has been criticized for failing to provide evidence as to whether appraisals cause emotion or whether emotion motivates the individual to make appraisals. Frijda (1993; Frijda & Zeelenberg, 2001) and Parkinson and Manstead (1992) have noted that, because of the verbal-report methods employed in most investigations in this area, it is unclear whether the identified appraisal characteristics preceded or followed the arousal of the emotional experience. “Nothing in the data resists the interpretation that the relevant appraisals were consequences rather than precedents of the emotional reactions” (Parkinson & Manstead, 1992, p. 129). Other scientists have questioned the necessity of specific appraisals for anger (Berkowitz & Harmon-Jones, 2004). For example, Berkowitz and Harmon-Jones have argued that once the fight system and anger are activated, the person begins to make appraisals and to do other cognitive processing of the situation, in order to determine who or what to attack, and how or whether to follow through behaviorally with these impulses. This conception differs from the appraisal models in that it proposes that an appraisal of the provoking situation is not necessary in order to produce emotion. According to Berkowitz and Harmon-Jones, appraisals are involved in the experience of anger, but come later in the process, and occur with anger, or are provoked by anger, rather than causing anger. (However, as appraisals occur, they may enhance or alter the emotion process.) Berkowitz’s cognitive neoassociative model better accounts for all of the data, including atypical anger occurrences that do not fit well into models that assume the necessity of self-relevance, goals, and blameworthy behavior by another person. Moreover, appraisal theorists’ definitions of “goals,” “cognitions,” and “appraisals” are sometimes so overly broad that they are untestable (for example, the “goal” of not experiencing discomfort). Regarding the necessity of the appraisal of “otherblame,” it has been suggested that, while other-blame does often occur along with anger, that it is the emotion of anger that motivates the individual to seek someone or something to blame for the negative situation. Fridja (1993) reports a number of instances where angry persons blamed, and even aggressed against, inanimate objects in a way that many would characterize as irrational, lending support to the idea that blaming is motivated by anger rather than the other way around. Lazarus’ claim that self-esteem threats are necessary for anger elicitation has also been questioned. While selfesteem threats may be common in anger-evoking situations, studies have shown that persons sometimes report

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experiencing anger in response to the frustration of transient goals that do not have high personal relevance. Moreover, it is not likely that the 2-month-old infants in Lewis and colleagues’ experiments (1990) were concerned about self-esteem. Finally, the claim that high coping potential is necessary for the experience of anger has recently been challenged by an experiment in which coping potential was manipulated and found to affect cortical activation (see below) but not the subjective experience of anger (Harmon-Jones, Sigelman, Bohlig, & Harmon-Jones, 2003).

MOTIVATIONAL COMPONENTS OF ANGER: SUBJECTIVE AND BEHAVIORAL EVIDENCE Theorists have suggested that anger is an emotion that evokes behavioral tendencies of approach (Darwin, 1872; Ekman & Friesen, 1975; Plutchik, 1980; Young, 1943). Of course, emotions are complex phenomena and both approach and withdrawal tendencies can be elicited in a given situation. However, we believe that the dominant behavioral tendency associated with anger is approach. In the animal behavior literature, a distinction has been made between offensive or irritable aggression and defensive aggression (Moyer, 1976). It has been posited that irritable aggression results from anger and that pure irritable aggression “involves attack without attempts to escape from the object being attacked” (Moyer, 1976, p. 187). A number of aggression researchers have suggested that offensive aggression is associated with anger, attack, and no attempts to escape, whereas defensive aggression is associated with fear, attempts to escape, and attack only if escape is impossible (Blanchard & Blanchard, 1984; Lagerspetz, 1969; Moyer, 1976). In demonstrating that organisms evidence offensive aggression and that this is an approach behavior, Lagerspetz (1969) found that under certain conditions mice would cross an electrified grid to attack another mouse. Other research has demonstrat that damage to the amygdala, a brain region involved in defensive behavior, has no effect on offensive aggression but reduces reactivity to nonpainful threat stimuli (Blanchard & Takahashi, 1988; Busch & Barfield, 1974). Further evidence supporting the conceptualization of anger as involved in offensive aggression comes from research on testosterone, which has been found to be associated with anger and aggression in humans (Olweus, 1986). In this research, testosterone treatments have been found to decrease defensive (fear) responses in a number of species (Boissy & Bouissou, 1994; Vandenheede & Bouissou, 1993). Taken together, these diverse lines of research suggest that

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offensive aggression is associated with different neural systems, hormones, and behaviors than defensive aggression. Moreover, these offensive aggressive behaviors are likely associated with anger (Blanchard & Blanchard, 1984; Moyer, 1976). In research with humans, anger has been found to be associated with attack (Berkowitz, 1993). Moreover, Depue and Iacono (1989) have suggested that irritable aggression is part of the behavioral facilitation system, a biobehavioral system similar to the behavioral approach system (BAS) (Gray, 1987). Whether anger results in a general tendency to approach as compared to a specific tendency to aggress is currently a topic of debate with some suggesting the former (Lewis, 1993) and some the latter (Berkowitz, 1999; Berkowitz, 2000). In support of the idea of anger evoking approach motivation, (Lewis et al. 1990; Lewis, Sullivan, Ramsey, & Alessandri, 1992) conditioned infants to pull a string to receive a reward. They found that infants who displayed anger when the reward was withdrawn demonstrated the highest levels of joy, interest, and required arm pull when the learning portion of the task was reinstated. Thus, subsequent to frustrating events, anger may maintain and increase task engagement and approach motivation. In other research, Baron (1977) demonstrated that angry individuals are reinforced positively by signs of their tormentor’s pain. Participants who had been deliberately provoked by another individual had an opportunity to assault him in return. Indications that their first attacks were hurting their target led to increased aggression for previously provoked participants, but to reduced aggression for unprovoked participants. The initial signs of their victim’s suffering showed the angry persons they were approaching their aggressive goal and thus evoked even stronger assaults from them. Additional support for the idea that anger is associated with approach motivation comes from research testing the conceptual model that integrated reactance theory with learned helplessness theory (Wortman & Brehm, 1975). According to this model, how individuals respond to uncontrollable outcomes depends on their expectation of being able to control the outcome and the importance of the outcome. When an individual expects to be able to control outcomes that are important, and those outcomes are found to be uncontrollable, psychological reactance should be aroused. Thus, for individuals who initially expect control, the first few bouts of uncontrollable outcomes should arouse reactance, a motivational state aimed at restoring control. After several exposures to uncontrollable outcomes, these individuals should become convinced that they cannot

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control the outcomes and should show decreased motivation (i.e., learned helplessness). In other words, reactance will precede helplessness for individuals who initially expect control. In one study testing this model, individuals who exhibited angry feelings in response to one unsolvable problem had better performance and were presumably more approach motivated on a subsequent cognitive task than did participants who exhibited less anger (Mikulincer, 1988). Other research has revealed that state anger relates to high levels of self-assurance, physical strength, and bravery (Izard, 1991), inclinations associated with approach motivation. In addition, trait anger has been found to relate to high levels of assertiveness and competitiveness (Buss & Perry, 1992). Lerner and Keltner (2001) found that anger (both trait and state) is associated with optimistic expectations, whereas fear is associated with pessimistic expectations. Moreover, happiness was associated with optimism, making anger and happiness appear more similar to each other in their relationship with optimism than fear and anger. Although Lerner and Keltner (2001) interpreted their findings as being due to the appraisals associated with anger, it seems equally plausible that it was the approach motivational character of anger that caused the relationship of anger and optimism. That is, anger creates optimism because anger engages the approach motivational system and produces greater optimistic expectations. Other evidence supporting the idea that anger is associated with an approach-orientation comes from research on bipolar disorder. The emotions of euphoria and anger often occur during manic phases of bipolar disorder (Cassidy, Forest, Murry, & Carroll, 1998; Depue & Iacono, 1989; Tyrer & Shopsin, 1982). Both euphoria and anger may be approach-oriented processes, and a dysregulated or hyperactive approach system may underlie mania (Depue & Iacono, 1989; Fowles, 1993). Furthermore, lithium carbonate, a treatment for bipolar disorder, reduces aggression (Malone, Delaney, Luebbert, Cater, & Campbell, 2000), suggesting that anger and aggression correlate with the other symptoms of bipolar disorder. Other individual different studies support the hypothesis that trait anger is related to trait approach motivation, or more specifically, trait BAS. BAS is a concept from Gray’s motivation theory, which posits that a BAS and behavioral inhibition system (BIS) motivate and guide behavior. In theory, the BAS is a motivational system that is sensitive to signals of conditioned reward, nonpunishment, and escape from punishment. Its activation causes movement toward goals. The BIS is hypothesized to be sensitive to signals of conditioned punishment,

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nonreward, novelty, and innate fear stimuli. The BIS inhibits behavior, increases arousal, prepares for vigorous action, and increases attention toward aversive stimuli. Carver and White’s (1994) BIS/BAS questionnaire assesses individual differences in BIS and BAS sensitivity. Sample items from the BIS scale include: “I worry about making mistakes” and “I have very few fears compared to my friends (reverse scored).” Sample items from the BAS include: “It would excite me to win a contest,” “I go out of my way to get things I want,” and “I crave excitement and new sensations.” In two studies, HarmonJones (2003) showed that trait BAS was positively related to trait anger, as assessed by the Buss and Perry (1992) aggression questionnaire, at the simple correlation level. Smits and Kuppens (2005) have replicated the relationship between BAS and trait anger. They also found that measures of the anger-coping styles of anger-out versus anger-in relate to BAS and BIS. That is, anger-out, or the tendency to express one’s anger outwardly, related directly with BAS and inversely with BIS. In contrast, anger-in, or the tendency to turn one’s anger inward, related directly with BIS and inversely with BAS. Other research has extended this work by showing that trait levels of BAS sensitivity relate to self-reported anger responses to laboratory manipulations of anger. For instance, Carver (2004) found that trait BAS predicts state anger in response to situational anger manipulations. Putman, Hermans, and van Honk (2004) found that trait BAS predicts attentional vigilance to angry faces presented below conscious thresholds, suggesting that individuals with stronger approach motivational sensitivities selectively attend to angry faces as in a dominance confrontation. Additional support for anger’s association with approach motivation comes from two experiments that examined the speed with which movement of angry and fearful faces toward or away from the direction of gaze is accurately detected (Adams, Ambady, Macrae, & Kleck, 2006). In one experiment, faces displaying anger or fear were presented in the center of a computer monitor. The gaze of the forward facing target was manipulated so that it appeared that the individual was looking to the left or the right. After 1000 ms, the faces shifted to the right or the left, and the participants were instructed to make a right or left mouse click in the same direction the face appeared to move. In other words, it appeared as if the faces were either approaching (moving toward their gaze fixation) or withdrawing (moving away from their gaze fixation). Reaction time results revealed that participants were quicker to detect angry faces moving in the direction of their gaze than any other facial display/movement direction combinations.

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These results suggest that that an approach behavioral intent is conveyed by facial expressions of anger.

MOTIVATIONAL COMPONENTS OF ANGER: ASYMMETRICAL FRONTAL CORTICAL ACTIVITY The above evidence using self-report and behavioral measures suggests that anger is often associated with approach rather than avoidance or withdrawal motivation. Guided by this past work, we have examined anger as a way to better understand the psychological and behavioral functions of asymmetrical frontal cortical activity. Over three decades of research has suggested that the left and right frontal cortical regions are asymmetrically involved in emotional and motivational processes. During this period, some scientists suggested that the left frontal cortical region is involved in the expression and experience of positive affect, whereas the right frontal cortical region is involved in the expression and experience of negative affect. Some of the earliest research suggestive of the idea that the left and right frontal cortices were involved in different emotional or motivational processes was provided by work with individuals who had suffered damage to the left or right frontal cortical region. In this research, it was found that individuals who suffered damage to the right frontal cortex were more likely to evidence mania, whereas individuals who suffered damage to the left frontal cortex were more likely to evidence depression (see review by Robinson & Downhill, 1995). This research is consistent with the view that mania may be associated with increased left frontal activity and increased approach tendencies, because the approach motivation functions of the left frontal cortex are released and not restrained by the withdrawal system in the right frontal cortex.

BASELINE EEG AND INDIVIDUAL DIFFERENCES A number of additional studies have examined the relationship between asymmetrical frontal cortical activity recorded during resting baseline with other measures of trait affect and motivation. This research is based on the idea that baseline asymmetrical frontal cortical activity reflects a trait (Tomarken, Davidson, Wheeler, & Kinney, 1992). Depression has been found to relate to resting frontal asymmetrical activity, with depressed individuals showing relatively less left than right frontal brain activity (Henriques & Davidson, 1990; Jacobs & Snyder,

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1996). Other research has revealed that trait positive affect is associated with greater left than right frontal brain activity, whereas trait negative affect is associated with greater right than left frontal brain activity (Tomarken, Davidson, Wheeler, & Doss, 1992). In this past research, trait positive and negative affect were assessed using the Positive and Negative Affect Schedule (Watson, Clark, & Tellegen, 1988). Watson et al. have recently stated that they consider this scale a measure of activated positive affect and activated negative affect (Watson et al., 1999), because the items on the scales assess activated or aroused positive and negative affects (e.g., active, interested, afraid, distressed) not ones lower in arousal (e.g., happy, sad). Other research has found that trait BAS relates to greater left than right frontal brain activity (Coan & Allen, 2003; Harmon-Jones & Allen, 1997; Sutton & Davidson, 1997). In this research, BAS was measured by Carver and White’s (1994) BIS/BAS questionnaire. Studies have produced inconsistent results regarding the relationship of behavioral inhibition sensitivity (BIS; “I worry about making mistakes.”) and frontal brain asymmetry. One study found a significant relationship between BIS and greater right than left frontal activity (Sutton & Davidson, 1997), while two others found a nonsignificant relationship (Coan & Allen, 2003; Harmon-Jones & Allen, 1997). While researchers have hypothesized that right frontal brain activity increases during withdrawal, BIS may not be equivalent to withdrawal motivation (Harmon-Jones & Allen, 1997). It is also possible that BIS taps withdrawal oriented attentional processes rather than withdrawal oriented action processes (Peterson, Gable, & Harmon-Jones, in press). This possibility is consistent with Gray’s (1987) original conception of BIS as a “stop, look, and listen” system.

BASELINE EEG AND RESPONSES TO EMOTION-ELICITING STIMULI Resting baseline frontal asymmetrical activity also predicts emotional responses to emotion-eliciting stimuli. Individuals with relatively greater right than left frontal activity exhibit larger negative affective responses to negative emotion-inducing films (fear and disgust) and smaller positive affective responses to positive emotioninducing films (happiness) (Tomarken, Davidson, & Henriques, 1990; Wheeler, Davidson, & Tomarken, 1993). In a related vein, research has found that resting baseline frontal asymmetrical activity predicts evaluative responses to novel stimuli that have been repeatedly

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exposed to participants (Harmon-Jones & Allen, 2001). According to theory, exposing individuals to novel stimuli without reward or punishment (mere exposure) signals safety. Individuals with greater relative right frontal activity reported more favorable attitudes toward familiarized stimuli than did individuals with relative left frontal activity. Other research has found that relative right frontal activity at baseline predicts crying in response to maternal separation in 10-month-old infants (Davidson & Fox, 1989). Although these effects are based on correlational evidence and hence subject to alternative explanations, one experiment has more strongly suggested that frontal asymmetry is causally involved in the production of these emotional responses. In this experiment, neurofeedback training was used to manipulate asymmetrical frontal cortical activity (Allen, Harmon-Jones, & Cavender, 2001). Participants were randomly assigned to receive neurofeedback training designed to increase right frontal relative to left frontal activity or to receive training in the opposite direction. Systematic alterations of frontal asymmetry were observed as a function of neurofeedback training. Moreover, subsequent self-reported affect in response to emotionally evocative film clips was significantly influenced by the direction of neurofeedback training. Individuals trained to increase left frontal activity reported more positive affect in response to the happy film clip than individuals trained to increase right frontal activity.

EEG ACTIVITY DURING EMOTIONAL SITUATIONS Research has also demonstrated that asymmetrical frontal brain activity is associated with state emotional responses. For instance, 10-month-old infants exhibited increased left frontal activation in response to a film clip of an actress generating a happy facial expression as compared to an actress generating a sad facial expression (Davidson & Fox, 1982). Newborn infants (2–3 days old) evidenced greater relative left-sided activation in frontal regions in response to sucrose as compared with water (Fox & Davidson, 1986). Frontal brain activity has been found to relate to facial expressions of positive and negative emotions, as well. For example, Coan, Allen, and Harmon-Jones (2001) found that voluntary contractions of the facial musculature to form a happy facial expression produced relatively greater left frontal activity, while voluntary contractions of the facial musculature to form a fearful facial expression produced relatively less left frontal activity.

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EXPLANATIONS OF THE ASYMMETRICAL FRONTAL BRAIN ACTIVITY AND EMOTION RELATIONSHIP The functions of the left and right frontal cortices of the brain continue to spark ongoing debate in the study of emotion. Various researchers have provided evidence that activity in the left frontal cortex relates to positive emotions, approach motivation, or both, while activity in the right frontal cortex relates to negative emotions, withdrawal motivation, or both (Davidson, 1998, Tomarken & Keener, 1998). Because positivity versus negativity was confounded with approach versus withdrawal in the past work cited above, it was impossible to determine whether the activity in the frontal hemispheres related to the valence of emotion (positive versus negative) or the direction of motivation (approach versus withdrawal). Because anger is a negatively valenced, approachmotivated emotion, it presents an opportunity to examine the true relationship of asymmetrical frontal activity and emotional valence or motivational direction. In one of the first studies examining this, Harmon-Jones and Allen (1998) found that trait anger related to increased left frontal activity and decreased right frontal activity. More recently, Harmon-Jones (2004) addressed an alternative explanation for these results. The alternative explanation suggested that persons with high levels of trait anger might experience anger as a positive emotion, and this positive feeling or attitude toward anger could be responsible for anger being associated with relative left frontal activity. After developing a valid and reliable assessment of attitude toward anger, a study was conducted to assess whether resting baseline asymmetrical activity related to trait anger and attitude toward anger. Results indicated that relative left frontal activity related to anger and not attitude toward anger. Moreover, further analyses revealed that the relationship between trait anger and left frontal activity was not due to anger being associated with a positive attitude toward anger. To address the limitations of the above correlational studies, experiments have been conducted in which anger is manipulated and its effects on regional brain activity are examined. In Harmon-Jones and Sigelman (2001), participants were randomly assigned to a condition in which another person insulted them or to a condition in which another person treated them in a neutral manner. Immediately following the treatment, EEG activity was assessed. As predicted, individuals who were insulted evidenced greater relative left frontal activity than individuals who were not insulted. Additional analyses revealed that within the insult condition, reported anger

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and aggression were positively correlated with relative left frontal activity. Neither of these correlations was significant in the no-insult condition. These results suggest that relative left-frontal activation was associated with more anger and aggression in the condition in which anger was evoked. Recent experimental evidence has replicated these results and also revealed that state anger evokes both increased left and decreased right frontal activity. Moreover, a manipulation of sympathy for the person who would later insult the participant revealed that sympathy reduced the effects of insult on left and right frontal activity (Harmon-Jones, Vaughn-Scott, Mohr, Sigelman, & Harmon-Jones, 2004). This research suggests that experiencing sympathy for another individual may reduce aggression toward that individual (see review by Miller & Eisenberg, 1988) by reducing the relative left frontal activity associated with anger. In the two experiments just described, the designs were tailored in such a way as to evoke anger that was approach oriented. Although most instances of anger involve approach inclinations, not all instances of anger are associated with approach motivation. To manipulate approach motivation independently of anger, Harmon-Jones et al. (2003) performed an experiment in which the ability to cope with the anger-producing event was manipulated. On the basis of the past research that has revealed that coping potential affects motivational intensity (Brehm & Self, 1989), it was predicted that the expectation of being able to take action to resolve the anger-producing event would increase approach motivational intensity relative to expecting to be unable to take action. Participants were exposed to an anger-eliciting situation. To manipulate coping potential, in one condition participants were led to believe that they could act to change the angering situation, while in the other condition participants were led to believe that there was nothing they could do to change the situation. Both conditions evoked significant increases in anger (over baseline) and the degree of anger did not differ between conditions. Consistent with predictions, participants who expected to engage in the approach-related action evidenced greater left frontal activity than participants who expected to be unable to engage in approach-related action. Moreover, within the action-possible condition, participants who evidenced greater left frontal activity in response to the angering event also evidenced greater self-reported anger, providing support for the idea that anger is often an approach-related emotional response. In the condition where action was not possible, greater left frontal activity did not relate to greater anger. In our view, this is because, although anger usually

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leads to approach motivation, when action is not possible, approach motivation remains low, even if angry feelings are high. Finally, within the action-possible condition, participants who evidenced greater left frontal activity in response to the event were more likely to engage in behavior that could change the situation. This research suggests that the left frontal region is most accurately described as a region sensitive to approach motivational intensity. It was only when anger was associated with an opportunity to resolve the angerproducing event that participants evidenced the increased relative left frontal activation. The increase in left frontal cortical activation during instances of anger where approach-related action is possible has been replicated (Harmon-Jones, Lueck, Fearn, Harmon-Jones, 2006). However, the results of these two experiments should not be taken to indicate that such explicit manipulations of action possibility are always necessary. Manipulations of action possibility may only potentiate the effects of emotion manipulations on asymmetrical frontal cortical activity. Indeed, in a recent study, participants were exposed to anger-inducing pictures (and other pictures) and given no explicit manipulations of action expectancy. Across all participants, a null effect of relative left frontal asymmetry occurred. However, individual differences in trait anger related to relative left frontal activity to the anger-inducing pictures, such that individuals high in trait anger showed greater left frontal activity to angerproducing pictures (controlling for activity to neutral pictures; Harmon-Jones, 2007). The reviewed research has revealed that the left frontal cortical region is involved in approach-motivated anger. A few studies using brain imaging technologies other than EEG have been conducted. In one, positron emission tomography (PET) was measured while men were exposed to personally created angry or neutral mental imagery scripts (Dougherty et al., 1999). Results revealed that as compared to neutral imagery, anger imagery caused an increase in the left orbital frontal cortex, the right anterior cingulate cortex, the bilateral anterior temporal poles, left precentral gyrus, bilateral medial frontal cortex, and bilateral cerebellum. Thus, the increase in activity in the left orbital frontal cortex is consistent with the anger research results obtained using EEG. However, Dougherty et al. (1999) interpreted the increase in left orbital frontal cortical activity very differently. They ascribed the increase “to inhibition of aggressive behavior in the face of anger” (p. 471). While this interpretation is consistent with some speculations of the role of the left orbital frontal cortex in response inhibition (Mega, Cummings, Salloway, & Malloy, 1997),

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it is inconsistent with the EEG results showing that increased left frontal activity is associated with increased aggression and approach behavior (Harmon-Jones & Sigelman, 2001; Harmon-Jones et al., 2003). The interpretation that the left frontal cortical region is involved in the inhibition of anger and aggression is also inconsistent with lesion data suggesting that mania results from damage to the right frontal region (Robinson & Downhill, 1995) and results obtained when the left relative to right frontal cortex is activated and angry attentional processes are measured (d’Alfonso, van Honk, Hermans, Postma, & de Haan, 2000). However, EEG is likely assessing dorsolateral frontal cortical activity and not orbital frontal activity, and left orbital frontal activity may be involved in the inhibition of anger, whereas left dorsolateral frontal activity may be involved in approach motivations like anger. An increase in dorsolateral frontal cortical activity may not have been found in the PET study because no approach opportunity was presented to the participants. In fact, it is possible that approach motivation may be more difficult to evoke under the conditions of immobility required during PET. Of course, it may be difficult to compare anger induced by imagery to anger induced by insulting feedback or goal blocking, as in the EEG experiments. In the imagery experiments, there was no report of a significant association between reported anger and regional brain activity. In the EEG experiments, self-reported anger has been found to correlate significantly with relative left frontal activity. Such correlations assist in determining whether the brain activation is related to emotional experience or some other nonemotional variable. In the previously discussed studies, the psychological variables of approach motivation and anger were manipulated and the physiological variable of relative left frontal activation was measured. Experimental approaches that manipulate brain activity provide complementary rather than redundant information about the relationship between brain activity and psychological/behavioral functions. As noted by Sarter, Berntson, and Cacioppo (1996), studies that manipulate brain activity and observe its effects on psychological/behavioral outcomes provide different information than studies that manipulate psychological processes and observe their effects on brain activity. The two experimental approaches differ in their heuristic power, with the brain manipulation studies providing stronger inferences. The change of psychological and behavioral function by change of neuronal processes in certain regions can establish a particular brain region as necessary for a particular psychological function. Although both assessment of and manipulation of brain

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activity can be studied experimentally, studies that examine the effects of a psychological process on brain activity are limited in the causal inferences that can be advanced, because the experimental alteration of a particular psychological process often alters brain activity in multiple regions, including those that presumably underlie the psychological process of interest. It remains possible that an alternate and perhaps undetected brain event could be causally mediating the relationship between the psychological process and the brain activity of interest. Although the reviewed research suggests that approach-oriented anger evokes left frontal activity, the causal inferences that can be drawn from this literature are limited because the evidence is based on studies examining the effects of a manipulated psychological process on brain activity. Fortunately, other research has addressed these limitations by manipulating regional brain activity and observing its effects on anger processes. For example, d’Alfonso et al. (2000) used slow repetitive transcranial magnetic stimulation (rTMS) to inhibit the left or right prefrontal cortex. Slow rTMS reduces cortical excitability, so that rTMS applied to the right prefrontal cortex decreases its activation and causes the left prefrontal cortex to become more active, while rTMS applied to the left prefrontal cortex causes activation of the right prefrontal cortex. They found that rTMS applied to the right prefrontal cortex caused selective attention toward angry faces whereas rTMS applied to the left prefrontal cortex caused selective attention away from angry faces. Thus, an increase in left prefrontal activity led participants to attentionally approach angry faces, as in an aggressive confrontation. In contrast, an increase in right prefrontal activity led participants to attentionally avoid angry faces, as in a fear-based avoidance. These results have been conceptually replicated by van Honk and Schutter (2006). The interpretation of these results is supported by research demonstrating that attention toward angry faces is associated with high levels of anger, BAS, and testosterone, and that attention away from angry faces is associated with high levels of social anxiety and cortisol (van Honk, Tuiten, de Haan, van den Hout, & Stam, 2001; van Honk et al., 1998, 1999). We recently extended the work of van Honk and colleagues by examining whether a manipulation of asymmetrical frontal cortical activity would affect behavioral aggression. On the basis of the past research showing that contraction of the left hand increases right frontal cortical activity and that contraction of the right hand increases left frontal cortical activity (Harmon-Jones, 2006), we manipulated asymmetrical frontal cortical activity by having participants contract their right or left hand.

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That is, participants squeezed a small ball in one hand or the other hand. Participants then received insulting feedback ostensibly from another participant. They then played a reaction time game on the computer against the other ostensible participant. Participants were told they could give the other participant a blast of 60, 70, 80, 90, or 100 dB white noise for up to 10 s if they were fastest to press the shift key when an image appeared on the screen. Results indicated that participants who squeezed with their right hand gave significantly louder and longer noise blasts to the other ostensible participant than those who squeezed with their left hand (Peterson, Shackman, & Harmon-Jones, 2008). In summary, the idea that anger is associated with approach motivational tendencies is supported by behavioral and neuroimaging evidence. However, it is possible that some instances of anger, such as anger mixed with fear, may be associated with withdrawal motivational tendencies (Zinner, Brodish, Devine, & Harmon-Jones, in press). In addition, some individuals may have learned to control their angry approach tendencies and may have instead converted these angry tendencies into withdrawal-oriented behaviors (Hewig, Hagemann, Seifert, Naumann, & Bartussek, 2004). More research is needed to understand whether and how this type of angry expression may emerge.

SUBJECTIVE FEELINGS ASSOCIATED WITH ANGER The conception of anger advanced in this chapter is much broader than some others, which suggest that there are different kinds of anger. For example, Ellsworth and Scherer (2002, p. 575) wrote, “Rather than a single emotion of anger, there can be many varieties of ‘almost anger’ and many nuances of the anger experience.” We do not reject such a possibility, but instead suggest a broader view that proposes that there is an important commonality overriding the “nuances” of anger experience. Spielberger et al. (1983, 1995) reflected this notion in regarding anger as encompassing low intensity feelings such as irritation or annoyance as well as high intensity feelings such as fury and rage. A factor analysis of the items in his State Anger scale (such as “I am furious” and “I feel irritated”) obtained only a single factor, suggesting that the feelings tapped by these items reflected a unitary affective state varying in intensity. Spielberger’s (Spielberger et al., 1983, 1995) distinction between “anger-in” and “anger-out,” it should be noted, refers to differences in the predisposition (i.e., trait) to openly express the motoric concomitants of anger rather than

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qualitative differences in the nature of the angry feelings (Spielberger et al., 1995). Our conception of anger experience is in accord with the prototype view of emotion concepts advanced by Shaver et al. (1987). Shaver et al. found that the anger prototype indicates that a variety of feelings labeled irritation, annoyance, exasperation, disgust, and hate are often included within the general notion of anger. In sum, there is some justification to not regarding the various “nuances” of anger experience as distinctly different emotional or affective states. It is often held that emotions, unlike moods, are about something in particular; they have a more definite cause and a more specific target. However, this clarity or focus is a matter of degree, as Frijda (1986, pp. 59–60) recognized, and people can vary in the extent to which they believe they know what produced the mood they are experiencing. As Frijda put it, the distinction between mood and emotion is “unsharp” (1986, p. 60). If people can vary in the extent to which they have a clear conception of the cause of their affective arousal, where do we place the cutting point on this continuum, putting mood on one side and emotion on the other? Anger is often regarded as a negative emotion by laypersons as well as psychological scientists. However, what is meant by negative is not always clearly defined in the literature. Emotions can be regarded as positive or negative (1) because of the conditions that evoked the emotion, (2) because of the emotion’s adaptive consequences, (3) or because of the emotion’s subjective feel. Thus, the emotion of anger can be viewed as negative when considering the conditions that evoked the emotion, because anger is evoked by aversive events. Anger could be viewed as either positive or negative when considering its adaptive consequences, depending upon the outcome of the behaviors evoked by anger. However, one would also need to define for whom the consequences are adaptive—the individual experiencing the anger or the individual or group toward whom the individual directs his or her behavior, and whether the consequences are adaptive in the short- or long term. Finally, anger could be viewed as either positive or negative when considering the subjective feel or evaluation of the emotion, depending on whether an individual likes or dislikes the subjective experience of anger. In considering the valence of an emotion, the definition of emotion must also be considered. Although there is no completely accepted definition of emotion, some scientists focus on the stimulus conditions when defining an emotion (e.g., a negative situation blamed on another causes anger), whereas other scientists focus on the responses evoked when defining an emotion (e.g., anger

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involves certain physiological changes, behavioral expressions, and subjective feelings). The stimulus-based definitions indicate that the individual’s evaluation of the stimulus causing the emotion determines the valence of the emotion (Lazarus, 1991). Thus, most appraisal theorists regard whether the emotion-evoking situation is appraised as positive or negative as the most important and frequent way of distinguishing positive from negative emotions. By this definition, then, anger is a negative emotion. Response-based definitions of emotion indicate that the individual’s subjective evaluation of the feeling determines the valence of the emotion. When anger is examined as a subjective experience, however, it is not necessarily negative; it can be subjectively accepted or rejected. Anger can be evaluated positively by the person experiencing the emotion, as when an individual says, “I like how it feels when I am furious.” Although most persons find the experience of anger unpleasant, some individuals find it relatively less unpleasant (Harmon-Jones, 2004). In general, both state and trait studies examining the valence of anger indicate that most individuals regard anger as a negative experience. However, there are some individuals who routinely find the experience of anger less negative than others (Harmon-Jones, 2004). Moreover, these individual differences in attitudes toward anger relate positively to Buss and Perry (1992) trait anger and trait hostility (as measured by the Positive and Negative Affect Schedule-Expanded (PANAS-X) of Watson & Clark, 1991), although the correlations are not so high as to suggest redundancy. These individual differences in attitude toward anger also relate negatively to trait fear (as measured by PANAS-X). Attitudes toward anger do not relate to self-reported affect intensity or social desirability. Thus, while the valence of anger is predominantly negative, some individuals find it less negative than others, and these attitudes toward anger may have important consequences. It is important to note that these individual differences in attitudes toward anger do not explain why trait anger relates to relative left frontal cortical activity (Harmon-Jones, 2004).

RELATIONSHIP TO OTHER EMOTIONAL EXPERIENCES In a given situation, anger may be the primary or even sole emotional experience. However, often times, anger occurs amid other negative emotions, as many conceptual perspectives recognize (Berkowitz, 1989). The idea that anger could co-occur with measures of positive affect is less often recognized. In a recent experiment, anger

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was manipulated using an interpersonal insult and selfreported affect was measured following the insult (Harmon-Jones et al., 2004). In addition to reporting feeling more anger, insult condition participants reported feeling more active, alert, determined, proud, and strong than the no-insult control condition participants. These latter items are from the PANAS measure of activated positive affect (Watson et al., 1988). On the surface, these results suggest that the insult manipulation caused more activated positive affect. Such an interpretation would be consistent with the idea that the activated positive affect scale is measuring approach motivation (Watson, 2000). However, another interpretation is that the words did not reflect feelings of positivity in this situation in which anger was present. These results for activated positive affect have since been replicated using a different anger manipulation. In addition, in this more recent study, trait BAS was positively related to both reported anger and reported activated positive affect, providing convergent evidence. Moreover, anger and activated positive affect were positively correlated, happiness and activated positive affect were positively correlated, and happiness and anger were negatively correlated (Harmon-Jones, Harmon-Jones, Abramson, & Peterson, 2008). Taken together, these results suggest that the PANAS measure called activated “positive activation” or PA may be a better measure of approach motivation or “pounce affect” than of positivity. In other words, the PA subscale may actually describe an action-tendency of approach—a motivation to “pounce.” The “pouncing” measured by these items may be an enthusiastic approach to a delicious dessert, a lustful embrace of an attractive mate, or an angry attack on an enemy.

CONCLUSION Empirical and theoretical developments on anger and its relationship with motivational direction were reviewed. Many models of anger suggest that anger occurs as a result of goal blocking, consistent with the idea that anger may often occur in approach motivated situations. Other theoretical and empirical developments have revealed that, unlike other negative emotions, anger responses are associated with approach motivation instead of withdrawal or avoidance motivation. Recent research and theoretical developments on anger have shed new light on our understanding of the relationship between motivational direction and emotional valence. Whereas most previous dimensional models of emotion and motivation suggested that approach motivation was only associated

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with positive affect, the evidence now suggests that at least one negative affect, anger, is often associated with approach motivation. These results suggest that dimensional models of emotion are in need of revision and that the motivational direction of emotion needs to be considered as independent of the valence of emotion. Practically, the reviewed evidence may assist in understanding why anger presents problems for the individual and society, but it also suggests that anger may provide some beneficial functions.

ACKNOWLEDGMENT Portions of the research described within this chapter were supported by a grant from the National Science Foundation (BCS 0350435) and by a grant from the National Institute of Mental Health (R03 MH60747–01).

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Well-Being Goals 24 Approach–Avoidance and Well-Being: One Size Does Not Fit All Maya Tamir and Ed Diener CONTENTS Motivation Is Central to Well-Being ..................................................................................................... 416 Impact of Motivation: Activity and Telic Theories of Well-Being .................................................. 416 Approach and Avoidance Goals Are Central to Well-Being ................................................................ 417 Approach–Avoidance Goals and Well-Being: An Activity Theory Perspective .................................. 417 Conceptual Distinctions ................................................................................................................... 417 Empirical Evidence .......................................................................................................................... 418 Approach–Avoidance Goals and Well-Being: A Telic Theory Perspective.......................................... 419 Approach–Avoidance Goals and Meaning in Life................................................................................ 419 Individual Differences Moderate the Link Between Approach–Avoidance Goals and Well-Being ......................................................................................................................................420 Desirability of Approach and Avoidance Goals: An Activity Theory Perspective .............................. 421 Desirability of Approach–Avoidance Goals: Cultural Differences as an Example ......................... 421 Feasibility of Approach and Avoidance Goals: A Telic Theory Perspective ........................................422 Feasibility of Approach–Avoidance Goals: Regulatory Fit as an Example .....................................423 Conflicting Goal Pursuits of Avoidance-Oriented Individuals .............................................................424 Summary ...............................................................................................................................................425 References .............................................................................................................................................425

April and Avalon are equally committed to their goals and work equally hard to achieve them. Their goals, however, are quite distinct. April wants to become a regional manager and works hard to climb up the promotion ladder. Avalon wants to keep her job and works hard not to lose her position as a regional manager. Whereas April is driven by an approach goal (i.e., get promoted), Avalon is driven by an avoidance goal (i.e., not get demoted). Do these distinct goals carry any implications for well-being? Are certain goals more conducive to well-being than others? Are some goals more conducive to the well-being

of one person than another? These and related questions are explored in the present chapter. Since the early philosophical discussions of wellbeing, it has been conceptualized from two distinct perspectives—one emphasizing hedonic pleasure and one emphasizing meaning in life. Aristippus, for instance, argued that the purpose of life is to maximize pleasure. Indeed, the hedonic perspective assumes that well-being is enhanced by experiences of pleasure and impaired by experiences of pain. Current hedonic approaches emphasize pleasures of the mind and the body, as indicated 415

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primarily by momentary experiences of pleasant (vs. unpleasant) affect (Kahneman, 1999). Aristotle, on the other hand, argued that true happiness is a function of virtue. Thus, an alternative perspective to well-being assumes that it is dependent upon the experience of meaning and value in life (Ryan & Deci, 2000; Ryff, 1989). That is, meaning involves a unified purpose in life that is consistent with one’s values. According to this approach, well-being is enhanced by the experience of meaning in life and impaired when life experiences are not personally meaningful or valuable to the individual. These two approaches to well-being highlight pleasure and meaning in life as two, conceptually distinct, sources of well-being. Pleasure and meaning, however, are often related to one another. Experiences of pleasure and pain can make events meaningful. For instance, a student may feel more drawn and personally committed to a topic taught in class, if she enjoys the lectures. In addition, the extent to which an event is personally meaningful can determine the hedonic consequences of the event. For instance, doing well on an exam is likely more pleasant and rewarding, if the exam covers a topic the student views as personally meaningful (Emmons, 1996). Pleasure and meaning in life are, nevertheless, conceptually distinct sources of well-being that can have different underpinnings and different implications. In exploring well-being, therefore, it is important to acknowledge both pleasure and meaning in life as critical determinants. Accordingly, in the present context, we define well-being as involving frequent experiences of pleasant affect, infrequent experiences of unpleasant affect, and a sense of meaning in life. This approach to well-being is reflected, to some extent, in research on subjective wellbeing, where meaning in life is an important contributor to life satisfaction (Diener, Oishi, & Lucas, 2003). The present chapter reviews the potential implications of approach and avoidance goals for well-being. In the first part of the chapter, we review the general implications of approach and avoidance goals for well-being. We begin by explaining why motivation features so prominently in accounts of well-being. We then review the implications of approach and avoidance goals for affective experiences and meaning in life, focusing on the potential contributions of the process and the outcome of goal pursuit. In the second part of the chapter, we argue that the link between approach–avoidance goals and well-being can be fully understood only when examined from an individual difference perspective. In particular, we propose that the extent to which approach

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and avoidance goals are beneficial for well-being may depend on the desirability and feasibility of such goals for the individual.

MOTIVATION IS CENTRAL TO WELL-BEING Motivation is arguably one of the most important building blocks of well-being (Diener, 1984). In part, this is because motivation is linked to pleasure and pain as well as to meaning in life. As noted earlier, affect-based approaches view momentary pleasant and unpleasant affective experiences as critical determinants of wellbeing (Kahneman, 1999; Kubovy, 1999). Momentary affective experiences, in turn, arise in response to events that are motivationally relevant (Frijda, 1988). Pleasant feelings signal an event that promotes the individual’s goals. For instance, when an individual aspires to be a good student, doing well on an exam is likely to result in pleasant affect. Unpleasant feelings signal an event that hinders the individual’s goals. For instance, if an individual is motivated to be a good student, doing poorly on an exam is likely to lead to unpleasant affect. If, however, the individual is not motivated to be a good student, doing poorly on an exam is less likely to lead to unpleasant affect. Whereas pleasure-based theories of well-being highlight the role of motivation in determining affective experiences, meaning-based theories highlight the role of motivation in creating meaning in life. A personally meaningful life, according to such approaches, is one that is characterized by the pursuit of self-defining goals that are consistent with the person’s core beliefs and values (Ryan & Deci, 2000; Waterman, 1993). For example, graduating from medical school would contribute to the well-being of an individual who has always dreamt of becoming a doctor, but it would not necessarily contribute to the well-being of an individual who has always dreamt of becoming a movie star.

IMPACT OF MOTIVATION: ACTIVITY AND TELIC THEORIES OF WELL-BEING Motivation can influence well-being by underlying both affective experiences and meaning in life. According to Diener (1984), such effects may depend on either the process or the outcome of motivational pursuits. The roles of the process and the outcome of goal pursuits are highlighted in activity and telic theories of well-being, respectively. Activity theories of well-being focus on the process of goal pursuit. According to such theories, it is the active

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Approach–Avoidance Goals and Well-Being: One Size Does Not Fit All

pursuit of goals, rather than their fulfillment, that contributes to well-being (Cantor, 1990; Palys & Little, 1983). The impact of goal pursuits on well-being, primarily goals that involve conscious objectives that are pursued in daily life, has been demonstrated in research on current concerns (Klinger, 1975), personal projects (Palys & Little, 1983), and personal strivings (Emmons, 1986). Such research demonstrates that the active pursuit of goals is an important determinant of well-being. Unlike activity theories, telic theories of well-being focus on the outcome of goal pursuits. Telic theories maintain that well-being is enhanced when a person successfully attains a goal, and impaired when a person fails to attain a goal (Diener, 1984). Successful pursuits may be defined in terms of adequate progress toward the target end-state (Carver & Scheier, 1990) or in terms of final goal implementation (Gollwitzer, 1999). In other words, the successful pursuit of goals is an important determinant of well-being (Ryan & Deci, 2000). In summary, both the pursuit and the fulfillment of goals can promote well-being. Consistent with affectbased theories, motivational pursuits underlie the experience of positive and negative affect. Consistent with meaning-based theories, motivational pursuits give meaning to life. But are some motivational pursuits more conducive to well-being than others? In other words, do specific goals differ in their affective or meaning-related consequences? The answer lies in the distinction between approach and avoidance goals.

APPROACH AND AVOIDANCE GOALS ARE CENTRAL TO WELL-BEING In the beginning of the chapter, we introduced two coworkers, April and Avalon. Although both work equally hard to attain their goals, April pursues an approach goal (i.e., is motivated to attain desirable outcomes) whereas Avalon pursues an avoidance goal (i.e., is motivated to avoid undesirable outcomes). This distinction between approach and avoidance is one of the most critical and influential distinctions in the study of motivation (see Elliot, 2008). From a functional point of view, both approach and avoidance goals are necessary for successful adaptation. Whereas approach motivation facilitates growth and flourishing, avoidance motivation facilitates protection and survival. Avoidance goals, for example, help individuals avoid taking unnecessary risks (Lauriola & Levin, 2001) or consuming harmful substances (Worth, Sullivan, Hertel, Rothman, & Jeffery, 2005). Approach and avoidance motivation promote distinct types of affective,

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cognitive, and behavioral processes, both of which are relevant to adaptive functioning. Although it is beneficial to pursue at least some degree of both approach and avoidance goals, pursuing such goals may carry different implications for well-being. What balance, therefore, of approach to avoidance goals should an individual pursue to optimize well-being? The answer, of course, depends on the differential implications of approach and avoidance goals for affective and meaningful experiences in life. In the sections that follow, we review such implications focusing on the process and the outcome of goal pursuits.

APPROACH–AVOIDANCE GOALS AND WELLBEING: AN ACTIVITY THEORY PERSPECTIVE What are the affective consequences of approach and avoidance goals and how do these consequences impact well-being? We begin to address these questions by focusing on the process of goal pursuit (i.e., adopting an activity perspective). In the following sections, we first explore conceptual differences in the process of approach and avoidance goal pursuits and then review some empirical evidence.

CONCEPTUAL DISTINCTIONS According to activity theories, well-being is determined by the process of goal pursuit. From this perspective, approach and avoidance goals are likely to carry different implications for well-being, only to the extent that there are substantive differences in the process of pursuing these goals. As we describe below, there are reasons to believe that the process of pursuing approach goals is qualitatively distinct from that of pursuing avoidance goals. The pursuit of approach goals should be more manageable than that of avoidance goals. According to cybernetic control models (Carver & Scheier, 1998), the pursuit of approach goals involves diminishing the discrepancy between a current state and a desired state. On the other hand, the pursuit of avoidance goals involves enlarging the discrepancy between a current state and an undesired state. From this conceptual viewpoint, the pursuit of approach goals should be more manageable than the pursuit of avoidance goals, because progress is more tangible and easier to monitor (Elliot, Sheldon, & Church, 1997; Higgins, 1997). To demonstrate this point, let us return to our two coworkers. April can monitor progress in her goal pursuit as she climbs up the promotion ladder. If she fails to get

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promoted to assistant regional manager, she knows that she is not making sufficient progress toward her desired position. If, however, she gets the promotion, she knows that she is getting closer to obtaining her goal. April, therefore, can easily monitor success and failure in her goal pursuit and experience pleasant or unpleasant affect as a result. Avalon, on the other hand, may have a harder time monitoring her progress. If she is demoted to assistant regional manager, she knows that she is failing in obtaining her goal of keeping her position. But what would indicate to her that she is succeeding in her goal pursuit? Finding indications of success in pursuing avoidance goals can often be challenging. Thus, Avalon may be more likely to detect failures than successes in her goal pursuit, making it more likely for her to experience unpleasant affect. In addition, the pursuits of approach and avoidance goals likely differ in the cognitions they give rise to. If goal pursuits involve constant comparisons of a current state to an end-state (Carver & Scheier, 1998), the pursuit of approach goals involves constantly monitoring positive outcomes, making them more accessible during goal pursuit. On the other hand, the pursuit of avoidance goals involves constantly monitoring negative outcomes, making them more accessible during goal pursuit. Thus, the pursuit of approach goals can maintain positive cognitions, whereas the pursuit of avoidance goals can maintain negative cognitions (Elliot & Sheldon, 1998; Higgins, Roney, Crowe, & Hymes, 1994). April and Avalon, therefore, may have different thoughts accessible to them in their daily lives. April may think of what it would be like to be the regional manager in her company and such thoughts might engender pleasant affect. Avalon, on the other hand, may think of what it would be like to lose her job and such thoughts may engender unpleasant affect. Overall, the process of pursuing approach goals is different from the process of pursuing avoidance goals. Approach goals appear to be easier to monitor and more manageable than avoidance goals. In addition, whereas approach goals elicit positive cognitions, avoidance goals elicit negative cognitions. According to activity theories, therefore, the pursuit of approach goals should be more likely than the pursuit of avoidance goals to promote well-being.

EMPIRICAL EVIDENCE According to activity theories of well-being, the process of pursuing approach goals should be more conducive to

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well-being than that of avoidance goals. Indeed, there are now several lines of research supporting this prediction. For example, Elliot and his collaborators (for a recent review, see Elliot & Friedman, 2007) asked participants to list goals that best describe what they are trying to achieve in life. After categorizing these goals as either approach- or avoidance-oriented, they created an avoidance (relative to approach) index for each participant. Using this procedure, the authors found that pursuing more approach than avoidance goals was associated with higher levels of well-being. In particular, pursuing more approach than avoidance goals was associated with higher levels of well-being in retrospective ratings (Elliot et al., 1997) and with less physical symptoms, such as headaches, sore throat, and dizziness (Elliot & Sheldon, 1998). The beneficial role of approach (vs. avoidance) goals has been demonstrated with respect to general goals and with respect to goals in specific life domains. In the achievement domain, pursuing approach achievement goals was associated with higher levels of subjective well-being (Elliot & Sheldon, 1997). Similarly, in the social domain, pursuing approach friendship goals was associated with higher levels of subjective well-being (Elliot, Gable, & Mapes, 2006). Consistent with core assumptions of activity theories, the relationships between approach–avoidance goals and well-being were fully mediated by perceptions of progress and competence in goal pursuit. Approach goals predicted higher perceptions of personal progress and competence in goal pursuit, which in turn, predicted higher levels of subjective well-being (Elliot & Sheldon, 1997; Elliot et al., 1997). There is also reason to believe that the pursuit of approach versus avoidance goals exerts a causal influence on well-being. For instance, Coats, Janoff-Bulman, and Alpert (1996) presented participants with tasks, framed in terms of either approach or avoidance goals. Pursuing approach (vs. avoidance) goals was associated with higher perceptions of success in the task and with higher levels of task satisfaction. Consistent with the predictions of activity theories, such research suggests that pursuing approach (vs. avoidance) goals leads to greater perceived progress, which in turn, promotes satisfaction with the experience as a whole. Taken together, according to activity theories of wellbeing, the pursuit of approach goals is more conducive to well-being than the pursuit of avoidance goals. This is primarily because it is easier to monitor and assess progress when pursuing approach compared to avoidance goals. Approach goals are more manageable than avoidance

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goals and they elicit positive (vs. negative) cognitions. The available evidence is consistent with these predictions, suggesting that pursuing more approach than avoidance goals leads to greater perceived progress and efficacy, which in turn, promote well-being.

APPROACH–AVOIDANCE GOALS AND WELL-BEING: A TELIC THEORY PERSPECTIVE In the previous section, we examined the differential implications of approach and avoidance goals, focusing on the process of goal pursuit. However, as mentioned earlier, both the process and the outcome of goal pursuit can influence well-being. In this section, therefore, we review the implications of success or failure in approach and avoidance goal pursuits and their anticipated impact on well-being. According to telic theories, well-being is determined by the outcome of goal pursuit. Contrary to the account of activity theories, from the telic perspective, approach and avoidance goals are likely to carry different implications for well-being, only to the extent that success or failure in pursuing approach goals has different consequences than success or failure in pursuing avoidance goals. As we describe below, the outcome of approach and avoidance goal pursuits indeed results in distinct affective experiences. Affective experiences are assumed to be driven by the appetitive and defensive motivational systems (i.e., approach and avoidance, respectively) (Davidson, 1993; Gray, 1990; Lang, 1995). An active approach system is linked to feelings such as excitement and elation whereas an active avoidance system is linked to feelings such as anxiety and fear (see Carver, 2008; Harmon-Jones, 2008). Such affective experiences are most likely to arise as a function of success or failure in goal pursuit. According to cybernetic control models (Carver & Scheier, 1998), affective reactions reflect the speed of progress in goal pursuit. Pleasant feelings arise when the rate of progress toward a goal is faster than anticipated, whereas unpleasant feelings arise when the rate of progress toward a goal is slower than anticipated (Carver, 2004). Thus, both approach and avoidance goals should have the potential of inducing pleasant as well as unpleasant feelings as a function of progress in goal pursuit. When pursuing approach goals, desirable outcomes elicit excitement whereas undesirable outcomes elicit sadness. When pursuing avoidance goals, desirable outcomes elicit calmness whereas undesirable outcomes elicit anxiety.

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For example, April may feel pleasant affect (i.e., excitement) when she is promoted and she may feel unpleasant affect (i.e., sadness) when she fails to get that promotion. Similarly, Avalon may feel pleasant affect (i.e., relief or calmness) when she discovers that the board decided to keep her on the job and she may feel unpleasant affect (i.e., anxiety) when she hears that the board decided to give her job to another employee. According to telic theories, therefore, the outcomes of approach and avoidance goal pursuits lead to distinct affective experiences, yet both have the potential of eliciting pleasant (e.g., excitement and relief) as well as unpleasant (e.g., sadness and anxiety) affective experiences. Well-being, in turn, likely reflects the frequency rather than the intensity of affective experiences (Diener & Lucas, 2000). According to telic theories, the extent to which approach or avoidance goals promote well-being depends on the frequency of success or failure when pursuing such goals. This, of course, is assuming that all pleasant emotions contribute to well-being and all unpleasant emotions impair well-being. In other words, according to telic theories, if success is always more likely when pursuing approach (vs. avoidance) goals, approach goals should be more likely to contribute to well-being compared to avoidance goals. However, if there are cases in which success is more likely when pursuing avoidance (vs. approach) goals, in such cases, avoidance goals should theoretically be more likely to contribute to well-being than approach goals.

APPROACH–AVOIDANCE GOALS AND MEANING IN LIFE In the previous sections, we suggested that the process and the outcome of pursuing approach and avoidance goals can have different implications for well-being. In daily life, however, individuals likely pursue multiple goals, some of which are more important or meaningful than others. The impact of approach and avoidance goals on well-being, therefore, may vary as a function of how important or meaningful the goal is for the individual (Brunstein, Schultheiss, & Maier, 1999; Emmons, 1986). According to both activity and telic theories, goals that are personally meaningful are likely to have a greater impact on well-being (Carver & Scheier, 1990; Palys & Little, 1983). Indeed, there is evidence to suggest that only progress toward personally meaningful goals predict increases in well-being (Brunstein, Schultheiss, & Grassman, 1998). The perceived importance of goals also

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determines the time spent on goal-relevant activities in daily life (Cantor et al. 1991; Emmons, 1991). Personal meaning determines the extent to which well-being is influenced by the outcome of goal pursuits. In a daily diary study, Oishi, Diener, Suh, and Lucas (1999) found that within-person changes in life satisfaction were strongly linked to success in domains that individuals valued. Similarly, Sheldon and Elliot (1999) found that goal fulfillment was associated with greater wellbeing, but only if the goals were consistent with the individual’s core values. April and Avalon can help demonstrate the importance of personally meaningful goals. Both of them want to get in shape and learn how to play the piano. For April, however, getting in shape is far more meaningful than playing the piano whereas the opposite is true for Avalon. Exercising, therefore, is more likely to promote the wellbeing of April compared to Avalon, whereas playing the piano is more likely to promote the well-being of Avalon compared to April. Are approach goals more meaningful to individuals than avoidance goals? There is currently no evidence to suggest that approach and avoidance goals differ in how meaningful or important they are to individuals, nor is there a reason to expect them to differ (Elliot & Church, 2002). To the extent that any goal can be personally meaningful, individuals may be able to experience meaning in life as they pursue approach or avoidance goals, as long as the goals they pursue are meaningful to them. It is theoretically possible, therefore, that some individuals view approach goals as more meaningful than avoidance goals. As an example, for April, winning the $100 prize in the pumpkin pie festival may be more meaningful than selling enough pies to cover her $100 investment. It is also theoretically possible, however, that some individuals view avoidance goals as more meaningful than approach goals. For Avalon, for example, selling enough pies to cover her investment is more important than winning the monetary prize. To the extent that both April and Avalon can fill their life with meaning by pursuing goals that are important to them, April is more likely to find meaning in life by pursuing approach goals, whereas Avalon is more likely to find meaning in life by pursuing avoidance goals. In summary, both approach and avoidance goals have the potential of promoting well-being by filling life with meaning. What is it, however, that leads individuals to view some goals as more meaningful than others? Clearly, individuals vary dramatically in the goals that they find personally meaningful. In the remainder of the chapter,

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we explore the role of individual differences in moderating the link between approach–avoidance goals and well-being.

INDIVIDUAL DIFFERENCES MODERATE THE LINK BETWEEN APPROACH–AVOIDANCE GOALS AND WELL-BEING The importance of individual differences has been highlighted in research on motivation as well as in research on well-being. Individual differences are critical in determining the propensity to pursue approach or avoidance goals (see Larsen, 2008). Individual differences are also critical in predicting overall levels of well-being (for a review, see Diener & Lucas, 1999). In fact, individuals who typically pursue approach goals tend to have higher levels of well-being, whereas those who typically pursue avoidance goals tend to have lower levels of well-being (Carver, Sutton, & Scheier, 2000; Urry et al., 2004). Prior research on individual differences assumed that the link between approach–avoidance goals and wellbeing is relatively fixed. In other words, there is a fixed balance between approach and avoidance goals that is optimal for well-being. From this perspective, individual differences cannot change the link between approach– avoidance goals and well-being, but they can determine which goals are more likely to be pursued and what level of well-being the individual is predisposed to experience. In this chapter, however, we propose a novel approach. We argue that the link between approach–avoidance goals and well-being is relatively dynamic. In other words, the balance between approach and avoidance goals that is optimal for well-being varies as a function of individual differences. For some individuals, increasing the pursuits of approach (vs. avoidance) goals may be beneficial for well-being, whereas for others this may carry little benefit. In other words, individual differences can change the nature of the link between approach– avoidance goals and well-being. What kind of individual differences might moderate the link between approach–avoidance goals and wellbeing? Building on activity and telic theories, two types of individual differences may be critical. Activity theories emphasize the importance of goal desirability. From this perspective, individual differences in the desirability of goals should moderate the link between goals and well-being. Second, telic theories emphasize the importance of goal feasibility (i.e., the likelihood of successful goal pursuits). From this perspective, individual differences in the feasibility of goals should moderate the link between goals and well-being.

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The desirability and feasibility of goals also feature prominently in theories of self-regulation as determinants of the personal value of goals (Ajzen, 1985; Gollwitzer, 1990; Heckhausen & Leppmann, 1991). In the following sections, therefore, we discuss the importance of individual differences in the desirability and feasibility of approach–avoidance goals and the potential implications of such differences for well-being. We begin by reviewing individual differences in the desirability of goals and proceed to review individual differences in the feasibility of goals. In each case, we review the role of individual differences from a theoretical perspective and then discuss one empirical example.

DESIRABILITY OF APPROACH AND AVOIDANCE GOALS: AN ACTIVITY THEORY PERSPECTIVE Individuals prefer to pursue goals that are desirable to them. The desirability of goals, in turn, is determined by the perceived attractiveness of goal attainment. Focusing on pleasure as the determinant of well-being, goal desirability should be determined by the degree of pleasant affect that is expected to result from goal attainment. The pursuit of goals that are expected to yield pleasant affect when attained (i.e., desirable goals) should promote well-being. Focusing on meaning as the determinant of wellbeing, goal desirability should be determined by the extent to which the goal is consistent with a person’s daimon, or true self (Ryan & Deci, 2000; Waterman, 1993). The pursuit of authentic (i.e., desirable) goals should promote well-being (Harter, 2002). For example, the self-concordance model (Sheldon & Elliot, 1999) maintains that the pursuit of self-concordant goals (i.e., goals that are consistent with the core values of the individual) moderates the link between goal attainment and well-being. Such moderation was found to be independent of self-efficacy, indicating that the desirability of goals can be separable from their feasibility. Individual differences in the desirability of approach– avoidance goals, therefore, may moderate their impact on well-being. For instance, if April perceives approach goals as more desirable than Avalon, she may find working for a promotion more rewarding and meaningful. The process of pursuing approach goals, therefore, may be more conducive to the well-being of April than Avalon. Indeed, we argue that individuals who view approach goals as more desirable than avoidance goals should be more likely to benefit from pursuing approach goals.

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However, individuals who view avoidance goals as more desirable than approach goals may not benefit as much from pursuing approach goals. To support this argument, in the next section we review cultural differences as reflecting individual differences in the desirability of approach and avoidance goals.

DESIRABILITY OF APPROACH–AVOIDANCE GOALS: CULTURAL DIFFERENCES AS AN EXAMPLE In this section, we focus on the role of culture in determining the desirability of approach and avoidance goals and the implications of such differences for well-being (for reviews on cultural differences in well-being, see Diener et al., 2003; Diener & Suh, 2000; Tov & Diener, 2007). We have emphasized the role of goal desirability as moderating the impact of goals on well-being. Indeed, many agree that the implications of a goal for well-being depend on the extent to which it is considered desirable in a given culture (Cantor & Sanderson, 1999). The role of culture in determining the desirability of goals has been explored primarily in the context of individualistic versus collectivistic cultures, focusing on the comparison between European Americans and Asians, respectively (e.g., Oishi, Schimmack, Diener, & Suh, 1998). In this context, there is evidence that culture determines the desirability of goals. For instance, individualistic goals are perceived as more desirable in individualistic cultures whereas collectivistic goals are perceived as more desirable in collectivistic cultures (Triandis, 1995). Furthermore, the pursuits of goals that are desirable according to cultural norms are more likely to promote well-being. For instance, pursuing goals that are consistent with individualistic values promoted well-being among European Americans but not Asian Americans. On the other hand, pursuing goals that are consistent with collectivistic values promoted wellbeing among Asian Americans, but not European Americans (Oishi & Diener, 2001). Individualistic and collectivistic cultures also differ in the extent to which approach and avoidance goals are considered desirable. In particular, compared to collectivistic cultures, individualistic cultures view approach goals as more desirable (Elliot, Chirkov, Kim, & Sheldon, 2001; Lee, Aaker, & Gardner, 2000). If well-being is enhanced by the pursuit of desirable goals, pursuing more approach than avoidance goals should promote the wellbeing of members of individualistic cultures (e.g., European Americans) but not the well-being of members of collectivistic cultures (e.g., Asians). This indeed seems to be the case. Although pursuing more approach than avoidance goals was conducive to the well-being of

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European Americans, this was not the case for Asian Americans, Koreans, and Russians (Elliot et al., 2001). It appears, therefore, that pursuing more approach than avoidance goals is conducive to well-being particularly in cultures that view approach goals as more desirable than avoidance goals. The pursuit of more approach than avoidance goals, however, does not promote wellbeing in cultures that consider approach and avoidance goals as equally desirable. This may be because the desirability of approach–avoidance goals influences how meaningful they are to the individual. More meaningful pursuits are more likely to promote well-being. Can the desirability of approach–avoidance goals also carry affective implications? In general, approach goals are associated with excitement or sadness whereas avoidance goals are associated with calmness or anxiety. Although the affective implications of approach and avoidance goals are likely consistent across individuals, their impact on well-being may differ across cultures. For instance, if approach and avoidance goals differ in their desirability across cultures, the affective experiences that are linked to approach and avoidance may also differ in their desirability across cultures. On the basis of an instrumental approach to emotion (Tamir, 2005; Tamir, Chiu, & Gross, 2007), individuals seek out either emotions that are pleasant or emotions that are instrumental for important goal pursuits. For instance, although it is unpleasant to experience, an individual may view anger as desirable when her goal is to confront a wrongdoer. Applying these assumptions to the present context, one could argue that cultures value affective experiences that are associated with the pursuit of culturally desirable goals. The idea that some cultures may value excitement, for example, more highly than other cultures may sound surprising to some. However, consistent with the predictions of the instrumental approach to emotion, there is now evidence that cultures differ in the affective experiences that they value. In a large cross-cultural study, Eid and Diener (2001) found that pride, which reflects approach goals, was viewed as more desirable by members of individualistic cultures. More recently, Tsai and her colleagues (Tsai, Knutson, & Fung, 2006) found that even after controlling for actual affect, European Americans valued feelings such as excitement that reflect approach goals. On the other hand, Asian Americans and Chinese valued feelings such as calmness and relief that reflect avoidance goals. In other words, members of individualistic (vs. collectivistic) cultures view approach-related affect as more desirable, whereas members of collectivistic (vs. individualistic) cultures view avoidance-related affect as more desirable.

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What are the implications of cross-cultural differences in affect valuation for well-being? One compelling question for future research is whether approach-related emotions are stronger predictors of well-being among individualistic cultures, whereas avoidance-related emotions are stronger predictors of well-being among collectivistic cultures. Although this hypothesis has not been tested directly, it is consistent with the idea that the impact of emotional experiences on well-being depends upon the desirability of such experiences in a given culture (Markus & Kitayama, 1994; Schimmack, Radhakrishnan, Oishi, Dzokoto, & Ahadi, 2002). Another important question involves the specific cultural beliefs that underlie such differences. Given that the studies reviewed above involved mainly Asian samples, it may be useful to explore whether the obtained cultural differences are associated with collectivism, broadly construed, or with the Confucian system, more specifically. In summary, the research reviewed in this section demonstrates that cultures differ in the desirability of approach and avoidance goals. Whereas individualistic (vs. collectivistic) cultures view approach goals as more desirable, collectivistic (vs. individualistic) cultures view avoidance goals as more desirable. As a result, the pursuit of approach goals is more meaningful to members of individualistic cultures and the emotions they give rise to are considered more desirable. It is, therefore, not surprising that the pursuit of approach (vs. avoidance) goals promotes well-being in individualistic, but not collectivistic, cultures. What about the pursuit of avoidance goals? Such pursuits do not necessarily impair well-being in members of collectivistic cultures. Whether or not the pursuit of avoidance (vs. approach) goals can promote well-being in collectivistic cultures remains to be seen.

FEASIBILITY OF APPROACH AND AVOIDANCE GOALS: A TELIC THEORY PERSPECTIVE As outlined earlier, both the process and the outcome of goal pursuit has implications for well-being. Indeed, individuals differ not only in how desirable a goal is for them but also in how feasible it is. Feasibility is determined by individuals’ judgments of their capabilities to perform relevant goal-directed behaviors (i.e., selfefficacy, Bandura, 1977) and the beliefs that these behaviors will be successful (Oettingen & Gollwitzer, 2004). Individuals prefer to pursue goals that are feasible to them (Brunstein, 1993) and the pursuit of feasible goals, in turn, promotes well-being (Brunstein et al., 1999).

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Feasibility or self-efficacy might be based on inherent skills and prior experience in pursuing the goal (Bandura, 1977). Individual differences in the feasibility of approach– avoidance goals, therefore, may moderate their impact on well-being. For instance, if successfully pursuing approach goals is more feasible for April than for Avalon, winning the first prize in the country fair may be more conducive to the well-being of April than Avalon. Indeed, we argue that individuals for whom approach goals are more feasible than avoidance goals should be more likely to benefit from pursuing approach goals. What about individuals for whom avoidance goals are more feasible than approach goals. Might it be possible that for these individuals, the pursuit of avoidance goals may be beneficial in some respect? To explore these questions in the next section, we review evidence for regulatory fit as reflecting individual differences in the feasibility of approach and avoidance goals.

FEASIBILITY OF APPROACH–AVOIDANCE GOALS: REGULATORY FIT AS AN EXAMPLE Might the pursuit of approach or avoidance goals be more feasible to some individuals compared to others? Research on regulatory fit suggests that the answer is yes. Regulatory fit is the sense of value that arises when people act in a way that sustains their motivational orientation (Higgins, 2000). For example, if an individual is primarily motivated to approach, framing a goal in terms of a desired end-state increases the value of pursing the goal. Similarly, if an individual is primarily motivated to avoid, framing a goal in terms of avoiding an undesired end-state increases the value of pursing that goal. When individuals pursue goals in a way that fits their motivational orientation, they are more engaged in goal pursuit, view the pursuit as more valuable, and are more likely to be successful (Förster, Higgins, & Idson, 1998; Higgins, Idson, Freitas, Spiegel, & Molden, 2003; Higgins et al., 1994; Shah, Higgins, & Friedman, 1998). Individuals also experience greater enjoyment during goal pursuit when they pursue the goal in a manner that fits their dispositional orientation (Freitas & Higgins, 2002). Such effects may be driven by the greater feasibility of motivationally consistent goals. Mann, Sherman, and Updegraff (2004) found that individuals were more effective in promoting health behaviors when health messages were framed in ways that matched their underlying motivational dispositions. Individuals who were approach motivated were more successful when health messages were framed as approach goals, whereas individuals who were avoidance motivated were more successful when

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health messages were framed as avoidance goals. Consistent with the emphasis of a telic approach on feasibility, the effects were fully mediated by perceptions of self-efficacy in goal pursuit (Sherman, Mann, & Updegraff, in press). Thus, if April is an approach-oriented person, she might find working toward winning the first prize in the pumpkin pie festival more feasible than selling enough pies. Such pursuits would be more enjoyable to her and she might eventually be more successful at them. On the other hand, if Avalon is an avoidance-oriented person, she might find selling enough pies to cover her expenses more feasible than winning the first prize. She might be more motivated to do so, and ultimately she might be more successful in doing so. The feasibility of approach–avoidance goals influences how meaningful they are to the individual. But what are the implications of greater goal feasibility for affective experiences? Recent evidence suggests that the feasibility of goals may determine the intensity of goalrelated emotional reactions. Idson, Liberman, and Higgins (2000) found that compared to approach-oriented individuals, avoidance-oriented individuals were less happy following the successful pursuit of approach goals and less sad following the unsuccessful pursuit of approach goals. On the other hand, they were calmer and more relieved following the successful pursuit of avoidance goals and more anxious following the unsuccessful pursuit of avoidance goals. These findings are astounding because they suggest that the affective consequences of goal pursuits might vary across individuals. April, for instance, may feel better (i.e., more excited) if she wins the first prize at a competition, whereas Avalon may feel better (i.e., more relieved) if she manages to sell enough pies to cover her expenses. The intensity of affective reactions to success and failure in goal pursuit may depend on how feasible the goal is for the individual. Furthermore, the implications of affective experience for well-being may also differ as a function of goal feasibility. In fact, individual differences in approach and avoidance motivation influence the extent to which wellbeing depends on pleasant and unpleasant affective experiences. Empirical evidence for this hypothesis was recently provided by Updegraff, Gable, and Taylor (2004). These authors demonstrated that the more approachoriented individuals were, the more they tended to base their judgments of well-being on the frequency of their pleasant affect. This finding suggests that the weight of pleasant and unpleasant affect in judgments of well-being may itself vary as a function of motivational dispositions.

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In summary, research on regulatory fit demonstrates that the feasibility of approach and avoidance goals varies as a function of basic motivational orientations. Pursuing approach goals may be more feasible for approach-oriented individuals, whereas pursuing avoidance goals may be more feasible for avoidance-oriented individuals. The pursuit of feasible goals, in turn, is likely to promote well-being because it is more meaningful, the chances of success are higher, and success leads to more intense pleasant experiences. On the basis of this analysis, approach-oriented individuals may be expected to experience greater well-being when pursuing more approach than avoidance goals. What about avoidance-oriented individuals? On the one hand, as discussed earlier, avoidance goals are harder to monitor and engender negative cognitions. Avoidance goals, therefore, should theoretically impair the well-being of avoidanceoriented individuals in some ways. On the other hand, as discussed in this section, avoidance goals may be more meaningful and feasible for avoidance-oriented individuals. Avoidance goals, therefore, could theoretically also contribute to the well-being of avoidance-oriented individuals in some ways. What are the implications of pursuing avoidance goals for avoidance-oriented individuals? We conclude this chapter by discussing this conflicting goal pursuit.

CONFLICTING GOAL PURSUITS OF AVOIDANCE-ORIENTED INDIVIDUALS In the previous sections, we argued that individual differences in the desirability and feasibility of goals can moderate the impact of such goals on well-being. In particular, we proposed that approach goals may be more desirable and feasible for individuals who are high (vs. low) in approach motivation. On the other hand, avoidance goals may be more desirable and feasible for individuals who are high (vs. low) in avoidance motivation. As we have demonstrated above, the pursuit of desirable and feasible goals is likely to promote well-being. Approach-oriented individuals, therefore, benefit from approach goals because of the general attributes of these goals and because of their desirability and feasibility. What about avoidance-oriented individuals? On the one hand, these individuals are likely to suffer some negative consequences when pursuing avoidance goals because of the attributes of such goals. On the other hand, avoidanceoriented individuals may attain some benefits from pursuing avoidance goals because such goals are more feasible and perhaps more desirable to them. Avoidanceoriented individuals, therefore, are likely to experience some degree of conflict in their goal pursuits.

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Avalon, for example, may find avoidance goals difficult to monitor and pursuing such goals make her focus on unpleasant future outcomes. Nevertheless, she might find such goals to be personally meaningful, she might be more successful at obtaining them, and she may experience more intense pleasant affect as a result. It is therefore possible that the pursuit of avoidance goals is not as harmful for Avalon as it is for April. However, does the pursuit of avoidance goals benefit Avalon in any way? We have begun to explore this interesting possibility in the context of trait neuroticism, a trait that is closely related to the avoidance motivational system (Carver et al., 2000; Elliot & Thrash, 2002). We began by examining whether individuals who are high (vs. low) in neuroticism can benefit from the ability to successfully pursue avoidance goals (Tamir, Robinson, & Solberg, 2006). Specifically, we examined neurotic individuals who varied in the extent to which they were skilled at identifying threats. Individuals who can quickly identify threats are more likely to successfully avoid them (Öhman, 2001; Robinson, 1998). Therefore, we expected individuals high in neuroticism to benefit from being skilled at threat identification. Our results supported this hypothesis. Neurotic individuals who were relatively skilled at threat identification experienced lower levels of negative affect in their daily lives over a week long period as well as higher levels of satisfaction in various life domains (Tamir et al., 2007). These findings suggest that individuals high (vs. low) in neuroticism may benefit in some respects from the successful pursuit of avoidance goals. Emotions can also promote successful goal pursuits. For instance, emotions direct attention toward potentially threatening or rewarding information (Mogg & Bradley, 1998; Oatley & Johnson-Laird, 1987; Tamir & Robinson, 2007), instigate physiological responses that support approach or avoidance behaviors (Frijda, 1988; Panksepp, 1982), and signal the effectiveness with which people are pursuing their goals (Carver, 2001). In particular, avoidance-related emotions, such as worry or anxiety, may promote the successful pursuit of avoidance goals (Parrott, 2002). If avoidance emotions (e.g., worry) promote the pursuit of avoidance goals, would the experience of such emotions promote the successful goal pursuits of neurotic individuals? Furthermore, assuming that successful goal pursuits promote well-being, would neurotic individuals be motivated to experience such emotions when engaged in goal pursuit? We recently tested these counterintuitive hypotheses by having neurotic individuals perform an anagram task following either a happy or a worried mood induction (Tamir, 2005). Individuals who were high in

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neuroticism solved more anagrams correctly following a worried (vs. happy) mood induction. Furthermore, individuals high (vs. low) in neuroticism were more motivated to increase their level of worry when they expected to perform a motivationally significant task. Taken together, these findings demonstrate that neurotic individuals may benefit, at least in some respect, from the ability to effectively pursue avoidance goals. These findings, however, do not necessarily show that pursuing avoidance goals is beneficial for the well-being of avoidance-oriented individuals. Instead, we propose that pursuing avoidance goals may have mixed implications (i.e., harmful in some respects and beneficial in others) for avoidance-oriented individuals. In summary, we argue that approach and avoidance goals can have both main effects as well as interactive effects on well-being. Some implications of goal pursuits are likely identical across individuals. Other implications of goal pursuits, however, likely differ among individuals. For instance, individuals differ in the extent to which approach and avoidance goals are desirable or feasible to them, leading such goals to have potentially different implications for affective experiences and meaning in life. For some individuals (e.g., approach-oriented), pursuing avoidance goals carries little benefit. For other individuals (e.g., avoidance-oriented), pursuing avoidance goals may carry at least some temporary benefits. The overall impact of avoidance goals on well-being may be influenced by the relative weight of their different implications (e.g., the cognitive content they evoke vs. how personally meaningful they are) and by the degree of conflict they evoke. Exploring the overall impact of avoidance goals on the well-being of avoidance-oriented individuals is an important endeavor for future research.

Approach goals also elicit positive cognitions, by leading individuals to focus on desirable outcomes. Avoidance goals, on the other hand, are more difficult to monitor and they elicit negative cognitions, by leading individuals to focus on undesirable outcomes. These characteristics make the pursuit of approach goals generally beneficial for well-being. In this chapter, however, we argued that the implications of approach and avoidance goals for well-being can also vary dramatically across individuals. Well-being, for instance, is enhanced by the pursuit of personally meaningful experiences. In particular, the pursuit of goals that are desirable and feasible is conducive to well-being. The desirability and feasibility of approach and avoidance goals vary as a function of motivationally relevant individual differences. Which goals are most likely to promote well-being? A combination of both approach and avoidance goals is important for adaptive functioning. We have argued that the extent to which individuals should pursue more approach than avoidance goals is influenced by the desirability and feasibility of these goals for a given individual. Individuals for whom approach goals are desirable or feasible may experience greater well-being if their goal pursuits are heavily skewed toward approach goals. This, however, is not the case for individuals for whom avoidance goals are desirable or feasible. Such individuals may not necessarily benefit from pursuing approach goals and may even benefit in certain ways from pursuing avoidance goals. As we have learned from April and Avalon, no single mix of approach and avoidance goals is optimal for the well-being of all individuals. Instead, to maximize well-being, individuals may need to find the mix that fits them best.

SUMMARY

REFERENCES

What is the source of happiness? What gives meaning to life? What makes life worth living? Greater well-being results from experiencing more frequent pleasant and less frequent unpleasant affect and from having personally meaningful experiences in life. In this chapter, we argued that the pursuits of approach and avoidance goals are inextricably linked to well-being because both the process and the outcome of their pursuits can shape affective experiences as well as provide meaning to life. What are the differential implications of approach and avoidance goals for well-being? Some of these implications are consistent across individuals. In particular, approach goals are likely easier to monitor so that perceived progress is likely greater during their pursuit.

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Part VI Cognition

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Challenge and Threat Appraisal

25 Challenge and Threat Jim Blascovich CONTENTS Challenge–Threat as Approach–Avoidance .......................................................................................... 432 Integration of Physiological Energization and Evaluation Theory ....................................................... 433 Overview .......................................................................................................................................... 433 Theoretical Roots ............................................................................................................................. 433 Biological Component ................................................................................................................. 433 Psychological Component............................................................................................................434 Integration....................................................................................................................................434 Validational Studies..........................................................................................................................434 Correlational ................................................................................................................................434 Experimental ...............................................................................................................................434 Predictive .....................................................................................................................................436 Summary ..........................................................................................................................................436 Biopsychosocial Model of Challenge and Threat ................................................................................. 437 Overview .......................................................................................................................................... 437 Nature and Limitations of Motivated Performance Situations ........................................................ 437 Goal Relevance and Task Engagement ........................................................................................ 437 Limits of Generalizability ...........................................................................................................438 Task Engagement and Energization .................................................................................................438 Resource/Demand Evaluations ........................................................................................................438 Physiological Modulation of Energization .................................................................................. 439 Performance and Feedback .............................................................................................................. 439 Research ................................................................................................................................................ 439 Overview .......................................................................................................................................... 439 Intraindividual Processes .................................................................................................................440 Dispositions: Belief in a Just World .............................................................................................440 Dispositions: Stability of Self-Esteem .........................................................................................440 Attitudes: Functionality ...............................................................................................................441 Beliefs ..........................................................................................................................................441 Interindividual Processes .................................................................................................................442 Social Facilitation ........................................................................................................................442 Social Comparison.......................................................................................................................442 Stigma ..........................................................................................................................................442 Stereotype Threat ........................................................................................................................443 Summary ...............................................................................................................................................443 References .............................................................................................................................................444

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The biopsychosocial model (BPSM) of challenge and threat has evolved over the last decade or so, becoming increasingly more complex as more evidence has accumulated (Blascovich, 2007; Blascovich & Mendes, 2000; Blascovich & Tomaka, 1996). This chapter begins with a discussion of the relationships of the model’s banner motivational constructs and the more general concepts of approach and avoidance motivation as elucidated in the introductory chapter to this volume and elsewhere, a comparison that has not been explored in any detail in the past. Such a comparison not only informs our challengethreat model but also may help expand understanding of approach–avoidance motivation more generally. The current version of the BPSM of challenge and threat motivation is presented subsequently with attention to selected approach–avoidance energization models.

CHALLENGE–THREAT AS APPROACH–AVOIDANCE Based on his broad and informed knowledge of the history of approach and avoidance motivational theory as well as his own contributions, Elliot (this volume; Elliot & Trash, 2002) defines approach motivation as the energization of behavior directed toward positive or desirable stimuli and avoidance motivation as the energization of behavior directed away from negative or undesirable stimuli. Elliot (this volume) argues convincingly that both energization and direction are necessary elements of approach–avoidance motivation. However, he points out that the direction of movement may in some cases (i.e., those associated with automatic evaluation) be predispositional and covert rather than overt, but still result in underlying physiological and somatic responses preparatory for approach and withdrawal. There are, of course, at least two other logical possibilities regarding the relationship of energization and direction; specifically, energization toward negative stimuli, and energization away from positive stimuli. What may energize and “move” people in these directions has to do with relationships among goals. Specifically, energization toward a positive superordinate but distal goal (e.g., entering a profession) may require energization or movement toward a negative subordinate proximal goal (e.g., taking very difficult exams). Furthermore, energization away from a negative superordinate distal goal (e.g., going bankrupt, going to jail) may require energization and movement away from a positive subordinate proximal goal (e.g., creating an overly optimistic business plan, selling recreational drugs). Hence, as Elliot (2006) and others have pointed out, one must take motivational hierarchies into account to understand

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approach and avoidance especially as they relate to approach–avoidance conflicts. According to the BPSM, challenge results when an individual’s evaluated resources outweigh situational demands and threat results when evaluated situational demands outweigh an individual’s resources. If individuals were merely motivated by purely hedonistic goals of experiencing positive affect and avoiding negative affect on a moment by moment basis (as might be the case for infants, young children at times, and addicts), then challenge would map onto approach (and energization and task engagement) and threat onto avoidance (and energization and task disengagement) and that would be the end of it. However, in order to achieve a desirable superordinate goal (e.g., entering a profession), an individual may be required to approach a series of subordinate goals (e.g., doing well on exams in school) that may prove threatening (i.e., ones in which an individual may not evaluate himself or herself as having personal resources that outweigh situational demands) to reach. Yet the superordinate goal is perceived as desirable enough (or the alternative to reaching the superordinate goal is so undesirable; e.g., flipping burgers for a living) that individuals will be energized to approach a necessary but negative subordinate goal and perform in what they themselves evaluate as threatening situations, even to the point of jeopardizing their physical well-being (Anderson et al., 1993; Blascovich, 2007). In order to provide an understanding of the ways in which challenge and threat constructs relate to approach and avoidance, one must take into account the context within which the BPS model of challenge and threat is generally applied, the hierarchical nature of goals, and Elliot’s important caveat regarding a possible disjunction between predispositions and actual (and we would add “gross”) movements, If one does so, the concepts of challenge and threat relate to Elliot’s approach–avoidance definitions albeit in a perhaps unexpected but important way. The BPS focuses on contexts that are labeled motivated performance situations, ones that we assume are goal relevant and, hence, task engaging for individuals, and ones that require instrumental cognitive responses (e.g., answering questions on exams, presenting material in lectures, the “gives” and “takes” of bargaining and negotiation, arguing and debating, making chess moves, chiseling stone to create sculpture, etc.). Within this type of context, challenge clearly fits within Elliot’s notions of energization and movement or approach toward positive or desirable stimuli. Arguably, however, the BPSM construct of threat can also be categorized as an approach construct but one involving movement toward negative or undesirable stimuli. Furthermore, because of the disjunction between

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Challenge and Threat

hedonic qualities of movement (i.e., toward) and affect (i.e., negative stimuli) for threat, the nature of threat approach undoubtedly differs from that of challenge as there is likely a tension between the need to approach and the desire to avoid. Hence, it fits long-lived notions of approach–avoidance conflict. Although both challenge and threat involve psychological, physiological, and sometimes overt physical movement toward a goal, threat includes at least predispositional (in Elliot’s terms) elements (e.g., neurophysiological and somatic ones) of movement away from a goal. Because of this tension, threat is likely the more variable, fragile, disruptible, and stressful of the two. Because both challenge and threat as so defined involve approach, they can be regarded as anchors of a bipolar motivational continuum separating them by degree of avoidance (see more discussion of this continuum below).

INTEGRATION OF PHYSIOLOGICAL ENERGIZATION AND EVALUATION THEORY OVERVIEW The BPSM of challenge and threat is so named because it attempts an integration of biological, psychological, and social psychological levels of analysis to explain motivational processes within human performance contexts, which in our view are necessarily social because nearly every aspect of human performance is influenced by the actual, imagined, and implied presence of others. The model also integrates processes within each of these levels of analysis. Within the biological level, the BPSM focuses on the interplay between autonomic and endocrine influences on the cardiovascular system. Within the psychological level, it incorporates cognitive and affective influences on evaluative processes. Within the social psychological level, it integrates intraindividual, interindividual, and environmental influences. Challenge/threat motivation is rooted in all three levels of analysis and the interplay within and among them. Hence, in our view, challenge and threat represent person/situation-evoked motivational states with affective, cognitive, and physiological antecedents and consequences.

THEORETICAL ROOTS Biological Component The BPSM is rooted in physiological energization theory, specifically Richard Dienstbier’s (1989) theory of physiological toughness. Based nearly exclusively on animal work, Dienstbier theorized that differing patterns of cardiovascular

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responses during potentially threatening performance situations (e.g., foraging for food in the vicinity of predators) represent differences in the near term for task performance and in the far term for survival. His work identified central nervous system controlled neural and endocrine processes that give rise to two different patterns of cardiovascular responses in potentially threatening performance situations, such as those necessary for survival among members of the same mammalian species (e.g., squirrels): one for those animals who appear to thrive during and following performance and one for animals who do not. Dienstbier labeled the performance and survival enhancing pattern as “physiological toughness,” leaving the performance and survival reducing pattern to be labeled “physiological weakness.” In terms of neurophysiological processes, both the physiological toughness and physiological weakness patterns involve sympathetic neural and adrenal medullary (SAM) axis activation. Such activation produces increased sympathetic neural stimulation increasing myocardial (i.e., heart muscle) contractility, more specifically left ventricle contractility (VC) and heart rate (HR). The left ventricle is the final pumping chamber of the heart forcing blood to the body through the aortic value and via the aorta. The adrenal medullary aspect of SAM axis activation eventuates in the release of epinephrine into the bloodstream further increasing HR and dilating the arteries, thereby decreasing total systemic peripheral vascular resistance (TPR). The result is relatively large increases in blood flow as measured by cardiac output (CO). However, in addition to SAM activation, physiologically weak animals experience activation of the hypothalamic pituitary adrenal (HPA) axis, more specifically the pituitary adrenal cortical (PAC) axis, along with the SAM activation. This HPA activation results in sustained adrenal cortical release of cortisol that dampens the SAM effects on TPR, thereby eliminating SAMdriven decreases in TPR (and often actually increasing TPR), thereby decreasing SAM-driven CO. By providing a neurophysiological rationale based on the SAM and HPA axes, specifying a set of measurable cardiovascular responses (VC, HR, CO, and TPR) sensitive to SAM and HPA activation, and specifying distinctive patterns among critical cardiovascular responses within that set, Dienstbier presented a clear distinction of functional and dysfunctional cardiovascular response patterns during goal-relevant performance situations in animals. Subsequently, we (see below) experimentally tested his notions regarding these responses in humans in order to verify whether or not they presented as clear a distinction of functionality during goal-relevant performance situations as in animals.

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Psychological Component The BPSM is rooted in cognitive appraisal theories, particularly that of Lazarus (1991) and his colleagues (Lazarus & Folkman, 1984). Indeed, in the past we freely borrowed and used the term appraisal as in “appraisal of personal resources and situational demands” (cf. Blascovich & Tomaka, 1996). However, over time and in concert with increasing evidence of the important operational role of nonconscious or automatic processes, particularly those related to affect in everyday behavior (cf. Blascovich & Mendes, 2000), we realized that the determining processes were often much less conscious than the label “cognitive appraisal” implies. Subsequently, we came to label the central psychological process as one of “evaluation,” which we believe not only has less conscious and cognitivistic connotations but also allows for the incorporation of more purely affective influences. Integration Lazarus and Folkman’s appraisal model (1984) on coping and stress suggested that the human antecedents of what Dienstbier (1989) had described in animals as physiological toughness and weakness involved cognitive appraisals or evaluations of goal relevance, performance demands, and coping resources. If such evaluations in humans were predictably associated with Dienstbier’s specified cardiovascular patterns of toughness and weakness responses, the biological and psychological aspects of performance motivation within a unified theory could be integrated. Furthermore, if Dienstbier’s work generalizes to humans, the cardiovascular patterns he identified could be utilized to identify motivational states in humans as a function of personality, social psychological, and context factors. Hence, we hypothesized that if an individual evaluated his or her personal resources as meeting or exceeding the demands of a goal-relevant performance situation, a positive hedonically toned motivational state, which we labeled challenge, would result. We also hypothesized that if an individual evaluated his or her personal resources as not meeting the demands, a negative hedonically toned motivational state would result, which we labeled threat.

VALIDATIONAL STUDIES Our empirical validational studies involved laboratorybased motivated performance situations as described above (ones that are goal relevant and task engaging and that require instrumental cognitive responses; i.e., active coping tasks; Obrist, 1981). These performance situations

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involved laboratory tasks such as vocal serial subtraction (i.e., “mental arithmetic”) and giving speeches, tasks often used by scientists in the cardiovascular psychophysiology community. The validational studies fall into three categories: correlational, experimental, and predictive. Measurement and recording equipment, including electrocardiographic, impedance cardiographic, and hemodynamic (i.e., blood pressure) measurement technologies described elsewhere (Blascovich, 2000; Blascovich & Seery, in press), allowed the assessment and or derivation of the cardiovascular response patterns (see Figure 25.1) of VC, HR, CO, and TPR specified by Dienstbier noninvasively in humans. In all of these studies, resting baseline measurements were recorded followed by measures during task performance. As is the common practice in cardiovascular psychophysiology research, reactivity scores were calculated by subtracting the last minute of asymptoted baseline values from corresponding values assessed during the tasks. Correlational We ran a series of correlational experiments to ascertain the association between self-reported evaluations of personal resources and situational demands made prior to task performance and patterns of cardiovascular responses during subsequent motivated task performance. In accord with the general hypotheses derived from our integration of Lazarus and Folkman’s (1984) appraisal theory and Dienstbier’s theory of physiological toughness, we hypothesized that evaluations of personal resources exceeding situational demands would result in a challenge motivational state that would be associated with increases in HR, VC, and CO, and a decrease in TPR, and that an evaluation of demands exceeding resources would be associated with increases in HR and VC, but little change in CO and little change or even increases in TPR (see Figure 25.1). As Figure 25.2 illustrates, our hypotheses were confirmed in these experiments (Tomaka, Blascovich, Kelsey, & Leitten, 1993) thereby extending the generalizability of Dienstbier’s work to humans. Experimental In order to determine whether the relationship between the evaluation of perceived demands and resources causes the cardiovascular patterns specified by Dienstbier, we experimentally manipulated overall challenge and threat evaluations prior to task performance and assessed subsequent CVR patterns during task performance. In this experiment (Study 1 in Tomaka, Blascovich, Kibler, & Ernst, 1997), manipulations of instructional content via

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VC = (−1 ∗ PEP)

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FIGURE 25.1 Dienstbier’s patterns of physiological toughness—increased ventricular contractility (VC), heart rate (HR), cardiac output (CO), and decreased total peripheral resistance (TPR)—and weakness—increased VC, HR, little or no increase in CO and little change in or increased TPR. 30

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FIGURE 25.2 Tomaka et al. (1993) validational patterns of challenge and threat in humans based on Dientbier’s patterns of physiological toughness and weakness, respectively (see Figure 25.1).

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cognitive manipulation (practice vs. criterion) together with affective manipulation via instructional tone (friendly vs. hostile vocal tone) of task instructions led to the hypothesized challenge and threat patterns of CVR as we predicted. In another (Hunter, 2001), we manipulated whether participants received instructions informing them that they would either be read or sing the U.S. national anthem while we recorded their cardiovascular responses. In order to give them an experience of what this would be like, participants were instructed to read or sing the first couple of stanzas. Significantly more of the participants who anticipated and practiced singing exhibited the cardiovascular pattern associated with threat than individuals who anticipated and practiced reading. Significantly more of the participants who anticipated and practiced reading evidenced the challenge pattern than individuals who anticipated and practiced singing. We also examined the possibility of a reversal of causality, a version of the neo-Jamesian hypothesis, to determine whether the physiological toughness and weakness cardiovascular patterns could somehow cause challenge and threat evaluations, respectively. To do so, we performed two experiments (Studies 2 and 3 in Tomaka et al., 1997) in which we experimentally manipulated physiology via physical means so that participants would experience a pattern of cardiovascular responses that mimic the challenge and threat patterns. In one study, participants either pedaled a bicycle ergometer (i.e., “exercise bike”) at a moderate workload (i.e., 50 watts) or sat stationary on it. Aerobic exercise is accompanied by a pattern of cardiovascular responses that mimics physiological toughness or challenge, whereas sitting stationery does not. In the other study, participants either immersed their hands in a warm or ice bath (i.e., pressors). The warm pressor typically is accompanied by a pattern of cardiovascular responses that mimics physiological toughness or challenge; the cold pressor typically is accompanied by a pattern that mimics physiological weakness or threat. In each study, we asked participants to self-report evaluations of demands and resources for an upcoming serial subtraction task during the manipulation (i.e., while on the ergometer or with hand immersed in the bath). Demand/resource evaluations did not differ as a function of the physical manipulations in either study, suggesting that interoception from the experience of the different cardiovascular patterns was not causally linked to demand/resource evaluations. Taken together, these experimental validational experiments indicate that the demand/resource evaluations are causally linked to Dienstbier’s patterns in humans. That is, these

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experimental studies provided strong evidence that Dienstbier’s patterns mapped on to our challenge and threat constructs. Predictive More recently, we (Blascovich, Seery, Mugridge, Weisbuch, & Norris, 2004) conducted a study to determine if the challenge–threat patterns of CVR are predictive of future performance. Members (position players other than pitchers; i.e., hitters) of our university’s varsity baseball and softball teams participated. Each athlete was required to give two three-minute speeches during which we recorded relevant cardiovascular data. One of the speeches was irrelevant to baseball/softball and served as a control for determining the level of cardiovascular responses related to challenge–threat caused by giving a speech in the laboratory experiment (“Why I am a good friend”). The second speech served as the experimental speech and was baseball-relevant (“How I would approach a critical hitting situation”). We derived a unitary physiological index of challenge–threat derived from our multiple cardiovascular measures for each speech. We collected offensive baseball statistics such as the runs generated index, batting averages, etc. during the varsity baseball season which began approximately 6 months after the experiment. Controlling for the unitary cardiovascular index of challenge–threat during the control speech, the unitary cardiovascular index of challengethreat reliably predicted the major measures of offensive baseball performance during the baseball-relevant speech (the runs generated index, batting averages, etc.) such that the greater the challenge the better the performance. Additionally, because there were no effects of sport (exclusively male-played baseball vs. exclusively female played softball) on these predictive relationships; gender was not a factor.

SUMMARY The validational studies confirm strongly that challenge and threat motivational states as defined and delineated in the BPSM involve the neuroendocrine processes described in Dienstbier’s theory of physiological toughness. Furthermore, given the assertion that both challenge and threat involve approach-like motivational states, the commonality of SAM access activity to both challenge and threat is likely associated with a physiological predisposition of movement toward a goal, and HPA activity is likely associated with a rudimentary predisposition to withdraw from a goal if necessary during threat. Most importantly, these validational studies demonstrate that

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psychological and biological substrates of motivational states are integrated and operate interactively. Additionally, these studies have validated distinctive patterns of cardiovascular responses as indexes of challenge and threat motivation. These indexes provide several methodological advantages—as they can be continuously and covertly recorded online—making them relatively impervious to sources of measurement error associated with more subjective self-report measures (e.g., impression management). Most importantly, these indexes can and have been used to test the motivational aspects of a wide range of personality and social psychological theories, not only informing these theories, but also providing further convergent validation of the indexes themselves.

BIOPSYCHOSOCIAL MODEL OF CHALLENGE AND THREAT OVERVIEW Figure 25.3 depicts the general components of the BPSM as described above. The model describes the theoretical processes underlying the generation of challenge–threat states within a motivated performance situation. The challenge–threat process is initiated when an individual becomes task engaged in a personally goal-relevant motivated performance situation requiring the performer to make resource and demand evaluations that result in energizing the individual for performance in ways consistent with challenge and threat. Interim performance

feedback informs reevaluation of demands and resources. Hence, the processes specified by the BPS follow a positive determination of goal relevance by the individual.

NATURE AND LIMITATIONS OF MOTIVATED PERFORMANCE SITUATIONS Goal Relevance and Task Engagement Because, by definition, motivated performance situations assume goal relevance, it follows that an individual’s performance must reach some standard in order to reach the self-relevant goal. Motivated performance situations differ from other more passive goal-relevant situations (e.g., watching a desirable movie) because they require instrumental actions that can be evaluated by others or the performers themselves. These actions are instrumental in the sense that they are necessary for the performance to continue to completion. If for example, a student was taking a standardized exam (e.g., SAT or GRE), the instrumental responses would take the form of answering each question in turn. If the student stopped answering questions before completing the exam, the situation would change dramatically from one of motivated performance to something more passive such as enduring emotional responses that do not require the same sort of instrumental cognitive responses. Within a motivated performance situation, instrumental actions may be primarily mental (e.g., silently rehearsing a speech) or more overt (e.g., giving a practice speech) in terms of affective, cognitive, and behavioral actions.

Sam activation Resource/demand evaluation

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FIGURE 25.3

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General components of the biopsychosocial model (BPS) of challenge and threat.

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Limits of Generalizability Note that the proponents of the BPS model have not extended its external validity nor the use of its indexes beyond motivated performance, or what some label active coping (cf. Obrist, 1981), situations. Furthermore, even within the limited motivated performance situation context, the cardiovascular indexes have not been validated in metabolically demanding ones (e.g., running a marathon), though research has shown that metabolic demands do not necessarily mask motivated performance situation driven changes in the relevant cardiovascular measures (Rousselle, Blascovich, & Kelsey, 1995). Nevertheless, these limitations do not minimize the external validity of the BPS model severely because motivated performance situations are ubiquitous in human societies. Most economies appear to be based on production and marketing of goods, services, or information that require a plethora of supportive activities, perhaps all of which are goal relevant for workers and require instrumental responses; that is, they are, motivated performance situations. Of course, motivated performance situations extend beyond work. They are also ubiquitous in terms of many interpersonal interactions, education and learning, recreation, volunteering, etc.

TASK ENGAGEMENT AND ENERGIZATION The goal relevance of a motivated performance situation drives task engagement; that is, the importance of the task to the individual determines the initial preparedness for action via the sympathetic neural component of the SAM axis. Hence, in terms of the cardiovascular markers, ventricular contractility (VC), which is largely sympathetically determined, and HR, which is both sympathetically and parasympathetically determined should increase relatively quickly, with neuroendocrine modulation of TPR and CO following a short time later (due to the relative speed of neural rather than endocrine activation). Continued modulation of all four cardiovascular responses depends on factors related to ongoing challenge–threat evaluations and activation of the HPA axis. Hence, neither HR nor VC increases can be regarded as distinctive to either challenge or threat, but rather mark task engagement proximally and goal relevance distally.

RESOURCE/DEMAND EVALUATIONS Once an individual is engaged in a motivated performance situation, a cybernetic evaluation–feedback process ensues. This process modulates challenge–threat motivation. Given increased VC and HR, the modulation can be

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marked by fluctuations in HPA axis influences on CO and TPR with increased CO and decreased TPR pointing toward the challenge end of the continuum and decreased or static CO and static or increased TPR pointing toward the threat end of the continuum (see Figure 25.1). Individuals iteratively reevaluate personal resources and situational demands as they gain additional experience in the motivated performance task situation including interim successes and failures. Such experience influences fluctuations within and between relevant evaluation factors (see below). Furthermore, we have experimentally demonstrated that these resource/demand evaluations can occur deliberately (i.e., consciously), automatically (i.e., unconsciously), or both. Furthermore, these dual processes can influence each other (cf. LeDoux, 1996). Finally, the evaluations can be primarily cognitive (e.g., semantic), affective (e.g., hedonic), or both. If the evaluative calculus results in unreasonable “ratios” of resources to demands; that is, ones which are extremely high (i.e., little or no probability of failure) or extremely low (little or no probability of success), the net effect will be disengagement because the task loses goal relevance (i.e., pragmatic meaning) for the performer, an argument based on Yerkes-Dodson’s Law. For example, if a rank amateur chess player were about to face a grand master, there would be little goal relevance and neither the amateur nor the master would likely be task engaged. However, if such calculus results in a midrange probability of success or failure (e.g., a chess match between two grand masters), goal relevance will be maintained and task engagement sustained. Furthermore, inherent or external interim feedback during performance via iterative reevaluation can skew the ratio in ways that decrease or increase goal relevance and task engagement. The most complex aspect of resource/demand evaluations involves specification of the factors or dimensions (i.e., antecedents) that may enter into the evaluation calculus. This complexity stems from the number of possible factors to be evaluated, their myriad interrelationships, and their subjectivity. Initially (Blascovich & Tomaka, 1996; Blascovich & Mendes, 2000), the BPS specified factors hierarchically within separate resource and demand categories. However, over time the model has been revised in this regard in recognition of the likelihood that almost any factor has implications for both resources and demands. Hence, factors are now specified (cf. Blascovich, 2007) as bipolar ones with regard to effects on resource and demand evaluations. Specified factors entering into this affective–cognitive evaluative calculus (see Figure 25.4) are ones within a Lewinian (1936) framework of person by situation factors

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Resources

Demands Safety/danger Uncertainty/certainty Novelty/familiarity Required effort Skills, knowledge, abilities Presence of others Attitudes

situation, SAM activation energizes him or her to perform. Once so engaged, however, continual iterative resource/ demand evaluations modulate SAM activation via HPA activation depending on the resource/demand ratio. If resources are sufficient to meet demands, little or no HPA activation occurs and challenge (i.e., Dienstbier’s physiological toughness pattern) predominates. If resources are insufficient HPA activation occurs and threat (i.e., physiological weakness pattern) predominates.

Beliefs

FIGURE 25.4 Factors in resource/demand evaluations.

that can interact among one another. They include: psychological and physical danger/safety, uncertainty/ certainty, novelty/familiarity, required effort, skills and knowledge, the presence of others, affective cues, attitudes and beliefs, etc. In other words, far more dimensions than those directly related to the performance requirements of the task itself (e.g., task difficulty) can influence the evaluation. For example, on the face of it, quickly serially subtracting “3’s” (or even on occasion “1’s”) from a four digit number would seemingly be challenging for almost anyone with an eighth grade education. However, in a situation in which such subtraction is carried out vocally, known to be monitored by highly evaluative others such as psychologists during a “psychology experiment,” and for which sensors have been placed on the individual to record their physiology, the performer’s evaluation of resources and demands is not so straightforward. Furthermore, these factors are not completely independent of each other. Rather, they tend to overlap (e.g., uncertainty/certainty and novelty/familiarity) and can be interactive or synergistic. For example, uncertainty can increase evaluated danger or required effort. Finally, although these factors are illustrative of ones that enter into resource/demand evaluations, undoubtedly, they do not represent the full set. Generally, perceptions of the levels of contributions of any of these factors to resource/demand evaluations are filtered via intraindividual processes including individual differences related to temperament, dispositional traits and states, and quality of self-knowledge. In addition, various interindividual social psychological processes can moderate the factors. Hence, the antecedents of demand/resource evaluations and reevaluations are complex indeed. Physiological Modulation of Energization As depicted in Figure 25.3, once an individual becomes task engaged in a goal-relevant motivated performance

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PERFORMANCE AND FEEDBACK According to the BPSM, individuals’ performance generally parallels the resource/demand ratio such that a challenge ratio leads to better performance than a threat ratio. However, both challenge and threat states are motivating and performance under threat may suffice for an individual to reach a goal. In certain cases, performance during threat may exceed performance during challenge. For example, threat appears to be related to better performance on vigilance tasks than challenge (Hunter, 2001). Of course, initial subjective judgments of the levels and interactions of antecedent resource/demand factors may prove inaccurate during an individual’s task performance itself, thereby causing those subjective judgments to vary during the task. Indeed, such judgments can cause fluctuations in the performer’s motivational state and concomitant variations in HPA axis activity (Quigley, Barrett, & Weinstein, 2002). For example, when a student is beginning a graduate record exam, he or she may evaluate personal resources as exceeding situational demands perhaps by believing he or she is well-prepared and knowledgeable. Upon experiencing uncertainty regarding the correct answer to a question or two, reevaluation may occur causing the performer to believe that he or she is not so wellprepared and knowledgeable. Answering more questions may further move the performer via reevaluation toward threat or may move the performer in the direction of challenge; for example, if the test taker starts experiencing certainty regarding his or her answers to questions. At the extremes, individuals may evaluate the motivated performance situation as one in which their resources so outweigh the demands, or vice-versa, that it loses goal relevance and, hence, they become disengaged.

RESEARCH OVERVIEW Research supporting the BPS of challenge and threat has appeared in the literature over the last 15 years. This

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work has not only taken the form of validational work as described above, but also includes a substantial body of work using the cardiovascular indexes of challenge and threat to test many personality and social psychological theories including ones focused on intraindividual processes and ones focused on interindividual processes. This kind of research is based on the rationale that if a personality or social psychological theory can be examined within a motivated performance situation and hypotheses deduced regarding resource/demand evaluations, then that theory can be tested via the BPSM using the cardiovascular indexes of challenge and threat. Furthermore, such work can come full circle to support the BPSM of challenge and threat in two ways, via identification of intraindividual and interindividual processes affecting resource/demand evaluations and via convergent validation of the cardiovascular indexes. Here, a sampling of such substantive research is reviewed.

INTRAINDIVIDUAL PROCESSES As indicated above, the antecedent factors that enter into the evaluative calculus underlying challenge and threat are filtered or moderated by intraindividual processes such as temperament, dispositions, attitudes, and beliefs. Although we have not studied temperament, we believe that our model is consistent with that of Elliot and Thrash (2002). However, we have studied how other intraindividual processes influence on the challenge and threat evaluation processes. A few are described here. Dispositions: Belief in a Just World Individuals vary dispositionally in their justice beliefs, with some adhering to the belief that individuals get what they deserve while others do not. Dispositional belief in a just world has been thought to protect individuals existentially by giving meaning to their lives and enabling them to adapt to life demands (Lerner, 1980). Hence, we hypothesized that dispositional belief in a just world should moderate challenge–threat evaluations and, thus, challenge–threat motivational states. Tomaka and Blascovich (1994) tested this hypothesis by having participants who had completed Rubin and Peplau’s (1975). Belief in a Just World (BJW) scale performs a serial subtraction task, a task not particularly related to justice beliefs, in a laboratory-based motivated performance situation. Cardiovascular responses assessed during a sequence of two performance periods demonstrated that those participants high in dispositional belief in a just world not only self-reported a higher ratio of resources to demands but also exhibited the

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cardiovascular pattern associated with challenge motivation. Those participants low in dispositional belief in a just world not only self-reported a higher ratio of demands to resources but also exhibited a cardiovascular pattern consistent with threat motivation. Dispositions: Stability of Self-Esteem More recently, we (Seery, Blascovich, Weisbuch, & Vick, 2004) examined the relationships among level of selfesteem, self-esteem stability, and cardiovascular reactions to performance feedback. Prior research on level of self-esteem and performance feedback (McFarlin & Blascovich, 1981) has indicated that individuals with high self-esteem following failure feedback expect to perform even better on the same motivated performance task (i.e., a version of the Remote Association Task; McFarlin & Blascovich, 1984) in the future than those receiving success feedback. Furthermore, this research also indicates that individuals with low self-esteem expect to perform worse in the future whether they receive either success or failure feedback. Similarly, Swann, Pelham, and Krull (1989) demonstrated self-verification processes such that high and low self-esteem individuals seek confirmation via high and low performance feedback, respectively. In the interim, personality psychologists (Kernis, Cornell, Sun, Berry, & Harlow, 1993) have convincingly demonstrated that self-esteem must not only be examined in terms of level (i.e., high to low) but also in terms of within person variability over time. Hence, in terms of self-esteem, individuals may be assessed not only from high to low globally, but also in terms of stability– instability. Hence, individuals with stable high selfesteem differ in important respects from those with unstable high self-esteem. Similarly, individuals with stable low self-esteem differ in important respects from those with unstable low self-esteem. In the Seery et al. (2004) experiments, individuals preassessed for self-esteem level and stability, participated in a challenge–threat experiment in which they performed in a motivated performance situation involving the remote associates task (RAT) in two sessions. The RAT in the first session was manipulated via selection of items (i.e., easy or difficult version) to produce relative success or failure. Participants are well aware of whether or not they perform well or poorly on easy and difficult versions of the RAT because the nature of the task makes it inherently clear whether they have correctly answered an item (McFarlin & Blascovich, 1984). The two experiments reported in Seery et al. differed only slightly in the wording of confirming verbal performance feedback following the first task. After receiving this verbal

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performance feedback, participants were told that the first task was a practice task and that the criterion task would follow. Subsequently, they completed a moderately difficult version of the RAT. Prior to, and during performance on the second task, the cardiovascular measures necessary to distinguish challenge from threat were recorded. Seery et al. (2004) hypothesized that the effects of self-esteem level, stability of self-esteem, and performance feedback would interact such that individuals high in stability and high in self-esteem would experience challenge during the second task despite failure performance feedback on the first task, but those unstable high self-esteem individuals would experience threat following failure feedback on the first task. In addition, Seery et al. expected that those low in stability and low in selfesteem would experience challenge following success feedback, but those high in stability and low in selfesteem would not. In both studies, participants with unstable high self-esteem experienced greater threat following failure feedback during criterion task performance than those with stable high self-esteem, and participants with unstable low self-esteem experienced greater challenge than those with stable low self-esteem. Attitudes: Functionality In the long history of the study of attitudes in social psychology, many theorists (Allport, 1935; Fazio, 1989) have maintained that attitudes (e.g., attitudes toward food items) function to ease decision-making in motivated performance situations that individuals face constantly in daily life. Accordingly, in terms of the BPS of challenge and threat, one would hypothesize that individuals with preexisting attitudes toward decision alternatives would be relatively challenged and that individuals without such attitudes would be threatened during a motivated performance situation involving a decision-making task for which such attitudes are relevant. Based on earlier work establishing an experimental attitude testing paradigm (Fazio, Blascovich, & Driscoll, 1992), Blascovich et al. (1993) essentially hypothesized that preexisting attitudes would serve as a resource to individuals finding themselves in a motivated performance situation in which the attitudes were relevant. In other words, preexisting attitudes would predispose individuals toward challenge in such a situation; whereas, without such attitudes individuals would be predisposed to threat. In two experiments (Studies 2 and 3 in Blascovich et al., 1993), participants rehearsed attitudes to a random set of 15 novel abstract paintings out of a larger group of

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30 such paintings. This procedure had been previously demonstrated (Fazio et al., 1992) to increase attitude accessibility toward targeted attitude objects, enabling individuals to make pairwise preference judgments more quickly between pairs of the paintings toward which participants had rehearsed attitudes than pairs of paintings that were novel. In the relevant experiments, Blascovich et al. (1993) confirmed the challenge–threat hypotheses. Specifically, participants exposed to paintings from the familiar rehearsed set exhibited the challenge pattern of cardiovascular reactivity while making rapid pairwise judgments of them. Participants exposed to paintings from the novel unrehearsed set exhibited the threat pattern. Beliefs In a recent study, Weisbuch-Remington, Mendes, Seery, & Blascovich (2005) examined how religious beliefs might influence resource/demand evaluations. Based on anthropological, sociological, and psychological theories, they reasoned that learned religious beliefs should serve as a resource for believers during relevant goal-relevant motivated performance situations. Furthermore, they created an experimental paradigm in which they primed religious beliefs outside of participants’ awareness, and conducted two experiments to test their hypotheses. In both experiments, participants were exposed subliminally to positive and negative graphic Christian religious icons or symbols. Each experiment involved two tasks. The first involved an estimation task in which participants were instructed to indicate the number of tiles in an abstract mosaic that actually served as the mask for the subliminal cues. The first experiment included only participants who during a previous apparently unrelated mass prescreening activity had indicated they were religious and Christian. Following, this task, participants were instructed to give a speech. Half were randomly assigned to give a speech about their own death and the other half gave a speech about going to the dentist. The results indicated that participants exposed to positive Christian subliminal cues prior to the speech exhibited the challenge pattern of cardiovascular reactivity during the speech, while participants exposed to negative Christian cues exhibited the threat pattern. Furthermore, these effects were stronger during the death speech than the dentist speech. The second experiment included both Christian and non-Christian participants, and all participants gave the death speech. Again, Christian participants exposed to positive Christian subliminal cues exhibited the challenge

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pattern and Christian participants exposed to negative Christian subliminal cues exhibited the threat pattern. However, non-Christian participants were not affected by the subliminal cues. These experiments confirmed the role of learned beliefs in resource/demand evaluations. Importantly, they also indicate that such evaluations can take place nonconsciously.

INTERINDIVIDUAL PROCESSES In addition to antecedent intraindividual factors, interindividual processes can also affect the evaluative resource/ demand calculus underlying challenge and threat. Among the interindividual processes that we have examined are: social facilitation, social comparison, stigma, and stereotype threat. These are reviewed briefly here. Social Facilitation The presence of observers and coactors should heighten the evaluative nature of motivated performance situations by increasing the psychological danger associated with failing to perform at a level that others present would perceive as good or acceptable. Hence, drawing on the BPSM, one would hypothesize that if a well-learned task is performed in the presence of such an audience, challenge is more likely to occur because failing to perform is unlikely. However, if a novel task is performed in the presence of an audience threat is more likely to occur because failing to perform well is more likely. Blascovich, Mendes, Hunter, and Salomon (1999) tested these hypotheses in a classic social facilitation experiment. The experiment consisted of two phases. In the first, participants learned one of two equally difficult tasks (number categorization or pattern recognition) and mastered it by performing to criterion. In the subsequent phase, participants were randomly assigned to perform either the well-learned task or the novel task (i.e., the one they did not perform or learn in the first phase). Within each performance task condition, participants were randomly assigned to perform alone or in the presence of two confederates. The results supported the hypotheses drawn from the BPS in two regards. First, task engagement, as indicated by the cardiovascular measures occurred only in the audience conditions during the second, criterion phase. Second, in the audience condition paired with the welllearned task, participants exhibited the challenge pattern of cardiovascular responses. In the audience condition paired with the novel task, participants exhibited the threat pattern. These results not only supported the BPS, but also delineated differences in patterns of physiological

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“arousal” associated with social facilitation and inhibition for the first time since Zajonc (1965) included physiological arousal in his social facilitation theory. Social Comparison Another classic social influence process that should affect resource/demand evaluations in motivated performance situations involving other performers is social comparison (Festinger, 1954). Although several social comparison researchers have incorporated the role of general arousal in theories of social comparison (Major, Testa, & Bylsma, 1991; Wills, 1991) and a few social comparison studies incorporated simple HR or skin conductance measures to assess such arousal, the motivational arousal construct underlying social comparison theory has been poorly delineated. Drawing on the BPSM and social comparison theory, Mendes, Blascovich, Major, and Seery (2001) hypothesized that participants performing in a motivated performance situation with partners who performed better than they did (i.e., upward social comparison) would experience threat and that participants paired with partners who performed worse (i.e., downward social comparison) would experience challenge. These experiments began with a brief participant–partner (i.e., a confederate) face-to-face interaction, followed by solo performance of a word finding task (similar to the game of Boggle) by the participant with veridical performance feedback. Subsequently, participants received information regarding their partner’s solo performance, which was the manipulation of upward or downward comparison. Finally, the participant and partner performed as a team during a final word finding task. As predicted, participants were task engaged (i.e., significant increases in VC during the final criterion task) whether they were in the upward or downward comparisons conditions. Also, as predicted, participants in the upward comparison condition exhibited a pattern of cardiovascular responses associated with threat, and participants in the downward comparison condition exhibited a pattern of cardiovascular responses associated with challenge. Stigma Social interactions between members of stigmatized (e.g., African-Americans, disfigured individuals, people low in socio-economic status, persons with mental illness) and nonstigmatized (e.g., Anglo-Americans, attractive individuals, people high in socio-economic status, and mentally healthy persons) groups have received much attention from social psychologists over the past half-century, particularly over the last two decades or so.

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Theorists have maintained that interacting with stigmatized individuals cause nonstigmatized individuals uncertainty, discomfort, anxiety, and danger during social interactions (Crocker, Major, & Steele, 1998). Similarly, by virtue of membership in socially devalued groups, stigmatized individuals may feel particularly susceptible to negative performance stereotypes increasing their sense of psychological danger (e.g., stereotype threat; Steele, 1992). Hence, it is not surprising that, since Goffman’s (1963) seminal work on stigma, social psychological theorists have considered social interactions between stigmatized and nonstigmatized individuals as threatening to the interactants. However, it is only in the new millennium that researchers have been able to demonstrate physiological evidence of threat, based in both nonstigmatized and stigmatized interactants during social interactions. This work began with the application of the BPSM of challenge and threat to such investigation. Blascovich, Mendes, Hunter, Lickel, and Kowai-Bell (2001) hypothesized that, during interactions with stigmatized others, members of nonstigmatized groups would experience resource/ demand evaluations in which demands outweighed resources resulting in threat motivation. Their work involved pairing nonstigmatized and stigmatized individuals as partners in cooperative motivated performance situations involving speech and word finding tasks. In their initial studies, the investigators experimentally manipulated stigma by placing opaque or transparent facial birthmarks on confederates (cf. Kleck & Strenta, 1980) who subsequently interacted with nonstigmatized others in the cooperative situations. Their results demonstrated that the nonstigmatized partners exhibited cardiovascular response patterns associated with threat when interacting with a birthmarked partner and challenge when interacting with a nonbirthmarked partner (Experiments 1 & 2; 2001). Blascovich and colleagues demonstrated similar effects when nonstigmatized individuals were partnered with African-Americans of the same gender compared to nonstigmatized individuals partnered with other nonstigmatized individuals (Experiment 3; 2001; Mendes, Blascovich, Lickel, & Hunter, 2002). Furthermore, using the birthmark manipulation on genuine participants, this research group has demonstrated that stigmatized individuals are also threatened when interacting with nonstigmatized individuals (reference forthcoming). Stereotype Threat According to Steele and Aronson’s (1995) stereotype threat theory, performing in a domain in which one is

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negatively stereotyped is associated with feelings of anxiety, uncertainty, etc. This “stereotype threat” stems from the possibility that one’s performance might confirm a negative stereotype and can result in poorer performance, thereby confirming the stereotype. Blascovich, Spencer, Quinn, and Steele (2001) published a paper demonstrating heightened cardiovascular responses among stereotype-threatened African-Americans taking a supposed verbal abilities test, however, they did not report cardiovascular measures that could confirm threat vis-à-vis the BPS. Recently, Vick, Seery, Blascovich and Weisbuch (in press) hypothesized that situations raising the salience of negative self-relevant stereotypes negatively affect resource/demand evaluations in a motivated performance situation. Specifically, stereotype-threatened individuals should experience increased demand evaluations (e.g., greater uncertainty, more psychological danger) thereby increasing the likelihood of threat. Some nonphysiological research supports these notions, confirming that stereotype-threatened individuals have lower expectations for performance and increased self-doubt (Steele & Aronson, 1995). They tested these hypotheses in a situation involving gender-math stereotypes involving male and female participants. In the Vick et al. experiment, participants completed a difficult math test, one that they had been led to believe was either gender-biased in favor of males or gender-fair, while appropriate cardiovascular data were assessed. During the test, stereotype-threatened women exhibited a cardiovascular pattern associated with threat, while nonstereotyped-threatened women exhibited challenge. Interestingly, the cardiovascular patterns were reversed for men. Specifically, men exhibited challenge when a male gender bias was implied, but threat when it was not.

SUMMARY The BPSM of challenge and threat has evolved over the last 15 years, becoming richer in detail and amassing validational evidence for its putative cardiovascular indexes of challenge and threat. The BPSM is at its essence a motivational model, one integrating biological, psychological (cognitive and affective), and social psychological (intrapersonal and interpersonal) levels of analysis. The BPSM is a domain specific (i.e., motivated performance situations) model, though this is arguably a quite broad and ubiquitous domain. The model fits within the family of approach–avoidance theories of motivation, although we argue that both

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challenge and threat involve approach, with the latter modulated by avoidance like neurophysiological processes. Research has demonstrated the applicability of the model in many domains pertinent to personality and social psychology. The research reviewed above as well as other research (Allen, Blascovich, & Mendes, 2002; Blascovich, Mendes, & Seery, 2002; Mendes, Blascovich, Hunter, Lickel, & Jost, in press; Mendes, Reis, Seery, & Blascovich, 2003) provides support for many of the processes specified by the BPSM. Furthermore, it demonstrates the utility of the model for testing theories focused on intraindividual and interindividual processes pertinent to person and situational influences in daily life by testing them within the context or empirical model of motivated performance situations.

REFERENCES Allen, K., Blascovich, J., & Mendes, W. B. (2002). Cardiovascular reactivity and the presence of pets, friends, and spouses: the truth about cats and dogs. Psychosomatic Medicine, 64(5), 727–739. Allport, G. W. (1935). Attitudes. In C. Murchison (Ed.), Handbook of social psychology. Worchester, MA: Clark University Press. Anderson, N., McNeilly, M., & Myers, H. (1993). A biopsychosocial model of race differences in vascular reactivity. In J. Blascovich & E. S. Katkin (Eds.), Cardiovascular reactivity to psychological stress and disease (pp. 83–110). Washington, DC: American Psychological Association. Blascovich, J. (2007). Challenge, threat, and health. In J. Shah & W. Gardner (Eds.), Handbook of motivation science (pp. 481–493). New York: Guilford. Blascovich, J., Ernst, J. M., Tomaka, J., Kelsey, R. M., Salomon, K. A., & Fazio, R. H. (1993). Attitude as a moderator of autonomic reactivity. Journal of Personality and Social Psychology, 64, 165–176. Blascovich, J., & Mendes, W. B. (2000). Challenge and threat appraisals: The role of affective cues. In J. Forgas (Ed.), Feeling and thinking: The role of affect in social cognition (pp. 59–82). Cambridge, UK: Cambridge University Press. Blascovich, J., Mendes, W. B., Hunter, S. B., Lickel, B., & Kowai-Bell, N. (2001). Perceiver threat in social interactions with stigmatized others. Journal of Personality and Social Psychology, 80, 253–267. Blascovich, J., Mendes, W., Hunter, S., & Salomon, K. (1999). Social facilitation, challenge, and threat. Journal of Personality and Social Psychology, 77, 68–77. Blascovich, J., Mendes, W. B., & Seery, M. (2002). Intergroup encounters and threat: A multi-method approach. In D. Mackie & E. Smith (Eds.), From prejudice to intergroup emotions: Differentiated reactions to social groups (pp. 89–110). New York: Psychology Press.

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Blascovich, J., Seery, M., Mugridge, C., Weisbuch, M., & Norris, K. (2004). Predicting athletic performance from cardiovascular indicators of challenge and threat. Journal of Experimental Social Psychology, 40, 683–688. Blascovich, J., Spencer, S., Quinn, D., & Steele, C. (2001). African-Americans and high blood pressure: The role of stereotype threat. Psychological Science, 12, 225–229. Blascovich, J., & Tomaka, J. (1996). The biopsychosocial model of arousal regulation. In M. Zanna (Ed.), Advances in Experimental Social Psychology Vol. 28 (pp. 1–51). New York: Academic Press. Crocker, J., Major, B., & Steele, C. (1998). Social stigma. In D. T. Gilbert, S. T. Fiske et al. (Eds.), The handbook of social psychology (4th ed., Vol. 2). Boston: McGraw-Hill. Dienstbier, R. A. (1989). Arousal and physiological toughness: Implications for mental and physical health. Psychological Review, 96, 84–100. Elliot, A. J. (2006). The hierarchical model of approach–avoidance motivation. Motivation and Emotion, 30, 111–116. Elliot, A. J., & Trash, T. M. (2002). Approach–avoidance motivation in personality: Approach and avoidance temperaments and goals. Journal of Personality and Social Psychology, 82(5), 804–818. Fazio, R. H. (1989). On the power and functionality of attitudes: The role of attitude accessibility. In A. R. Pratkanis, S. J. Breckler, & A. G. Greenwald (Eds.), Attitude structure and function (pp. 153–179). Hillsdale, NJ: Lawrence Erlbaum. Fazio, R. H., Blascovich, J., & Driscoll, D. M. (1992). On the functional value of attitudes: The influence of accessible attitudes upon the ease and quality of decision-making. Personality and Social Psychology Bulletin, 18, 388–401. Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7, 117–140. Goffman, E. (1963). Stigma. Englewood Cliffs, NJ: Prentice-Hall. Hunter, S. B. (2001). Performance under pressure: The impact of challenge and threat states on information processing. Unpublished doctoral dissertation, University of California, Santa Barbara. Kernis, M. H., Cornell, D. P., Sun, C., Berry, A., & Harlow, A. (1993). There’s more to self-esteem than whether it is high or low: The importance of stability of self-esteem. Journal of Personality and Social Psychology, 65(6), 1190–1204. Kleck, R. E., & Strenta, A. (1980). Perceptions of the impact of negatively valued physical characteristics on social interaction. Journal of Personality and Social Psychology, 39, 861–873. Lazarus, R. S. (1991). Progress on a cognitive-motivationalrelational theory of emotion. The American Psychologist, 46(8), 819–834. Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. New York: Springer. Lerner, M. J. (1980). The belief in a just world. New York: Plenum. Lewin, K. (1936). Principles of topological psychology. New York: McGraw-Hill.

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LeDoux, J. E. (1996). The emotional brain: The mysterious underpinnings of emotional life. New York: Simon & Schuster. Major, B. N., Testa, M., & Bylsma, W. H. (1991). Responses to upward and downward social comparisons: The impact of esteem-relevance and perceived control. In J. M. Suls & T. A. Wills (Eds.), Social comparison (pp. 230–260). Hillsdale NJ: Erlbaum. McFarlin, D. B., & Blascovich, J. (1981). The effects of selfesteem and performance feedback on affective preferences and cognitive expectations. Journal of Personality and Social Psychology, 4, 521–531. McFarlin, D. B., & Blascovich, J. (1984). On the remote associates test (RAT) as an alternative to illusory performance feedback: A methodological note. Basic and Applied Social Psychology, 5, 223–228. Mendes, W. B., Blascovich, J., Hunter, S. B., Lickel, B., & Jost, J. T. (2007). Threatened by the unexpected: Physiological responses during social interactions with expectancyviolating partners. Journal of Personality and Social Psychology, 93, 698–716. Mendes, W. B., Blascovich, J., Lickel, B., & Hunter, S. (2002). Challenge and threat during interactions with White and Black men. Personality and Social Psychology Bulletin, 28, 939–952. Mendes, W. B., Blascovich, J., Major, B., & Seery, M. (2001). Effects of social comparisons on challenge and threat reactivity. European Journal of Social Psychology, 31, 477–479. Mendes, W. B., Reis, H. T., Seery, M., & Blascovich, J. (2003). Cardiovascular correlates of emotional disclosure and suppression: Do content and gender context matter. Journal of Personality and Social Psychology, 84, 771–792. Obrist, P. (1981). Cardiovascular psychophysiology: A perspective. New York: Plenum. Quigley, K. S., Barrett, L. F., & Weinstein, S. (2002). Cardiovascular patterns associated with threat and challenge appraisals: A within-subjects analysis. Psychophysiology, 39(3), 292–302. Rousselle, J. G., Blascovich, J., & Kelsey, R. M. (1995). Cardiorespiratory response under combined psychological and

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exercise stress. International Journal of Psychophysiology, 20, 49–58. Rubin, Z., & Peplau, L. A. (1975). Who believes in a just world? The Journal of Social Issues, 31(3), 65–89. Seery, M., Blascovich, J., Weisbuch, M., & Vick, S. B. (2004). The relationship between self-esteem, self-esteem stability, and cardiovascular reactions to performance feedback. Journal of Personality and Social Psychology, 87, 133–145. Steele, C. M. (1992). Race and the schooling of Black Americans. The Atlantic Monthly, 269(4), 68–78 Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69(5), 797–811. Swann, W. B., Pelham, B. W., & Krull, D. S. (1989). Agreeable fancy or disagreeable truth? Reconciling selfenhancement and self-verification. Journal of Personality and Social Psychology, 57(5), 782–791. Tomaka, J., & Blascovich, J. (1994). Effects of justice beliefs on cognitive appraisal of and subjective, physiological, and behavioral responses to potential stress. Journal of Personality and Social Psychology, 67, 732–740. Tomaka, J., Blascovich, J., Kelsey, R. M., & Leitten, C. L. (1993). Subjective, physiological, and behavioral effects of threat and challenge appraisal. Journal of Personality and Social Psychology, 65, 248–260. Tomaka, J., Blascovich, J., Kibler, J., & Ernst, J. M. (1997). Cognitive and physiological antecedents of threat and challenge appraisal. Journal of Personality and Social Psychology, 73, 63–72. Vick, S. B., Seery, M. D., Blascovich, J., & Weisbuch, M. (in press). The effect of gender stereotype activation on challenge and threat motivational states. Journal of Experimental Social Psychology Weisbuch-Remington, M., Mendes, W. B., Seery, M. D., & Blascovich, J. (2005). The non-conscious influence of religious symbols in motivated performance situations. Personality and Social Psychology Bulletin, 31, 1203–1216. Wills, T. A. (1991). Similarity and self-esteem in downward social comparison. In J. M. Suls & T. A. Wills (Eds.), Social comparison (pp. 51–78). Hillsdale NJ: Erlbaum. Zajonc, R. B. (1965). Social facilitation. Science, 149, 269–274.

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Mental Control Suppression and 26 Thought Psychopathology Sadia Najmi and Daniel M. Wegner CONTENTS Suppression of Unwanted Thoughts ......................................................................................................448 Suppression and Psychopathology ........................................................................................................449 Suppression and Posttraumatic Stress Disorder ....................................................................................449 Suppression and Obsessive-Compulsive Disorder ................................................................................450 Suppression and Depression .................................................................................................................. 451 Suppression of Worry in Generalized Anxiety Disorder and Insomnia ............................................... 452 Suppression and Alcohol Use and Abuse .............................................................................................. 453 Suppression and Self-Injurious Thoughts and Behaviors ..................................................................... 453 Suppression and Psychosis ....................................................................................................................454 Suppression and Dreams ....................................................................................................................... 455 Conclusion .............................................................................................................................................456 Acknowledgment ...................................................................................................................................456 References .............................................................................................................................................456 There are very few theories of psychopathology that trace all disorders of the mind to a single common cause. The demon-possession theory gave it a good try for a while, at least in the medieval popular mind. And later, as psychology developed, theorists with big ideas made their own suggestions for unifying themes: Freud and repression, Adler and inferiority, Rogers and low selfregard, Skinner and contingencies of reinforcement. Students of introductory psychology can name these and more, and can also note that in every case there are major exceptions to these one-factor theories. Something as miraculously complex as the human mind is susceptible to potential pathological influences with similar complexity, so theories suggesting a common theme will always fall prey to the criticism of oversimplification. Still, we plan in this chapter to make the same darn mistake—by examining the potential role of thought suppression as a causal factor in, if not all, then a wide range of psychological disorders.

Why would we stumble off to perform a fool’s errand? Our attraction to this idea comes from a basic realization about mental disorder. The inner life of disorder is often painful, unpleasant, a focus of suffering—and thus will commonly motivate thought suppression as a reaction. People typically do not want to think about their sorrows, their symptoms, their fears, their abnormalities, the voices in their heads—they hope to avoid their psychopathological mental states. This reaction, then, could be very broad, a standard and stereotypical response to mental turmoil in every form of psychopathology in which a person remains conscious and experiences distress. And while the suppression of thoughts may seem to be an effective solution, this strategy can have profound and unexpected consequences in the unwanted magnification of the psychological influences of the suppressed thought. The unifying feature of this approach to psychopathology, then, is not that thought suppression might somehow initiate a significant range of the psychological 447

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disorders, but rather that it may expand their psychological damage, prolong their course, and make them more resistant to treatment. The unifying theme of thought suppression is not that it is a general cause of disorder, but that it is a general human response to distress that may seriously complicate any disorder that arises. This chapter begins by describing the phenomena of suppression and considering how suppression might complicate disorders. Next, we review the evidence to date for a role of suppression in various forms of mood, anxiety, and impulsive disorders. We then consider recent theoretical proposals regarding a potential role of thought suppression in psychosis. Throughout, we illustrate how suppression is differentially implicated in distinct forms of psychopathology, in some instances potentially as an etiological mechanism, but more often as a disordercomplicating moderator of psychopathology. More broadly, suppression is characterized in this chapter as a product of avoidance motivation that has detrimental consequences for psychological functioning and well-being.

SUPPRESSION OF UNWANTED THOUGHTS The idea that trying to keep things out of mind can be a factor in psychopathology has always been a central tenet in Freudian psychoanalysis and in psychodynamic psychology. Although there remains significant debate on this issue (Erdelyi, 2006), the predominant sentiment underlying this approach has been that attempts to stop thinking can be successful—that people can indeed control their minds (Wegner, Eich, & Bjork, 1994). In contrast to this presumption, the initial experimental studies of thought suppression revealed that suppression simply does not work (Wegner, Schneider, Carter, & White, 1987). People cannot keep the thought of a white bear out of mind for 5 minutes, let alone suppress something for a lifetime. The fact is, though, that people often try not to think about things despite the futility of the enterprise. Thought suppression is one of various strategies that people may use to manage or control thoughts that trigger unpleasant emotions. Conceptualized this way, it is a prime cognitive exemplar of avoidance motivation. What is most critical to pathology of intrusive thoughts is that this strategy is often unsustainable, especially in the face of competing cognitive demands. Moreover, when the strategy fails, the unwanted thoughts often do not return to their initial baseline level and instead escalate to a much higher level of frequency. According to the ironic process theory of mental control (Wegner, 1994), this occurs because mental control involves processes that usually work together to effect thought suppression, but that can fail and yield intrusions under conditions of high mental load. The

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theory posits an effortful and conscious operating process that diverts attention away from unwanted thoughts, and an effortless and unconscious ironic monitoring process that both maintains vigilance for occurrences in awareness of the unwanted thought, and triggers further action of the operating process if the unwanted thought appears in awareness. These two processes work hand in hand to ensure that unwanted thoughts remain outside of awareness. Ironically, however, by maintaining vigilance for the unwanted thought, the monitoring system helps assure that the unwanted thought never becomes dormant. Research has demonstrated two characteristics of suppressed thoughts—the ease of return to suppressed thoughts, and the difficulty of escape from suppressed thoughts. In the original thought suppression experiment, Wegner et al. (1987) found evidence for ease of return— after a period of thought suppression, people instructed to discontinue suppression of the thought and instead to begin thinking about it reported more returns of the thought than occurred without prior suppression. Subsequent studies revealed that this effect is particularly likely to occur under conditions of mental load. The ease of return illustrated by this “rebound effect” has since been observed repeatedly (see reviews by Abramowitz, Tolin, & Street, 2001; Rassin, 2005; Wenzlaff & Wegner, 2000). Common to these studies with clinical and nonclinical populations is the finding that the unwanted thought is faster to return to consciousness while it is being actively suppressed. Studies examining the phenomenon of hyperaccessibility in interference effects have shown evidence for the difficulty of escape from suppressed thoughts. Wegner and Erber (1992) found that people suppressing a thought under cognitive load showed interference with the task of color-naming in a modified Stroop (1935) paradigm. Remarkably, this interference was even greater than the interference found when people were concentrating on the thought under load. These results imply that people could not disengage attention to escape from the unwanted thought, and this difficulty became more pronounced with the imposition of cognitive load. This effect, too, has been observed repeatedly (Arndt, Greenberg, Solomon, Pyszczynski, & Simon, 1997; Klein, 2007; Newman, Duff, & Baumeister, 1997; Page, Locke, & Trio, 2005). The ease of return and difficulty of escape from unwanted thoughts may underlie a certain asymmetry in the way unwanted thoughts are linked to other thoughts— the remarkable phenomenon that we find ourselves being reminded of a particular unwanted thought by most everything that comes to mind, but the idea itself seems to remind us of nothing more than our desire to eliminate it from consciousness. This unusual asymmetry in the way unwanted thoughts are linked to other thoughts was

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Thought Suppression and Psychopathology

examined in a recent study (Najmi & Wegner, in press). Participants who were asked to suppress a thought or to concentrate on it completed a task assessing the influence of priming on reaction time to word/nonword judgments (associative priming lexical decision task). Results indicated that suppression under cognitive load produced a sort of asymmetric priming. Priming with the associate of a suppressed word speeded reaction time to the suppressed word, but priming with a suppressed word did not speed reaction time to associated words. This suggests that suppression induces an unusual form of cognitive accessibility in which movement of activation toward the suppressed thought from associates is facilitated but movement of activation away from the suppressed thought to associates is undermined. Thus, suppression of an unwanted thought ironically increases its return while precluding other related thoughts from entering into awareness.

SUPPRESSION AND PSYCHOPATHOLOGY Early theories of psychopathology portrayed a state of mind much like the one produced by simple instructions to suppress. These theories described psychopathological states in terms of the idée fi xe—a thought that intrudes repeatedly upon consciousness and becomes difficult to control—and pointed to such fixed ideas as the very basis of mental disorder (Janet, 1894; Ribot, 1881). In presenting William James’ views on psychopathology, Taylor (1984) provides a list of “exceptional mental states” characterized by an idée fi xe, highlighting the notion that characteristic of many emotional disorders is perseverative thinking of aversive thoughts and attempted control of these thoughts in the service of emotion regulation. Ironically, it may be avoidance of the thoughts that fuels their persistence. James suggests that this “power of the buried idea” may underlie symptoms of hysteria, while intolerance and avoidance of uncertainty (folie du doute or doubting mania) may mark the beginnings of obsessive thinking (Taylor, 1984). Although theories of psychopathology have grown more sophisticated than this, there remains evidence that unwanted intrusive thoughts characterize a range of emotional disorders (Clark, 2005). Intrusive thoughts are typically experienced as ego-dystonic and unacceptable, they cause distress, and interrupt current mental activity (Rachman, 1978, 1981). The drive to eliminate thoughts from consciousness may create the precise formula for turning the ordinary experience of unwanted thoughts into the painful experience of persistent intrusions that characterize many forms of psychopathology, from obsessive-compulsive disorder (OCD) and posttraumatic stress disorder (PTSD) to depression and beyond (Clark, 2005).

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It is often the case that overwhelming intrusions have no obvious beginnings. For example, in the case of patients with OCD, it is nearly impossible to identify when the unwanted thought of contamination or blasphemy first gained acute emotional import. One approach to this problem is to suggest that suppression itself is the cause of subsequent obsession. This idea was developed in a theory of synthetic obsessions (Wegner, 1989) that oriented much of the early empirical investigation of thought suppression in psychopathology toward testing the idea that suppression failure was a primary etiological process in certain forms of psychopathology. This possibility remains open, as little research assessing the causal role of thought suppression in OCD and other forms of psychopathology has been reported as yet (but see Wegner & Zanakos, 1994; Wenzlaff, 2005). In focusing our approach in this chapter on the potential for thought suppression to play a role across a wide range of psychopathologies, we will set aside for now the specific analysis of a potential etiological role for suppression in any one disorder. Rather, we will examine the associations that have been observed between psychological disorders and various indicators of thought suppression tendencies and effectiveness. A review by Wenzlaff and Wegner (2000) presented empirical findings related to the suppression of intrusive thoughts in PTSD, OCD, and depression. In the sections that follow, we expand this earlier review to incorporate more recent findings in these areas and in a wider array of disorders.

SUPPRESSION AND POSTTRAUMATIC STRESS DISORDER Two of the primary characteristics of PTSD—unwanted intrusions of traumatic recollections and avoidance of all things associated with the trauma—suggest that individuals with PTSD are motivated to suppress trauma-related thoughts. Most empirical investigations of the effects of thought suppression in PTSD indicate that the disorder is characterized by a bias in the ability to suppress traumarelated thoughts. Shipherd and Beck (1999) examined the effects of instructed suppression of rape-related thoughts in female sexual assault survivors with PTSD and those without PTSD following the sexual assault. They found that trauma survivors with PTSD experienced a postsuppression rebound in the frequency of rape-related thoughts, whereas trauma survivors without PTSD did not experience a rebound. A more recent study (Shipherd & Beck, 2005) replicated these findings in a follow-up investigation of the deliberate suppression of trauma-related thoughts in survivors of motor vehicle accidents with and without PTSD. These

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researchers found that both groups successfully suppressed trauma-related thoughts temporarily, but that the PTSD group experienced a postsuppression rebound, whereas the no-PTSD group did not. In this study, participants were given an additional task of suppressing a personally relevant thought that was not related to the trauma. In this task, the PTSD group did not experience a rebound effect, suggesting that this effect was specific to the suppression of their trauma-related thoughts. However, in a further follow up study (Beck, Gudmundsdottir, Palyo, Miller, & Grant, 2006), both PTSD and no-PTSD groups showed a postsuppression rebound of trauma-related thoughts, suggesting that difficulties in suppressing trauma-related thoughts may be ubiquitous, and not specific to PTSD. Results to date suggest, then, that attempted suppression of trauma-related thoughts and their subsequent rebound may exacerbate trauma-related intrusions. Whether ineffective suppression is a precursor of PTSD or a consequence of the disorder cannot be determined by these studies. Furthermore, while the jury is still out on whether or not PTSD is associated with a bias in ability to suppress trauma-related thoughts, it is clear that suppression complicates the disorder by escalating the intrusions. Finally, it is interesting to note that Harvey and Bryant (1998) observed a postsuppression rebound effect for accident-related thoughts in survivors of motor vehicle accidents with acute stress disorder (ASD), but a follow-up study (Guthrie & Bryant, 2000) found that these effects were temporary. It may be that the effects of attempted suppression of trauma-related thoughts is fleeting but that repeated, failed, attempts at suppressing trauma-related thoughts contribute to the escalation of intrusions from acute stress disorder to PTSD.

SUPPRESSION AND OBSESSIVECOMPULSIVE DISORDER OCD is characterized by the avoidance of anxiety that is produced by persistent obsessions. Although the relentlessness of unwanted intrusive thoughts is a defining feature of OCD, several studies have established that the experience of unwanted intrusive thoughts with obsessional content is a normative phenomenon (Purdon & Clark, 1993; Rachman & de Silva, 1978; Salkovskis & Harrison, 1984). This idea was foreshadowed in James’s degeneracy theory of mental illness (Taylor, 1984) in which he suggested that cognitive and behavioral avoidance and the intensity of unwanted thoughts lie on a dimension from normalcy to pathology. Indeed, empirical studies have established that the difference between “normal” and “clinical” obsessions is a

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matter of degree rather than kind. Nonclinical individuals indicate that their most common negative intrusive thoughts occur a few times a year (Purdon & Clark, 1994a,b). Normal individuals who report significant recurrence of distressing unwanted thoughts also return high scores on the White Bear Suppression Inventory, a scale developed to assess motivation to suppress thoughts (Wegner & Zanakos, 1994). Compared to nonclinical individuals, however, OCD patients experience more frequent, distressing intrusive thoughts, perceive them to be less controllable, and more strongly try to resist them using maladaptive mental control strategies such as thought suppression (Janeck & Calamari, 1999; Rachman & de Silva, 1978). According to the cognitive-behavioral perspective on OCD (Rachman, 1997; Salkovskis, 1985), the intrusive thoughts that characterize many psychological disorders may persist because of three types of processes “(a) preexisting ideas, beliefs or schemas, (b) faulty interpretation and appraisal of the intrusion, and (c) futile efforts to intentionally control or suppress unwanted cognitions” (Clark, 2001, p. 125). According to Salkovskis’s model of OCD, dysfunctional appraisals of responsibility and unsuccessful attempts to neutralize and control the intrusive thoughts cause normal intrusive thoughts to escalate into clinical obsessions. Thus, according to the model, thought suppression alone is not the cause of obsessions, but rather it is the suppression of unwanted, intrusive thoughts motivated by the need to eliminate them from consciousness in order to avert harm. With a few exceptions (Kelly & Kahn, 1994; Purdon & Clark, 2001), the paradoxical effects of suppressing obsessional thoughts in nonclinical samples have been observed fairly consistently. In a series of studies, Salkovskis and colleagues (Salkovskis & Campbell, 1994; Salkovskis & Reynolds, 1994; Trinder & Salkovskis, 1994) observed a suppression-related increase in intrusive thoughts both in the lab and over a 4-day naturalistic follow-up. McNally and Ricciardi (1996) presented nonclinical participants with a list of thoughts reflecting various themes of obsessions and asked them to identify one that they had previously experienced. They observed a marginally significant tendency for the obsessional thought to occur more often after suppression whereas neutral thoughts tended to occur less frequently after suppression. To date, there has not been much investigation of the effects of instructed suppression of obsessional thoughts in OCD. One problem in conducting the thought suppression experiment with OCD patients is the difficulty of finding an appropriate control condition. Tolin et al. (2002b) note that instructing individuals with OCD to

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suppress an obsessional thought is essentially a “nonintervention” since individuals in the nonsuppression control group are being asked to act against what they would naturally do. Purdon, Rowa, and Antony (2005) found that individuals with OCD exerted effort to suppress their obsessional thought despite explicit instructions not to suppress, and that this suppression effort was correlated with their perceived urgency to control the thought. This may explain the absence of suppression rebound or enhancement effects in the studies of instructed suppression of obsessional thoughts conducted with clinical samples of OCD patients (Janeck & Calamari, 1999; Purdon et al., 2005). Tolin et al. (2002b) argue that if individuals with OCD have general deficits in their ability to control thoughts, this will be manifested in their ability to control neutral thoughts. Moreover, this design overcomes the problem of spontaneous suppression of obsessional thoughts in the OCD control group. Consistent with their hypothesis, they found that individuals with OCD had higher occurrences of a neutral target thought after suppressing compared to baseline. The initial observations of thought suppression suggested that it is not very successful (Wegner et al., 1987). What does this mean for the role of suppression in OCD if we conclude that the rebound or enhancement effect is not experienced by the majority of OCD subjects instructed to suppress their obsessions? One possibility is that suppression works temporarily. If so, it serves as a neutralization strategy; that is, it terminates exposure to the obsession thereby curtailing habituation of the anxiety associated with the obsession (Roemer & Borkovec, 1994) and preventing disconfirmation of the perceived negative consequences of the obsession. Another possibility is that suppression fails. Failed suppression can serve to increase the salience of the unwanted thought and the need to control it in order to avoid the perceived negative consequences. Failure of suppression is associated with worse mood, and faulty appraisals of suppression failure may lead to greater effort to suppress (Purdon et al., 2005). Conceptualized this way, it may well be the case that repeated attempts at suppression serve to exacerbate an already existent obsessional state. Faulty appraisals of the failure of suppression and faulty beliefs about the need to control thoughts and about the controllability of thoughts may be both causal precursors of the obsessional state as well as complicating factors that further aggravate it. Purdon and Clark (2000) have argued that certain individuals hold preexisting metacognitive beliefs that result in thought suppression, namely, that unwanted thoughts can and should be controlled and that intrusive thoughts are the product of an

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unhealthy mind. For example, Tolin et al. (2002a) observed that OCD patients were more likely than anxious and nonanxious controls to attribute a failure of thought suppression to internal, negative attributions (e.g., “I am mentally weak”). These beliefs may predispose the individual to exert greater control over thoughts, and consequently, to suffer the counterproductive effects of mental control. Indeed, results from studies using correlational designs such as path analysis (Smári & Hólmsteinsson, 2001) and structural equation modeling (Rassin, Muris, Schmidt, & Merckelbach, 2000) suggest that negative thought appraisal predicts suppression, which in turn predicts OCD symptoms.

SUPPRESSION AND DEPRESSION Research investigating the role of thought suppression in depression has yielded two primary inferences: One is the fairly robust observation that the motivated avoidance of depressotypic intrusions results in a rebound of these cognitions (Wenzlaff, Wegner, & Roper, 1988), and the other is the suggestion that the suppression of depressive thoughts may mask a cognitive vulnerability to depression (Wenzlaff & Bates, 1998). According to Wenzlaff (2005) there are a number of reasons why depressed individuals are prone to experiencing the suppression-induced rebound of depressotypic intrusions. Consistent with the idea of a depressive schema underlying the disorder that makes depressotypic information more accessible (Beck, 1967), depressed individuals are likely to undertake suppression by choosing distracters that are mood congruent and hence closely linked to their suppression target (Wenzlaff et al., 1988). This finding has been replicated reliably in studies of suppression in dysphoric individuals (Conway, Howell, & Giannopoulos, 1991; Howell & Conway, 1992; Renaud & McConnell, 2002; Wenzlaff, Wegner, & Klein, 1991). A recent study extended these findings to the domain of autobiographical memory (Dalgleish & Yiend, 2006). Results showed that in dysphoric individuals, the suppression of a negative memory resulted in increased activation of other negative information (presumably distracters used in order to achieve suppression), thereby rendering negative information more accessible on a subsequent autobiographical-memory retrieval task. Moreover, depressed mood may deplete cognitive resources needed for an effortful cognitive process such as suppression. Hartlage, Alloy, Vázquez, and Dykman (1993) have observed that depression interferes mostly with effortful processing and only minimally with automatic processing. Thus, ironic process theory (Wegner,

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1994) predicts that suppression undertaken during a depressed mood would impair functioning of the effortful operating process (which diverts attention away from the target thought) and leave unhindered the functioning of the automatic monitoring process (which maintains vigilance for the target thought), thereby increasing accessibility of the target thought. The hypothesis that suppression conceals a cognitive vulnerability to depression was proposed by Wenzlaff and Bates (1998) and tested in a series of studies with individuals at high risk for depression (e.g., individuals remitted from depression). Theories of cognitive vulnerability to depression assert that depressive schemata may be latent but can be activated by conditions similar to those experiences that were initially responsible for creation of the schemata (Beck, Rush, Shaw, & Emery, 1979). Other models based on Bower’s (1987) associative network model (Miranda & Gross, 1997) predict that because depressive schemata are likely to develop in a negative emotional context, they should be associated with a negative mood in memory. When the individual is no longer experiencing the negative mood, the associated depressotypic cognitions should be less accessible, thereby allowing them to become dormant or latent. It appears, however, that studies aimed at revealing negative schemata in remitted depressed individuals using methods of mood induction are, at best, equivocal (Ingram, Miranda, & Segal, 1998). According to Wenzlaff and Bates (1998), one possible reason why such attempts at revealing depressive schemata fail may be that remitted depressed individuals are trying to suppress the very thoughts investigators are attempting to detect. In this sense, the depressive cognitions of remitted-depressed individuals are latent not in that they are inactive but because their influence is concealed by active suppression. Research in this area supports the idea that thought suppression masks a cognitive vulnerability to depression, that this vulnerability becomes apparent when mental control is disabled (e.g., when rehearsing a 9 digit number during the task), and that this effect is particularly pronounced among those who engage in chronic thought suppression (Wenzlaff & Bates, 1998; Wenzlaff & Eisenberg, 2001; Wegner & Zanakos, 1994; Wenzlaff, Meir, & Salas, 2002; Wenzlaff, Rude, Taylor, Stultz, & Sweatt, 2001). One such study, for example, revealed that the imposition of a cognitive load caused remitteddepressed individuals to interpret recorded homophones in a more negative fashion (performing more similar to depressed than to control subjects), and that this was not the case without the cognitive load. Similar studies have been done using scrambled sentences which could be

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unscrambled to form depression-relevant (i.e., depressotypic) themes. In all of these studies, the increase in negative thinking induced by the cognitive load was significantly correlated with Wegner and Zanakos’s (1994) measure of propensity to suppress unwanted thoughts. The rationale behind these studies is that if remitted depressed individuals are actively suppressing depressotypic thinking, it should be possible to detect the suppressed negative bias by imposing a cognitive load. Taken together, results of these studies are consistent with the hypothesis that the active suppression of depressotypic thoughts may serve to mask an underlying depressive schema in individuals at risk for depression.

SUPPRESSION OF WORRY IN GENERALIZED ANXIETY DISORDER AND INSOMNIA Worry is conceptualized as thoughts that are motivated by the avoidance of emotionally negative imagery and of concomitant aversive somatic sensations (Borkovec & Inz, 1990). Although worry is initiated in order to avoid imagery of future catastrophe and of current anxiety sensations, it quickly becomes undesirable in itself and is experienced as increasingly uncontrollable (Borkovec & Roemer, 1995). Thus, an important difference between worries and other unwanted intrusive thoughts (e.g., those in OCD) is that they are ego-syntonic and hence the motivation to suppress them is not obvious. However, once the worries themselves become unwelcome, they may initiate a cycle of self-perpetuating counterproductive attempts at controlling them. Nevertheless, a study conducted by Behar, Vescio, and Borkovec (2005) to distinguish between the effects of thought- versus image-suppression about a worrisome target did not reveal a rebound effect for either group. A cardinal feature of generalized anxiety disorder (GAD) is the persistence of uncontrollable worries. Becker, Rinck, Roth, and Margraf (1998) tested the hypothesis that patients with GAD show a bias in ability to suppress their worries. Consistent with their hypothesis, they observed that GAD patients found it more difficult to suppress thoughts of their worries than thoughts of a neutral target. However, Mathews and Milroy (1994) did not observe a suppression-specific rebound effect for worries in a nonclinical sample of excessive worriers. They found that worriers had more frequent worry thoughts than nonworrying individuals regardless of mental control instruction. Taken together, these findings suggest that thought suppression may play a limited role in exacerbating worries in GAD. Harvey (2003) further illuminated the role of thought suppression in the maintenance of worry by investigating

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its effects in clinical insomnia. Worries surface as a persistent cognitive activity in clinical insomnia (Borkovec, 1982). Harvey (2003) found that compared to control participants, insomniacs reported a greater use of suppression to control their presleep worries. Furthermore, insomniacs instructed to suppress their self-identified worry reported worse sleep quality and longer sleeponset latency than did insomniacs in the no-suppression condition. The intriguing finding is that this was the case in the absence of a rebound of the worrying thought for the suppression group, suggesting that the act of suppression—possibly due to the effort devoted to the endeavor—appears to exacerbate the disorder.

SUPPRESSION AND ALCOHOL USE AND ABUSE Alcohol abuse is conceptualized as a disorder of overactivation of approach motivation toward the positive effects of alcohol (Palfai & Ostafin, 2003) coupled with underactivation of avoidance motivation away from its negative consequences (Ostafin, Palfai, & Wechsler, 2003). It follows that cognitive avoidance strategies at odds with this pattern of motivation—such as the suppression of positive alcohol-related thought—meet with little success. The research on thought suppression in alcohol use was motivated by a finding that individuals in the process of quitting smoking experienced an enhancement of smoking-related intrusions under suppression (Salkovskis & Reynolds, 1994). Palfai, Colby, Monti, and Rohsenow (1997) tested the hypothesis that in a sample of heavy social drinkers, suppression of urges to drink would lead to increased accessibility of alcoholrelated information, particularly information regarding expectancies about the effects of alcohol. In their study, heavy social drinkers were exposed to their usual alcoholic drink during which one group was instructed to suppress the urge to drink alcohol and the other group received no instructions. Following this, both groups made timed judgments about the applicability of a number of alcohol outcome expectancies. As hypothesized, those in the suppression condition were faster to endorse alcohol outcome expectancies than those in the control condition. This suppression-induced hyperaccessibility of alcohol-related information in heavy social drinkers is consistent with results of a study conducted with a sample of alcohol abusers. In this study, Klein (2007) found that alcoholic subjects who had tried to suppress thoughts of alcohol prior to performing a modified Stroop task showed increased interference for the word “alcohol” as compared to those alcoholic subjects

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who had expressed thoughts about alcohol freely prior to the task. These results are consistent with the idea that suppression leads to hyperaccessibility (Wegner & Erber, 1992) of suppressed information and that this bias in information-processing may play a role in maintaining the disorder. The effects of suppression in alcohol abuse have also been assessed, though less directly, on biological indicators of psychological well-being, such as heart-rate variability (HRV). HRV has been shown to be positively correlated with measures of cognitive flexibility and with the ability to regulate emotion (Johnsen et al., 2003). Consistent with this idea, Ingjaldsson, Laberg, and Thayer (2003) found a negative association between HRV and the propensity to suppress unwanted thoughts in chronic alcohol abuse. These results support earlier findings that suggest that low HRV is associated with impaired cognitive control and rigid thinking (Thayer & Lane, 2002), and that thought suppression is particularly counterproductive for mitigating alcohol-related urges and cravings (Palfai, Colby et al., 1997; Palfai, Monti, Colby, & Rohsenow, 1997). It is interesting to note that the suppression of alcoholrelated urges may have cross-substance effects. For instance, Palfai, Colby et al. (1997) have discovered that those who had previously suppressed their urge to drink alcohol showed an increase in smoking behavior. It remains to be seen whether these cross-substance effects are specific to the relationship between alcohol and smoking or if they can be extended to the suppression of other unwanted urges. Confirmation of the latter would expand considerably the scope of suppression-related negative consequences for addictions.

SUPPRESSION AND SELF-INJURIOUS THOUGHTS AND BEHAVIORS Self-injurious thoughts and behaviors (SITB) include suicidal ideation, suicide attempts, and nonsuicidal selfinjury (NSSI) or direct, deliberate destruction of body tissue in which there is no intent to die (e.g., cutting or burning one’s skin). Recent conceptualizations of SITB suggest that it is a disorder of avoidance motivation in that it functions to avoid aversive cognitive and emotional experiences (Baumeister, 1990; Boergers, Spirito, & Donaldson, 1998; Chapman, Gratz, & Brown, 2005; Nock & Prinstein, 2004, 2005). Take the example of a 13-year-old patient who has an argument with her boyfriend. She has a predisposition for high emotional reactivity and is immediately overwhelmed by anger, sadness, fear of her boyfriend forsaking her, and thoughts

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of her own worthlessness, among a host of other negative cognitions and emotions. She cannot bear the emotional arousal, tries to not think about it, fails, only thinks about it more, and then finds some, though minimal, relief in focusing on thoughts of cutting herself. Ultimately, it is the behavior of cutting that helps reduce her emotional arousal. Research has suggested that when people try to suppress thoughts, they tend to undertake an unfocused distraction strategy—the iterative use of many different distracters rather than just one focus—and experience a rebound of the suppressed thought (Wegner, Schneider, Knutson, & McMahon, 1991). However, this rebound effect is less likely to occur if suppression is undertaken using a focused distracter thought (Wegner et al., 1987). This successful focused distraction from certain thoughts is often an adaptive strategy for reducing the frequency of the thoughts or the distress associated with them (Johnstone & Page, 2004; Salkovskis & Campbell, 1994). However, it may be maladaptive in cases when the distracter itself is harmful, such as in the example above, when SITB becomes the focused distracter from thoughts that create aversive emotions. A study by Najmi, Wegner, and Nock (2007) tested a model suggesting that the propensity to suppress unwanted thoughts is a cognitive mediator of the relationship between emotional reactivity and SITB. Results of this cross-sectional study revealed that the self-reported propensity to suppress unwanted thoughts partially mediates the relationship between emotional reactivity and the frequency of NSSI and suicidal ideation. Moreover, those with a higher tendency to suppress unwanted thoughts reported engaging in NSSI primarily in order to reduce aversive emotions. Thus, the general tendency to suppress unwanted thoughts was demonstrated in the need to suppress the specific aversive thoughts and emotions that trigger NSSI.

SUPPRESSION AND PSYCHOSIS The study of thought suppression in psychosis has not attracted many researchers, probably because they recognize that other factors are likely to cause such disorders, and that the study of suppression is thus unlikely to get to the heart of the problem. However, this approach may obscure how suppression could be involved in the amplification of symptoms. As discussed above, ironic process theory predicts that when mental capacity is compromised by cognitive load, the control falls below a baseline level and produces the opposite of the intended effect. However, this is not unique to thoughts, but in fact is the

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same process at work when people are burdened by competing cognitive demands as they try to relax (Wegner, Broome, & Blumberg, 1997), concentrate (Wegner, Erber, & Zanakos, 1993), sleep (Ansfield, Wegner, & Bowser, 1996), avoid being prejudiced (Macrae, Bodenhausen, Milne, & Jetten, 1994), or ignore pain (Cioffi & Holloway, 1993; Masedo & Esteve, 2007). Could suppression of psychotic symptoms also serve to intensify them? The ironic process theory suggests an exploration of the intriguing possibility that suppression may play a role in the persistence of hallucinations in psychotic disorders (Morris & Wegner, 2000). The hypothesis that hallucinations are maintained by avoidance motivation follows from the idea that auditory hallucinations share certain features with the intrusion of unwanted thoughts (Morrison, Haddock, & Tarrier, 1995). Much like auditory hallucinations, intrusive thoughts often take the form of repetitive, ego-dystonic, unacceptable images, or impulses, which, if appraised negatively, can generate feelings of “mental pollution” (Rachman, 1994). Morrison and Baker (2000) found that patients who experienced auditory hallucinations had more intrusive thoughts than did the no-hallucinations schizophrenia control group and the nonpsychiatric control group. Furthermore, patients who experienced auditory hallucinations found their intrusive thoughts more distressing, uncontrollable, and unacceptable than did the control groups, and the degree of distress caused by the voices was associated with their negative appraisal of the voices. According to Morrison et al.’s (1995) heuristic model, auditory hallucinations are experienced when intrusive thoughts are attributed to an external source in order to reduce cognitive dissonance. They propose that this dissonance is caused by the lack of concordance between the intrusive thoughts and preexisting metacognitive beliefs such as those concerning the controllability of these thoughts. This is consistent with Bentall’s (1990a,b) hypothesis that implicates faulty metacognitive beliefs as a critical factor that influences attempted suppression and persistence of auditory hallucinations, an idea that has been suggested earlier regarding maintenance of intrusive thoughts in OCD. Analogous to the research on intrusive thoughts, Barrett and Etheridge (1992) have found that hallucinations are a normative experience. Thus it is possible that what makes a normal hallucination clinically significant might in part be failed cognitive avoidance strategies, such as suppression. Morrison (1998) suggests that the process underlying disturbing intrusive thoughts in anxiety disorders and disturbing intrusive auditory hallucinations in psychotic disorders may in fact be similar. The

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cognitive model of panic (Clark, 1986) suggests that panic attacks result from a predisposition to misinterpret certain bodily sensations, especially common somatic responses to anxiety, in a catastrophic manner, appraising them as being indicative of immediate danger. This predisposition is maintained in part by cognitive and behavioral avoidance that prevents disconfirmation of threat (Salkovskis, 1996). Morrison (1998) suggests that appraisals of hallucinations in psychosis may be analogous to this catastrophic misinterpretation in panic. Although there are as yet no empirical studies addressing this hypothesis directly, there exists some preliminary evidence consistent with the proposed framework. For example, it has been shown that individuals who experience auditory hallucinations exhibit stronger metacognitive beliefs regarding the uncontrollability of mental events, in comparison with psychiatric and nonpsychiatric controls (Baker & Morrison, 1998). To the extent that beliefs about controllability influence attempts at mental control, as has been suggested in the case of intrusive thoughts in OCD, these findings are consistent with the possibility that attempts to avoid or suppress might play a role in the maintenance of hallucinations. Morrison and Wells (2000) assessed various strategies used to control unwanted thoughts—distraction, social control, punishment, worry, and reappraisal—and showed that individuals with schizophrenia used significantly more punishment and worry strategies and significantly less distraction strategies than did control subjects. Romme, Honig, Noorthorn, and Escher (1992) found that use of distraction as a coping strategy was inversely correlated with ability to cope with hallucinations, whereas Nayani and David (1996) found that the use of distraction coping strategies was correlated with reports of worsening the hallucinations. Although these results do not assess thought suppression per se, they are consistent with the idea that the use of certain cognitive techniques can exacerbate or maintain auditory hallucinations in a manner similar to that which occurs with unwanted, intrusive thoughts. According to Bentall (1990a,b), auditory hallucinations may reflect a bias, rather than a deficit, in the monitoring of internal events, and this bias may be influenced in part by beliefs and in part by negative reinforcement in the form of anxiety reduction. For instance, the misattribution of certain kinds of internally generated events, such as negative, ego-dystonic, thoughts about the self, as being externally generated may be reinforced by a temporary reduction in anxiety. Bentall’s ideas are consistent with those of Morrison et al. (1995), namely that beliefs inconsistent with intrusive thoughts lead to cognitive

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dissonance which is then reduced when the intrusive thoughts are attributed to an external source, as in auditory hallucinations. The individual, instead of remaining indifferent to the appraisal of the hallucination, will then engage in counterproductive avoidance strategies, such as suppression (Morrison, 1998, 2001; Morrison et al., 1995). The idea that hallucinations are maintained by suppression of self-discrepant, ego-dystonic, thoughts (Morrison & Baker, 2000; Morrison et al., 1995) was examined empirically by García-Montes, Perez-Alvarez, and Fidalgo (2003) using a nonclinical sample. They investigated the effects of the repeated suppression of self-discrepant thoughts on the vividness of auditory illusions. They found that when discrepancy of thoughts was high, suppression indeed increased the quality of the illusions reported by participants; on the other hand, when discrepancy of thoughts was low, their suppression had no effect on the quality of auditory illusions. This study of illusions in a nonclinical sample provides a basis for examining the phenomenon of hallucinations in a clinical sample. Treatment using the normalizing approach of Kingdon and Turkington (1993), in which they propose the use of psychoeducation regarding the commonness of hallucinations, may help to prevent catastrophic misinterpretation of hallucinations and the subsequent use of misguided mental control to get rid of them. A model for this exists in the treatment of OCD in which the original thought suppression experiment (Wegner et al., 1987) has been used for several years now as a behavioral experiment in therapy. Patients have been invited to suppress thoughts of a neutral target, e.g., giraffe, and the subsequent occurrence of the giraffe images is then used as the basis for educational discussion about the need to control thoughts (Baer, 2001; Salkovskis & Campbell, 1994).

SUPPRESSION AND DREAMS As a final note on mental disorder and suppression, it is worth noting that one of the more insidious symptoms of disorder—recurrent distressing nightmares (Hartmann, Russ, van der Kolk, Falke, & Oldfield, 1981)—might also be open to a suppression analysis. Wegner, Wenzlaff, and Kozak (2004) asked participants in a nonclinical sample to spend some time before bed attempting to suppress the thought of a person; those in comparison conditions either thought about the person for this time or thought about anything (after having their attention directed to the person). Dream diaries collected the next morning revealed that thinking about the person increased the

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likelihood of dreaming about the person, but that suppression of thoughts about the person increased such dreaming even more. This was true regardless of the emotional valence of the person (attractive or not), suggesting that the tendency to suppress thoughts in waking may make them return in dreams. If people suffering from severely distressing thoughts in the daytime put them aside through suppression, it makes sense that they might end up paying for this strategy with horrific nightmares. The role of such processes in psychopathology has yet to be discerned, but these results suggest that thought suppression may play a part in magnifying mental distress.

CONCLUSION Taken together, studies on thought suppression in psychopathology present a more nuanced picture now than was emerging in the early years of its investigation. Some evidence is consistent with the idea that the counterproductive effects of suppression are causally implicated in the disorder, but for the most part a more parsimonious conclusion is that thought suppression acts as a complication of the disorder. The detrimental effects of suppression are often different across a wide range of emotional disorders. Suppression is rarely successful in the long run, but in some cases it can be successful in the short-term and prevent exposure to and habituation of undesirable emotional states; in other cases, suppression is often counterproductive, exacerbating aversive thoughts, and concomitant aversive emotions; finally, faulty beliefs about the possibility of successful suppression and subsequent attributions of the inevitable failure of suppression can exacerbate the negative emotional state and trigger further futile suppression attempts. In one way or another, suppression, like most experiential avoidance strategies, is detrimental to psychological well-being. Future research should focus on evaluating the relative merits of alternatives. Recently reported successes of mindful-acceptance based techniques in the treatment of emotional disorders (Bach & Hayes, 2002; Foa & Wilson, 2001; Hayes, Strosahl, & Wilson, 1999; Roemer & Orsillo, 2002; Segal, Williams, & Teasdale, 2002) suggest a possible mechanism that encourages exposure to unwanted thoughts and feelings, at the very least by explicitly discouraging suppression. Wenzlaff (2005) suggested that one way of understanding mindfulness-based therapies is that they work against avoidance motivation, specifically the individual’s tendency to try to suppress unwanted thoughts. “The instruction to be mindful instead promotes an abandonment of mental control intentions .… This kind of therapy may have salutary effects because it replaces the

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use of a self-defeating mental control technique with a simple relaxation of the control motive” (p. 74).

ACKNOWLEDGMENT The research reported here was supported in part by NIMH Grant MH49127.

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Orienting and Attentional Processes and Attentional 27 Motivational Components of Personality Douglas Derryberry and Marjorie Reed CONTENTS Temperament Framework for Motivation, Attention, and Personality .................................................462 Motivational Systems .......................................................................................................................462 Attentional Systems ..........................................................................................................................463 Personality ........................................................................................................................................463 Reaction Time Studies of Approach and Avoidance.............................................................................464 Basic Experimental Paradigm ..........................................................................................................464 Approach-Related Processing ..........................................................................................................466 Avoidance-Related Processing .........................................................................................................467 Processing Relative Value ................................................................................................................468 Motivated Attention and Personality Development .............................................................................. 470 Approachful Children....................................................................................................................... 470 Avoidant Children ............................................................................................................................ 470 Attentional Control ........................................................................................................................... 471 Conclusion ............................................................................................................................................. 472 References ............................................................................................................................................. 472

Although approach and avoidance motivation are most often discussed in terms of behaviors, it is now clear that such motivation also regulates attention. From a motivational perspective, states related to appetitive and defensive needs appear to bias attention in favor of stimuli capable of satisfying or blocking that need. Given defensive needs, for example, attention to signals predicting danger and safety is enhanced. Such enhancement helps link sensory and response pathways, making it easier for the individual to avoid the danger and approach safety (Derryberry & Reed, 2002; Posner & Rothbart, 1998). Motivational influences on attention are also important because they provide a mechanism through which motivational states can influence a wide range of cognitive processes. In these cases, attention is directed away from sensory channels toward more internal pathways

involved in conceptual, affective, and response processing. For example, achievement-related needs may bias attention toward stored information related to success and failure, and social needs may allocate attention toward information related to acceptance and rejection. Such information can be used in thinking about the past, in anticipating the future, and in formulating coping strategies that help the person approach positive outcomes and avoid negative outcomes (Matthews, 1997). In addition, motivated attention is important in that attention is one of the processes that stabilize information in memory (Grossberg, 1999). Enhanced attention helps store motivationally significant information in memory, building representations that are more developed regarding sources of success and failure. These representations can then be called upon to help guide behavior in future 461

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situations. When viewed in terms of learning and development, it is not hard to see that motivational influences on attention may play a central role in personality development. As the child grows older, underlying approach and avoidance processes bias attention in relation to the individual’s unique needs and environment, gradually shaping representations of the self, others, and the future. Combined with the underlying motivational systems, such representations are often viewed as central to personality (Derryberry & Reed, 1996; Elliot & Thrash, 2002). This chapter consists of three sections. We begin with a theoretical overview, briefly laying out physiological and psychological models of motivation, attention, and personality. The second section describes three sets of reaction time studies that we have used to explore motivational and personality influences on attention. These studies demonstrate that in situations involving approach or avoidance, attention is modulated by the previous outcome of success or failure and by personality traits of Extraversion, Anxiety, and Attentional Control. Finally, the last section returns to a developmental perspective to consider interactions among motivational, attentional, and representational processes in the development of personality.

TEMPERAMENT FRAMEWORK FOR MOTIVATION, ATTENTION, AND PERSONALITY In laying out our temperament framework, we briefly describe circuitry relevant to approach and avoidance behavior, followed by a description of attentional systems and their connections with the motivational systems. We then consider how individual differences in these systems are related to personality and clinical problems.

MOTIVATIONAL SYSTEMS Since physiological mechanisms are covered in other chapters, we provide a brief outline of our theoretical model. The model is based on multiple, parallel motivational systems such as those involved in appetitive, defensive, and nurturant needs. These motivational systems share control over other circuits involved in orchestrating approach and avoidance behavior. In addition to controlling behavior, the motivational systems regulate attention to environmental stimuli relevant to the current need. The motivational systems are distributed throughout the brain, providing a variety of approach and avoidance behaviors. If we look at the defensive system, for example, individual motor and autonomic components arise from

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circuits in the medulla. These components are coordinated by descending projections from the midbrain’s periaqueductal gray (PAG) area. The PAG contains columns of cells that elicit distinct avoidance behaviors depending upon the nature of the immediate threat. An explosive form of escape behavior is elicited when an organism is under immediate threat but has an escape route. If the organism is cornered with no escape route, then defensive aggression is triggered in an attempt to fight off the predator. If the organism is injured and defensive aggression is not possible, then a form of tonic immobility (playing dead) can be activated (Bandler & Shipley, 1994; Keay & Bandler, 2001). The PAG columns are reciprocally connected with higher circuits within the limbic system and cortex. These circuits allow more complex avoidance behavior in relation to stimuli that are spatially and temporally more distant. Descending connections from the hypothalamus are thought to be involved in more directed forms of escape (active avoidance) given a more distant threat. Connections from the amygdala appear to orchestrate avoidance (e.g., active or passive avoidance) in relation to conditioned stimuli that signal threat, whereas hippocampal projections help co-ordinate a form of “risk assessment” when an organism cautiously enters an area previously occupied by a threat (Gray & McNaughton, 1996). Descending connections from the orbital and medial frontal cortex provide further fine tuning of avoidance behaviors, presumably in relation to more abstract dangers such as failure, rejection, and so on. As can be seen, the defensive circuitry appears to have evolved in such a way as to take increasing advantage of distant stimuli, dangers that are spatially and temporally more distant from the individual. The circuitry underlying appetitive motivation is less well understood, but appears to be similarly distributed across the brain. Within the PAG, for example, columns have been located related to sexual and feeding behavior. These behaviors are strongly regulated from the hypothalamus, as well as via descending projections from the amygdala and frontal cortex. Again, it is likely that the higher projections regulate approach in relation to more abstract types of rewards. Additional research has found that approach is regulated via critical circuits converging on the nucleus accumbens, a ventral extension of the striatum. Most of this forebrain circuitry is under the facilitatory influence of dopaminergic projections arising from the midbrain. The approach-related circuitry has been discussed in terms of a “behavioral activation system” (Gray, 1987), a “behavioral facilitation system” (Depue & Collins, 1999), and an “expectancy-foraging system” (Panksepp, 1998).

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Motivational and Attentional Components of Personality

ATTENTIONAL SYSTEMS Appetitive and defensive systems possess extensive connections to the brain’s attentional systems. The resulting attentional control increases the efficacy of approach and avoidance by facilitating relevant stimuli (e.g., rewards to be approached, dangers to be avoided). The attentional effects can be exerted in several ways, perhaps best described in terms of Posner’s three interacting attentional systems (Posner & Raichle, 1994). Posner has discussed a “vigilance” system involving norepinephrine projections from the brainstem’s locus coeruleus to the cortex. This system is thought to lack the specificity required for highly selective attention, but nevertheless to be involved in tonic maintenance and phasic adjustments in general alertness. Phasic alerting may enhance signal-to-noise ratios across multiple sets of synapses, biasing relatively large forebrain circuits in relation to motivationally significant stimuli. Also, the noradrenergic system plays an important role in neuronal plasticity, helping to store important information in memory (Berridge & Waterhouse, 2003; Gu, 2002). In addition to the noradrenergic systems, a number of other projection systems are likely to be involved in general attentional functions. These include the serotonergic projections from the raphe nuclei, dopaminergic projections from the ventral tegmental area, histaminergic projections from the hypothalamus, and cholinergic projections from the nucleus basalis (Gu, 2002). Together with the noradrenergic projections, these systems form an intricate network that exerts highly complex neuromodulatory effects on distinct cortical layers and regions. All of these projection systems appear closely linked to motivation, with the source nuclei receiving inputs from the PAG, hypothalamus, amygdala, and frontal cortex. A second set of attentional circuits is involved in orienting attention from one specific location to another. This “posterior attentional system” is distributed across the midbrain’s superior colliculus, the pulvinar nucleus of the thalamus, and the parietal lobe within the cortex. Its functioning can be best understood in terms of component operations that allow attention to “disengage” (parietal lobe) from one location, “move” (superior colliculus) to a new location, and “engage” (thalamus) or enhance that location (Posner & Raichle, 1994). So far, fewer motivational inputs to the orienting system have been identified compared to the vigilance system. The frontal cortex has direct projections to most of the orienting circuitry, as does the vigilance-related systems, but other motivation-related regions, such as the amygdala and hypothalamus, have less direct or weaker connections.

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A third attentional system is located within the frontal cortex and the anterior cingulate region. This “anterior attentional system” is viewed as a voluntary, executive system responsible for regulating the posterior attentional system and controlling attention to semantic and response information (Posner & Raichle, 1994; Rothbart, Derryberry, & Posner, 1994). A similar formulation can be found in Shallice’s “supervisory attentional system” (Stuss, Shallice, Alexander, & Picton, 1995). Posner and Rothbart (1998) suggest that the anterior system underlies the conscious, “effortful control” of behavior through which the individual can regulate more reactive motivational functions. In addition, we have suggested that individual motivational systems can recruit the anterior system during voluntary motivational states (Derryberry, Reed, & Pilkenton-Taylor, 2003). Connections through which motivational states may access voluntary attention are plentiful, including ascending frontal connections from the PAG, hypothalamus, amygdala, and hippocampus (Ongur & Price, 2000). To provide a more functional example, consider someone entering a grocery store and scanning for a tasty food item. Individual food items are processed in detail within the cortex and then delivered to the motivational systems (though more direct inputs from the thalamus are also available; LeDoux, 2000). If a rewarding item is detected, attention will be directed toward the item to facilitate processing and evaluation. In more detail, brainstem vigilance mechanisms (e.g., the noradrenergic projections) will exert a relatively general alerting effect on the cortex; attention will orient (disengage, move, and engage) to the new location, facilitating the further processing of the food information in that location; and within the anterior system, additional conceptual information may be brought into play, prepotent response and conceptual pathways may be inhibited, and the orienting will be brought under voluntary control. This regulated information will then converge on the approach and avoidance systems, and if approach is more strongly activated, then the reaching response will be guided (via the enhanced sensory information) toward the food item. In addition, attention will help stabilize the relevant pathways in memory in order to update the individual’s “food map” for future use. This memory effect is likely to involve several attentional components, such as the ascending noradrenergic effect on the cortex (Berridge & Waterhouse, 2003; Grossberg, 1999).

PERSONALITY Most temperament models assume that the motivational systems vary in reactivity or strength across individuals

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and that these differences underlie major personality dimensions. As the approach system increases in strength, individuals are thought to move from the introverted to the extraverted end of the Extraversion dimension. Thus, extraverts should be more sensitive to rewarding stimuli, more likely to attend to and to approach these stimuli, and more likely to experience feelings such as hope, desire, and positive anticipation (Depue & Collins, 1999; Eysenck & Eysenck, 1985; Gray, 1987; Watson & Clark, 1992). Given the idea that attention facilitates learning, extraverts would be expected to develop representations that feature positive as opposed to negative elements. Because they feed back into the motivational systems, the extravert’s “optimistic” representations should preferentially engage the appetitive circuitry, leading to increased probability of future approach behavior (Derryberry & Reed, 1996). In contrast, the defensive or avoidance system is usually related to neuroticism. As one moves from the “stable” to the “neurotic” end of this dimension, the individual becomes more sensitive to negative information, more likely to attend to it, to avoid it, and to suffer from negative emotions such as anxiety, depression, and anger. In addition, attention to negative information may lead to relatively negative and pessimistic representations, thereby increasing the probability of future avoidance (Eysenck & Eysenck, 1985; Watson & Clark, 1992). It is worth noting that some models propose that the underlying motivational process does not map directly onto Extraversion and Neuroticism, but rather aligns with two other dimensions running diagonally within the twodimensional space (Gray, 1987; Wallace, Newman, & Bachorowski, 1991). Thus, approach reactivity is viewed as increasing along an “Impulsivity” dimension running from stable introversion to neurotic extraversion, and avoidance reactivity (behavioral inhibition) is viewed as increasing along an “Anxiety” dimension that runs from the stable extravert to the neurotic introvert. In contrast to motivational tendencies, traditional personality models have not addressed attentional capabilities. In early studies, however, we found that differences in self-reported “attentional focusing” and “attentional shifting” were evident and related to other personality measures (Derryberry & Rothbart, 1988). For example, the attentional measures were negatively related to measures of negative emotions, suggesting that individuals with better control can use their attention to reduce negative affect. Rothbart and Posner went on to build a developmental model in which individual differences in frontal circuits related to executive attention are proposed to underlie a dimension of “Effortful Control” (Posner & Raichle, 1994; Rothbart & Bates, 1998). Effortful control is thought to

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provide a voluntary means of controlling more reactive approach and avoidance tendencies. For example, good effortful control may allow an individual to inhibit a prepotent approach (or avoidance) response, and thus execute a more situationally appropriate avoidance (or approach) response. As described later in the section on reaction time studies, we have combined our earlier shifting and focusing scales into a single measure of “Attentional Control” (Derryberry & Reed, 2002). Unpublished work has found Attentional Control to correlate most strongly with the dimension of conscientiousness (r = .5 to .6), but to also correlate with Neuroticism (r = −.3 to −.4) and Extraversion (r = .2 to .3).

REACTION TIME STUDIES OF APPROACH AND AVOIDANCE We will return to personality in the last section of the chapter where we adopt a developmental perspective. But first, it is necessary to provide specific evidence for the types of motivational, attentional, and personality processes that have driven our theorizing. The studies we will describe seem particularly relevant to the theme of this handbook because we have always framed our paradigms around approach and avoidance orientations. We first describe the general paradigm, followed by three sets of experimental findings.

BASIC EXPERIMENTAL PARADIGM Our primary goal has always been to examine the theoretical ideas expressed above by investigating attentional biases related to approach and avoidance states. It is possible to elicit these states fairly easily by using a game framework within which participants can gain or lose points on each trial. Positive (approach-related) trials led to a gain of 10 points if the response was accurate and faster than the participant’s median reaction time from the last game (success), but no loss of points if the response was too slow (failure). In contrast, negative (avoidance-related) targets led to a loss of 10 points if the response was slower than the median RT (failure), and no loss of points if the response was faster (success). Because the criterion for success and failure was based on each person’s average speed, cumulative scores (across a block of trials or a set of blocks) tended to stay close to zero. This made the games more challenging and prevented confounding by states related to particularly low or high scores. Participants were simply told that the game is programmed to be challenging, and that the average score, at the end of the set of blocks, tended to be

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close to zero. They were told that sometimes their score would be above zero, at other times below zero, but that their overall goal should be to break zero at the end of the set. In motivational terms, we assumed that participants were motivated to “approach” winning points and to “avoid” losing points, and that this underlying motivation could be manipulated, with some precision, by the signals presented on each trial. Each trial consisted of three signals. First, a cue appeared, signaling whether the trial would be positive or negative in nature. For example, some studies used a cue on the right side to signal the opportunity to gain points and a cue on the left side to signal the chance of losing points. Other studies used the letter M to signal a positive trial and the letter W a negative trial. These signals were assumed to elicit a brief, phasic motivational state related to approach or avoidance. Second, the effect of this state is assayed by presenting a simple target within 500 ms following the cue. Targets could involve a simple dot to be detected, a word to be categorized, or a letter to be categorized. They could match or mismatch the cue in location or meaning. Third, a feedback signal was presented roughly 1 s after the response. These signals took several different forms across different studies, including smiling and frowning faces, green and red squares, and so on. The feedback signal was assumed to elicit an outcome-related motivational state (success or failure) that might extend across time to influence cue and target processing on the next trial. Here is an example using our simplest spatial orienting task (Posner, 1978). The trial begins with a cue in the form of an arrow pointing up on the right side of the screen, signaling that if the subsequent target appears on the right 10 points can be gained, but if the target appears on the left no points can be gained. The cue is assumed to activate a positive, approach-related state that motivates an attentional shift to the more important right side of the screen. A simple detection target appears on the right or left side of the screen. If the target appears in the attended (e.g., right) location, the RT will be fast because attention has already moved and facilitated detection on the right (a “valid” trial). But if the target appears in the unattended location (e.g., left), then the RT will be slow because attention must be shifted from the attended to the unattended targeted location (an “invalid” trial). The relative strength of this attentional bias can be estimated by subtracting the fast RTs on the attended (right) side from the slower RTs to targets on the unattended (left) side (i.e., invalid–valid RTs). Thus, it is possible to compute the size of this basic attentional effect on both approach and avoidance trials. The bias can also be

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assessed in relation to the outcome of the previous trial, to determine whether previous success and failure influence subsequent attention. We designed this paradigm because it allows improved control of the targeted motivational processes and attentional processes. Other success and failure manipulations have been shown to elicit the intended positive and negative emotions (Nummenmaa & Niemi, 2004). Our game format allows honest success and failure feedback in a relatively balanced mix, with no danger of participants not believing the feedback. Importantly, it allows assessment of approach and avoidance motivation within the same person. Both types of contexts involved the same number of points and thus the same distance toward or away from the goal. In most studies, positive and negative signals were also made as identical as possible in terms of their physical properties, varying only in location (left or right) or orientation (M or W, 2 or 5). The design also provides better control over attention. For one thing, we were able to partially disentangle attentional from response effects by using the same exact response (a key press with the right index finger) for both types of targets. In addition, we were able to track attentional movement across time by presenting the targets at varying intervals (SOAs: stimulus onset asynchronies) following a cue. Furthermore, these paradigms can be modified to provide a more precise view of attention itself. They can be used to break attention down into components such as Posner’s disengage, move, and engage operations, and to examine more voluntary as opposed to involuntary processes. A main disadvantage, at least in the context of approach and avoidance motivation, is that our paradigm focuses on a specific type of avoidance motivation in which one performs an arbitrary response (neither approaching or avoiding in structural terms) in order to avoid a negative outcome. Although this may not fit well within the more classic notions of avoidance (physically avoiding an object or location), it is nevertheless a common form of motivation that may be found in contexts of performance, achievement, and social acceptance where success and failure are primary outcomes. We have performed a few studies in which subjects physically avoided a certain target location, but the results can be difficult to interpret given the more complex programming required for avoidance than approach responses. We will summarize the results from three sets of studies completed across the last 15 years. The first focuses on approach motivation and the conditions under which it is enhanced. The second set of studies focuses on avoidance motivation, underlying attentional mechanisms, and

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individual differences. The last set describes studies investigating attentional effects of relative value, where a conflict is set up by presenting two simultaneous targets differing in incentive value (e.g., worth 5 points or 2 points).

APPROACH-RELATED PROCESSING One of our initial questions was whether the cue-elicited attentional effect would be stronger for positive trials (where points could be gained) or negative trials (where points could be lost). Some have argued that the human processing system is basically biased toward positive information, a tendency sometimes referred to as the “Pollyanna Effect” (Matlin & Stang, 1978). However, others, such as Kahneman and Tversky (1979) and Baumeister, Bratslavsky, Finkenauer, and Vohs (2001) have argued that humans show a general “loss aversion,” viewing losses as more important than equivalent gains. We approached this question by comparing the strength of attentional effects elicited by positive and negative cues. As described above, such effects can be estimated by computing the difference between valid trials (where cue and target match) and invalid trials (where cue and target mismatch requiring a reorienting of attention). Our earliest studies presented positive (an arrow pointed up) and negative (an arrow pointed down) cues to indicate whether points could be gained or lost. This was followed by a state-descriptive adjective that was to be categorized as positive (e.g., happy) or negative (e.g., sad). Although both kinds of cues elicited strong attentional effects, we could find no general differences between the positive and negative cues (Derryberry, 1988). Other studies using a spatial orienting task presented cues in a positive or negative location, followed by a detection target in the cued or uncued location. Again, orienting was found to both positive and negative locations, but with no general biases favoring one location or the other (Derryberry & Reed, 1994). Thus, we have been unable to find any general differences in the overall attentional effects related to approach and avoidance motivation. We suspect that such general effects will be difficult to find because motivational states are not always equally active, and thus, will only lead to attentional biases under certain circumstances. Although a positive attentional bias is not generally active, such an effect does arise following failure. In other words, the outcome states of success and failure alter motivational activity and appear to change the impact of positive and negative incentives. In our early studies with state adjectives, we found what we termed an “incongruent effect,” i.e., following positive feedback,

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attentional effects were equal for positive (61 ms) and negative (57 ms) cues, but following negative feedback, attentional effects were stronger for positive (56 ms) than negative (32 ms) cues (Derryberry, 1988). Using the spatial orienting paradigm, attentional effects following positive feedback were equal for positive (17 ms) and negative (16 ms) cues, but following negative feedback, attentional effects were stronger for positive (17 ms) than negative (10 ms) cues (Derryberry & Reed, 1994). Similar examples of incongruent effects can be found in Derryberry (1993) and more recently in Rothermund (2003). Such effects suggest that approach and avoidance motivation are modulated by the previous outcome, with failure enhancing the attentional impact of positive relative to negative cues. This type of effect would be adaptive in helping the person to continue approaching a task following a failure. The incongruent effect is generally compatible with the notion that motivational states have “inertial tendencies,” such that approach-related motivation may build in strength following failure (Atkinson & Birch, 1978). The effect is also consistent with neural models featuring positive and negative motivational systems that are connected by reciprocal inhibitory neurons (Grossberg & Schmajuk, 1987). When one system (e.g., avoidance) is weakened by repeated activation, the other system (e.g., approach) is disinhibited, resulting in a rebound enhancement. In addition to regulation by the previous outcome, the attentional effects are also influenced by the more enduring motivational processes related to personality. Our spatial orienting studies have employed measures of extraversion, neuroticism, anxiety, and impulsivity to investigate models such as Gray’s (1987). Predictions are fairly clear from these models that extraverts (or neurotic extraverts) should show relatively strong attentional effects under approach conditions (potential gain), whereas neurotics (or neurotic introverts) should show stronger effects in avoidance situations (potential loss). Two sets of studies have found such differences (Derryberry, 1987; Derryberry & Reed, 1994). Averaged across the two 1994 studies, positive cues elicited greater attention in extraverts (35 ms) than introverts (25 ms) and negative cues elicit greater attention in introverts (26 ms) than extraverts (18 ms). Thus, we find evidence for the Pollyanna effect and the loss aversion effect, but importantly, in different individuals. As suggested by models such as Gray’s (1987), the approach or behavioral activation system should be engaged more strongly in extraverts than introverts and should facilitate approach behavior given positive cues. The behavioral inhibition system should be engaged more strongly in introverts and

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should inhibit approach and direct attention to threats requiring potential avoidance. A closer look at this data suggests that the Extraversion effect is strongest in neurotic extraverts and neurotic introverts, and that it interacts with the failure-related enhancement of the positive bias. Averaged across the two studies, failure-related increase in the positive bias is greatest in neurotic extraverts. Following failure, neurotic extraverts show an attentional effect of 39 ms for positive cues and 16 ms for negative cues, whereas stable extraverts show an effect of 30 ms for positive and 23 ms for negative cues Thus, extraverts and especially neurotic extraverts respond to failure with enhanced attention to positive cues affording the opportunity to gain points, while introverts show no changes in response to positive cues. This effect may reflect a basic motivational difference between extraverts and introverts. Extraverts may show enhanced approach motivation following failure that allows them to remain optimistic and to persist in the face of difficulties (which may or may not prove adaptive). Such a process is supported by the work of Newman and his colleagues with extraverts and psychopaths (Newman, 1987; Wallace et al., 1991). These researchers proposed that negative feedback engages a nonspecific arousal system related to neuroticism, which in turn facilitates the positive and negative motivational processes related to extraversion (Wallace et al.). As a result, negative feedback should enhance attention to positive cues in neurotic extraverts and to negative cues in neurotic introverts. In summary, our studies suggest that the positive bias is rather elusive, appearing in only some people under some conditions. In general, approach and avoidance motivation appear roughly equal in terms of their effects on attention. However, approach motivation gets stronger after unsuccessful compared to successful outcomes, with this enhancement effect appearing primarily in extraverts.

AVOIDANCE-RELATED PROCESSING We turn now to a set of studies examining negative attentional effects. Again, we found that an individual difference approach was essential to studying such effects. As predicted by models such as Gray’s, anxious individuals (e.g., neurotic introverts) showed a relative general bias favoring negative cues that signaled a potential loss of points. In the 1994 studies, for example, the attentional effect of a negative cue is stronger in neurotic introverts (25 ms) than neurotic extraverts (15 ms). Unlike the positive bias, the negative bias did not depend on the previous outcome (Derryberry & Reed, 1994). In general, the negative bias is consistent with many other findings that anxious

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individuals (who tend to be neurotic introverts) show an attentional bias favoring threatening information (MacLeod & Mathews, 1988; Fox, Russo, Bowles, & Dutton, 2001). Several of our studies have attempted to examine the specific operations underlying this negative attentional bias. Although so far we have spoken in terms of an overall “attentional effect” computed by subtracting RTs following valid cues from those following invalid cues, it is possible to begin to consider underlying operations by examining the valid and invalid trials separately. Given a valid cue, attention must disengage from a neutral location (a fixation point), move to the cued location, and engage the cued location. But given an invalid cue, attention must also disengage from the cued location, move to the uncued location, and then engage the target. Such an analysis suggests that valid trials primarily reflect the time required by the move and engage operations, whereas invalid trials reflect in large part the extra time required to disengage attention. Almost all of our studies have found motivational and personality effects to appear on invalid rather than valid trials. Typically RTs will be similar given valid cues but different given the invalid cues that require attention to be disengaged from the cued location. In our 1994 studies, introverts (especially neurotic introverts) showed greater delays given invalid negative cues than did extraverts (Derryberry & Reed, 1994). This pattern suggests that high anxious people are not faster than low anxious people in moving to and engaging a cued negative location, but rather, are slow to disengage from that location once it has been attended. The delayed disengagement has been replicated by Derryberry and Reed (2002) and also by Fox et al. (2001). Although more research is needed, the delayed disengagement provides an interesting approach to understanding anxious cognition. It may be misleading to say that an introvert or anxious person is more likely to attend to or notice perceptual or conceptual threats. In contrast, the impaired disengagement may make it difficult to respond to other relevant information, such as the safety signals that are beneficial in coping with the threat. While less anxious people may shift away, more anxious people may become “stuck” in worrisome and ruminative lines of thought. As more anxiety is elicited, a positive feedback loop can be established leading to increasingly pessimistic thought, stronger anxiety, and stronger tendencies to employ avoidant coping strategies. It thus becomes important to consider mechanisms through which this loop can be attenuated and hopefully broken. Our most recent studies have focused on the relationship between negative biases and individual differences in attentional control. Earlier we described models suggesting

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that individuals differ not only in underlying motivational systems, but also in their capacity to use executive, effortful attentional mechanisms. In early questionnaire work, we developed scales to measure individual differences in “Attentional Focusing” and “Attentional Shifting” (Derryberry & Rothbart, 1988). More recently, we have combined the focusing and shifting measures into a single, 20-item measure of “Attentional Control” which we have used in conjunction with our other personality measures. One set of RT studies (Derryberry & Reed, 2002) examined the anxiety-related attentional bias reported above (Derryberry & Reed, 1994), which we suspected would be decreased in people with good attentional control. The design was a modified spatial orienting task where the approach and avoidance trials, rather than being randomly interspersed, were separated into positive games (where points could be gained) and negative games (where points could be lost). Pretarget cues appeared in the left or right visual field. Rather than indicating the incentive value of the upcoming target, they signaled whether a target in that location would be “difficult” or “easy.” The criteria for “fast” and “slow” responses were adjusted such that the difficult cues (an arrow pointing down) signaled that targets in that location would result in slow responses on 75% of the trials. The easy cues (an arrow pointing up) indicated that targets in that location would be responded to fast 75% of the time such that the cue predicted positive feedback. Thus, the difficult cues tagged a dangerous location by predicting negative feedback, whereas the easy cues labeled a safe location by predicting positive feedback. In addition, in order to examine shifts in attention between the dangerous and safe locations across time, we presented the detection targets at two intervals, either 250 ms or 500 ms following the cue. When the target appeared 250 ms after the cue, the anxiety-related bias was evident. All high anxious subjects were slow to disengage from invalid negative cues. Individual differences in attentional control were not influential at this short delay. When the target appeared after 500 ms, however, attentional control attenuated the effects of anxiety. Anxious subjects with poor attentional control were still slow to shift from threatening cues, as if they were stuck at the negative location. In contrast, anxious persons with good attentional control were better able to disengage and shift from the dangerous to the safe location (as were all low anxious participants). This is an important finding for it suggests that a general mechanism (attentional control) helps some people attenuate their anxiety. In social situations, for example,

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they may be better able to shift from cues related to potential rejection by one person to signals of acceptance from others. In thinking about the self, good attention may facilitate attention to positive as well as negative traits, and to the possibility of succeeding as well as failing in an achievement task. In adopting coping strategies, attentional skill may allow the person to make use of more difficult but effective coping strategies (e.g., positive reappraisal) as opposed to simpler but less effective strategies (e.g., disengagement). In general, attentional control should allow the person to take advantage of more relevant information, and thus to employ more informed and effective coping strategies (Derryberry, Reed, & Pilkenton-Taylor, 2003). In summary, our studies provide additional evidence, besides that arising from Stroop and Dot-probe tasks, of an attentional bias favoring threatening cues in high trait anxious individuals. They also provide additional evidence that the bias involves delays in the disengage attentional operation. Most intriguing, our studies indicate that individuals vary in their ability to control attention, and that while some anxious individuals may have difficulty disengaging from threat, others are better able to do so.

PROCESSING RELATIVE VALUE A third set of studies has examined attention to stimuli carrying different point values. Selecting between stimuli possessing different incentive values within the same valence is a common occurrence in everyday life. We must often choose which of several attractive activities (e.g., two movies) or between several less attractive activities (e.g., two chores) to approach. Although such decisions can be complex, we wanted to begin with a model task that would be as simple as possible. Thus, we examined attentional preferences for targets that differed in terms of the number of points that could be gained or lost. Such biases can be estimated in terms of a “value effect,” computed by subtracting the faster RTs to high value targets from those to slower low value targets. An initial study presented a composite target on each trial that consisted of two symbols: a letter M or W signaled whether points could be gained or lost, respectively, and a number 2 or 5 signaled how many points were at stake (Derryberry, 1993). Subjects were instructed to categorize the target as valuable (M2, M5, W2, W5) by pressing one key or as worthless (M3, W4, A5, V2) by pressing another key. As expected, RTs were consistently faster given high value (M5, W5) than low value targets (M2, W2), with a mean value effect (low value RTs–high value RTs) of roughly 25 ms. When a pretarget cue was

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presented before the target (e.g., M followed by M5), an incongruent feedback effect was found. Positive feedback led to slow shifts from negative cues whereas negative feedback was followed by slow shifts from positive cues. This is consistent with our previously discussed findings (Derryberry, 1988). However, when the target was presented with no preceding cue, so that attentional shifts from cue to target were not involved, the incongruent effect was replaced with a congruent effect. Failure was followed by roughly equal value effects for positive and negative targets (30 ms), but success led to larger value effects for positive (50 ms) than negative (0 ms) targets. This effect is consistent with other findings of congruency, such as those showing that positive affect leads to an increased optimism regarding potential gains (Nygren & Isen, 1985) and to decreased estimates of risk (Johnson & Tversky, 1983). More generally, these findings suggest that feedback elicits multiple parallel effects. A congruent effect favoring high value targets that may function to stabilize and prolong the motivational state, and an incongruent effect that may help attenuate or shift the motivational state. More recent studies have moved from feedback effects to concentrate on individual differences. The studies used a modified spatial orienting task in which different point values were assigned to the two sides of the screen. Positive and negative valences were presented in alternating games where points could be gained but not lost and games where points could be lost but not gained. Several studies began each trial by presenting two numbers on the screen, such as a 2 on the left and a 5 on the right. These numbers indicated how many points were at stake given a detection target at either location. Before the target appeared, one of the numbers turned red, signaling which number was more likely to be targeted. Thus, we were interested in the general bias favoring the high value location, and how this effect might interact with the attentional validity effect generated by the red cue. As expected, subjects showed faster RTs to the cued location (attentional effect) and also to the higher valued location (value effect). Interactions between these two effects depended on individual differences. Both studies found a stronger interaction in participants with good attentional control. Participants with poor attention showed similar attentional effects (i.e., invalid–valid RTs) for low value (5 ms) and high value (10 ms) locations, whereas those with good attention showed greater attention to high value (20 ms) than low value locations (−5 ms). Not only did they shift strongly to a cued high value location, good attenders tended to shift away from cued low value location. These findings are interesting in that this type of relative value

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or preference coding is carried out within the orbital frontal cortex (Schultz, Tremblay, & Hollerman, 1998), an area with important connections to the anterior cingulate region (i.e., Posner’s executive attentional system). A nearly identical, noninteracting, effect was found for Extraversion. Introverts showed similar attentional effects to low (5 ms) and high value (10 ms) cues, but extraverts showed stronger orienting to high value (15 ms) than low value (−5 ms) locations. Thus, both extraverts and good attenders show enhanced performance at high value locations, patterns suggesting a more flexible and effective strategy that can result in a higher score. Although more research is required, several aspects of the data suggest separate mechanisms may be involved in extraverts and good attenders. The Attentional Control effect is consistent with our other studies in focusing on the invalid trials, suggesting delays in shifting attention from the high value cues. In contrast, the Extraversion effect is limited to valid trials and involves higher error rates (i.e., pressing the key following a high value cue on trials when no target was presented). Such differences suggest that the Attentional Control effect may reflect attention whereas the Extraversion effect may reflect response potentiation elicited by the high value cue. Our studies of incentive value are consistent with our studies of approach- and avoidance-related processing. On the one hand, attentional processes appear to be modulated as a function of the previous outcome, though incentive value is subject to a congruent as well as an incongruent influence. In addition, people differ in their orienting to high value targets; both good attenders and extraverts show facilitated processing when expecting a high value target. More generally, our findings suggest that approach and avoidance motivation are quite flexible. They vary in relation to ongoing states resulting from success and failure, with feedback exerting two complementary effects on subsequent processing. A congruent effect functions in the absence of pretarget cues and facilitates high value positive targets following positive feedback. Such an effect may serve to lock in and enhance approach motivation, something that would be adaptive when responses are achieving success. When a pretarget cue is presented, an incongruent potential is revealed that increases the attentional impact of cues differing in valence from the previous outcome. Such an effect is important in countering the congruent effect, and thus making it easier for the person to break loose and shift to an alternative state of approach or avoidance. Regarding the attentional effects, our findings indicate that feedback and temperament influence attention by

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regulating the time to disengage from certain types of stimuli. Although this may suggest that motivational pathways function by directly adjusting the disengage circuitry, we cannot say for sure that this is the real locus of the effect. The problem is that slow disengagement may also arise as an indirect consequence of facilitating the engage mechanism. Thus, anxious people may tend to strongly engage threatening stimuli, making it more difficult for them to disengage. An effect of enhancing engagement would make sense in that it affords a more direct influence in facilitating the processing and storage of the important information. Finally, our findings support approaches to personality based on the notion that personality is framed around basic forms of motivation related to approach and avoidance (Elliot & Thrash, 2002). Extraversion does appear related to approach motivation, though the effect is relatively subtle and appears primarily after negative feedback. Anxiety is consistently related to avoidance situations involving threat. However, evidence suggests that individuals vary in terms of other systems related to voluntary attention, and that these differences in Attentional Control are crucial to understanding the effects of Extraversion and Anxiety. Therefore, we will focus on personality in the final section, describing some of the potential interactions arising between extraversion, anxiety, and attentional control.

MOTIVATED ATTENTION AND PERSONALITY DEVELOPMENT A developmental perspective is especially useful for viewing the motivational and attentional components of personality. We adopt such a perspective in this final section, and explore both the benefits and the costs related to certain personality profiles. As will be seen, approach and avoidance motives, along with attention and the child’s developing representations, are at the heart of the self-organizing processes which shape the child’s personality.

APPROACHFUL CHILDREN Beginning with approach motivation, children who are more extraverted or impulsive will be more sensitive to environmental rewards and thus more likely to approach a variety of objects and people. Such approach can be beneficial in providing the child with more opportunities to learn about the various rewards available in the world. Because they show biases toward positive cues following failure, extraverted children may find it easier to remain

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optimistic without becoming discouraged. In addition, their friendly approach of other people tends to elicit positive affect in return, allowing the child to benefit from pleasant and stimulating social interactions. As the child becomes older and forms more complex representations, the attentional bias should function to stabilize the more positive components of the representations. In thinking about the self, for example, the child’s failures may be associated with positive as well as negative information, providing for a sense of confidence and efficacy. Along similar lines, noticing positive aspects of an unsuccessful outcome provides additional options for coping. Such children are likely to adopt the more adaptive approachbased rather than avoidant strategies. On the other hand, children with strong approach motivation can also run into trouble. A major goal of socialization is to bring approach tendencies into line with cultural standards. The more impulsive children may find themselves making inappropriate approaches, leading to punishment from their friends, family, or teachers. Newman has suggested that such failures may further enhance approach motivation, such that the child fails to learn from the failure because the approach orientation interferes with attention to the faulty behaviors and relevant rules. The extraverted child may utilize approach-oriented strategies, but they may be less optimal strategies such as those involving confrontation and lacking planning. In addition, the child’s persistence following failure may make it difficult to shift to a new coping strategy. Finally, the child with strong approach motivation may be vulnerable to frustration and anger when approach is unsuccessful (Carver, 2004; Derryberry & Rothbart, 1997). In the most serious cases, children with strong approach motivation will be vulnerable to externalizing or impulsive disorders, such as conduct disorder and hyperactivity (Derryberry et al., 2003; Fowles, 1994).

AVOIDANT CHILDREN In contrast, more fearful children prone to avoidance may tend to inhibit approach of new people and situations. This may make it easier for them to avoid impulsive problems, resulting in praise from parents and teachers for their good behavior. Although they may be less likely to elicit high-stimulating social interactions, fearful or shy children may still evoke rewarding social interactions, though these may be fewer in number and calmer in nature. High anxious children show more empathy (Rothbart, Ahadi, & Hershey, 1994) and an enhanced development of conscience (Kochanska, 1997;

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Kochanska, Coy, & Murray, 2001; Kochanska, Gross, Lin, & Nichols, 2002) compared to low anxious children. One explanation is that they pay greater attention to punishment, to their behavior and feelings of guilt, to negative cues indicating feelings of others, and to the principle involved in moral behavior. Attention results in a binding of these feelings and behaviors to the moral principle. Unfortunately, anxious children can run into problems in several ways. In behavioral terms, their tendency to avoid certain situations can make it difficult to learn the skills required to cope with stressful situations. In addition, their performance in social situations may be impaired due to their general inhibition and difficulty in disengaging from negative cues (e.g., perceived frowns, potential embarrassment). In performance or achievement contexts, anxious children may respond to failure with discouragement and less effort, especially if they are introverted and lack the facilitation of approach found in extraverts. Their difficulty in disengaging from negative information may lead to memory representations that emphasize negative aspects of the self (e.g., as incompetent), others (as rejecting), and of the world in general (as dangerous). In more extreme cases, such children will be vulnerable to internalizing disorders such as childhood anxiety (e.g., overanxious disorder; school phobia) and depression (Derryberry et al., 2003; Fowles, 1994). Our examples above describe adaptive and maladaptive outcomes in terms of a single motivational system. It is important to note, however, that these systems interact and thus all systems need to be taken into consideration. From such a perspective, it can be seen that the most vulnerable children will be those with strong approach and weak avoidance systems and those with strong avoidance and weak approach systems. For example, children with strong approach and weak avoidance are most likely to be overly impulsive and disinhibited, and limited in their capacity to learn from mistakes and to develop strong moral principles (Quay, 1993). Conversely, children with strong avoidance and weak approach are most likely to be overly inhibited, withdrawn, and to give up in the face of even minor failure. If anxious children had a strong approach system, then they could temper their withdrawal and gain more environmental rewards (Derryberry & Rothbart, 1997).

ATTENTIONAL CONTROL Especially important interactions involve attentional control. In general, good attention should help the child avoid problems related to the extremes of approach and avoidance motivation. Children with strong approach tendencies and poor attentional control will be most vulnerable to

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impulsive, externalizing problems (especially if they are also low in anxiety). In contrast, children with good attentional control will be better able to delay the gratifications and resist the temptations accompanying strong approach motivation. Mischel has found that the ability to delay gratification (e.g., to wait 10 min before approaching an attractive object) depends on various attentional strategies that serve to amplify the “cool” relative to the “hot” aspects of the situation. For example, children are better able to delay eating a marshmallow when they look away from it or think of it as a puffy white cloud (Mischel, 1983; Metcalfe & Mischel, 1999). It is worth noting that this attention-related ability shows remarkable stability, with preschool ability to delay gratification predicting competent coping during adolescence (Shoda, Mischel, & Peake, 1990) and coping with rejection sensitivity in the early thirties (Mischel & Ayduk, 2002). As mentioned above, another potential problem related to strong approach motivation involves frustration and anger when the goal is blocked. Good attentional control can protect against such problems by allowing more effective use of coping strategies. In a study of 4–6 yearold children, boys with good attentional control were found to deal with anger by using nonhostile, verbal methods rather than more overt aggressive methods (Eisenberg, Fabes, Nyman, Bernzweig, & Pinulas, 1994). A more recent study examined the effectiveness of different anger-regulating strategies in three and a half yearolds while they waited to eat a cookie (Gilliom, Shaw, Beck, Schonberg, & Lukon, 2002). Children who used strategies of voluntarily directing attention away from the cookie (e.g., distraction, passive waiting) were most effective in controlling their anger, whereas those who focused on the cookie showed increased anger. When assessed at the age of six, children who had used passive waiting and distraction strategies showed fewer externalizing symptoms, whereas those who focused on the cookie showed more externalizing. Finally, attentional control may constrain problematic approach behavior by facilitating empathy and conscience development. Although empathy and morality can arise from strong fear motivation, they are also related to strong “effortful control” (Kochanska, 1997; Rothbart et al., 1994). An attentional explanation suggests that morality involves complex representations linking behaviors, feelings, and principles. Children with good attentional control may have the flexibility required to shift between and thereby progressively link the relevant sources of information. Once internalized, the child’s moral principles can provide powerful constraints on approach behavior.

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In cases of anxiety, it is again children with poor attentional control who will most likely suffer from their fears. Such children may have difficulty shifting attention from anxious content in social or achievement situations, resulting in an increase in their anxiety and consequent decrease in their performance. After the punishing event, anxious children may continue to think about their failures, giving rise to cognitive representations that are biased in favor of negative aspects of the self and the world. In contrast, anxious children with good attention can benefit in many ways. In anticipating a novel social situation, for example, such children should be better able to disengage from the possible threats that they might encounter in the situation (e.g., strangers), and shift their attention to possible sources of reward (e.g., fun games). The more balanced anticipation should make it more likely that these children will approach rather than avoid the situation, and thus gain from the experience. Upon entering the social situation, anxious children with good attention should be better able to disengage from the threatening aspects and to shift attention to a source of safety or reassurance (e.g., their friends). Again, this should attenuate their anxiety, improve performance, and make them more likely to enjoy the situation. Afterwards, as these children think about the experience, their attentional flexibility should allow them to develop representations that are more balanced, featuring positive as well as negative memories. They may also be able to utilize cognitive coping strategies such as positive reappraisal (“It wasn’t as bad as I had feared”) or compensation (“I was scared but I was still friendly”). Although more research is needed, these ideas are supported by findings of negative relations between attentional control and anxiety in adults (Derryberry & Rothbart, 1988) and children (Rothbart et al., 1994). Attentional control has also been found to moderate the effects of negative emotionality on social competence and shyness (Eisenberg, et al., 2001), and as described above, good attentional control allows anxious adults to shift from a threatening to a safe location (Derryberry & Reed, 2002). Related ideas can be found in Lonigan, Vasey, Phillips, and Haze (2004), Mathews, Yiend, and Lawrence (2004), and Muris and Dietvorst (2006).

CONCLUSION This chapter has developed the idea that we can gain a better understanding of approach and avoidance motivation by going beyond behavior to study effects on attention and related cognitive processes. When this is done, we can see that attention arises from a highly complex set of

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systems that work together to control alertness, orienting, and executive functions. This attentional complexity affords motivational processes a range of mechanisms through which to influence information processing. Although most current research has focused on a few motivational processes (e.g., anxiety) and mechanisms (e.g., orienting), we are only beginning to appreciate the many potential ways in which motivation might influence attention and cognition. Similarly, the complexity of motivational states may go beyond our usual formulations. We have described our rather obvious findings that approach-related states are regulated depending on the previous outcome or feedback. This regulation is not simple, however, and appears to involve at least two complementary effects. A congruent effect serves to strengthen and prolong the motivational state, while an incongruent effect prepares a shift to a new state. In addition, feedback signals appear to interact with attentional systems at the highest executive levels within the anterior cingulate (Luu, Tucker, Derryberry, Reed, & Poulsen, 2003). This is consistent with the notion that feedback-related states are among the brain’s most important forms of self-regulation. Finally, our research suggests that we can gain a better understanding of personality by adopting a developmental perspective that focuses on the systems related to approach and avoidance. Depending on their temperament and environment, each child will possess diverse tendencies to approach and avoid. The related motivational systems will recruit attentional systems to regulate forebrain processing in an adaptive way. Because attention is fundamental to learning, this regulation can be viewed as a progressive binding and sculpting of the child’s representations, an extension of the motivational systems into the cortex. But at the same time, the representations feed back upon the motivational circuitry, providing the motivational systems with the enhanced evaluative and strategic potential arising from the cortex’s architecture. Thus, motivational and cognitive processes become progressively intertwined, and we can better appreciate the extent to which personality is a self-organizing process.

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Posner, M. I., & Rothbart, M. K. (1998). Attention, self-regulation and consciousness. Philosophical Transactions of the Royal Society of London B, 353, 1915–1927. Quay, H. C. (1993). The psychobiology of undersocialized aggressive conduct disorder: A theoretical perspective. Development and Psychopathology, 5, 165–180. Rothbart, M. K., Ahadi, S. A., & Hershey, K. L. (1994). Temperament and social behavior in childhood. Merrill-Palmer Quarterly, 40, 21–39. Rothbart, M. K., & Bates, J. E. (1998). Temperament. In W. S. E. Damon & N. V. E. Eisenberg (Eds.), Handbook of child psychology: (Vol. 3, pp. 105–176). Social, emotional and personality development. (5th ed.). New York: Wiley. Rothbart, M. K., Derryberry, D., & Posner, M. I. (1994). A psychobiological approach to the development of temperament. In J. E. Bates & T. D. Wachs (Eds.), Temperament: Individual differences at the interface of biology and behavior (pp. 83–116). Washington, DC: American Psychological Association. Rothermund, K. (2003). Motivation and attention: Incongruent effects of feedback on the processing of valence. Emotion, 3, 223–238. Schultz, W., Tremblay, L., & Hollerman, J. R. (1998). Reward prediction in primate basal ganglia and frontal cortex. Neuropharmacology, 37, 421–429. Shoda, Y., Mischel, W., & Peake, P. K. (1990). Predicting adolescent cognitive and self-regulatory competencies from preschool delay of gratification: Identifying diagnostic conditions. Developmental Psychology, 26, 978–986. Stuss, D. T., Shallice, T., Alexander, M. P., & Picton, T. W. (1995). A multidisciplinary approach to anterior attentional functions. In J. Grafman, K. J. Holyoak, & F. Boller (Eds.), Annals of the New York Academy of Sciences, Volume 769. Structure and functions of the human prefrontal cortex, New York: The New York Academy of Sciences. Wallace, J. F., Newman, J. P., & Bachorowski, J. (1991). Failures of response modulation: Impulsive behavior in anxious and impulsive individuals. Journal of Research in Personality, 25, 23–44. Watson, D., & Clark, L. A. (1992). On traits and temperament: General and specific factors of emotional experience and their relation to the five-factor model. Journal of Personality, 60, 441–476.

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Framing Persons and Situations 28 How Regulate Message Framing Effects: The Study of Health Behavior Alexander J. Rothman, Jhon T. Wlaschin, Roger D. Bartels, Amy Latimer, and Peter Salovey CONTENTS Message Framing and Health Behavior: The Function of the Behavior ............................................... 476 Detection and Prevention Behaviors: A First Look .............................................................................. 476 Specifying the Distinction Between Detection and Prevention Behaviors ...........................................477 Message Framing and Health Behavior: The Role of Dispositional Factors ........................................ 478 Message Framing and Health Behaviors: Integrating Situational and Dispositional Factors .............. 479 Prevention- and Promotion-Oriented Health Behaviors: Implications Beyond Message Framing ................................................................................................482 Final Thoughts ......................................................................................................................................484 References .............................................................................................................................................484

Joan flips through her mail and notices a postcard from her health plan urging her to get a mammogram. Across the top it reads, “The costs of not having a mammogram.” Across town, Carla notices a similar postcard. However, the slogan on her card reads, “The benefits of having a mammogram.” Six months later, the health plan finds that women who received a card with a loss-framed appeal (such as Joan received) were more likely to have obtained a mammogram than were women who received a card with a gain-framed appeal (such as Carla received). The observation that the manner in which a message is framed can affect people’s behavioral decisions is fascinating and has intrigued both basic and applied behavioral scientists. Over the past 15 years, investigators have worked to specify the factors that guide the impact of gain- and loss-framed appeals and have strived to provide practitioners with a set of guidelines that could be used to maximize the impact of health communication programs

(Rothman, Bartels, Wlaschin, & Salovey, 2006; Rothman, Kelly, Hertel, & Salovey, 2003; Rothman & Salovey, 1997; Rothman, Stark, & Salovey, 2006). To date, two perspectives have guided our understanding of when loss- and gain-framed messages are maximally persuasive. One view has emphasized the manner in which the function of the health behavior—in particular, whether it is designed to detect or to prevent a health problem— moderates the impact of framed appeals (Rothman & Salovey, 1997), whereas the other view has emphasized how people’s dispositional sensitivity to favorable or unfavorable outcomes moderates the impact of framed appeals (Mann, Sherman, & Updegraff, 2004). In this chapter, we examine the conceptual frameworks that underlie each of these perspectives and review the available empirical evidence. We then provide a new conceptualization of framing effects that integrates the two dominant perspectives. Specifically, we propose that people’s responses to framed appeals are contingent on their 475

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self-regulatory tendencies and the accessibility of these tendencies is a function of people’s dispositional preferences and features of the behavioral decision. We believe this new perspective has the potential not only to advance our understanding of when and how gain- and loss-framed messages are effective, but also to generate new, innovative predictions regarding other aspects of health cognition and health behavior.

MESSAGE FRAMING AND HEALTH BEHAVIOR: THE FUNCTION OF THE BEHAVIOR Health communications can be framed in terms of the benefits afforded by adopting a health behavior (a gainframed appeal) or in terms of the costs associated with failing to adopt a health behavior (a loss-framed appeal). As illustrated in the earlier example, a brochure promoting mammography could emphasize the benefits of screening—“By getting a mammogram you give yourself the best chance of detecting breast cancer early”—or the costs of not screening—“By failing to get a mammogram, you will miss the best chance of detecting breast cancer early.” The premise that altering how information is framed can affect people’s behavioral decisions was motivated by the framing postulate of Prospect Theory (Tversky & Kahneman, 1981). According to Prospect Theory, people’s preferences are sensitive to how information is framed: people act to avoid risks when considering the potential gains afforded by a decision (they are risk-averse in their preferences), but are willing to take risks when considering the potential losses afforded by their decision (they are risk-seeking in their preferences). Rothman and Salovey (1997) proposed that predictions regarding the relative influence of gain- and lossframed messages on health behavior can be derived from the conceptual framework outlined in Prospect Theory. Given the premise that people are more willing to take risks when faced with loss-framed information but are more risk-averse when faced with gain-framed information, the influence of a given frame on behavior should depend on whether the behavior under consideration is perceived to reflect a risk-averse or risk-seeking course of action. To the extent a decision to engage in a health behavior involves some degree of uncertainty or risk, people will be more responsive to a loss-framed message. Conversely, to the extent a health behavioral decision affords a relatively certain or safe outcome, people will be more responsive to a gain-framed message. Consistent with this perspective, a taxonomy of healthrelevant situations—classifying them as risk-averse or

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risk-seeking—was developed that affords predictions as to when gain- or loss-framed health appeals are maximally persuasive (Rothman & Salovey, 1997; Rothman et al., 2003). When people are considering a behavior that they perceive involves some risk of an unpleasant outcome (e.g., it may detect a health problem), loss-framed appeals should be more persuasive. When people are considering a behavior that they perceive involves a relatively low risk of an unpleasant outcome (e.g., it prevents the onset of a health problem), gain-framed appeals should be more persuasive. At the heart of this taxonomy is the observation that the function served by a health behavior can serve as a reliable heuristic for whether people construe a behavior as a relatively risky or safe course of action. The primary function of detection or screening behaviors such as colonoscopy or mammography is to detect the presence of a health problem. Because of this emphasis on the behavior’s ability to inform people that they are symptomatic or ill, choosing to initiate the behavior may be considered a risky decision. In contrast, the primary function of prevention behaviors, such as the regular use of sunscreen or condoms, is to prevent the onset of an illness and maintain a person’s current health status. Thus, choosing to adopt a prevention behavior affords people a relatively safe option as there are few potential costs associated with performing them. The primary risk associated with these behaviors concerns the decision not to take action (e.g., failing to apply sunscreen when one’s skin is exposed to the sun places one at risk for skin cancer). Taken together, this framework suggests that loss-framed appeals would be more effective in promoting the use of detection behaviors but gain-framed appeals would be more effective in promoting the use of prevention behaviors.

DETECTION AND PREVENTION BEHAVIORS: A FIRST LOOK The distinction between prevention and detection behaviors has proven to be a relatively useful heuristic for understanding the impact of message framing on health behavior. Research on detection behaviors has tended to reveal an advantage for loss-framed appeals, with the majority of these studies having focused on promoting cancer screening practices (e.g., screening mammography and breast self-examination [BSE]; Banks et al., 1995; Cox & Cox, 2001; Finney & Iannoti, 2002; Meyerowitz & Chaiken, 1987; Schneider et al., 2001; colorectal cancer screening; Myers et al., 1991). Although no study has shown gain-framed appeals to be more effective than loss-framed appeals in promoting cancer screening behaviors, several studies have either failed to

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How Persons and Situations Regulate Message Framing Effects

find an advantage for either frame (Lalor & Hailey, 1990; Lauver & Rubin, 1990; Lerman et al., 1992) or have found the effect to be limited to a specific subset of individuals (Apanovitch, McCarthy, & Salovey, 2003; Finney & Iannoti, 2002; Schneider et al., 2001). Fewer empirical studies have examined prevention behaviors than have examined detection behaviors. However, research has generally supported the prediction that gain-framed messages should effectively promote behaviors that prevent the onset of health problems (Detweiler, Bedell, Salovey, Pronin, & Rothman, 1999; Jones, Sinclair, & Courneya, 2003; Linville, Fischer, & Fischhoff, 1993; Millar & Millar, 2000; Rothman, Salovey, Antone, Keough, & Martin, 1993; but see McCaul, Johnson, & Rothman, 2002). Although the pattern of findings across studies is generally consistent with the guiding framework, the most persuasive evidence that framing effects are contingent on the function of the advocated behavior comes from a study in which a single health behavior served either a detection or a prevention function. Rothman, Martino, Bedell, Detweiler, and Salovey (1999) presented participants with framed messages advocating the use of a mouthrinse that was designed either to detect the presence of plaque (i.e., a detection behavior) or to prevent the accumulation of plaque (i.e., a prevention behavior). The results of the study revealed the predicted interaction between frame and behavior: participants were more likely to request a free sample of the plaque-detecting mouthrinse after having read a loss-framed message, but were more likely to request a free sample of the plaquepreventing mouthrinse after having read a gain-framed message. Rivers, Pizarro, Schneider, Pizarro, and Salovey (2005) conceptually replicated these findings in a randomized field study examining Pap test utilization.

SPECIFYING THE DISTINCTION BETWEEN DETECTION AND PREVENTION BEHAVIORS The empirical evidence indicates that the function of the behavior regulates the impact of gain- and loss-framed messages. But this premise is grounded on an underlying assumption regarding how people construe the behavior. For example, it is because detection behaviors are perceived to afford a degree of uncertainty and risk that lossframed appeals are thought to be more persuasive. To the extent there is variability in how a given behavior is construed, the relative influence of loss- and gain-framed messages will vary. Early evidence of this premise was reported by Meyerowitz, Wilson, and Chaiken (1991) who found that loss-framed messages were most effective

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in promoting BSE, but only for those women who perceived the behavior to be relatively risky. To experimentally test the assumption that the risk posed by adopting a behavior is responsible for the relative impact of framed messages, Bartels, Kelly, and Rothman (2006) manipulated the risk implications posed by both a prevention behavior (a vaccine) and a detection behavior (a screening test). In one study, participants read about a new vaccine for West Nile virus (i.e., a prevention behavior). Some participants learned that the vaccine was effective for 9 out of 10 people who are vaccinated and thus there was no risk to being vaccinated, whereas other participants learned that the vaccine was effective for only 6 out of 10 people who are vaccinated and thus relying on the vaccine to protect their health posed some degree of risk. Consistent with predictions, participants who considered a vaccine whose effectiveness was uncertain were more persuaded by a loss-framed article, whereas participants who considered a vaccine whose effectiveness was assured were more persuaded by a gain-framed article. A second study examined what happens when one varies the risk implications associated with a detection behavior. In this case, participants learned about a fictitious enzyme, Thioamine Acelytase (TAA) that was said to either confer a health benefit (i.e., the enzyme made them more resistant to a complex set of pancreatic disorders) or indicate a health problem (i.e., the enzyme made them more susceptible to a complex set of pancreatic disorders; for a full description, see Croyle & Ditto, 1990). We predicted that participants would perceive testing for the potentially harmful enzyme to be a relatively risky decision, and therefore, a loss-framed message would render them more willing to schedule a test at the university health center. On the other hand, participants would ascribe little risk to testing for the beneficial enzyme, and therefore, a gain-framed message would render them more willing to schedule a test. The relative rates with which participants were willing to schedule a TAA screening test at the university health center were consistent with predictions, but this was true only for those individuals who had previously utilized the university health services. Recent research on framing effects and attitudes toward condoms has provided a conceptually similar pattern of results. Kiene and colleagues (Kiene, Barta, Zelenski, & Cothran, 2005) explored the thesis that using condoms is seen to pose little risk when construed in terms of the health benefits they afford, but is seen as risky when construed in terms of the interpersonal negotiations associated with deciding whether to use them. Consistent with

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prior studies, Kiene et al. (2005) found that gain-framed messages were more effective when health concerns were salient, but loss-framed messages were more effective when interpersonal concerns were salient. The proposed framework may also help explain why O’Connor, Ferguson, and O’Connor (2005) found that loss-framed appeals were more effective in promoting interest in using a new hormonal contraceptive pill for men. One might imagine that because the contraceptive pill eliminates the need for unpleasant partner negotiations the pill would be construed as a health promoting behavior. However, a systematic assessment of how men construe taking a hormonal drug for contraception revealed that using a new biomedical treatment evoked a broad range of concerns regarding the risk of side effects and the uncertainty of using a new treatment. Given this focus on the risks posed by the behavior, a loss-framed advantage is not unexpected. However, one might hypothesize that as the procedure becomes more familiar and there is limited evidence of troubling side effects people might begin to construe the pill as a health promoting behavior, affording an advantage for gain-framed appeals. Taken together, these studies provide further evidence that how people construe a health behavior regulates the impact of gain- and loss-framed appeals. At the heart of this view is the thesis that health behaviors systematically elicit from people a set of thoughts and feelings and that it is the fit between this psychological state and the message frame that regulates its impact on decision-making and behavior. We will return to this thesis after examining evidence for how dispositional factors can moderate the impact of framed appeals.

MESSAGE FRAMING AND HEALTH BEHAVIOR: THE ROLE OF DISPOSITIONAL FACTORS If the way in which people construe a health behavior moderates the impact of framed appeals, one might hypothesize that people’s dispositional inclination to think about the decisions they face in terms of gains or losses might similarly affect their reaction to gain- and loss-framed messages. Several independent teams of investigators have demonstrated that people systematically differ in the degree to which they monitor for and respond to favorable and unfavorable outcomes. Some investigators have focused on the tendency with which people are motivated to approach or seek out favorable outcomes or to avoid unfavorable outcomes (Carver & White, 1994; see also Elliot & Thrash, 2002), whereas others have emphasized the notion that people differ in

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their sensitivity to the presence or absence of positive and negative events (Higgins, 1999). In either case, researchers have pursued the thesis that people who are sensitive to positive outcomes (as indexed by higher scores on promotion focus [Higgins, 1999]) or are motivated to approach favorable goals (as indexed by higher scores on behavioral activation [Carver & White, 1994]) respond more favorably to gain-framed appeals, whereas people who are sensitive to negative outcomes (as indexed by higher scores on prevention focus [Higgins, 1999]) or are motivated to avoid unfavorable goals (as indexed by higher scores on behavioral inhibition [Carver & White, 1994]) respond more favorably to loss-framed appeals. Several studies have provided empirical support for the thesis that these dispositional factors moderate the impact of framed health appeals (Latimer et al., 2007; Mann et al., 2004; Sherman, Mann, & Updegraff, in press; for similar findings outside the health domain, see Cesario, Grant, & Higgins, 2004; Lee & Aaker, 2004). For example, in a study designed to encourage dental flossing, undergraduate students who had a relatively stronger avoidance orientation (as indexed by a difference between their behavioral activation and their behavioral inhibition scores; Carver & White, 1994) reported flossing more after having read a loss-framed message, whereas those who had a relatively stronger approach orientation reported flossing more after having read a gainframed message (Mann et al., 2004). A similar pattern of results emerged in an experiment encouraging inactive adults to increase their participation in physical activity (Latimer et al., 2007). In this study, individuals were categorized in terms of whether they were more promotion- or prevention-oriented. When given gain-framed messages, promotion-oriented people reported engaging in more physical activity at the follow-up interview than did prevention-oriented people. When given loss-framed messages, prevention-oriented participants tended to report more physical activity at the follow-up interview than did the promotion-oriented individuals, but this difference was not statistically significant. What might account for the finding that dispositional tendencies can moderate the impact of framed appeals? The observed benefit of matching message frame to a person’s disposition is consistent with the broader finding that tailoring a message to fit an individual’s needs and characteristics enhances persuasion (Kreuter & Skinner, 2000; Kreuter & Wray, 2003). Messages can be tailored to a variety of characteristics such as demographics (Kreuter, Strecher, & Glassman, 1999), stage of change (Marshall et al., 2003), and dispositional factors (Latimer, Katulak, Mowad, & Salovey, 2005). Tailored messages

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are thought to be effective because they enhance the perceived relevance or importance of the message, which in turn increases the likelihood that the message will be processed systematically (Cacioppo & Petty, 1984; Eagly & Chaiken, 1993). All else being equal, greater elaboration of a strong health message is desirable as wellreasoned attitudes are more stable over time and better predictors of behavior (Petty & Wegener, 1998). Consistent with this perspective, studies have demonstrated that tailored messages are more likely to be read and remembered than are nontailored messages (Skinner, Strecher, & Hospers, 1994), are more likely to be discussed with others (Brug, Steenhuis, van Assema, & de Vries, 1996), and are perceived as more interesting and engaging (Brug et al., 1996; Kreuter, Bull, Clark, & Oswald, 1999). Regulatory focus theory (Higgins, 1998) similarly suggests that messages that are tailored to a person’s dispositional outlook may have increased persuasive impact. According to the theory, individuals experience regulatory fit when they think about or utilize behavioral strategies that match their promotion/prevention orientation. Regulatory fit makes people “feel right” about what they are doing and strengthens their engagement with and valuation of goal-directed behaviors (Higgins, 2000; Higgins et al., 2003; Spiegel, Grant-Pillow, & Higgins, 2004). This suggests that the match between message content and disposition might not only enhance the degree to which people process a message but also affect the psychological experience elicited by engaging with and responding to the message.

MESSAGE FRAMING AND HEALTH BEHAVIORS: INTEGRATING SITUATIONAL AND DISPOSITIONAL FACTORS To date, there is evidence that framing effects differ based on people’s dispositional tendencies as well as on features of the behavioral decision. In both cases, the fit between how the message is framed and the person or situation is thought to maximize the effectiveness of the framed appeal. Yet, these two lines of work have been examined independently and efforts considering how these two approaches might be related to each other have only begun to appear (Rothman et al., 2006). We believe that these two, heretofore, independent sets of moderating factors may in fact rest on the operation of a single set of underlying cognitive and affective processes. Specifically, the self-regulatory foci described in regulatory focus theory may provide an effective way to conceptualize the psychological processes that regulate the impact of gain- and loss-framed messages.

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Research on regulatory focus theory (Higgins, 1998, 1999) has demonstrated that people will adopt a prevention or promotion focus because it reflects either a chronic dispositional tendency or a mindset that is induced temporarily by features of the situation. We believe that when people contemplate or engage in a specific class of health behavior, they experience a predictable set of thoughts and feelings that represent a mindset that is conceptually analogous to the two self-regulatory orientations proposed by Higgins—prevention focus and promotion focus. The extent to which a health behavior is perceived to afford the opportunity to either achieve a desired state (i.e., promote health) or monitor for an unwanted outcome (i.e., detect an illness) may serve as a strong situation that evokes a unique set of thoughts and feelings, which in turn regulate how people respond to gain- and loss-framed messages. In some sense health behaviors can be said to engender a “personality” in that they evoke a pattern of thoughts and feelings that are consistently present whenever a person contemplates or engages in the behavior. Behaviors that promote health such as exercise or sunscreen are designed to afford favorable outcomes when performed consistently. Thus, when people think about engaging in these behaviors, they are more likely to attend to the presence or absence of favorable outcomes. For example, regular exercise affords the opportunity to be in shape (i.e., the presence of a favorable outcome), whereas failing to exercise can result in being out of shape (i.e., the absence of favorable outcome). Thus, intentions to perform these behaviors are typically grounded in the goal of maintaining or maximizing health, fitness, and well-being. Moreover, the motivation to engage in this type of behavior is thought to represent a personal choice that is expressed as an eagerness to advance toward a desired outcome. Finally, achieving the goals associated with these behaviors should elicit feelings of satisfaction, whereas failing to achieve these goals should elicit feelings of disappointment. Taken together, these psychological experiences are consistent with Higgins’ characterization of a promotion-focused self-regulatory process (Higgins, 1999). Screening behaviors such as mammography or blood cholesterol testing may engender a different set of thoughts and feelings. Because these behaviors are designed to determine the presence or absence of a health problem, we propose that when people think about engaging in these behaviors they focus on the presence or absence of unfavorable outcomes. For example, a mammogram is perceived to indicate whether you do or do not have breast cancer. Screening represents a process through which people monitor vigilantly for unwanted outcomes. Therefore, the decision to perform

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a screening behavior may feel more like a duty or an obligation (i.e., something one ought to do) than a desirable choice (i.e., something one wants to do). Finally, having attained goals associated with these behaviors (i.e., the absence of a problem) should elicit feelings of relief, whereas failing to achieve these goals (i.e., the presence of a problem) should elicit feelings of anxiety. Taken together, this set of psychological experiences is consistent with Higgins’ characterization of a preventionfocused self-regulatory process. What evidence is there that different classes of health behaviors systematically evoke distinct patterns of thoughts, motivations, and feelings? In an initial study, participants were asked to write about the thoughts and feelings they have when contemplating either exercising or having a cholesterol test (Wlaschin, Rothman, Bartels, & Bachnick, 2006). We predicted that when people think about engaging in a behavior designed to promote health (e.g., exercise), they will report thoughts and feelings consistent with a promotion-focus mindset, whereas when people think about a behavior designed to detect the presence of a health problem (e.g., cholesterol test), they will report thoughts and feelings consistent with a prevention-focus mindset. Participants’ responses were coded in terms of their fit with either a prevention or promotion mindset. Statements that described a desire to achieve a positive outcome, feelings along a satisfaction/disappointment continuum, and internal or ideal motivations were coded as promotion-oriented. Statements that described the desire to avoid negative outcomes, feelings along an anxious/calm continuum, and external or ought motivations were coded as prevention-oriented. As predicted, people who wrote about exercise provided more promotion-oriented statements than prevention-oriented statements, whereas people who wrote about a cholesterol test provided more prevention-oriented than promotion-oriented statements (see Figure 28.1). Those participants who indicated they would be willing to engage in the behavior were also asked to indicate which statement best characterized their willingness to perform the behavior—they would do the behavior because they liked to do it or they would do the behavior because they ought to do it. The decision to exercise was more likely to be characterized as a desirable choice (66% vs. 29%), whereas the decision to get a cholesterol test was more likely to be characterized as an obligation (71% vs. 34%). Finally, the different behaviors elicited two distinct patterns of emotional experience. When people thought about an exercise program, they were much more likely to describe any associated emotions with terms related to satisfaction and dejection. On

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the other hand, when people thought about the cholesterol test, their affective reactions were typically grounded in feelings of worry and relief. The clear motivational and emotional distinction between these two behaviors suggests that each experience evokes a particular regulatory mindset. However, one must be cautious in interpreting these initial findings. In particular, it is important to recognize that there are likely to be behaviors for which people differ systematically in the mindset that is elicited. For example, Apanovitch et al. (2003) assessed women’s beliefs about HIV screening. Women who believed they had some risk of HIV infection construed the behavior as a means for detecting HIV. Other women who felt they were at low risk of HIV infection construed the behavior more as a means for confirming they were HIV free. How people think about a screening test for HIV may depend on the certainty of the outcome. An uncertain outcome may create feelings of anxiety and people may be more motivated to have an HIV test out of a sense of obligation or responsibility rather than a personal choice. People who are confident that the HIV test would assure them that they are not HIV positive would naturally be less worried about being screened and view the test more as a means for confirming health. Certainty in this outcome should afford a sense of satisfaction and people may be more willing to take the test as a personal choice rather than as an obligation. In fact, Apanovitch et al. found that women who construed an HIV test as health affirming were more likely to get tested after viewing the gain-framed video,

Promotion statements

12

Prevention statements 10 8 6 4 2 0 Exercise

Cholesterol screening

FIGURE 28.1 Mean number of total prevention and promotion statements for exercise and cholesterol screening.

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whereas those who construed the behavior in terms of disease detection were somewhat more likely to get tested after viewing the loss-framed video. Although Wlaschin et al. (2006) found considerable consistency in how participants construed exercise or a cholesterol test, one could imagine situations in which people might differ in how they conceptualize engaging in exercise or having a cholesterol test. For example, people with a history of low cholesterol—either due to family history or to having had a series of normal test results—would come to construe the procedure as a means for affirming their vascular health. In a similar manner, people who have to follow an exercise plan in response to a health problem might be less likely to construe the decision to exercise as a personal choice and be more likely to construe it as a duty and obligation (see Rothman et al., 2003 for a discussion of a related series of issues). There may also be behaviors that more readily afford the adoption of different construals. For example, a regular dental visit can be perceived as an opportunity to enhance the health of one’s teeth or to learn whether one has dental problems. To the extent that the prospect of a dental visit elicits thoughts about detecting cavities, it should induce a prevention-oriented mindset, whereas if it elicits thoughts about keeping one’s teeth healthy and clean, it should induce a promotion-oriented mindset. In a recent survey of college undergraduates, we found that slightly more than two-thirds of the sample construed a regular dental visit as an opportunity to have their teeth cleaned and to promote the health of their teeth and gums, with the remaining third adopting a cavity-detection construal (Wlaschin, Bartels, & Rothman, 2007). Consistent with findings reported for cholesterol and exercise, students who focused on the detection of cavities were more likely to report affective and motivational concerns that were consistent with a prevention-oriented mindset (e.g., feelings of relief and anxiety), whereas those who focused on having their teeth cleaned were more likely to report affective and motivational concerns that were consistent with a promotion-focused mindset (e.g., feelings of satisfaction and disappointment). For example, people with a teeth-cleaning mindset were more likely to characterize attending a dental visit as reflecting a personal choice, whereas those who adopted a cavity-detection mindset characterized attending a dental visit as a duty or obligation. Given the thesis that behaviors may differ in the types of construal they evoke and that, moreover, for certain behaviors there is variability among people in the specific construal that is evoked, what determines the type of

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construal that is adopted? Why is a mammogram typically construed as an illness-detection behavior? Why are students more likely to think about a dental visit in terms of healthy teeth and gums than about cavities? Although these questions have received limited empirical attention, we believe there are, at least, three critical determinants. First, how people construe a given behavior is likely to reflect the manner in which they are socialized to think about that behavior. For example, to the extent that information presented in the media or communicated by health professionals regarding mammography emphasizes its ability to detect cancer, people are likely to adopt an illness-detection construal. We are in the process of examining one facet of this hypothesis by conducting an archival analysis of newspaper and magazine articles about cholesterol screening and about physical exercise to determine whether the media consistently uses a given construal when communicating about each of these behavioral domains. For example, we anticipate that the media will portray deciding whether to exercise as a personal choice but deciding whether to have a cholesterol test as an obligation or duty. In addition, building on a recent finding by Semin and colleagues (Semin, Higgins, de Montes, Estourget, & Valencia, 2005) that promotion-focused statements utilize more abstract words (e.g., adjectives, state verbs), whereas preventionfocused statements utilize more concrete words (e.g., descriptive action verbs) we also plan to examine whether articles about exercise and cholesterol employ more abstract and concrete words, respectively. Second, personal experience with the behavior as well as the experience of close others may shape how people perceive the behavior. In the dental health area, the extent to which visits to the dentist during childhood were characterized by cavities likely affords the development of an illness-detecting construal. If this construal makes people less eager to visit the dentist (e.g., because they are worried the dentist will find a problem), it may elicit a pattern of behavior that undermines dental health which, in turn, increases the likelihood that when the dental visit does occur their experience is less pleasant, which reinforces the initial construal. At the same time, a repeated series of favorable experiences (e.g., visits to the dentist at which no cavities are found) may over time induce a more favorable construal of a dental visit. The experiences of friends and family may also shape how one thinks about a behavior. Because events that involve the presence of disease are more memorable than those that involve the absence of disease, the adverse experiences of others may prove to have a particularly influential effect on how people think about a screening test.

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A person’s chronic tendency to adopt a promotion- or prevention-oriented mindset might also affect the extent to which a particular behavioral construal develops. Messages and experiences that match a person’s dispositional tendencies are likely to resonate and be easier to recall. The moderating impact of disposition might be particularly important in domains where the media or health professionals provide an inconsistent or weak construal or in new or novel behavioral domains where a dominant construal has yet to emerge. Finally, there may be some behaviors that fail to evoke a particularly strong promotion- or prevention-oriented mindset. In these situations, a person’s chronic tendency to adopt a preventionoriented or a promotion-oriented mindset may have a direct effect on decision-making independent of the existence of any particular behavioral construal. The thesis that a prevention- or promotion-oriented mindset can be evoked either by features of the behavioral domain or the person offers a unifying framework for thinking about the persuasive impact of gain- and loss-framed messages. Prior demonstrations that framing effects depend on whether a behavior is perceived in terms of the possibility of an unwanted outcome (Bartels et al., 2006; Rothman et al., 1999) can now be understood within this broader conceptual framework. When a behavior leads people to focus on the presence or absence of a negative outcome—which is what a screening behavior typically does, it can be understood to have induced a prevention-focused mindset that, in turn, elicits a unique set of affective and motivational concerns that guide decision-making and behavior. At the same time, when a behavior leads people to focus on the presence or absence of a positive outcome—which is what a health promotion or prevention behavior typically does, it can be understood to have induced a promotion-focused mindset that, in turn, affords its own unique set of affective and motivational concerns. One potentially important advantage of thinking about a behavior in terms of its ability to evoke a prevention- or a promotion-oriented mindset is that it provides investigators with a broader set of dimensions to specify how a particular behavior is construed and, thus, generate predictions regarding the differential impact of gain- and loss-framed appeals. For example, it might be difficult to specify the risk implications people ascribe to a treatment regimen, but it could be possible to determine whether the regimen evokes feelings of anxiety or calm or feelings of disappointment or satisfaction. Alternatively, one could examine the extent to which the behavior is perceived to represent an obligation or duty. These affective and motivational markers could then be used to predict whether

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the treatment should be categorized as a prevention- or a promotion-oriented behavior and to guide the dissemination of gain- or loss-framed appeals. However, some behaviors may fail to elicit a systematic or strong mindset. It is under these conditions (i.e., when the situation is weak) that we expect dispositional differences in people’s sensitivity to favorable and unfavorable outcomes to regulate the impact of framed messages. Flossing, the behavior examined in the studies by Mann and colleagues (Mann et al., 2004; Sherman et al., in press) may prove to be a good example of a behavior that does not elicit strong affective or motivational concerns. Alternatively, it may be the case that framing effects are maximized when there is consistency between the mindset evoked by the behavior and a person’s personality. Recall that Latimer et al. (2007) found that when encouraging exercise there was a gain-frame advantage for promotion-focused people but not a loss-framed advantage for prevention-focused people. This may provide some suggestive support for the thesis that tailoring messages that harmonize with a person’s chronic regulatory disposition and the general construal of the behavior will afford the most persuasive effect. However, additional research is needed that examines the impact of behavior and disposition on framing simultaneously before any firm conclusions can be drawn.

PREVENTION- AND PROMOTION-ORIENTED HEALTH BEHAVIORS: IMPLICATIONS BEYOND MESSAGE FRAMING The premise that health behaviors systematically induce a promotion- or a prevention-oriented mindset affords predictions not only regarding how and when people will respond to gain- and loss-framed messages, but also about other aspects of health judgment and behavioral decision-making. For example, Higgins and colleagues have observed that promotion- and prevention-focused people differ in how they judge the utility of a particular course of action. Classical models of utility suggest that people weight the likelihood (i.e., expectancy) and value of potential outcomes in a multiplicative manner that allows them to maximize utility. Across a series of studies, promotion-focused people were shown to weight expectancy and value in this manner when making behavioral decisions (Shah, Higgins, & Friedman, 1998). However, the behavioral decisions made by preventionfocused people did not reflect the normative relation between expectancy and value. Instead, preventionfocused people were more responsive to the value of a potential outcome and, in particular, as perceived value

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increased were less sensitive to information about the likelihood of the outcome. This pattern of judgment is thought to reflect the tendency for prevention-focused individuals to construe actions in terms of obligations and duties. The differential weighting of expectancy and value may have interesting implications for the application of several models of health behavior that rely on the assumption that people weight expectancy and value in a multiplicative manner. For example, several models assume that people assess the threat posed by an event (e.g., contracting the flu) based on a weighting of its perceived personal risk (i.e., likelihood) and perceived severity (i.e., value) and that perceptions of threat predict people’s willingness to take precautionary action (Weinstein, 1993). For behaviors that induce a promotion-oriented mindset, this predicted pattern of relations among constructs should hold. On the other hand, when people contemplate performing a behavior that induces a prevention-oriented mindset, people may not act in a manner that reflects the expected weighting of risk and severity. Instead, they may prove to be more responsive to the perceived severity of the outcome when considering a precautionary behavior. This is not to suggest that people in a prevention-oriented mindset are not responsive to perceptions of personal risk, but rather that perceptions of risk do not moderate the impact of perceived severity on behavioral decisions. A similar analysis could be applied to facets of other models that rely on the normative weighting of expectancy and value. The extended parallel process model (Witte, 1992) offers an interesting example. In this model, people’s behavioral decisions are thought to rest on an interaction between judgments of threat and self-efficacy such that action is most likely when people are provided information that induces perceptions of both high threat and high efficacy. In light of the present framework, we would predict that this relation would be particularly robust when applied in behavioral domains that induce a promotion-oriented mindset (e.g., behaviors that prevent HIV infection), but be less effective when applied in behavioral domains that induce a prevention-oriented mindset (e.g., screening behaviors). Of course, the viability of these predictions, as well as those outlined in the preceding paragraph, awaits empirical scrutiny. Recently, researchers have demonstrated that the adoption of a promotion- as compared to a prevention-oriented mindset evokes greater attention to long-term outcomes (Pennington & Roese, 2003) and more global (i.e., abstract) attributes (Förster & Higgins, 2005). This would suggest that health promoting behaviors may elicit greater attention to, and perhaps weighting of, long-term outcomes. For

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example, people may be willing to initiate exercise or to start eating more fruits and vegetables based on the prospect of delayed outcomes. On the other hand, decisionregarding behaviors that induce a prevention-oriented mindset may be particularly sensitive to short-term outcomes. This might possibly help to explain why perceptions of screening behaviors rest primarily on their ability to detect the presence of disease and not on the longer-term health benefits that are afforded by the treatment options that come from early detection. In fact, to the extent that people can focus on the longer-term benefits associated with a screening behavior, their construal of that behavior should change dramatically (see Orbell, Perugini, & Rakow, 2004) for an interesting demonstration regarding attitudes toward colorectal cancer screening. The observation that people who adopt a preventionoriented mindset are focused on more concrete factors might suggest that prevention-oriented behaviors will lead people to be more interested in information about how a behavior is performed. People may find that they are more reassured by instructions about how to engage in the behavior than by more general information about why a person should do it (Vallacher & Wegner, 1987). Because a prevention focus has been shown to induce a more conservative and cautious approach to decisionmaking (Higgins, 2000), behaviors that induce a prevention-oriented mindset should evoke a similar pattern of behavior. To the extent that prevention-oriented behaviors are perceived to be more prescriptive, one would predict that they would elicit limited debate about the wisdom of the behavior, and thus lead people to be more likely to follow instructions and comply with prevention-oriented than with promotion-oriented behaviors. For example, one would predict that people perceive behavioral guidelines for a screening behavior (which should induce a prevention-oriented mindset) as rules that must be followed, whereas behavioral guidelines for exercise (which should induce a promotion-oriented mindset) are perceived as a general framework that can be modified according to personal preference. An additional consequence of this approach is that people may also find it easier to maintain prevention-oriented behaviors over time (Fugelstad, Rothman, & Jeffery, in press). Finally, specifying the degree to which a behavior induces a prevention- or a promotion-oriented mindset may have implications for the impact an implementation intention intervention has on behavior. Implementation intention interventions ask people to specify how, when, and where they will implement their intention to act and have been shown to dramatically increase the likelihood that stated intentions are translated into action (Armitage,

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2004; Sheeran & Orbell, 1999, 2000; for a review, see Gollwitzer & Sheeran, 2006). Because implementation plans render salient the specific structural and situational factors that underlie people’s ability to take action, one might predict that this intervention strategy would be particularly effective for behaviors that induce a prevention-focused mindset as this type of information would likely resonate with its emphasis on procedural details. On the other hand, one might expect that precisely because these behaviors already prompt people to focus on the specific, concrete details associated with performing the behavior, any additional benefit afforded by the implementation plan would be attenuated. From this perspective, one would expect implementation intention interventions to be more effective for behaviors that induce a promotion-focused mindset as they would compensate for the fact that people might focus more on general, abstract concerns and less on procedural details. Although investigators have begun to elucidate the processes that underlie the impact of implementation intentions, the degree to which features of the behavior regulate its effectiveness remains to be specified. The conceptual framework outlined above offers a potentially promising line of inquiry.

FINAL THOUGHTS Research on message framing has proven quite successful in producing both clinically and statistically significant behavioral outcomes, but has proven less successful at specifying the mechanisms that underlie these effects. To a certain extent, this state of affairs reflects the fact that the guiding theoretical frameworks have focused on the role of moderating factors—behavioral and dispositional factors that regulate the persuasiveness of gain- and loss-framed appeals. The new, integrative framework described in this chapter may afford an opportunity to address this discrepancy and to revitalize theorizing about message framing. By providing a psychologically richer account of the moderating factors identified in prior research it offers investigators a range of variables that could serve to clarify how framed appeals are perceived and processed and how they subsequently affect behavioral decision-making. The new framework also provides an opportunity to extend research on message framing in two important directions. First, it can inform how to apply message framing in new behavioral domains. Message framing research has focused primarily on screening behaviors and prevention behaviors—reflecting the classes of behaviors highlighted by Rothman and Salovey (1997)—and it has been unclear how to apply message framing to other behavioral domains

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such as treatments or efforts at cessation. The broader set of psychological states that are predicted to characterize a prevention- or promotion-oriented mindset may provide investigators with a more productive and functional set of dimensions upon which to classify a behavior, which in turn can guide predictions regarding the impact of gain- or loss-framed appeals. Second, there is an opportunity to better situate how our understanding of message framing effects fits within the broader study of health cognition and health behavior (Rothman & Salovey, in press). Message framing effects may be but one of a series of effects that can be derived from the mindset that people adopt when thinking about their health. Moreover, the focus within message framing research on features of health behaviors may provide an opportunity to think about how other phenomena may or may not generalize across behavioral domains. To date, psychological theories of health decision-making offer a rich description of people’s thoughts and feelings, but little guidance as to the applicability of these states across behavioral domains. Thus, questions regarding the generalizability of predictions and findings across health domains are difficult to answer. The thesis that behaviors systematically elicit a set of self-regulatory tendencies may provide a framework with which to begin to answer those questions.

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Kreuter, M. W., & Skinner, C. S. (2000). Tailoring: What’s in a name? Health Education Research, 15, 1–4. Kreuter, M. W., Strecher, V. J., & Glassman, B. (1999). One size does not fit all: The case for tailoring print materials. Annals of Behavioral Medicine, 21, 276–283. Kreuter, M. W., & Wray, R. J. (2003). Tailored and targeted health communication: Strategies for enhancing information relevance. American Journal of Health Behavior, 27, S227–S232. Latimer, A. E., Rivers, S. E., Rench, T. A., Katulak, N. A., Mowad, L. Z., Higgins, E. T., et al. (2007). A field experiment testing the utility of regulatory fit messages for encouraging participation in physical activity. Unpublished manuscript, Yale University, New Haven, CT. Latimer, A. E., Katulak, N., Mowad, L., & Salovey, P. (2005). Motivating cancer prevention and early detection behaviors using psychologically tailored messages. Journal of Health Communication, s137–s156. Lalor, K. M., & Hailey, B. J. (1990). The effects of message framing and feelings of susceptibility to breast cancer on reported frequency of breast self-examination. International Quarterly of Community Health Education, 10, 183–192. Lauver, D., & Rubin, M. (1990). Message framing, dispositional optimism, and follow-up for abnormal Papanicolaou tests. Research in Nursing and Health, 13, 199–207. Lee, A. Y., & Aaker, J. L. (2004). Bringing the frame into focus: The influence of regulatory fit on processing fluency and persuasion. Journal of Personality and Social Psychology, 86, 205–218. Lerman, C., Ross, E., Boyce, A., Gorchov, P. M., McLauglin, R., Rimer, B., et al. (1992). The impact of mailing psychoeducational materials to women with abnormal mammograms. American Journal of Public Health, 82, 729–730. Linville, P. W., Fischer, G. W., & Fischhoff, B. (1993). AIDS risk perceptions and decision biases. In J. B. Pryor & G. D. Reeder (Eds.), The social psychology of HIV infection (pp. 5–38). Hillsdale, NJ: Lawrence Erlbaum. Mann, T., Sherman, D., & Updegraff, J. (2004). Dispositional motivations and message framing: A test of the congruency hypothesis in college students. Health Psychology, 23, 330–334. Marshall, A. L., Bauman, A. E., Owen, N., Booth, M. L., Crawford, D., & Marcus, B. H. (2003). Population-based randomized controlled trial of a stage-targeted physical activity intervention. Annals of Behavioral Medicine, 25, 194–202. McCaul, K. D., Johnson, R. J., & Rothman, A. J. (2002). The effects of framing and action instructions on whether older adults obtain flu shots. Health Psychology, 21, 624–628. Meyerowitz, B. E., & Chaiken, S. (1987). The effect of message framing on breast self-examination attitudes, intentions, and behavior. Journal of Personality and Social Psychology, 52, 500–510. Meyerowitz, B. E., Wilson, D. K., & Chaiken, S. (1991, June). Loss-framed messages increase breast self-examination for women who perceive risk. Paper presented at the

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practices. In J. Trafton (Ed.), Best practices in the behavioral management of chronic diseases, (Vol. 3, pp. 31–48). Institute for Disease Management: Los Altos, CA. Schneider, T. R., Salovey, P., Apanovitch, A. M., Pizarro, J., McCarthy, D., Zullo, J., et al. (2001). The effects of message framing and ethnic targeting on mammography use among low-income women. Health Psychology, 20, 256–266. Semin, G. R., Higgins, E. T., de Montes, L. G., Estourget, Y., & Valencia, J. F. (2005). Linguistic signatures of regulatory focus: How abstraction fits promotion more than prevention. Journal of Personality and Social Psychology, 89, 36–45. Shah, J., Higgins, E. T., & Friedman, R. S. (1998). Performance incentives and means: How regulatory focus influences goal attainment. Journal of Personality and Social Psychology, 74, 285–293. Sheeran, P., & Orbell, S. (1999). Implementation intentions and repeated behavior: Augmenting the predictive validity of the theory of planned behavior. European Journal of Social Psychology, 29, 349–369. Sheeran, P., & Orbell, S. (2000). Using implementation intentions to increase attendance for cervical cancer screening. Health Psychology, 19, 283–289. Sherman, D. K., Mann, T. L., & Updegraff, J. A. (in press). Approach/avoidance orientation, message framing, and health behavior: Understanding the congruency effect. Motivation and Emotion. Skinner, C. S., Strecher, V. J., & Hospers, H. (1994). Physicians’ recommendations for mammography: Do tailored messages make a difference? American Journal of Public Health, 84, 43–49. Spiegel, S., Grant-Pillow, H., & Higgins, E. T. (2004). How regulatory fit enhances motivational strength during goal pursuit. European Journal of Social Psychology, 34, 39–54. Tversky, A., & Kahneman, D. (1981). The framing of decisions and the rationality of choice. Science, 221, 453–458. Vallacher, R. R., & Wegner, D. M. (1987). What do people think they’re doing? Action identification and human behavior. Psychological Review, 94, 3–15. Weinstein, N. D. (1993). Testing four competing theories of health-protective behavior. Health Psychology, 12, 324–333. Witte, K. (1992). Putting the fear back into fear appeals: The extended parallel process model. Communication Monographs, 59, 329–349. Wlaschin, J. T., Bartels, R. D., & Rothman, A. J. (2007, January). Regulatory focus and health behavior: Testing how behaviors can evoke a prevention or promotion mindset. Presented at the annual meeting of the Society for Personality and Social Psychology, Memphis, TN. Wlaschin, J. T., Rothman, A. J., Bartels, R. D., & Bachnick, L. (2006, May). Behaviors with personality: Testing the mindset evoked by prevention and detection behaviors. Presented at the annual meeting of the American Psychological Society, New York.

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Part VII The Self

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Self-Regulation Levels of Approach 29 Distinguishing and Avoidance: An Analysis Using Regulatory Focus Theory Abigail A. Scholer and E. Tory Higgins CONTENTS Levels of Approach and Avoidance: An Overview ...............................................................................490 Approach and Avoidance Levels in Regulatory Focus .........................................................................492 Empirical Evidence for the System–Strategy Distinction in the Case of Regulatory Focus ................493 Strategies Versus Tactics .......................................................................................................................496 Empirical Evidence for the Strategy–Tactic Distinction .......................................................................496 Approach and Avoidance Hierarchies: Multiple Perspectives ..............................................................499 Targeting the Hierarchy: Implications for Interventions.......................................................................500 Acknowledgment ................................................................................................................................... 501 References ............................................................................................................................................. 501

Jack and Jill walk down the aisle, now officially a married couple. Both beam at their friends and family on this special day. Both know that marriage will not always be this blissful, but both have the goal of having a good marriage. While Jack is thinking, “I am going to do all that I can to build a good marriage,” Jill reflects, “I am going to be careful not to mess up this good marriage.” Jack recalls the advice his mother gave him that morning, “The secret of a good marriage is never to go to bed angry,” while Jill remembers the words of her mother, “Show him you love him every day. You can’t express it too often.” What does it mean to approach and avoid? Both Jack and Jill are approaching the same desired end-state (a good marriage), yet there are clear differences in the strategies and tactics each plans to use to achieve that goal. The strategic preference of Jack to “do all that he can” to have a good marriage reflects strategic approach (eagerly approaching matches to “good marriage”), whereas the strategic preference of Jill to be “careful not

to mess up” reflects strategic avoidance (vigilantly avoiding mismatches to “good marriage”). And while Jack embraces approach at the strategic level, tactically he advocates avoidance (“don’t go to bed angry”). In contrast, Jill endorses strategic avoidance while tactically embracing approach (telling spouse “I love you” every day). In this chapter, we argue that one cannot fully answer the question of what it means to approach and avoid without considering the different levels at which approach and avoidance occur. As Andrew Elliot reviews in the introductory chapter, though the interest in approach and avoidance motivations has a long and rich history, there has been considerable variability in the ways that researchers have approached this issue. In particular, approach and avoidance motivations have been studied and conceptualized at various levels of abstraction. Distinguishing between these levels, we argue, is critical for understanding both the antecedents and consequences of self-regulation with regard to approach and avoidance. 489

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LEVELS OF APPROACH AND AVOIDANCE: AN OVERVIEW There are a number of theories that have discussed the importance of distinguishing between levels of selfregulation. Different approaches have emphasized the importance of different kinds of distinctions—between goals and subgoals (Miller, Galanter, & Pribram, 1960), between principles, programs, and sequences of movement (Carver & Scheier, 1998), between low and high levels of action identification (Vallacher & Wegner, 1985, 1987), between life-task goals, strategies, and plans or tactics (Cantor & Kihlstrom, 1987), between self-regulatory systems and strategies (Higgins, 1997; Higgins, Roney, Crowe, & Hymes, 1994), and between temperaments, motive dispositions, goals, and behaviors (Elliot, 2006; Elliot & Church, 1997; Gable, 2006; Pervin, 1989, 2001). Although these approaches differ somewhat in the preferred terminology and number of these levels, a common thread runs throughout: at any lower level in the hierarchy, there are multiple means (e.g., goals, subgoals, programs, strategies, tactics, or behaviors) that can serve a higher level. In this chapter, we address the distinction between levels of self-regulation specifically with respect to levels of approach and avoidance in the service of self-regulation (Elliot, 2006; Elliot & Church, 1997; Gable, 2006; Higgins, 1997; Higgins et al., 1994). We propose that within a hierarchy of approach and avoidance motivations, the levels of approach and avoidance are independent. Thus, approach or avoidance at one level is independent of approach or avoidance at another level (cf. Elliot & Church, 1997; Elliot & Thrash, 2002; Gable, in press; Higgins, 1997; Higgins et al., 1994). In the present discussion of levels of approach and avoidance, we distinguish between three levels: the system, strategic, and tactical levels (Higgins, 1997; Scholer, Stroessner, & Higgins, in press). Our approach shares many similarities with other hierarchical models of approach and avoidance motivation, but we differ in the distinctions among the levels that we emphasize. For example, the hierarchical model of approach and avoidance motivation proposed by Elliot and colleagues (Elliot, 2006; Elliot & Church, 1997) emphasizes how underlying motives and temperaments can be served by different goals, whereas we emphasize how underlying approach and avoidance goals can be served by different strategies and tactics. In the concluding section of the chapter, we return to a discussion of the similarities and differences between these approaches. At the system level, approach and avoidance motivations have been defined in relation to whether behavior is energized by positive stimuli (desirable end-states or reference points) or negative stimuli (undesirable end-states or

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reference points) (Carver & Scheier, 1981, 1990, 1998; Elliot & Thrash, 2002; Freud, 1920/1952; Gray, 1982; Lang, 1995; Lewin, 1935; Miller, 1944; Mowrer, 1960). The system level is characterized by the end-states that regulate behavior as goals, standards, or reference points. This is perhaps the most ubiquitous way in which approach and avoidance motivations have been conceptualized and correspond to the idea of regulatory reference (Higgins, 1997). While the system level tells us about whether an individual is regulating in regards to a desired end-state (e.g., a goal to get an A in a course) or undesired end-state (e.g., a goal to avoid an F), it does not tell us about the strategic or tactical ways in which the approach or avoidance system’s directional motivation may be playing out. At the strategic level, approach and avoidance motivations are about the means or process of moving towards desired end-states or moving away from undesired endstates. Strategies reflect the general plans or means for goal pursuit. Critically, there are different ways both of approaching desired end-states and of avoiding undesired end-states. Regarding the most common case of approaching desired end-states, strategic means are about whether one is approaching eagerly (moving towards the desired end-state by approaching matches to it) or approaching vigilantly (moving towards the desired end-state by avoiding mismatches to it). Though less commonly discussed, there are also different ways of avoiding undesired endstates. To move away from an undesired end-state at the system level, one can either strategically approach mismatches or strategically avoid matches to it (Higgins et al., 1994). Thus, approach and avoidance at the strategic level differs from approach and avoidance at the system level because the strategic level is about the means or process, rather than about the endpoints. Approach and avoidance at the strategic level differ from the tactical level (which we discuss next) because the strategic level is about broad-level descriptions of the means rather than the more specific instantiations of those means. At the tactical level, approach and avoidance are reflected in the specific ways in which one might, for example, eagerly approach matches to a desired end-state in a particular context. Tactics are thus the instantiation of a strategy in a given context and are about the means or process at a more concrete, in-context level (Cantor & Kihlstrom, 1987; Higgins, 1997). Just as approach and avoidance are reflected in the strategic level, so too are approach and avoidance reflected in the tactical level. For example, in the signal detection sense, approach and avoidance tactics are reflected in the bias for the acceptance threshold that one adopts. A bias towards a lenient or liberal criterion for acceptance represents approach; this is a tactic that maximizes hits (even at the cost of

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Distinguishing Levels of Approach and Avoidance

false alarms)—a so-called risky bias. In contrast, a bias towards a strict criterion for acceptance represents avoidance; this is a tactic that maximizes correct rejections (even at the cost of misses)—a so-called conservative bias. In the opening example, tactics encompassed the different kinds of behaviors that Jack and Jill embraced for pursuit of a good marriage (“not going to bed angry” versus “expressing ‘I love you’ every day”). Our distinction between strategy and tactics also parallels the military distinction between strategy (long range planning and development for victory) and tactics (how troops are actually deployed in a particular combat situation). Our notion of the tactical level that implements a strategy in a particular situation is broader than approach and avoidance at the behavioral level, especially as it has been described in the literature. It is common to associate approach and avoidance at the behavioral level with action and inaction, respectively (cf. Gray, 1982). These associations do not always characterize the full range of behavioral possibilities, however. For example, taking action at the behavioral level in the service of the same tactic may reflect either approach or avoidance depending on the circumstances. To illustrate, imagine that Donald is walking down a city street and thinks he sees an old college buddy walking towards him. Donald tries to decide if he should approach this man and say hello. If Donald adopts a lenient criterion of acceptance (an approach tactic), he is likely to decide, “Yes, that’s him” and approach the man to say hello (behavioral approach). However, if instead Donald wonders if the man approaching him is the escaped (and dangerous) convict that he saw on the morning news, the adoption of the same lenient criterion for acceptance is likely to lead to a different behavioral response. Here, adopting an approach tactic (a lenient criterion for acceptance) is again likely to lead Donald to decide, “Yes, that’s him.” But this time such a decision will lead to an avoidance action at the behavioral level, not an approach action. Donald is unlikely to approach the convict to have a little chat; rather, he is likely to walk away and perhaps even notify the authorities. In this example, then, we see that either an approach behavioral action or an avoidance behavioral action can reflect the same approach tactic (a lenient criterion for acceptance). It is also possible that the same tactic could be instantiated by either action or inaction at the behavioral level. To illustrate, if Jack’s avoidance tactic is “to not go to bed angry,” he might either stop thinking about what Jill did that angered him that day (inaction at the behavioral level) or try to remind himself of why he loves being with her (action at the behavioral level). In other words, “not going to bed angry” could be instantiated by thinking

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about the nice things your partner did for you that day (action) or by not thinking about the mean things (inaction). Thus, the tactical level as we are defining it here is broader than the behavioral level defined simply as activation or inhibition, action or inaction. It involves the constellation of responses or behaviors (motor movements, attention, etc.) that embody a strategy played out in a specific context. While a discussion of hierarchical levels of approach and avoidance could include these lower behavioral levels, they are not the focus of our discussion here. We raise the point, however, because the behavioral level has been the focus of other theories of approach and avoidance (notably Gray, 1982, 1990; Miller, 1944; Mowrer, 1960), and we want to be clear that our conceptualization of tactics is at a broader level than simply activation or inhibition of behavior or approach versus avoidance at the behavioral output level. Our perspective may be illuminated further by considering how one influential theory of approach and avoidance relates to our distinction between the system, strategic, and tactical levels. Gray (1982, 1990) proposed two motivational–behavioral systems that regulate behavior: a behavioral approach system (also referred to as a behavioral activation system) (Fowles, 1980, 1987) and a behavioral inhibition system (BIS). In Gray’s conception, the behavioral approach system (BAS) responds to inputs related to signals of conditioned reward—either the presence of reward (e.g., food) or the absence of punishment (e.g., safety). It is important to note that these inputs (reward, nonpunishment relief) are functionally equivalent in the model (Fowles, 1987; Gray, 1982). These inputs result in behavioral approach or action. Thus, BAS is a theory of approach at the highest level of our hierarchy (its inputs are desired end-states such as food and safety), but it is also a theory of approach at a lower level than we discuss here, in that its outputs are behavioral action and approach (e.g., approach learning, active avoidance, skilled escape, predatory aggression). Similarly, BIS responds to inputs related to conditioned punishment— either to the presence of punishment or the absence of reward (frustrative nonreward). As in BAS, these inputs are functionally equivalent: punishment and frustrative nonreward are believed to activate the same underlying neural substrate (Fowles, 1987; Gray, 1982). Activation of BIS results in behavioral inhibition (e.g., passive avoidance and extinction). Thus, BIS is a theory of avoidance at the highest level of our hierarchy (its inputs are undesired end-states) but its outputs are behavioral, reflecting inhibition of some ongoing behavior. While this dual emphasis on different levels of the approach and avoidance hierarchy has been reflected in

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the various ways that the BAS/BIS conceptions have been applied to the study of emotions and personality, the fact that the model involves two different levels of approach– avoidance analysis—one very high (system) and one very low (behavioral)—has received little attention. Indeed, many have concluded that these dimensions simply represent fundamental approach versus avoidance motivations (Carver, Sutton, & Scheier, 2000; Elliot & Thrash, 2002; Gable, Reis, & Elliot, 2003). The fact that the BAS/ BIS distinction involves two levels of approach–avoidance analysis raises the issue of whether it is reasonable to assume, as the BAS/BIS distinction does, at least implicitly, that approach behaviors necessarily go with approaching desired end-states and avoidance behaviors necessarily go with avoiding undesired end-states. As suggested by our earlier discussion, we do not believe that this assumption is necessary (cf. Higgins, 1997). While not denying the ubiquitous or fundamental nature of approach and avoidance motivations, we argue that consideration of an approach and avoidance hierarchy such as we propose here will elucidate some issues within self-regulation while raising some important new questions. Does some underlying general “approach” disposition increase the likelihood that a person will approach at all levels of analysis? When is avoidance at the strategic level likely to reflect approach at the system level? Are the costs of avoidance at the system level the same as the costs of avoidance at the strategic level? What are the implications of concordance or divergence between approach (or avoidance) at different levels in the hierarchy? In sum, we suggest that it is important to distinguish how individuals approach and avoid at multiple levels of analysis. In the following sections, we use regulatory focus theory (Higgins, 1997) and empirical evidence from studies testing regulatory focus theory to illustrate the importance of distinguishing among the system, strategic, and tactical levels. We then explore the implications of these distinctions for understanding approach and avoidance motivations in self-regulation. In the remainder of the chapter we will not describe evidence for the distinction between the tactical versus behavioral levels of approach–avoidance as this has not been formally addressed yet by regulatory focus theory (or by any other theory of which we are aware). We do believe the distinction is important, however, and deserves future research attention. For example, as discussed earlier, at these levels as well there could be implications of concordance or divergence between approach–avoidance at the tactical level and approach–avoidance at the behavioral output level.

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APPROACH AND AVOIDANCE LEVELS IN REGULATORY FOCUS One of the original contributions of regulatory focus theory was to distinguish between the system and strategic levels of self-regulation. Until recently, the tactical level of self-regulation was not emphasized. We begin with an overview of regulatory focus theory, including a discussion of the relation of the theory to approach and avoidance more generally, and then go on to discuss experimental evidence that makes it clear why the system/ strategic/tactical distinction is both necessary and useful. Building on earlier distinctions (Bowlby, 1969, 1973; Higgins, 1987; Mowrer, 1960), regulatory focus theory distinguishes between two coexisting regulatory systems or general orientations that serve critically important but different survival needs (Higgins, 1997). The promotion orientation regulates nurturance needs and is concerned with growth, advancement, and accomplishment. Individuals in a promotion focus are striving towards ideals, wishes, and aspirations and are particularly sensitive to the presence and absence of positive outcomes (gains and nongains). In contrast, the prevention orientation regulates security needs. Individuals in a prevention focus are concerned with safety and responsibility and with meeting one’s oughts, duties, and responsibilities. Prevention-focused individuals are particularly sensitive to the absence and presence of negative outcomes (nonlosses and losses). At the system level, regulatory focus theory is orthogonal to the system-level distinction between approaching desired end-states and avoiding undesired end-states because promotion and prevention orientations each involve both approaching desired endstates (e.g., approaching accomplishment or safety, respectively) and avoiding undesired end-states (e.g., avoiding nonfulfillment or danger, respectively). Regulatory focus theory also distinguishes between the different strategic ways that individuals pursue different desired end-states (Higgins, 1997; Higgins et al., 1994). Although the same desired end-state (e.g., having a good marriage) can be pursued by both promotion-focused and prevention-focused individuals, they have different preferred strategies for doing so. Thus, promotion-focused individuals prefer to use eager approach strategies (approaching matches to desired end-states, approaching mismatches to undesired end-states) whereas preventionfocused individuals prefer to use vigilant avoidance strategies (avoiding mismatches to desired end-states, avoiding matches to undesired end-states). The eager strategic means preferred by individuals in a promotionfocus reflect their concerns with advancement and

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accomplishment and their pursuit of ideals and growth. The vigilant strategic means preferred by individuals in a prevention focus reflect their concerns with safety and responsibility and the need to guard against mistakes. Thus, at the strategic level of approach and avoidance, differences between promotion and prevention foci relate to differences in preference for using eager approach and vigilant avoidance strategies, respectively.

EMPIRICAL EVIDENCE FOR THE SYSTEM– STRATEGY DISTINCTION IN THE CASE OF REGULATORY FOCUS How do we know that the system level and the strategic level are truly independent? For example, how do we know that when a prevention-focused individual pursues the goal of “good marriage” they are approaching at the system level while avoiding at the strategic level? We review empirical evidence in this section that supports the claim that these are independent levels of self-regulation. A study that capitalized on the classic “goal looms larger” effect provides especially clear evidence for the independence of the system and strategic levels (Förster, Higgins, & Idson, 1998). The finding that motivational strength increases as the distance from a goal decreases has been labeled the “goal looms larger” effect (Lewin, 1935; Miller, 1944, 1959). The initial work was done with rats (Brown, 1948), but the effect has been replicated across many contexts (Losco & Epstein, 1977; Smith, 1965, 1969). Why is it that a goal looms larger as we approach it? As we approach the desired end-state, each step takes us closer to the goal, thus reducing the goal discrepancy. The contribution of any one of those steps to the value of success depends on the magnitude of the discrepancy that it reduces; thus, each subsequent step reduces a greater proportion of the discrepancy, assuming the steps are of equal size (Förster et al., 1998). The motivational properties subsequently “loom larger” as one gets closer to a goal, increasing the strength of strategic motivations likely to produce success (see Brendl & Higgins, 1995, for a review). While the goal looms larger effect posits that motivation should increase as one approaches ever nearer to the desired end-state, it does not specify what type of motivation may be increasing. Thus, it could be that either strategic approach motivation or strategic avoidance motivation increases. Imagine two individuals preparing for a date. Both promotion- and prevention-focused individuals may be motivated to have their evening date end in a pleasant kiss; at the system level, both individuals are approaching a desired end-state (a pleasant kiss as the

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successful ending to the date). However, as the eve of the date approaches, a promotion-focused individual may eagerly purchase a box of mints (approaching a match to the pleasant kiss) whereas a prevention-focused individual may be careful to avoid the garlic bread at lunch (avoiding a mismatch to the pleasant kiss). Thus, as a goal looms larger for prevention- and promotion-focused individuals, promotion-focused individuals should show an increase in strategic approach motivation (getting more and more enthusiastic) whereas prevention-focused individuals should show an increase in strategic avoidance motivation (getting more and more careful). Förster et al. (1998) tested these ideas in a series of studies. In one study (Förster et al., 1998, Study 3), the goal for all participants was to perform well on an anagram task (as payment depended on good performance). The effects of regulatory focus were evaluated both as a chronic variable (measured in an earlier session) and as a manipulated variable. Participants were assigned to one of the two framing conditions: promotion or prevention (the regulatory focus manipulation). To assess the differential strength of approach or avoidance strategic motivations, two different types of anagrams were presented. Participants were told that for each green anagram for which they found all possible solutions, they would gain a point (strategic approach problems). They were told that for each red anagram for which they found all possible solutions, they would avoid losing a point (strategic avoidance problems). Motivational strength in this study was measured by persistence (duration of time participants spent working on the anagrams). According to the goal looms larger effect, persistence should increase for anagrams late in the set relative to those early in the set. Indeed, to be confident that both promotion- and prevention-focused participants are, indeed, approaching a desired end-state at the system level, a goal looms larger effect is needed for all participants. However, the way in which motivational strength increases for promotion- versus prevention-focused participants should differ. According to regulatory focus theory and the argument that the system versus strategic levels are independent, promotion-focused individuals should show greater approach strength at the strategic level as the goal looms larger whereas prevention-focused individuals should show greater avoidance strength at the strategic level as the goal looms larger. The design allowed differences in the motivational strength of these two strategies to be assessed via persistence on the two different types of anagram problems (red or green). The specific prediction was that promotion-focused participants would persist longer on green (strategic approach)

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anagrams late versus early in the task, whereas prevention-focused participants would persist longer on red (strategic avoidance) anagrams late versus early in the task. For both the situational manipulation of regulatory focus and for chronic regulatory focus, these predicted effects were obtained, independent of both outcome valence and outcome expectancy. In other words, while all participants showed evidence of the “goal looms larger” effect from steadily approaching a desired endstate, this resulted in increasing strategic approach motivation for promotion-focused participants but increasing strategic avoidance motivation for prevention-focused participants (for further evidence of these effects, see also Förster, Grant, Idson, & Higgins, 2001). The basic assumptions underlying studies testing regulatory fit theory (Higgins, 2000) also support the independence of the system and strategic levels of approach and avoidance. Regulatory fit theory posits that individuals derive value from using strategic means that fit their underlying regulatory orientations. As we have discussed, one way to differentiate between types of strategic means is to recognize that people may use either approach strategic means or avoidance strategic means. Within the context of regulatory focus theory, approach strategic means (eager means) fit a promotion focus whereas avoidance strategic means (vigilant means) fit a prevention focus. When individuals experience regulatory fit by using strategic means that sustain their underlying orientation, they “feel right” about what they are doing (Higgins, 2000) and also experience increased engagement (Higgins, 2006). Regulatory fit theory is not restricted to fit between regulatory focus orientations and means (Avnet & Higgins, 2003; Bianco, Higgins, and Klem, 2003), but it is the evidence within regulatory focus theory that is germane to our present discussion of approach and avoidance motivations within self-regulation. Of most relevance to the current discussion, such regulatory fit effects could not occur if the strategic level of approach and avoidance was not dissociable from the system level of approach and avoidance. Across the studies that we will review, everyone is approaching a desired end-state at the system level, but the value of what people are doing is intensified when they pursue goals with eager approach or vigilant avoidance strategies that fit their regulatory system orientation. A series of studies found support for the idea that the value created when people use strategic means that fit their regulatory orientation not only affects the value of the goal pursuit activity but also affects the value of subsequent object appraisals (Higgins, Idson, Freitas, Spiegel, & Molden, 2003). Higgins et al. gave participants an unexpected gift—a choice between a university

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logo coffee mug and a cheap disposable pen. These gifts had been preselected so that the mug was seen as more desirable by almost everyone. All participants were asked to focus on the positive attributes of the objects (desired end-states), but the strategic ways in which they were asked to do so differed. Half of the participants were told to think about what they would gain by choosing the mug and what they would gain by choosing the pen (eager approach strategy). The other half of the participants were told to think about what they would lose by not choosing the mug and what they would lose by not choosing the pen (vigilant avoidance strategy). In both conditions, participants were focusing on desired end-states; in both conditions making the choice itself resulted in a desired end-state (owning the positive attributes of the mug they selected). Thus, across conditions, the system level of approach was held constant. Of interest was how the fit or nonfit between participants’ chronic regulatory focus orientations (assessed by the Self-Guide Strength Measure) (Higgins, Shah, & Friedman, 1997) and the assigned strategy would affect the value of the mug. Value of the mug was measured by the amount of their own money that participants were willing to spend to purchase the mug. The price offered to buy the mug was almost 70% higher under regulatory fit than under nonfit (Higgins et al., Study 2). Thus, although all participants were approaching a desired endstate, the strategic means they used had a dramatic impact on their experience of the decision activity, which in turn intensified the attractiveness of the mug, as reflected in the price they were willing to pay to buy it. It is notable that there was no main effect of the strategic means in these studies; in other words, it was not better overall to use approach strategic means or avoidance strategic means. This highlights an important distinction between the benefits and costs of approach and avoidance at the system level versus the benefits and costs of approach and avoidance at the strategic level. While a number of studies have found support for the idea that approach goals result in better outcomes than avoidance goals (Elliot & Harackiewicz, 1996; Elliot & Sheldon, 1997, 1998; Elliot, Sheldon, & Church, 1997), this may be primarily in regards to approach and avoidance at the system level. Approaching desired end-states as reference points may indeed have benefits that avoiding undesired end-states do not. However, at the strategic level value may be derived more from a fit between the strategic means and one’s regulatory orientation, rather than from a main effect of approach versus avoidance per se. What processes other than assigning monetary value are impacted by regulatory fit? In one study (Higgins

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et al., 2003, Study 5), all of the participants had to think about things that would improve the transition from elementary school to middle school (i.e., all participants were approaching a desired end-state at the system level). However, half of the participants had to do this by using an approach strategy (thinking of improvements that could be added to middle school to maximize the positive aspects of middle school) while half of the participants had to do this using an avoidance strategy (thinking of things that should be eliminated from middle school to ensure that students avoid negative experiences). Regulatory focus was again measured using the SelfGuide Strength Measure (Higgins et al., 1997). Not only did participants rate middle school experiences as more important under fit, but they also performed better by generating more options for improving middle school. Shah, Higgins, and Friedman (1998) also found that participants performed better on an anagram task under fit. For participants with a chronic promotion focus, strategic approach framing led to better performance. In contrast, for participants with a chronic prevention focus, strategic avoidance framing led to better performance. Freitas and Higgins (2002) further found that under fit individuals reported greater task enjoyment and greater subjective perceptions of success. This is additional evidence that at the strategic level neither approach nor avoidance strategies per se produce better outcomes overall (in terms of performance or subjective well-being). Instead, these strategies have differential effects dependent on their relation to one’s underlying regulatory focus orientation (fit versus nonfit). Spiegel, Grant-Pillow, and Higgins (2004) extended these findings to real-life health behaviors. In one study, for example, participants were told that they were participating in a two-session study to track the nutritional habits of college students (Study 2). In the initial session, all participants were given health messages to read that advocated pursuit of the same desired end-state—eating more fruits and vegetables. The key manipulations took place as part of the messages that participants received. Although all participants were given the same message (“eat more fruits and vegetables”), a promotion versus prevention focus was manipulated through the concerns (accomplishments versus safety, respectively) that were highlighted within the messages. Additionally, within each regulatory focus condition, participants were asked either to imagine the benefits they would get if they complied with the health message (strategic approach) or the costs they would incur if they did not comply with the health message (strategic avoidance). Participants were asked to keep a nutritional log for the following week;

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the critical dependent variable was whether participants in conditions of fit would consume more fruits and vegetables than participants in conditions of nonfit. Indeed, participants in conditions of fit ate more fruits and vegetables in the week following the first session than participants in conditions of nonfit. All of the work that we have reviewed so far makes clear that approach at the system level may be served by either approach or avoidance strategies. Indeed, the literature in general has paid much more attention to exploring how individuals approach desired end-states than avoid undesired end-states (Higgins, 1997). However, a few studies have examined how avoidance at the system level can also be served by approach or avoidance strategies (Grant, Higgins, Baer, & Bolger, 2006; Higgins et al., 1994). These studies provide further evidence for the independence of the system and strategic levels. Higgins et al. (1994, Study 2) found support for the notion of the independence of the system and strategic levels in an investigation that included both desired and undesired end-states. Regulatory focus was manipulated by either having participants write a brief essay about how their current hopes and goals changed as they were growing up (promotion manipulation) or how their current duties and obligations changed as they were growing up (prevention manipulation). Participants were then presented with a story about the life of an individual over several days. In the story, the target faced a number of different episodes that differed at the system level (e.g., involved desired versus undesired end-states). The target either used approach or avoidance strategies in dealing with these situations. An example of an episode involving an undesired end-state would be a target who “disliked eating in crowded places.” In one version, the target might deal with this undesired end-state by approaching a mismatch: “At noon I picked up a sandwich from a local deli and ate outside.” In contrast, the target might deal with this undesired end-state by avoiding a match: “At noon I avoided eating at the school cafeteria.” The primary dependent variable was recall for these episodes. The underlying assumption was that activation of the prevention or promotion system should increase accessibility and sensitivity to regulatory forms associated with the activated system, thus impacting recall for episodes that are associated with those forms (Higgins & Tykocinski, 1992). Of particular interest was whether regulatory focus orientation would impact recall at the system or the strategic level. Participants in a promotion focus had better memory for episodes in which the target used approach strategies (e.g., approaching matches to desired end-states or

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approaching mismatches to undesired end-states). Recall was better for approach strategies, irrespective of whether the episode involved a desired or undesired end-state. In contrast, participants in a prevention focus had better memory for episodes in which the target used avoidance strategies (e.g., avoiding mismatches to desired endstates, avoiding matches to undesired end-states). Again, recall was better for avoidance strategies, regardless of whether the episode involved a desired or undesired endstate. In other words, regulatory focus orientation involved sensitivity to the strategic ways in which individuals were pursuing desired end-states and avoiding undesired endstates, rather than to sensitivity at the system level. Grant et al. (2006) further investigated the impact of regulatory fit on coping with undesired end-states (daily life problems). In a daily diary study, participants reported the “most upsetting or bothersome incident” that happened to them each day. Participants also completed a daily measure of distress as well as a coping measure that assessed the use of eager (approach) strategies and vigilant (avoidance) strategies for coping. Prior to beginning the diary portion of the study, all participants completed the regulatory focus questionnaire (Higgins et al., 2001), a chronic measure of regulatory focus that assesses the extent to which participants believe that they have achieved success within the promotion and prevention systems. Using the principles of regulatory fit theory, Grant et al. (2006) predicted that regulatory fit would increase a strategy’s effectiveness by influencing the extent to which individuals would “feel right” about whatever coping strategies they used, thereby directly reducing the experience of distress. Specifically, they predicted that on days when participants used more coping strategies that fit their underlying orientations, they would experience less distress. Grant et al. also predicted that there would be a significant impact of nonfit: on days when participants used more coping strategies that did not fit their underlying orientations, they would experience more distress. At the system level, all participants were avoiding an undesired end-state (daily stressors). Support for the regulatory fit predictions would provide evidence that there are different strategic ways that individuals can avoid undesired end-states. Both predictions were supported. Promotion-focused individuals who used eager (approach) coping strategies to deal with undesired end-states experienced less distress than promotion-focused individuals who used vigilant (avoidant) coping strategies. Similarly, prevention-focused individuals who used vigilant strategies reported less distress than prevention-focused individuals who used eager coping strategies. It is important to note that there was no main effect of promotion or

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prevention pride on distress; chronic regulatory orientation did not affect reactivity to stress. What were critical were the strategic ways in which individuals coped with daily stressors. While there was some evidence in this study that approach strategies generally led to less distress than avoidance strategies, the fit or nonfit between participants’ underlying orientations and the strategy employed was especially important for well-being.

STRATEGIES VERSUS TACTICS In the previous section, we reviewed evidence for the independence of the system and strategic levels of approach and avoidance. We extend our discussion here to explore what it means for the strategic and tactical levels of approach and avoidance to be independent. Tactics reflect the specific ways in which one might approach matches to desired end-states or avoid mismatches to undesired end-states in a particular context. Given our supposition that these levels are independent, the tactics that serve a particular strategy may shift depending on the context. While it may be that much of the time, approach tactics are more likely to follow from approach strategies and that avoidance tactics are more likely to follow from avoidance strategies, this will not always be the case. If the strategic and tactical levels of approach and avoidance are independent, then the same approach tactic could serve either strategic approach (eagerness) or strategic avoidance (vigilance), and the same avoidance tactic could serve either strategic approach or strategic avoidance. In addition, the same strategy (eager approach or vigilant avoidance) could be better served by either an approach tactic in one case or an avoidance tactic in another case.

EMPIRICAL EVIDENCE FOR THE STRATEGY–TACTIC DISTINCTION As reviewed earlier, the original conception of regulatory focus theory made a critical distinction between the system and the strategic levels of approach and avoidance (Higgins, 1997). However, regulatory focus theory has historically tended to conflate the strategic and tactical levels, especially for those predictions made within a signal detection framework (Crowe & Higgins, 1997). As we will see, this was in part because the research emphasis was on those cases where the initial state of the participants was in the neutral to slightly positive region. In the current section, we discuss how recent work within regulatory focus theory—where the initial state is no longer only in the neutral to slightly positive region—makes

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clear that the strategic and tactical levels of approach and avoidance also need to be treated as independent. Given that individuals in a promotion focus prefer approach strategies (e.g., eagerly approaching matches to desired end-states), have general concerns with advancement, growth, and accomplishment, and exhibit greater sensitivity to the presence and absence of positive outcomes, the original prediction was that those in a promotion focus would also adopt approach tactics in a signal detection paradigm. In a signal detection paradigm, an individual is differentiating between “signal” and “noise” under uncertainty. Responses are influenced in part by a bias for where one sets the criterion for acceptance. A lenient threshold for acceptance maximizes the chances of hits, while also increasing the chances of false alarms. Within the signal detection framework, a bias to set a lenient threshold has been described as “liberal” or “risky” (Crowe & Higgins, 1997; Swets, 1973; Tanner & Swets, 1954). Thus, given the promotion focus concerns with advancement and the desire to achieve hits or positive outcomes, the prediction was that promotion-focused individuals should exhibit a risky bias in the signal detection framework; they should be willing to incur false alarms to insure hits. In contrast, individuals in a prevention focus were predicted to exhibit a conservative bias, an avoidance tactic, within the signal detection framework. A conservative bias reflects the adoption of a strict criterion for acceptance. Such a tactic minimizes the chances of false alarms— ensuring correct rejections at the cost of potentially increased misses. Given the prevention focus concerns with security and safety, and the greater sensitivity to the presence and absence of negative outcomes, the prediction was that the avoidance strategies of prevention-focused individuals would also result in avoidance tactics. Indeed, in two studies that examined regulatory focus tactical differences in a signal detection framework (Crowe & Higgins, 1997; Friedman & Förster, 2001), promotion-focused individuals were shown to have a risky bias (approach tactic) and prevention-focused individuals were shown to have a conservative bias (avoidance tactic). However, both of these studies examined these tactical differences with regards to neutral stimuli—nonwords (Crowe & Higgins, 1997) or neutral words (Friedman & Förster, 2001). It is possible that in the neutral case concordance between approach (avoidance) strategies and approach (avoidance) tactics is more likely. As long as a concordant tactic serves the underlying strategy, it may more easily and naturally be adopted. When, then, might strategies and tactics diverge? If a concordant tactic no longer serves the strategy, we

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hypothesized that a tactic that is instrumentally effective should be preferred, even if it is not concordant. Within regulatory focus theory, we thought that a shift in the valence of the signals themselves—from neutral to negative—might demonstrate the independence of strategies and tactics. Given prevention focus concerns with the absence or presence of negative outcomes, an individual in a prevention focus should be especially concerned with negativity in the environment. Prevention-focused individuals should be especially motivated not to “miss” negative objects and events because this negativity poses a direct threat to the primary concern of individuals in a prevention focus—safety and security. Consequently, we predicted that when negative conditions were involved, individuals in a prevention focus would show a willingness to incur false alarms to insure that no negative information is missed—an approach tactic serving their strategic vigilance. If individuals in a prevention focus do adopt risky tactics in order to vigilantly deal with negative conditions, this would be evidence for the independence of the strategic and tactical levels of self-regulation. We conducted a series of six studies to examine this prediction that prevention-focused individuals would adopt an approach tactic (i.e., a risky bias) when confronting negative signals (Scholer, et al., in press). All of these studies employed the same basic recognition memory signal detection paradigm. Regulatory focus was experimentally manipulated in every study. Across the studies, we tested a number of potential moderators: the nature of the regulatory focus manipulation; the timing of the regulatory focus manipulation; whether valence was manipulated between or within-participants; and the presentation speed of the stimuli. None of these moderators impacted the strength of the basic finding. In every study, individuals in a prevention focus exhibited a risky bias in the recognition memory signal detection. This bias was risky relative to the conservative bias that prevention-focused participants showed towards positive words and relative to the risky bias promotion-focused participants showed towards negative words. A significant meta-analysis confirmed the consistency of this pattern across the six studies. This is clear evidence of the independence of the strategic and tactical levels of approach and avoidance. When conditions are positive, one tactic (a conservative bias, or avoidance tactic) is adopted by participants in a prevention focus to serve their vigilant avoidance strategy; when conditions are negative, a different tactic (a risky bias, or approach tactic) is adopted by participants to serve the same vigilant avoidance strategy. In other contexts, what kinds of tactics represent approach versus avoidance tendencies? Within the

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decision-making domain, much attention has been paid to contexts in which individuals are risk-seeking versus riskaverse (Kahneman & Tversky, 1979, 2000). Risk-seeking in the traditional decision-making sense (i.e., choosing gambles over certainty) can be seen as an approach tactic, whereas risk aversion (i.e., preferring certainty over gambles) can be seen as an avoidance tactic. In the signal detection studies we described, we found evidence that tactical approach (a risky bias) could serve a vigilant avoidant strategy. Would we find evidence of this dissociation in other decision-making domains with a different operationalization of a “risky” approach tactic? We used a stock-investment paradigm to investigate this question (Scholer, Zou, Fujita, Stroessner, & Higgins, 2008). Participants arrived at the lab and completed a battery of questionnaires, including the Self-Guide Strength measure, a measure of chronic promotion-focus strength (the chronic accessibility of ideals) and chronic prevention-focus strength (the chronic accessibility of oughts; see Higgins et al., 1997). After completing these questionnaires, participants were paid for their participation. They were then given a choice to leave the study or to invest their payment in a second, stock-investment study. Participants were told that, in general, participants walked away with additional money in the stockinvestment study but that there was a chance that they could lose real money. Most participants decided to invest in the stock-investment study. After making their initial investment decision, participants tracked the performance of their stock over time. At the end of the first round, all participants learned that they had lost not only their original investment but also additional money (manipulation checks confirmed that participants did indeed experience their situation as a real loss). At this point, participants were given a choice between investing in two stocks for the second round of the study, a risky stock and a conservative stock. The expected value of these stocks was equivalent, but the risky stock was riskier both in the objective sense that its variance was greater (Markowitz, 1952) and in the subjective sense (participants rated the risky stock as riskier). In a state of loss, would prevention-focused participants prefer the riskier stock? Indeed, as chronic preventionfocus strength increased, the probability of selecting the risky option also increased substantially. In this first stock-investment study, only the risky option had the potential of returning participants to their break-even point. Given that the underlying motivation of prevention-focused individuals concerns doing what is necessary to remain secure, to restore safety, this choice necessitated a risky option: it was the only tactic that

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could return participants to “safety.” Interested in exploring more deeply what might be motivating the risky choice of prevention-focused participants in this study, we considered what might happen if prevention-focused participants had the option of a conservative tactic that could return them to their break-even point. If a conservative tactic could return them to the status quo, to safety, the necessity of choosing a risky tactic would no longer exist. We predicted that in this case they would evince a stronger preference for the conservative avoidance tactic because it more naturally suits the vigilant avoidance strategy preferred by individuals in a prevention focus. While the instrumental effectiveness of the tactics will normally triumph, when tactics are equivalent in instrumentality, we propose that there may be a preference for tactic–strategy concordance. Specifically, the notion was that if both a risky approach tactic and a conservative avoidance tactic served the vigilant avoidance strategy of restoring the status quo (restoring safety), participants with a strong prevention focus would prefer the conservative avoidance tactic. To examine this question, we ran a second study replicating the first stock-investment study with the addition of a new condition. In the new condition, participants had a choice between the same risky stock and a new conservative stock that did have the potential to get participants back to their break-even point. As in the other condition, the expected value of these stocks was equivalent but the risky stock was riskier both in the objective and subjective sense. We replicated the findings of Study 1 in the original condition where the conservative option would not bring participants back to safety (the status quo); as preventionfocus strength increased, participants were more likely to choose the risky option. However, when preventionfocused participants had a conservative option that could return them to safety, their tactical preference shifted dramatically back to a clear preference for the conservative tactic. Within the same study, then, we have clear evidence of the independence of the strategic and tactical levels of approach and avoidance in self-regulation. In one condition (where the conservation choice would not restore the status quo), an approach tactic (the risky stock) served a vigilant avoidance strategy, whereas in the other condition (where the conservation choice would restore the status quo), an avoidance tactic (the conservative stock) served the vigilant avoidance strategy. Thus, there is evidence both within the classic “signal versus noise” signal detection framework and within the traditional “choosing between options” decision-making framework that approach and avoidance strategies (eagerness versus vigilance) are independent of approach and

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avoidance tactics. The empirical evidence we presented in this section highlighted how a vigilant avoidance strategy can be served by both approach and avoidance tactics. We are currently exploring the flip side of this issue: when and how eager approach strategies might be served by avoidance, as well as approach, tactics.

APPROACH AND AVOIDANCE HIERARCHIES: MULTIPLE PERSPECTIVES In this chapter, we have illustrated one way of conceptualizing a hierarchy of approach and avoidance motivations. Our model is inspired by regulatory focus theory, which historically emphasized the different strategic ways that individuals can approach desirable end-states or avoid undesirable end-states as reference points at the system level, and that recently recognizes the different tactical ways that individuals can serve their strategic preferences. Our model shares similarities with Elliot and colleagues’ (Elliot, 2006; Elliot & Church, 1997; Elliot, Gable, & Mapes, 2006; Gable, 2006) hierarchical model of approach and avoidance motivation but differs in both significant and subtle ways in how we parse and define the levels within the hierarchy. Both models emphasize that the highest level does not specify how individuals go about approaching or avoiding. In our characterization, the system level is akin to a goal: “I want to approach a good marriage” versus “I want to avoid a bad marriage.” In Elliot’s model, goals per se do not enter at the highest level; rather, this level reflects underlying approach and avoidance motives and temperaments. Goals enter as mid-level constructs that specify how individuals strategically go about addressing the underlying approach and avoidance motives and temperaments. Thus, goals for Elliot provide direction for the underlying motives and temperaments and in some ways incorporate aspects of both the system and strategic levels of our model (e.g., achievement goals such as “My goal in this class is to get a better grade than most of the students” or “I just want to avoid doing poorly in this class”) (Elliot & Church, 1997). Much of the work exploring the implications of Elliot’s hierarchical model of approach and avoidance motivation has been done in the achievement domain, exploring differences between two types of approach goals (performance-approach goals, mastery-approach goals) and two types of avoidance goals (performance-avoidance goals, mastery-avoidance goals) (Elliot & Church, 1997; Elliot & McGregor, 2001). Recently, the hierarchical model of approach and avoidance motivation has been extended to the social domain, examining differences in goals reflecting positive social outcomes (approaching

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affiliation and intimacy) versus goals involving negative social outcomes (avoiding rejection and conflict) (Elliot, Gable, & Mapes, 2006; Gable, 2006). These goals represent the channels through which approach and avoidance motives and temperaments are “concretized”; the independence in the approach and avoidance hierarchy posited by Elliot and colleagues is that an avoidance motive disposition (e.g., need to avoid failure) can be served by an approach goal (e.g., performance-approach goal, such as “I am motivated by the thought of outperforming my peers in this class”) (Elliot & Church, 1997). Our model takes this a step further by positing that approach (avoidance) goals can be served by either approach or avoidance strategies. Furthermore, in our conception, both an approach strategy and an avoidance strategy can serve either approaching desirable or avoiding undesirable endstates (or reference points). Our model also goes further by distinguishing approach and avoidance tactics from approach and avoidance strategies. While these approaches differ in emphasis, there are many ways in which they complement each other’s strengths and share a common perspective. While the approach–avoidance hierarchy of Elliot and colleagues emphasizes the interactions between dispositional motives and temperaments and goals, we focus primarily on the relations among goals, strategies, and tactics. It will be interesting in future work to consider how these two approaches might together suggest new ways in which to study approach and avoidance motivations in self-regulation. For instance, Elliot (2006) has suggested that “avoidance motivation is posited to be problematic at all levels of the hierarchy” (p. 115; see also Elliot & Sheldon, 1997, 1998; Emmons, 1996). However, this perspective emerges primarily in reference to the dispositional and goal levels of the hierarchy. We do not disagree that avoidance at those levels (or at the system level in our model) often leads to poorer outcomes. However, we argue that avoidance at the strategic level, or at the tactical level, is not inherently problematic. Indeed, regulatory fit theory provides evidence of times when avoidance strategies lead to better performance (Förster et al., 2001), enjoyment (Freitas & Higgins, 2002), and subjective well-being (Grant et al., 2006). We have also emphasized in this chapter that despite promotion sometimes being characterized as synonymous with systemic approach and prevention with systemic avoidance (cf. Gable, 2006), promotion and prevention orientations are not the same as approach and avoidance at the system level. In part, we suspect that this confusion has arisen because at the strategic level of the approach and avoidance hierarchy, rather than the system level,

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such parallels can be drawn. Further, some measures of approach and avoidance orientations, such as the wellknown Carver and White (1994) BAS/BIS questionnaire, have tended to emphasize promotion system concerns and eager-related tactics in the approach scales, perhaps causing scientists to perceive too strong an association between BAS, as measured in this questionnaire, and promotion focus (cf. Eddington, Dolcos, Cabeza, Krishnan, & Strauman, in press). It is also possible that this confusion reflects an actuarial reality that promotion goals tend to be reflected more often in approach at the system level and prevention goals may tend to be reflected more often in avoidance at the system level. Indeed, a preference for eager strategies and the concerns of the promotion system do result in greater sensitivity to the presence and absence of positive outcomes, just as a preference for vigilant strategies and the concerns of the prevention system result in greater sensitivity to the absence and presence of negative outcomes. However, although individuals in a promotion- or prevention-focused state have differential sensitivity to positive and negative outcomes, this does not mean that promotion-focused individuals only pursue desired end-states and that prevention-focused individuals only avoid undesired endstates. At the system level, both promotion- and prevention-focused individuals avoid undesired end-states and approach desired end-states. Thus, when measuring or manipulating approach and avoidance at the system level, it is important to differentiate between whether an individual is pursuing a desired end-state and whether that individual is in a promotion- or prevention-focused state. Consideration of the dimension of regulatory focus at the system level further suggests that beyond the benefits of pursuing approach versus avoidance, there are additional benefits that result when there is a fit between an individual’s regulatory focus orientation and the approach or avoidance strategy that is employed. For all individuals, approaching a desired end-state (e.g., good marriage) is posited to typically result in better outcomes than avoiding an undesired end-state (e.g., bad marriage). However, imagine two individuals both pursuing a good marriage. A promotion-focused individual is likely to represent that end-state as an ideal whereas a preventionfocused individual is likely to represent that end-state as an ought. Given the different ways in which these individuals represent the desired end-state at the system level, eager approach strategies will result in better outcomes for the promotion-focused individual and vigilant avoidance strategies will result in better outcomes for the prevention-focused individual; in other words, regulatory fit produces better outcomes. Thus, the idea that “approach

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is better” at all levels of the hierarchy does not hold up when one considers the orthogonal but related dimension of regulatory focus at the system level. This also suggests that the fit between one’s underlying regulatory focus orientation and the employed strategy may have a greater impact on well-being than the compatibility or concordance between approach (avoidance) at the system level and approach (avoidance) at the strategic level.

TARGETING THE HIERARCHY: IMPLICATIONS FOR INTERVENTIONS In this closing section, we would like to explore briefly some potential implications of how thinking about approach and avoidance in this way might be of interest not only for understanding self-regulation in theory, but also in practice. The interest that many of us have in selfregulation is motivated, at least in part, by an understanding of how to make real differences for the ways that individuals struggle to self-regulate effectively (Vohs & Baumeister, 2004). How might thinking about distinctions between the system, strategic, and tactical levels of approach and avoidance help us design and target interventions that are more effective? Individuals sometimes have maladaptive strategies for getting along in the world; these strategies are also served by more (or less) adaptive tactics, depending on the context. If one accepts the premise that the strategic and tactical levels of self-regulation are independent, it follows that interventions could be targeted at either the strategic or the tactical level. Although speculative, it seems plausible that in some cases, it may be easier to help an individual to first adopt new, more adaptive tactics (framed as serving an existing strategy) and then work to modify or challenge the underlying strategy if needed. Imagine an individual who has the goal of avoiding rejection (systemlevel avoidance). She may adopt an avoidance strategy (avoid matches to rejection); this strategy can be served by multiple tactics. For example, she could preemptively reject after conflict (Downey, Freitas, Michaelis, & Khouri, 1998), self-silence her own needs in the face of potential rejection (Ayduk, May, Downey, & Higgins, 2003), or increase ingratiation efforts (Romero-Canyas & Downey, 2005). While all of these tactics serve the underlying strategy, some may be preferred because they are less maladaptive in certain situations (though admittedly all are maladaptive to some extent). Additionally, there may well be other, even more adaptive tactics that could be implemented. Thus, if the underlying systemic and strategic preferences are harder to initially alter, the adoption of more adaptive tactics might be an easier first step.

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Such an approach reflects a potential therapeutic advantage of considering hierarchies of self-regulation. The Grant et al. (2006) diary study suggests a further implication of the present model of approach and avoidance motivations. In the daily diary study, promotionfocused individuals who used eager coping strategies to cope with a stressor did better than promotion-focused individuals who used vigilant coping strategies, whereas the reverse was true for prevention-focused individuals. Thus, interventions that identify the best way to frame a coping strategy in terms of approach versus avoidance for a given client may be particularly effective. For instance, people suffering from clinical depression tend to have a dominant promotion focus, and those suffering from clinical anxiety tend to have a dominant prevention focus (Strauman, 1992). If new (and generally positive) tactics for coping with the client’s everyday problems are being proposed (e.g., by the therapist), then it would make sense to frame a new intervention tactic as serving an eager (approach) strategy for the depressed client and as serving a vigilant (avoidance) strategy for the anxious client— thereby intensifying the attractiveness of the tactical activity to the client and increasing the likelihood that he or she will engage in it. For example, the tactics of choosing to exercise more or to improve one’s eating habits, which benefit clients with either type of clinical problem, could be framed differentially. In other words, the tactical direction of the therapist to these two clients could be the same (e.g., “begin an exercise regimen”) but the framing of the tactic could be tailored to reflect the eager approach or vigilant avoidance strategy that would be most motivating given the client’s underlying systemlevel symptoms and diagnosis (promotion-related depression or prevention-related anxiety). In closing, we have found that thinking about approach and avoidance motivations at the system, strategic, and tactical levels has been generative for us in exploring both theoretical and applied issues. Although we have begun to answer some questions, our exploration raises as many (or more) new questions as it answers. But that is as it should be. We ourselves have struggled with the difficulties in clearly defining these levels and certainly recognize that our way of parsing these motivations is not the only alternative. We believe that the field is entering a new conceptual growth period for the study of approach and avoidance motivations in self-regulation, and thus it is timely for this volume to appear. We also believe that identifying the levels at which individuals are approaching or avoiding is critical in order to fully understand and predict effective and ineffective self-regulation.

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ACKNOWLEDGMENT The research reported in this paper was supported by Grant 39429 from the National Institute of Mental Health to E. Tory Higgins. Correspondence concerning this chapter may be sent to E. Tory Higgins, Department of Psychology, Columbia University, Schermerhorn Hall 406, 1190 Amsterdam Avenue, New York, 10027.

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Self-Esteem and Self-Concept and Avoidance 30 Approach Motivations in the Self-Concept and Self-Esteem Dianne M. Tice and E. J. Masicampo CONTENTS Pursuit of Self-Esteem...........................................................................................................................506 Functions of Self-Esteem..................................................................................................................506 Self-Deception: Approaching Good, Avoiding Bad..............................................................................507 Competing Motives in Self-Knowledge ...........................................................................................509 Origins and Costs of Pursuing Self-Esteem ..................................................................................... 510 Trait Differences in Self-Esteem ........................................................................................................... 511 Definition and Measurement ............................................................................................................ 513 Conclusion ............................................................................................................................................. 517 References ............................................................................................................................................. 517

How do we come to know ourselves and what impact does our self-knowledge have on the way we behave? Over time, each of us gathers information that instructs us of who we are and what we are like. We learn about ourselves through our experiences, and we form positive or negative evaluations for the various characteristics we perceive ourselves to have. Social psychologists refer to these aspects of self-knowledge collectively as the selfconcept. Our self-concepts provide us with information about ourselves, and this information in turn influences the actions we take and the goals we decide to pursue. If we know that we like something, then we seek it out. If we think we can accomplish a task, then we will happily engage it. The purpose of this chapter is to examine these relationships—namely, how knowledge about one’s self is tied to motivated behavior. This chapter will review the relationship between motivation and the self-concept, particularly with regard to self-esteem and approach and avoidance motivations. Many of our motivations are driven not merely by the

content of our self-concepts, but by the way we evaluate our self-concepts, or our levels of self-esteem. Each of us expends a great deal of energy toward maintaining certain (usually positive) evaluations of ourselves and this self-esteem maintenance can manifest itself in a wide range of behaviors, including self-handicapping (Tice, 1991), world view defense (Greenberg, Pyszczynski, & Solomon, 1986), and aggressive behavior toward others (Tesser, 1988). Furthermore, by utilizing the approach– avoidance distinction, we can gain a better understanding of when, why, and by whom these various behaviors are likely to be performed. We will review the social psychological literature with a special focus on findings related to the function of selfesteem, how self-esteem has been defined and measured, and the behaviors individuals engage in that relate to self-esteem maintenance. As we review this literature, we will make reference to two primary modes by which the self-concept and self-esteem relate to approach and avoidance motivations. First, we review evidence that individual 505

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differences in self-esteem level relate to dispositional tendencies toward approach- and avoidance-related behaviors. We will also expound on these findings by suggesting ways that the more distinct self-esteem components may relate to motivated behavior. Second, we suggest that the content of individuals’ self-concepts can help predict the contexts under which approach and avoidance behaviors will be engaged. Before starting, it is vital to acknowledge that selfesteem is discussed and conceptualized in two very different ways by social and personality psychologists, and that these different ways have quite different implications for approach and avoidance motivation. One widespread conceptualization emphasizes individual differences in level of self-esteem (and related traits). As we shall propose, these different levels of self-esteem are associated with different kinds of social strategies. In particular, high self-esteem appears to foster an approach strategy, whereas low self-esteem is associated with more avoidance strategies. The other conceptualization treats self-esteem as itself a motivation rather than a trait, in the sense that people are widely seen as striving to think well of themselves. The self-esteem motive can be deconstructed into self-enhancement, which is primarily an approach motive in the sense that one seeks to approach positive outcomes, and self-protection, which is mainly concerned with the avoidance of failure and loss. We shall suggest, furthermore, that the trait and the motivation are intertwined.

PURSUIT OF SELF-ESTEEM The notion that people strive to think well of themselves, and that they also strive to be well thought of by others, is hardly new in modern social psychology. On the contrary, it is a relatively ancient observation and underlies many conceptions of human vanity and hypocrisy. Pride— especially puffing up an inflated, unwarranted sense of superiority over others—was regarded by medieval theologians as one of the Seven Deadly Sins. Before them, hubris was presented as one of humankind’s most dangerous failings in ancient mythology, and humans who fancied themselves to be on the level with the gods were often punished with severe comeuppances.

FUNCTIONS OF SELF-ESTEEM The benefits of having high self-esteem are manifold and some researchers have argued that the motive to see one’s self in a positive regard is universal (Sedikides, Gaertner, & Toguchi, 2003). However, researchers have

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largely taken for granted the fact that each of us has a desire to see ourselves in a positive light (however, see Swann, 1997 for an important opposing view). Few have bothered to ask why this is so. What is the function of self-esteem? Why is high self-esteem beneficial at all and why should we seek it? There are two major social psychological models as they relate to this issue: terror management theory (TMT; Greenberg et al., 1986) and sociometer theory (Leary, Tambor, Terdal, & Downs, 1995; Leary & Baumeister, 2000). Each theory provides a framework for understanding both why we have self-esteem and what we do to maintain it. Greenberg and colleagues (1986) put forth the idea that self-esteem serves as a buffer against the potentially paralyzing anxiety brought about by the awareness of one’s own mortality. Based on the work of cultural anthropologist Ernest Becker, TMT suggests that one uniquely human characteristic is that we are each aware of our own impending death. This awareness of mortality coupled with the inborn urge to defy death causes a potentially paralyzing anxiety within each individual. Accordingly, we use culture and religion to achieve symbolic immortality, thereby defeating on some level the looming threat of death. Furthermore, self-esteem informs us of whether or not we are adhering to the culture to which we feel we belong. According to Sociometer Theory (Leary et al., 1995), self-esteem serves as a gauge that informs us of our level of inclusion with others. This theory is based on the idea that humans rely on others to survive, thus belonging to social groups is an innate human need (Baumeister & Leary, 1995). As such, social exclusion is seen as detrimental to human functioning and survival, and selfesteem is suggested as the primary tool by which we avoid any instances of social rejection. Inclusion from others makes us feel good, and so we seek acceptance as a form of self-esteem fulfillment. Exclusion decreases self-esteem, and so when we try to boost our self-esteem we work to once again gain acceptance from others. Why is the purpose of self-esteem important for the approach–avoidance distinction? Each theory of selfesteem has unique consequences for self-esteem maintenance and how approach and avoidance motivations should be understood as they relate to self-esteem. The authors of Sociometer Theory, for instance, suggest that “human beings possess a fundamental motive to seek inclusion and to avoid exclusion from important social groups” (Leary et al., 1995, p. 519). Thus, self-esteem related approach behaviors should be manifested in one’s behavior toward maintaining interpersonal relationships,

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Approach and Avoidance Motivations in the Self-Concept and Self-Esteem

whereas self-esteem related avoidant behaviors should come in the form of avoiding social exclusion and rejection. On the other hand, TMT focuses on self-esteem as an anxiety buffer. From this perspective, self-esteem maintenance should be particularly important when threats to mortality-related anxiety are high. Moreover, one might expect that (risky) acts of self-enhancement will be relatively higher and acts of self-protection lower when mortality concerns are absent and thus pose no threat to the individual. Where the two theories overlap is also informative for our understanding of approach and avoidance motivations. To the extent that self-esteem is conceptualized as a buffer against mortality-related anxiety, or as a monitor that warns a person of harmful social-exclusion situations, both theories seem to frame self-esteem maintenance as a largely avoidant behavior. This may have larger consequences for motivation as a whole, beyond behaviors directly related to self-esteem or the self-concept. Self-esteem maintenance then may relate to avoidant behaviors in general, such that individuals will behave in avoidant, self-protective ways when a self-esteem threat is present. Conversely then, perhaps approach behaviors are only possible when self-esteem is high and threats to self-esteem are absent. This idea is consistent with the suggestion by Baumeister, Campbell, Krueger, and Vohs (2003) that high self-esteem seems beneficial only to the extent that it impels behavior. Baumeister et al. (2003) suggested that high self-esteem appears linked to greater initiative. People with high self-esteem are, for example, said to initiate behaviors more and persist longer in the face of failure. Thus, when self-esteem maintenance is unnecessary and esteem needs are met, individuals are free to seek other behaviors and to adopt a general approach orientation toward goals. Do people seek self-esteem beyond its functional level? In other words, do people seek high levels of selfesteem for its own sake or only in the face of ego-threats such as mortality salience or social exclusion? If selfesteem is seen largely as a defense mechanism, then it may best be understood through the scope of avoidant behavior. The following section reviews some documented cases of self-esteem maintenance. While previous research has not focused on the approach and avoidance distinction in relation to self-esteem maintenance, we review the previous research with this distinction in mind, and we suggest likely instances of this fundamental separation. Patterns in this research are consistent with the proposed idea that individual differences in self-esteem level produce differences in approach and avoidance behaviors.

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SELF-DECEPTION: APPROACHING GOOD, AVOIDING BAD Modern psychology owes a debt to Calvinist Protestantism, because the Calvinists developed a much more thorough understanding of self-deception than had prevailed earlier. Calvin held that because God knows everything, God knows whether each person is going to end up in heaven or in hell, in which case everyone’s fate is already “predestined.” Calvin added that it was usually possible to figure which of those fates awaited any particular person, especially because God tended to favor the Elect with worldly success to complement their virtuous piety and good works. Generations of Calvinists therefore became fascinated with trying to persuade themselves that they were headed for heaven. Along the way, they noticed that their neighbors were likewise trying to fancy themselves members of the Elect, and they became aware of how people try to twist the facts to furnish a flattering picture of self. Self-deception, as documented in today’s research laboratories, is perhaps less focused than in the Puritan era on persuading oneself about one’s eternal fate. (How much this reflects a change in the self-deceptive goals of individuals, and how much it reflects the relatively secular emphases of modern research methods, could be debated to some extent.) But the basic truth continues to be widely assumed and often confirmed. People twist and spin the facts so as to enable them to think well of themselves. We now summarize some of the patterns of selfdeception that psychologists have documented. By self-deception we mean the broad range of cognitive strategies people employ in order to enable them to think well of themselves. This broad definition is more in keeping with everyday, colloquial usages of the term and with modern research findings, as opposed to stricter and narrower definitions that required proof that the same person can both know something and not know it simultaneously (Sackeim & Gur, 1979). It does assume that people have a basic self-esteem motivation, which is to say they are driven to create and hold generally favorable views of themselves. This assumption—that pretty much everyone desires a measure of self-respect and self-esteem—appears uncontroversial in modern social psychology as practiced in Western civilizations, although there remain some questions about cultural relativity. In particular, Heine, Lehman, Markus, and Kitayama (1999) proposed that Japanese persons do not have the same “self-enhancement” motive and instead strive for humility and self-improvement. But perhaps there are commonalities even there, insofar as Japanese

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too seek the respect of others and like to regard themselves as good members of valued groups (Sedikides et al., 2003). Perhaps the Japanese have the same goal of being a good person and are simply more disciplined than others at rejecting self-deception as a way to get there, so that substantive goodness rather than cognitive distortion is the most effective means of satisfying this goal. This may be reflected in the Japanese orientation toward self-improvement, as well as their cultural tradition of committing suicide in response to personal disgrace. It is certainly clear that, at least from the perspective of what is best for society, becoming a better person is the preferred way to earn self-esteem. But that requires hard work, discipline, and the sacrifices of virtue. Thus, it is probably not surprising that many persons, at least in the West, occasionally indulge in self-deception. Selfdeception offers a shortcut to self-esteem. Instead of actually becoming a better person, one can simply convince oneself that one already is a better person. The path of self-congratulation is ever gentler and less steep than the path of virtue. Self-deception, as practiced by modern Westerners and observed by social psychologists, is often a liberal mix of approach and avoidance. Self-deception is essentially a manipulation of information. One approaches information (and/or its implications) that offers positive views of self, and one avoids information (and implications) that threaten negative views of self. Let us review some of the relevant findings. The self-serving bias is a well-documented pattern by which people interpret events in ways that benefit their self-esteem. A review by Zuckerman (1979) concluded already at that early date that the evidence was consistent and robust. The essence of the self-serving bias is that people attribute outcomes in a biased manner. Success is attributed to internal causes, whereas failure is attributed to external causes. This well-documented pattern can be decomposed into two biases. Success is approached, in the sense that it is pulled closer to the self by means of embracing it and seizing responsibility. Failure is avoided, in that the self distances itself from it and from responsibility for it. Information processing strategies also use selective approach and avoidance in the service of self-deception. One of these is simply to devote more time to thinking about and elaborating on good information than bad information (Crary, 1966; Kuiper & Derry, 1982; Mischel, Ebbesen, & Zeiss, 1976). People replay flattering events in their memory but prefer not to dwell on or relive humiliating moments; and to the extent they can direct

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their minds to follow that pattern, memory will become slanted toward emphasis on positive events that make the self look good. The relative approach and avoidance of evaluative information about the self was specifically studied by Baumeister and Cairns (1992) who allowed participants to self-select the amount of time they spent reading computer-presented feedback about their personalities. Participants spent significantly longer reading their feedback when it was good than when it was bad. Moreover, this pattern was especially pronounced among repressors, who tend to exhibit the strongest and clearest patterns of self-deception. The selective avoidance of disturbing information was the key to Greenwald’s (1988) so-called junk mail theory of self-deception. Greenwald sought to address one of the classic philosophical dilemmas of self-deception and indeed selective attention generally, which is the apparent impossibility or paradox of using one’s mind to keep things out of one’s mind. That is, how do you know not to look at something until you see it—whereupon it is already too late to avoid looking? The analogy to junk mail offered a solution. People cannot prevent themselves entirely from receiving and recognizing junk mail, but often they can recognize it from the envelope and then discard it without opening and reading it. Applied to selfdeception, the idea is that people do not entirely avoid threatening information but they can minimize it by turning attention away as soon as they recognize its unwelcome aspect. Partial avoidance is thus an important strategy for self-deception. Mentally approaching and avoiding other people is another strategy that can be used in self-deception. As Festinger (1954) pointed out early in the rise of social psychology, many traits are objectively meaningless and can only be evaluated in comparison with other people. Hence the selection of comparison targets becomes a potentially decisive factor in how one evaluates oneself. There is ample evidence that people are often quite strategic about choosing to compare themselves with people who are doing less well than they themselves are doing, so that they can maintain a favorable verdict about their own qualities (Crocker & Major, 1989; Taylor & Brown, 1988; Wills, 1981). This strategy too has both approach and avoidance aspects: people avoid comparing themselves with others who are doing better and would make them feel bad, while they seek out comparison targets who will give them the favorable contrast they seek. Moreover, the approach and avoidance of others in the service of self-deception is more than an idle cognitive exercise. Tesser’s (1988) Self-Evaluation Maintenance

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(SEM) theory holds that people are most threatened to be outperformed on personally important things by people who are close to them. Hence if a relationship partner or other close friend begins to perform too well in a sphere that is central to one’s own self-definition, one may begin to distance oneself from the friend at potentially significant cost to the relationship. In this case, the wish to avoid any bad implications about the self can take the form of avoiding a significant other person.

COMPETING MOTIVES IN SELF-KNOWLEDGE Social psychologists have not been alone in recognizing that people have an extensive thirst to learn about themselves. Astrologers, fortune tellers, writers of magazine self-quizzes, the self-help book industry, and a great many others have catered to this thirst, and in fact the Delphic oracle in ancient Greece advertised with the slogan “know thyself,” although it is possible that the phrase had a somewhat different connotation back then. Nonetheless, it is apparent that people are well motivated to approach information about the self. Not all information is equally approachable, however. Indeed, the precise nature of the motivation to seek selfknowledge was the basis of lively controversy for many years. Three main theories came to dominate the battle, and rather than one of them being the winner, the consensus gradually emerged that all are genuine and distinct motives. In a sense, the battle moved from a dispute between researchers to an everyday conflict within people’s minds and behaviors. The three motives operate, sometimes together, sometimes at cross-purposes. One motive is the desire to hold a favorable view of self. This motive, termed positivity or self-enhancement, is understood largely as the preference for favorable and flattering feedback. It is associated with the desire to raise one’s self-esteem from wherever it is, although in some versions the desire simply to cling to an established (though possibly inaccurate and unjustified) favorable view of self is enough. The second motive is based on consistency. Its most ardent advocate was Swann (1987), who has favored the term self-verification. That term emphasizes that the person is not really seeking to learn new information about the self so much as to verify already established beliefs (including ones that may be inaccurate or unjustified). Self-verification and self-enhancement motives can be regarded as concurring in the preference for information that confirms favorable views of self, but of course they differ sharply when it comes to predicting what sort

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of information will be approached and preferred by people with unfavorable views of self. The third motive is the simple desire for accurate, correct information about oneself. This so-called diagnosticity motive (see Trope, 1983, 1986) is marked by the quest to find out the truth, regardless of whether it is favorable or unfavorable, and regardless of whether it confirms or shatters the existing views of self. As social psychologists compiled studies and findings demonstrating these various motives, a landmark attempt to pit them against each other so as to test their relative power was conducted by Sedikides (1993). He concluded that the self-enhancement motive tended to dominate the others and in a sense was the strongest of the three. The consistency motive came second, as a genuine and powerful motive. And diagnosticity or accuracy was also genuine, but weaker than the other two. Thus, to different degrees, and in different circumstances, people seek all three types of information. The rank ordering of these three motives has implications for understanding approach and avoidance processes in self-esteem. The one thing that all three motives agree on is the strong dislike of being insulted—insofar as we define insults to consist of negative evaluations of the self that are inaccurate or unfair and contrary to existing self-knowledge. Furthermore, the two stronger motives (positivity and consistency) also concur in predicting that people will have a strong dislike for any evaluations that are more negative than what they already think about themselves. Put another way, any broad desire to learn more about oneself will be tempered by a strong wish to avoid criticism. Thus, despite the general information-seeking (approach) pattern, avoidance will tend to take precedence. People are more strongly motivated to avoid bad information about the self than to approach good information. This may be part of the broader pattern by which bad is stronger than good (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001). Yet the very breadth of that pattern indicates why the fear of criticism does not turn people into information-avoiders as a general orientation. Whatever the (greater) power of individual bad events, life remains largely good because of the preponderance of good events. In the same way, people mostly hear favorable things about themselves, partly just because of other people’s politeness and reluctance to transmit bad news (Tesser & Rosen, 1972). They also probably remain generally optimistic (Taylor & Brown, 1988), and so they may approach unknown information and diagnostic situations in the possibly mistaken expectation that what they learn about themselves will be gratifying.

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ORIGINS AND COSTS OF PURSUING SELF-ESTEEM Although some researchers have attempted in recent years to explain the need for self-esteem (Leary et al., 1995; Greenberg et al., 1986), psychologists have largely taken for granted that self-esteem is both necessary and good for the individual. The simple and obvious explanation for self-esteem has been that it has so many adaptive consequences that people seek it out for the sake of these benefits. With self-esteem, however, the case for adaptive benefits has become clouded. To be sure, it has had its advocates. Indeed, spurred by a mass of early research findings showing many positive correlations between (high) self-esteem and various positive outcomes that included academic and occupational success, popularity, and avoidance of a broad range of personal and psychological problems, many American groups and institutions began to put efforts and resources into trying to increase selfesteem across various broad segments of the population. The most famous of these was the California Task Force to promote self-esteem and personal and social responsibility (see California Task Force, 1990), which hoped that increasing the self-esteem of all California citizens would lead to a host of benefits, including reductions in crime, drug dependency, and teen pregnancy, and various improvements ranging from academic performance to more tax revenues for the state. Although that group disbanded in the 1990s, the self-esteem movement remains influential across the United States, particularly in schools, where it is hoped that raising the youngers’ selfesteem will lead to better performance in school as well as various other moral and socially desirable outcomes. The hope that raising self-esteem will produce a host of positive outcomes has, however, been battered by the accumulation of research findings. An extensive review by Baumeister and colleagues (2003) and a less extensive but still authoritative one by Emler (2002) concluded that the benefits of high self-esteem are far less than previously thought. The exciting findings that initially fostered so many fond hopes have been found to be subject to the familiar problem of drawing causal conclusions from correlational findings. For example, although it is true that higher self-esteem is moderately correlated with getting better grades in school, the correlation appears to arise because academic success leads to higher self-esteem, not because self-esteem somehow results in doing better on tests (Bachman & O’Malley, 1976). Third variable explanations are also relevant: coming from a well-off family appears to contribute to both higher self-esteem and better academic performance (Bachman & O’Malley, 1976).

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Indeed, artificial attempts to boost self-esteem, such as by the sort of self-flattering exercises happily practiced in many schools, may if anything be counterproductive. One of the few rigorous experimental tests of such interventions was recently carried out by Forsyth, Kerr, Burnette, and Baumeister (2007). Struggling students were randomly assigned to receive either just a weekly review question, or that same question accompanied by either a self-esteem boost or an exhortation to take personal responsibility for one’s schoolwork. Final examination scores revealed that the group whose self-esteem was boosted scored significantly worse than the other groups and significantly worse than their own midterm examination performance. A possible implication of these disturbing findings is that when people begin to focus on self-esteem as an end in itself, they often abandon rather than renew their efforts to change their behaviors and performances for the better. To understand why that might happen, it is necessary to reconsider why people want self-esteem so much in the first place. As we said, if high self-esteem led directly to a great many positive outcomes, the pursuit of self-esteem would be unsurprising and even rational and adaptive. In the apparent absence of so many benefits, however, one must ask why that motivation seems so pervasive. Why have evolution and culture shaped people to want self-esteem, if self-esteem confers so few benefits? Terror management theory (Greenberg, et al., 1986) and sociometer theory (Leary et al., 1995) which we reviewed earlier in this chapter shed some light on this issue. Greenberg and colleagues (1986) suggest that selfesteem serves as a buffer against the anxiety brought about by the awareness of one’s own mortality. Sociometer Theory (Leary et al.), on the other hand, proposes that self-esteem serves as a gauge that informs us of our level of social inclusion. The Terror Management view depicts the quest for selfesteem as part of the generally self-deceptive project. The idea is that self-esteem helps shield the person from awareness of impending death. This has, however, the important value that it will enable the person to function from day to day, whereas a full awareness of mortality would supposedly paralyze the person with terror. To be sure, selfesteem does not really do any good in preventing death, but it helps the person downplay the thought of it. The function of self-esteem in Sociometer Theory is much clearer. People need acceptance from others, and self-esteem tells them whether they are likely to get it. Low self-esteem signifies a high likelihood of social exclusion and rejection, and so people in that state should be motivated to change so as to improve their prospects

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of acceptance. Leary and Schreindorfer (1997) showed that low self-esteem was uncorrelated with death anxiety (contrary to the Terror Management view) but substantially correlated with social anxiety. These views thus suggest why people might desire self-esteem even though its objective benefits are small. They also suggest, however, that the pursuit of self-esteem as an end in itself might have problematic, even undesirable consequences. One problem with pursuing self-esteem was explicated by Leary and Baumeister (2000). According to the sociometer view, the purpose of self-esteem is to tell you whether you are the sort of person whom others will want to accept and include, such as by befriending, hiring, or marrying you. Low self-esteem should signify that one’s eligibility is low, and so one should change the self so as to make it more appealing to others. That process would possibly lead eventually and, most important, indirectly, to a rise in self-esteem, by way of becoming a better person. But some individuals may be tempted to skip the hard work of improving the self and instead simply revise their opinion of themselves based on dubious or phony reassurances. Rather than become a better person, it is easier and pleasanter to merely claim and think that one is a better person. The more people focus on self-esteem as the goal rather than as a signal of goal attainment, the more they will be tempted to “fool the meter” by selfdeceptive processes. The fi ndings cited above by Forsyth et al. (2007) capture this problem. According to sociometer theory, the link between getting good grades and self-esteem should be there because people know (correctly) that good grades will improve their chances of future social acceptance. Doing poorly in school should threaten selfesteem, which ideally would lead to redoubled efforts to perform better such as by studying harder. However, apparently the students who were encouraged to focus on maintaining their self-esteem reduced their effort, either because they decided that their own high self-worth did not need any objective validation in terms of good grades, or simply because they found it easier to think well of themselves when they avoided spending time and effort on a class that had already provided esteem-threatening feedback in terms of a low midterm grade. Making selfesteem the goal and focus of their motivation thus led them to do worse rather than better. A broad and masterful indictment of the dangers of pursuing self-esteem for its own sake was furnished by Crocker and Park (2004). Crocker and Park argued that the importance of self-esteem lies in the way people define, pursue, and maintain their levels of self-esteem,

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rather than people’s self-esteem levels per se. A major thrust of their argument is that in domains in which individuals’ self-esteem is contingent, self-esteem goals tend to override other, often beneficial goals related to that domain. For instance, Crocker (2003) found that individuals who based their self-esteem on academics were more concerned with obtaining good grades than they were with actual learning. In important domains, positive performance becomes a means to validate the self rather than an opportunity to learn, improve, or master ones goals, and negative performance becomes a major self-threat rather than an opportunity to learn from one’s mistakes. Crocker and Park (2004) reviewed a wide range of self-defeating behaviors and strategies that people engage in when operating in domains important to their selfesteem. Individuals will often avoid thinking about or selectively forget negative feedback (Crary, 1966; Mischel et al., 1976), and focus on receiving positive feedback without trying to understand what led to their success (Carver, 2003). Such self-serving behavior often undermines a person’s ability to improve on the given domain. People also tend to become focused on themselves in self-relevant domains to the point that their inattention to others compromises interpersonal relationships (Park & Crocker, 2003). Furthermore, feeling that one has to do something in order to feel worthy threatens their sense of autonomy in that domain, and leads to high levels of stress and anxiety that can diminish one’s self-regulatory capacity and even compromise both mental and physical health (Dykman, 1998). Many of these potential costs of self-esteem pursuit are not inherent to either an approach or an avoidance orientation to motivation. Crocker and Park (2004) acknowledge that while high and low self-esteem individuals may approach or avoid self-relevant domains in different ways, both types of behavior can have costs for the individual. Thus, the consequences of self-esteem related behavior will hinge not only on one’s motivational orientation, but how people define self-worth for themselves and in what domains they decide to pursue it.

TRAIT DIFFERENCES IN SELF-ESTEEM We turn now from the pursuit of self-esteem to trait differences in self-esteem. This section will review the relationship between self-esteem level and motivation. Findings in the self-esteem literature are consistent with research on approach–avoidance motivations such that a subset of self-esteem related behaviors can be defined as approaching desired, positive outcomes, while others are aimed at avoiding undesired, negative outcomes.

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In addition, trait self-esteem levels have been found to be closely related to individual differences in the chronic preference for one motivational orientation (approach or avoidance) over the other. We will review the literature on self-esteem and how it relates to motivation for the purpose of illuminating this relationship between the self-concept and approach–avoidance behaviors. Self-esteem is perhaps the most studied construct in social psychological research on the self (Baumeister et al., 2003), and self-esteem’s development and maintenance have been found to be a large factor in determining one’s goals and motivations. The most common conceptualization of self-esteem is as a person’s positive or negative evaluation of him- or herself (James, 1890). Thus, individuals are said to have either a positive (or high) self-esteem or a negative (or low) self-esteem. Although reliable self-esteem differences have been measured, a number of positive benefits have been conferred to the positive (as opposed to negative) evaluation of the self (Baumeister et al.), and furthermore, the inborn desire to evaluate one’s self in a positive regard has become axiomatic in the psychological literature (Crocker & Wolfe, 2001; Pyszczynski, Greenberg, Solomon, Arndt, & Schimel, 2004; Tesser, 1988). The tendency to seek out favorable self-knowledge has been observed as taking precedence over other motivations related to the evaluation of the self-concept, including the motivations to obtain accurate self-relevant feedback (self-assessment) and to confirm one’s existing views about one’s self (selfverification; Sedikides, 1993). This desire to view one’s self in a positive regard has been seen as both powerful and universal (Sedikides et al., 2003), and thus serves as a common focal point in the literature on self-esteem and the self-concept. A wide range of behaviors aimed at producing a positive view of the self have now been documented, and the relationships between them dovetail quite nicely with the literature on the distinction between approach and avoidance motivations. The approach–avoidance distinction refers to the idea that human behavior relies on two primary motivational systems (Carver & Scheier, 1998; Gray, 1981; Elliot, 1997; Higgins, 1997). Gray (1981) differentiated between a behavioral approach system (BAS) which deals with appetitive motivations and approach behaviors, and a behavioral inhibition system (BIS) which deals with aversive motivations and withdrawal behaviors. Carver and Scheier (1981) developed a similar motivational model based on two self-regulating feedback systems. One system, a discrepancy-reducing feedback system, maps quite well onto Gray’s BAS idea. Similarly, a second discrepancy-enlarging feedback

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system which focuses on avoidant behavior is reminiscent of the BIS. A third line of research that is consistent with this theme is work by Higgins (1996) on the distinction between promotion and prevention as self-regulatory foci. In theory, each focus (promotion and prevention) is applicable to both approach and avoidance goals, but some researchers suggest (Carver, Sutton, & Scheier, 2000) that the promotion focus tends to deal with appetitive goals while the prevention focus tends to deal with aversion goals. All three lines of research support the idea of two fundamental human motivations: roughly, approach and avoidance. Furthermore, each of the previous theories also supports the idea of measurable individual differences in the chronic preferences for one motivation system over the other. Do individual differences in motivation relate to chronic self-esteem levels? One sweeping formulation of motivational differences that depend on level of selfesteem was proposed by Baumeister, Tice, and Hutton (1989). In some respects anticipating the sociometer theory, particularly with regard to putting an emphasis on interpersonal goals and motives, they began by examining the actual responses to trait scales that resulted in being classified as high or low in self-esteem. Somewhat surprisingly, they did not find that low self-esteem scores came from describing oneself in unflattering terms, which the literal definition of low self-esteem would imply. Rather, they found that low scores on self-esteem were only relatively low, and in absolute terms they were medium, noncommittal responses. They went on to propose that neutral, noncommittal descriptions of self (unlike negative, self-derogating ones) could well serve effective functions, specifically with regard to protecting the self from the dangers of extravagant claims. They followed earlier work by McFarlin and Blascovich (1981), which resolved the earlier and intense debates about the motivational orientation of people with low self-esteem. Contrary to views that low self-esteem was characterized by a positive desire for failure (e.g., to confirm negative views of self), McFarlin and Blascovich showed that people with low self-esteem had the same values and aspirations as people with high self-esteem, namely to succeed and be liked—the people with low self-esteem simply had less confidence that they would actually achieve those goals. Thus, people of different levels of self-esteem agree in their desire to succeed but differ in their perceived likelihood of reaching it. The differential confidence leads to a different orientation toward risky undertakings. People with high self-esteem expect frequent success and are therefore willing to take some risks. Their optimistic,

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confident outlook predisposes them to look for new ways to achieve success and thereby to glorify the self. In contrast, people with low self-esteem anticipate that many undertakings will turn out badly. For them, avoiding embarrassment, humiliation, and other failures becomes a central focus. To be sure, they would like just fine to achieve a great new success or to discover something new and wonderful about themselves, but they do not expect many such fine outcomes. Moreover, having less self-esteem to start, they are less willing than others to gamble with it. Baumeister, Cooper, and Skib (1979) compared self-esteem to money. Those with plenty of it are more willing to gamble and speculate in the hope of achieving a sizable return. Those with only a little of it must avoid taking chances and only invest it in the safest opportunities. Hence the balance between approaching and avoiding may be different as a function of trait level of self-esteem. Risky endeavors that contain the chances of both dramatic success and embarrassing failure will appeal far more to approach-oriented people having high self-esteem than to avoidance-oriented people with low self-esteem. It is true (contrary to some early theories) that both high and low self-esteem go with preferring success over failure, and when one is immersed in working toward a goal, people of all levels of self-esteem will try to do well. But in terms of who will seek out such a high-risk, high-payoff undertaking, different levels of trait self-esteem will push people in different ways. For those with low self-esteem, avoidance of failure will be paramount, whereas for those with high self-esteem, the chance to approach success will outweigh most risks of possible failure. A direct test of this motivational theory of self-esteem was provided by Tice (1991). She used the strategic behavior of self-handicapping which was first identified by Jones and Berglas (1978; see also Berglas & Jones, 1978; Frankel & Snyder, 1978). Self-handicapping refers to a seemingly self-destructive pattern by which people act in ways that reduce their own chances of success. For example, in preparation for an upcoming examination, a prudent strategy would be to study hard and then get a good night’s sleep, whereas a self-handicapper might avoid studying and spend the night on a drunken outing. The appeal of such strategies is that they alter the attributional calculus so as to bias it in the self-handicapper’s favor. In the preceding example, the unprepared and hungover test-taker is protected against being shown to be stupid or incompetent, because failure on the test will be attributed to the obstacles (lack of preparation and alcoholic hangover) rather than to lack of ability. Meanwhile, to perform well despite not having studied nor properly slept would be taken as a sign of unusually high ability.

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Thus, self-handicapping has two attributional benefits. It avoids negative implications of failure while enhancing the credit one would get for success. Tice (1991) undertook to separate these two attributional benefits, by means such as describing an upcoming test as only suited for identifying exceptionally low or exceptionally high levels of talent. Her findings supported the view that high selfesteem is oriented toward self-enhancement whereas low self-esteem aims for self-protection. People who scored high in self-esteem were more likely to engage in selfhandicapping when it was a strategy for self-enhancement and when self-protection was irrelevant (such as if the test was described as suited only for identifying exceptionally gifted individuals, so that any scores but extremely high ones were meaningless). People with low self-esteem, in contrast, engaged in self-handicapping mainly to protect themselves against failure. To be sure, Tice (1991) found that the self-protection motive was more common. Both high and low self-esteem were associated with some degree of self-protective selfhandicapping (although the pattern was stronger among people with low than high self-esteem). This fits our earlier assertion of the primacy of avoidance: everyone wants to avoid losing self-esteem. More recent findings have demonstrated that the tendency for low (and high) self-esteem individuals to engage in avoidance (and approach) related behaviors applies to personal goals in general (Heimpel, Elliot, & Wood, 2006), and not just self-evaluation or self-presentation. Thus, self-esteem level seems intimately tied to dispositional approach and avoidance behaviors, and a more detailed understanding of this relationship hinges on a more accurate definition of what it means to have high or low self-esteem. In the following section, we continue our assessment of motivation and self-esteem with a review of the research that has focused on defining exactly what self-esteem is, what the construct comprises of, and how it should be measured.

DEFINITION AND MEASUREMENT The definition and measurement of self-esteem has not been without controversy. The most common conceptualization of self-esteem is as a person’s positive or negative evaluation of him- or herself (James, 1890). However, this unidimensional view of self-esteem has been somewhat inconsistent in its predictions for high and low self-esteem individuals’ behavioral and psychological outcomes (Baumeister et al., 2003; Kernis, 2003). For instance, although there is an abundance of research suggesting that high self-esteem is unequivocally beneficial to the

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individual, some theorists have begun to question this assumption based on such findings as those indicating that high self-esteem individuals may have fragile selfconcepts that make them susceptible to overly defensive behaviors. Unidimensional self-esteem has also proven somewhat inconsistent in its predictions for interpersonal behaviors; some theorists have suggested that low selfesteem causes aggression toward others, while research findings suggest that high self-esteem (or some kinds of high self-esteem) can facilitate the same antisocial behavior. Together, these data suggest that self-esteem is perhaps a more complicated construct than a unidimensional scale would suggest. Rosenberg (1965) developed a scale based on a unidimensional definition of self-esteem several decades ago and it still serves as the major tool for assessing selfesteem today (Blascovich & Tomaka, 1991). However, a close inspection of the Rosenberg Self-Esteem Scale (RSES) has yielded results that indicate more than one dimension of self-esteem, with positive feelings loading onto one factor and negative feelings loading onto another (Marsh, 1996). Others have suggested that the RSES does indeed follow a single common factor (Gray-Little, Williams, & Hancock, 1997) and others have argued that the two-factor findings are an artifact of language (Corwyn, 2000; Dunbar, Ford, Hunt, & Der, 2000). Elliot and Mapes (2005) recently suggested that a two-factor model of global self-esteem may not be a meaningless artifact of the RSES. They propose utilizing the apparent separation between negative and positive self-evaluations in future research, and they cite the approach–avoidance distinction as a rationale for this approach. Consistent with this suggestion, the coexistence of dual attitudes has been well documented in the literature, and this ambivalence has furthermore been seen as predictive of approach versus avoidance motivations. Thus, the approach–avoidance distinction provides one direction toward resolving the controversy of selfesteem measurement, and future research on this distinction may shed light on some of the individual differences in self-esteem motivation. Work by Showers (1992) suggests that the manner in which we store our self-knowledge has important consequences for self-evaluation. Her research showed that the compartmentalization of positive and negative information about the self explained variance in self-esteem beyond the mere amount of positive and negative content in the self-concept. Similarly, Pelham (1991) revealed that individuals seem to harbor pockets of positive and negative self-evaluation such that even depressed individuals were found to have specific self-views that were

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just as positive as those held by nondepressed persons. The evidence provided by Showers (1992) and Pelham (1991) suggests that measures of global self-esteem are incomplete measures of self-evaluation (see also Harter, Waters, & Whitesell, 1998), and so it should not be surprising that global measures have yielded variable success in predicting behavioral outcomes. More research needs to be done on the relationship between motivated behavior and self-evaluation in specific domains. Although individuals with low self-esteem have been shown to avoid negative self-evaluations, in which domains does this trend apply? If low self-esteem individuals harbor pockets of positive self-evaluation, how do they maintain these pockets? One possibility is that they behave similarly to high self-esteem individuals in domains in which they hold strong, positive selfevaluations. Such confidence in one’s domain-specific abilities may allow those with low global self-esteem to take more risks and approach positive evaluations in these particular contexts. On the other hand, they may be especially self-protective in such domains, for the reason that these domains serve as their only avenues toward self-worth. Taken together, the findings on self-esteem measurement suggest that future research must take into account a much more detailed measure of self-evaluation than the traditional unidimensional approach. To what extent do people feel good about themselves? To what extent do people evaluate themselves negatively? Furthermore, in which domains do these evaluations occur and in which domains does the individual feel most personally invested? A complete understanding of one’s motivations must take these questions into account. We begin to touch on the interaction between these various issues in the next section as we review some of the interpersonal strategies people use to maintain their self-esteem. Motivation in the Self-Concept: Self-Esteem Maintenance in Action. Regardless of the exact function of self-esteem, researchers are in agreement that most individuals are motivated to achieve and maintain high levels of selfesteem. The ways in which people do this are manifold and we review many of these strategies below. These lines of research have rarely, if ever, acknowledged the approach and avoidance distinction. We speculate about how such factors would play into these phenomena. There are many social cognitive strategies by which individuals work to maintain positive self-evaluations. One way individuals can increase their feelings of selfworth is by associating themselves with other individuals or groups that have performed well on some domain.

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This idea of basking in the reflected glory (BIRGing; Cialdini et al., 1976; Cialdini & Richardson, 1980) of others was famously illustrated by the observation by Cialdini and colleagues (1976) that college students are more likely to adorn their university’s clothing immediately following a win rather than a loss by the school’s football team. By associating themselves with winners, individuals are able both to feel good about themselves and to present themselves in a positive light. On the other hand, people avoid negative self-evaluations by distancing themselves from those who are performing poorly. By cutting of reflected failure (CORFing; Snyder, Lassegard, & Ford, 1986), individuals are able to protect themselves from potential negative evaluations. In either case, selfesteem maintenance has a strong influence on the affiliations one will make. The trend of relating self-enhancement to approach motivations and self-protection to avoidance motivations may not be as straightforwardly applied in the case of BIRGing and CORFing as it can be in other situations. For instance, although BIRGing may resemble an approach-oriented behavior to the extent that it involves seeking out positive evaluations, this tendency to reflect in the positive performance of others appears to be a rather risk-free instance of self-evaluation. In the cases of BIRGing and CORFing, one need not perform in order to meet expectations, one must simply choose to share in another’s success or choose not to share in another’s failure. Thus, it seems reasonable that in this case, those with low self-esteem need not fear the act of approaching positive evaluations since there are no negative consequences for doing so. In fact, evidence suggests that individuals with low self-esteem are not only undeterred by this form of “safe” self-enhancement but are actually more likely to engage in it than individuals who are high in self-esteem. Brown, Collins, and Schmidt (1988) found that low self-esteem individuals were more likely to self-enhance by displaying favoritism toward wellperforming others than those with high self-esteem. More specifically, the findings by Brown and colleagues (1988) suggest that low self-esteem people are more likely to enhance their self-worth in situations where they are not directly implicated in the domain being evaluated. Somewhat consistent with this are findings suggesting that individuals are more likely to BIRG when their selfconcepts are vulnerable—that is, individuals have been found to BIRG more often after incidents of self-threat (Cialdini et al., 1976). While the reflection processes in BIRGing and CORFing involve identifying with the performances of others, social comparison strategies, as the name suggests,

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involve comparing one’s own performance with the performance of others. Social comparison theory was originally predicated on the inborn motivation to obtain accurate self-knowledge. Individuals were said to compare themselves with others in order to gain a more clear understanding of themselves and their place in the world (Festinger, 1954). More recent research has focused on how individuals use social comparison as a tool for selfenhancement (Suls, Martin, & Wheeler, 2002; Wood, 1989). There are two main mechanisms by which people are able to do this. First, individuals can make downward social comparisons—they can choose to compare themselves with worse-off others in order to make themselves appear better off and to boost their self-esteem. Wood, Taylor, and Lichtman (1985), for instance, found that many women with breast cancer spontaneously compare themselves with other patients who are in worse condition. Secondly, there is some evidence that upward social comparisons can also increase self-regard. The option to compare oneself with those who are better off can be a fairly dangerous strategy in that one risks appearing inferior, however, to the extent that individuals are able to use this type of comparison to motivate themselves toward self-improvement (Berger, 1977; Blanton, Buunk, Gibbons, & Kuyper, 1999; Vrugt & Koenis, 2002), or convince themselves that they are similar to the better-off others (Wheeler, 1966), upward comparisons can be beneficial for one’s self-regard. Findings suggest that low self-esteem individuals are more likely to seek self-enhancement through social comparisons when such comparisons are perceived to be safe. For instance, those low in self-esteem are more likely to seek social comparisons when they have received success (rather than failure) feedback, and in addition are more likely to do so than those with high self-esteem. These findings are consistent with the BIRGing literature in the suggestion that low self-esteem individuals are perfectly willing to seek positive self-regard so long as the situation is deemed to be of little risk. It is likely that low self-esteem individuals are more likely to take advantage of downward social comparisons while high self-esteem individuals are more likely to make upward social comparisons. If upward social comparisons are only beneficial to the extent that they impel individuals toward active self-improvement, then one intuitive conclusion is that those who are high in self-esteem and of an approach-oriented motivation will be most likely to engage in it. On the other hand, Elliot and Mapes (2005) propose that self-improvement motives may parallel an aversion to the deterioration of one’s abilities. However, the factors that dictate whether self-improvement will be

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driven by a desire for self-enhancement or an aversion to deterioration remains to be seen. Tesser and colleagues (Tesser, 1988; Tesser, Campbell, & Smith, 1984; Tesser & Smith, 1980) provide a comprehensive account of the interaction between the reflection and comparison processes outlined above, and they review a variety of behaviors by which individuals may work to maintain positive self-regard with relation to these variables. Though BIRGing and social comparison can both be used as strategies to enhance one’s self-esteem, the two processes present near opposite responses to the performance of others—reflection requires one to identify with another’s performance while comparison requires one to contrast one’s own performance with the performance of others. Furthermore, the two processes appear to have the opposite result in any given situation. One consequence of BIRGing is that the closer the other person is whose performance one is reflecting in, and the better that person’s performance, the greater the benefit for the BIRGing individual’s self-worth. In contrast, when comparing one’s performance to the performance of another, the closer the other person is to the individual and the better the other person’s performance, the greater the negative impact will be for the individual’s self-worth. What dictates whether one will engage in reflection or comparison when confronted with the performance of another? An understanding of the interaction between the reflection and comparison processes requires relating them to an important third variable: relevance. A task is considered relevant to an individual to the extent that the task is central to the individual’s self-concept, the individual strives to perform well at the task, and the individual freely chooses to engage in the task. According to Tesser’s Self-Evaluation Maintenance (SEM; 1988) model, the comparison process will take precedence for tasks that are relevant, while the reflection process will take precedence for tasks that are not. The SEM model describes a variety of strategies by which individuals maintain positive self-regard. A few of these strategies include affecting the performance of others (Tesser & Smith, 1980), changing one’s own performance (Tesser et al., 1984), modifying relationship closeness (Pleban & Tesser, 1981), and adjusting task relevance (i.e., adjusting one’s self-concept; Tesser & Paulhus, 1983). To provide an example of these strategies, imagine that a self-described cellist finds out a close friend and fellow orchestra member is eligible for the spot as the first-chair cellist in the orchestra. Because cello performance in this case is relevant to the individual, comparison becomes the more important process. One strategy the individual can engage in would be to sabotage

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her friend’s performance in order to avoid looking inferior by comparison. Alternatively, the individual can start working harder in order to boost her relative performance and perhaps herself become eligible for the principal cellist position. She can also distance herself from her friend thereby reducing the strength of the comparison. Finally, she may decide to abandon music altogether in order to reduce the relevance of the domain and allow herself to focus on other tasks. This strategy would also allow her to reflect in the glory of her friend’s no longer threatening abilities. The particular strategy that an individual will choose to pursue in situations like that in the previous example will likely depend in large part on the context (e.g., some strategies may not be plausible in a given situation); however, it is reasonable to assume that there are many individual differences in strategy preference as well. Approach-oriented people may be more likely to try to improve their own performance when threatened by such a comparison. Those who are more avoidant in nature, particularly those who are less confident in themselves or their abilities, may be more likely to flee a given situation—possibly by abandoning the domain altogether or by stepping away from the relationship in order to avoid hurtful comparisons. Given the wide range of positive and negative consequences that can result from each of these strategies, a firm understanding of both the contextual variables and the individual differences that predict strategy preferences should prove very valuable. This is certainly true with regard to the strategy of hurting another’s performance in cases of social comparison, or alternatively helping another’s performance when presented with the possibility of reflecting in their subsequent glory. These behaviors present an interesting subset of anti- and prosocial behaviors. Are certain people more likely to hurt or help the performance of another? When self-worth is implicated in prosocial behavior as they are in these situations, how does self-esteem level interact with behavior? How do approach and avoidance dispositions relate to such behaviors? Again, the relationships here are speculative. High self-esteem may help serve as a buffer against the threatening aspects of such situations, and may additionally impel self-enhancing (rather than self-protective) behaviors. Of course, self-enhancement may come in the form of self-improvement or just as plausibly the disruption of another’s performance, which would be consistent with findings suggesting that high self-esteem individuals may be particularly capable of aggressive behaviors. A likely moderating factor in any act of self-esteem maintenance will be the content of people’s self-concept

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and the contingencies of their self-worth. Although people may be threatened by the performance of another, if they are particularly invested in that domain they will not be likely to walk away from it. Additionally, if that person is particularly invested in his or her relationship with the comparison target, or if that person is personally invested in interpersonal relationships in general, then he or she may not be likely to hinder the other’s performance or create distance in the relationship.

CONCLUSION We have examined the relationship between the selfconcept and motivation with a special emphasis on selfevaluation and the seemingly universal pursuit of high self-esteem. We reviewed research on the self that has suggested that high self-esteem is directly related to approach-oriented aspects of self-esteem maintenance, while low self-esteem is connected with the avoidanceoriented aspects of self-esteem maintenance. In other words, research indicates that those with high and low self-esteem are particularly oriented toward self-enhancement and self-protection, respectively. While research does suggest that low self-esteem individuals will engage in self-enhancement in situations that are deemed “safe” from a self-evaluative standpoint, the relationship between self-esteem level and approach–avoidance orientation seems to hold up in a variety of processes, including selfhandicapping (Tice, 1991) and the pursuit of personal goals in general (Heimpel et al., 2006). We have also reviewed recent research on the functions of self-esteem. Self-esteem theories such as sociometer theory (Leary et al., 1995) and TMT (Greenberg et al., 1986) suggest that self-esteem maintenance may be a largely avoidant process to the extent that individuals are oriented toward avoiding social exclusion or mortalityrelated anxiety. This is consistent with the observed relationship between self-esteem level and motivation orientation. Those with low self-esteem should be particularly attuned to self-evaluative motives, while those with high self-esteem levels should feel free to approach a much wider range of goals and behaviors, an idea that is consistent with a number of findings. Research on the strategies by which people maintain their feelings of self-worth, such as self-deception, BIRGing (Cialdini et al., 1976) and CORFing (Snyder et al., 1986), social comparison (Wood, 1989), and SEM (Tesser, 1988), also promise to be an insightful resource for understanding motivation. Though few have addressed how these strategies relate to the approach and avoidance distinction, research suggests that the answer will come

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by combing these strategies with more detailed accounts and measurements of the self-concept—such as domain specific self-evaluation and contingencies of self-worth. A firm grasp on these aspects of the self-concept may help psychologists understand a wide range of motivated behavior.

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Self-Knowledge of Resilience: Approaching 31 Secrets Negative Self-Aspects Without Aversion Carolin J. Showers and Kristy L. Boyce CONTENTS Role of Self-Structure............................................................................................................................522 Basic Model of Evaluative Organization...............................................................................................523 Assumptions ..........................................................................................................................................523 Compartmentalization and Integration .................................................................................................523 Methodology .........................................................................................................................................524 Long-Term Outcomes ............................................................................................................................526 Links between Self-Organization and Self-Motives .............................................................................527 Positive Compartmentalization ........................................................................................................527 Integration ........................................................................................................................................527 Negative Compartmentalization .......................................................................................................528 Dynamic Model: Change in Self-Structure ..........................................................................................528 Additional Features of Self-Structure and Links to Self-Motives ........................................................529 Multiple Selves Perspectives ............................................................................................................529 Self-Concept Clarity, Self-Stability, and Contingencies of Self-Worth ...........................................530 Self-Strategies: Self-Enhancement Versus Self-Verification ............................................................ 531 Conclusion ............................................................................................................................................. 532 References ............................................................................................................................................. 533

Motives to approach and to avoid traditionally have not been conceptualized as self-relevant motives. Yet, from a physiological perspective, the activation of the BAS and BIS system depends heavily on appraisals mediated by self-perceptions of control and efficacy, as articulated in Carver and Scheier’s (1998) control theory model. From a traditional personality perspective, approach motivation is characteristic of individuals with high achievement orientation, who are generally confident with high selfesteem; whereas avoidance motivation is characteristic of trait-anxious individuals, whose self-concept is likely to be insecure (Atkinson & Birch, 1970). More recently,

hypothesized correspondences between self-discrepancies and promotion versus prevention goals make a concrete link between the structure of the self-concept and fundamental motivational orientations, highlighting the inherent role of the self in motivation (Higgins, 1997). Yet, all of these perspectives to date imply that a positive and secure self-concept fosters confidence and the motive to approach positive stimuli and outcomes; whereas a negative, insecure self-concept fosters anxiety and the motive to avoid negative stimuli and outcomes. In the present chapter, we consider the prevailing concern of what we call a resilient self, that is, a self that is 521

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well-prepared to cope with negative experience or stress. This concern is how to approach negative stimuli (i.e., negative attributes or experiences) without an aversive response. We argue that the approach–avoidance framework offers unique insights regarding this concern. In fact, this circumstance has been addressed indirectly by the hierarchical model of approach–avoidance motivation (Elliot & Thrash, 2001). On the face of it, approach toward negative stimuli without aversion is anathema to approach–avoidance models. The avoidance system allows for vigilance to negative stimuli, but is accompanied by aroused physiological states and impulses to avoid or withdraw (Lang, Bradley, & Cuthbert, 1998). What Elliot and Thrash (2001) proposed is that, at times, the approach system can work in service of long-term avoidance goals—that is, an individual can work toward a positive outcome in the short-term in order to avoid the feared outcome in the long-term. So, for example, a college student who fears failing a multiple-choice test can mobilize her efforts by preparing elaborate outlines of every chapter in the textbook, thereby ensuring adequate (and possibly exceptional) performance on the exam (cf. Norem & Illingworth, 1993; Showers, 1992c). The premise of the present chapter is even more general and far-reaching, namely that at least some individuals may be motivated to approach negative attributes or feelings about the self, without aversion, in order to address or make sense of the concerns they pose. For instance, consider the individual who, when faced with the prospect of a social interaction that will make him feel shy, says to himself “I’m shy, but I’m a loyal friend.” Although the initial thought of his shyness may conjure the motivation to avoid focusing on this negative attribute, such an individual quickly converts that motivation to an approach state by linking shyness to a positive attribute (loyalty), thereby making attention to the social self more rewarding. Individuals who respond in this way should, over time, be increasingly willing to approach their negative attributes or experiences, because they do not experience the same aversive conditioning as someone in whom the initial avoidance motivation proceeds unchecked. Thus, we contend that the possibility that individuals sometimes approach negative stimuli with minimal aversion represents an important lacuna in approach–avoidance models. Although previous work on the hierarchy of motivational states does address this issue, negative approach systems are understudied. We suggest that the ability to approach negative stimuli without aversion is an important feature of resilience and good coping, and that,

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therefore, a full exploration of these processes within the framework of approach–avoidance models will be a fruitful contribution to the literature.

ROLE OF SELF-STRUCTURE Recent research on the evaluative structure of the self may offer insight into how individuals are able to approach negative stimuli with minimal aversion. Showers’ (1992a) model of evaluative self-organization focuses on how individuals represent positive and negative selfbeliefs, and the associative links and category structures which represent them. This is largely a cognitive information processing model, but since the cognitive elements are valenced self-beliefs, affective, and motivational processes are inherently involved. Evaluative self-structures are presumably influenced by underlying self-relevant motivations (e.g., self-enhancement or self-accuracy) (Cantor & Kihlstrom, 1987). In turn, evaluative selfstructures likely facilitate certain self-motives (in a bidirectional fashion) (Showers, 1995). Similarly, evaluative self-structures may be both influenced by emotionality and affective processes (such as reactivity or intensity) (cf. Niedenthal, Halberstadt, & Innes-Ker, 1999), and have important emotional consequences. In the present chapter, we extend previous theorizing about affective and motivational processes associated with evaluative self-organization by considering them through the framework of approach–avoidance models and systems. Previous formulations (Showers & Zeigler-Hill, 2007) suggested distinct motivational characterizations for individuals with relatively positive or relatively negative self-concepts and relatively integrative or relatively compartmentalized self-structures (as described below). As an overview, for individuals with largely positive selfconcepts, those with compartmentalized self-structures seem to experience a need for self-enhancement, whereas integrative self-structures were associated with a need for realism. For individuals with largely negative selfconcepts, the motivation of individuals with integrative self-structures might be characterized as struggling to cope, whereas those who were compartmentalized showed strategies of resignation or withdrawal (giving up). Here, we will extend these motivational considerations by applying an approach–avoidance framework and, more concretely, their possible manifestations in preference for certain types of achievement goals (e.g., mastery versus performance). In addition, we will examine what that framework suggests with regard to more traditional selfgoals and coping strategies, such as self-enhancement versus realism; or active coping versus withdrawal.

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BASIC MODEL OF EVALUATIVE ORGANIZATION

may influence global feelings about the self and represent self-relevant motivations (cf. Showers, 1995).

This model of self-structure was developed to understand how individuals process and organize positive and negative beliefs about the self (Showers, 1992a, 1995). The so-called basic model of evaluative organization considers the association between self-structure and mood or selfesteem. In particular, the model identifies two alternative approaches to organizing self-knowledge, referred to as “compartmentalized” or “integrative.” Numerous empirical studies have documented the association between an integrative or compartmentalized style of self-organization and the individual’s mood or self-esteem (Showers, 1992b; Showers & Kevlyn, 1999; Showers & Ryff, 1996). Extensions of the model consider the dynamics of selfstructure (i.e., how and when an individual’s self-structure might change) and the implications for the stability of self-esteem (Showers, 2000; Zeigler-Hill & Showers, 2007). In addition, this model has been tested in a variety of special populations (college students with eating disorders (McMahon, Showers, Reider, Abramson, & Hogan, 2003); college students who had experienced childhood maltreatment (Showers, Zeigler-Hill, & Limke, 2006); and counseling clients (Showers, Limke, & Zeigler-Hill, 2004) to help understand their unique self processes. The general compartmentalization model has also been extended beyond the case of self-structure to the case of how people organize knowledge about someone else (e.g., a parent or a romantic partner), linking the individual’s parent or partner structure to their global attitudes toward that person and the quality of their relationship (Showers & Kevlyn, 1999; Showers & Zeigler-Hill, 2004).

COMPARTMENTALIZATION AND INTEGRATION

ASSUMPTIONS A fundamental assumption of the compartmentalization model of evaluative self-organization is the belief that the self is multifaceted and consists of multiple selves or personae (Cantor & Kihlstrom, 1987; Markus & Wurf, 1987). The self-concept is viewed as an enormous repertoire of self-relevant information, including both episodic and semantic knowledge. This knowledge is organized into categories (or some kind of network structure), which represent a person’s multiple selves. In any behavioral context, one or more of these selves is activated, creating a working self-concept. This working self-concept consists of subsets of self-knowledge associated with the activated selves. The model of evaluative self-organization is an information processing model that suggests how the organization of positive and negative self-beliefs across multiple self-aspects

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The terms compartmentalization and integration refer to the evaluative structure of a person’s multiple selves (or selfaspect categories). In individuals with compartmentalized self-structures, the specific attributes of their multiple selves tend to be either purely positive or purely negative—that is, they likely have both positive and negative attributes in their self-concept, but they are associated with distinct self-aspects (e.g., “me as an honors student”: intelligent, hardworking, curious; “me before exams”: weary, disorganized, tense). In individuals with evaluatively integrative self-structures, a similar set of positive and negative attributes may be endorsed, but the attributes within each self-aspect category tend to be mixed (e.g., “me in drama class”: creative, involved, disorganized, lazy). According to the model, these evaluative structures may affect individuals’ global feelings about the self. For example, if a compartmentalized individual most often experiences the Honors student self (which is purely positive), then that individual should feel quite good. However, when the exam self is activated, the individual will feel quite bad. In contrast, the integrative individual who typically experiences a mixture of positive and negative attributes regardless of which multiple self is activated should have less extreme and perhaps more stable feelings about the self. Note that in the case of the compartmentalized self, overall feelings depend on whether the positive selfaspects or the negative self-aspects are most important or salient. These individuals can be identified as positively compartmentalized or negatively compartmentalized to distinguish them. Similarly, integrative individuals may have a self that is predominantly positive or negative, and so they too may be identified as positive integrative or negative integrative. However, the two integrative types should be more similar in their overall self-evaluations than the two compartmentalized types, because integrative self-aspect categories contain a mixture of positive and negative attributes. Note also that although we have labeled compartmentalized and integrative structures in a discrete fashion, in fact this feature of self-structure is measured on a continuum from perfectly compartmentalized (no self-aspect categories with attributes of mixed valence) to perfectly integrative (equal proportions of positive and negative attributes across all self-aspect categories) (cf. Showers, 1992a).

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Thus, the model of evaluative self-organization predicts an association between the self-structure and a person’s mood or self-esteem that can be summarized as follows. For individuals with largely positive self-concepts (i.e., when positive attributes or self-aspects are important or salient), positive compartmentalization should be associated with more positive mood and higher selfesteem than positive integration. This is because the compartmentalized structure helps to isolate negative self-beliefs, minimizing their likelihood of activation. However, for individuals with relatively negative selfconcepts (i.e., when negative attributes or self-aspects are important or salient), negative integration should be associated with less negative mood and higher self-esteem than negative compartmentalization. This is because integrative organization minimizes the impact of negative self-beliefs that likely could not be avoided. These associations between type of self-structure and current mood or self-esteem have been documented in multiple correlational studies (Showers, 1992a,b; Showers, Abramson, & Hogan, 1998; Showers & Kling, 1996; Showers & Ryff, 1996).

METHODOLOGY Most empirical studies based on the model of evaluative organization have employed a card-sorting task to assess self-concept structure (Showers, 1992a). In this task, participants are given 40 cards that each contains a potentially self-descriptive attribute (20 positive and 20 negative attributes). This task is similar to one used by Linville (1987) to assess self-complexity, although Linville’s version uses 33 cards, the majority of which contain positive attributes. Participants are asked to think of the different aspects of the self and sort the cards into groups such that each group describes a different part of the self. Participants are allowed flexibility to choose the number of self-aspect groups as well as the number and valence of adjectives they include in each group. Once participants have completed this section of the task, they are asked to rate the positivity, negativity, and importance of each group. This task provides three measures that are used to examine self-structure. The first of these measures is the phi coefficient, which is based on a chi-square statistic (Cramer’s ν; Cramer, 1945/1974). Phi provides an index of compartmentalization by contrasting the proportion of positive and negative attributes in each of the groups with that which would be expected based on chance (i.e., equal proportions of negative attributes across all groups). The phi coefficient is a continuous measure of

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compartmentalization, ranging from 0 (perfect integration) to 1 (perfect compartmentalization). A score of 0 means that equal proportions of negative attributes appear in all groups, whereas a score of 1 means that the positive and negative adjectives are completely segregated into different self-aspect groups. Table 31.1 presents sample integrative and compartmentalized self-descriptive card sorts generated by actual research participants, and their calculated phi values. The second measure is an index of differential importance (DI) (Pelham & Swann, 1989). Although based on theory by Pelham and Swann, the card sort measure of DI does not employ their Self Attributes Questionnaire. Instead, this index is computed by correlating importance ratings and the positivity–negativity ratings across an individual’s self-aspect groups (cf. Showers, 1992a). A positive value of DI indicates that a participant perceives her relatively positive groups to be more important than her relatively negative groups, whereas negative values indicate that negative groups are perceived to be more important than positive groups. A third measure is negativity (neg), the proportion of negative attributes used in an individual’s card sort that are negative. The measures of DI and neg are used together to distinguish positively compartmentalized from negatively compartmentalized card sorts, and positively integrative from negatively integrative card sorts (Showers & Kevlyn, 1999). In addition to the card-sorting task, several other tasks have been used to assess evaluative organization. One alternative measure of compartmentalization is a listing task (Showers, 1992b). In this task, participants generate a list of attributes to describe themselves in a specific domain (e.g., academic situations; social situations), with instructions to list the attributes in the order in which they come to mind. The order of positive and negative attributes listed is then analyzed by calculating the extent of clustering of similarly valenced attributes (i.e., the tendency for positive attributes to be listed together and for negative attributes to be listed together). An evaluatively clustered list in which positive adjectives are followed by other positive traits and negative adjectives are followed by other negatives is considered to be compartmentalized. A list in which positive and negative adjectives are intermixed together is considered integrative. Therefore, this task should reflect the tendency to compartmentalize or integrate positive and negative attributes on recall or, possibly, the evaluative structure of self-knowledge stored in memory. The paragraph task (McMahon et al., 2003; Showers, 1992b) can be conceptualized as a measure of integrative ability or potential. In this task, participants identify an

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Communicative Organized Interested Outgoing Hardworking Happy Friendly

Happy Friendly Optimistic

Organized Giving Happy –Irritable Optimistic

Needed

Hardworking –Tense

–Lazy Mature –Irritable Organized Intelligent Interested

Successful

Student

Hardworking

Successful Capable Independent Organized Interested

Me in Class

Interested Outgoing Energetic Happy Friendly

Fun and Entertaining

Successful Giving Confident Comfortable Lovable

Me and My Sorority

Organized Confident –Irritable

–Hopeless

African American –Irritable –Immature –Insecure –Inferior Organized –Tense

Comfortable

Intimate Relationship

Panel B: Integrative Organization

Interested Outgoing Hardworking Happy Friendly Optimistic

Successful Confident Comfortable Independent Fun and Entertaining

Me in Norman, OK

–Not the “real me”

–Uncomfortable –Insecure –Irritable –Isolated Organized Friendly

Giving

Friendship

–Weary –Inferior –Tense

Me with People I do not Know

Organized –Weary

Independent

Dreams (as in Goals)

–Disorganized –Tense

–Hopeless –Not the “real me” –Uncomfortable –Sad and blue –Irritable

Outgoing Hardworking –Tense

–Disagreeing –Irritable Capable Confident Organized Intelligent

Successful

Perfectionist

Me When I am Stressed

Note:

Negative attributes are identified by a minus sign. Panel A: compartmentalization = 1.00; differential importance = .80; and proportion of negative attributes = .17. Panel B: compartmentalization = .32; differential importance = .65; and proportion of negative attributes = .40.

Source: From “Self-structure and self-esteem stability: The hidden vulnerability of compartmentalization,” by V. Zeigler-Hill and C.J. Showers, 2007, Personality and Social Psychology Bulletin, 33, p. 143.

Energetic

–Irritable –Disagreeing –Self-centered Communicative Lovable Fun and Entertaining

Organized

Religion

Successful Capable Confident Comfortable Needed

Giving Confident Comfortable Lovable Outgoing

Family

Me at Work

Me at Home

Panel A: Compartmentalized Organization

TABLE 31.1 Examples of Actual Card Sorts Illustrating Compartmentalization and Integration

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extremely negative attribute that describes them and write about how that attribute relates to other aspects of the self, as well as the consequences it has for them. The paragraph or individual sentences are then coded for the presence of integrative thinking (e.g., I am shy, but I am a loyal friend). Individuals that tend to integrate negative information are linking their negative attributes to other more positive features of the self, which should help to minimize the impact of negative self-beliefs. Finally, a variation on an affective priming task is currently being tested as a measure of underlying integrative processes or potential (Boyce & Showers, 2007). In this reaction time task, participants are shown a potentially self-relevant prime followed by a target word and asked to decide if the target is “good” or “bad.” Primes and targets are positive and negative self-descriptive adjectives. On the basis of the work of Fazio, Sanbonmatsu, Powell, and Kardes (1986), one would expect participants to have the quickest reaction times on trials for which prime and target share the same valence, due to the spreading activation of valence through memory. However, individuals who are able to integrate negative traits with positive traits may have relatively quicker reaction times on trials with incongruent valence—that is, trials on which the valence of the prime (e.g., negative) is different from the target valence (e.g., positive). However, this research is still exploratory (cf. Graham & Clark, 2006).

LONG-TERM OUTCOMES Data on current mood and self-esteem, however, do not present a complete picture of the associations between evaluative organization and psychological well-being. Although concurrent well-being data suggest advantages to positive compartmentalization and negative integration, some potential drawbacks of these organizational styles and strategies are revealed in longitudinal and diary studies, and also in studies of special populations. First, consider positively compartmentalized college students, whose concurrent mood and self-esteem are high (Showers, 1992a). Daily diary data reveal their vulnerability to changes in self-esteem, corresponding to everyday life events (Zeigler-Hill & Showers, 2007). Although compartmentalized individuals’ baseline level of self-esteem is high, their self-esteem is actually relatively unstable, fluctuating in response to positive and negative events reported each day. Presumably, negative events activate negative compartments of self, causing a substantial (but temporary) impact on self-esteem. In

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contrast, individuals with positively integrative structures show greater self-esteem stability, both in daily diary data and in response to social rejection in the laboratory. Second, negatively integrative individuals may experience a concurrent lift in their feelings, given the proportion of negative attributes they endorse, but longitudinal results suggest that over time, attempts to integrate important negative beliefs may wear themselves out. This is most apparent in a study of college students’ perceptions of their romantic partners (Showers & Zeigler-Hill, 2004). Although individuals with negatively integrative perceptions reported relatively positive feelings about their partner at the outset of the study (given the proportion of negative attributes they perceived), 1 year later they were especially likely to have ended the relationship. Hence, negative integration may help an individual make the best of a bad situation, but over time, that integrative perspective may be difficult to maintain and the relationship may ultimately fail. Perhaps positive integration (i.e., integration in the context of largely positive beliefs) is more likely to be associated with realism and resilience over the long-term. Consistent with the romantic partners study, a study of college students who reported childhood maltreatment suggested that integration of important negative attributes may reflect an ongoing struggle with important negative beliefs rather than successful resolution of those concerns (Showers, Zeigler-Hill, & Limke, 2006). In this study, college students indicated whether specific events associated with sexual or emotional maltreatment had occurred to them before age 15. Those who had experienced the most severe maltreatment (i.e., both sexual and emotional events) had relatively integrative selfstructures, presumably to help them cope with important negative self-beliefs. Those who had one type of maltreatment (especially sexual maltreatment, but not both) were relatively compartmentalized, presumably to help isolate any negative self-beliefs. Interestingly, the integrative structures of those with severe maltreatment were not associated with enhanced psychological wellbeing; well-being in the severely maltreated was consistently poor. However, for individuals with only one type of maltreatment (especially sexual maltreatment, but not both), integration was associated with more negative adjustment (i.e., borderline features, depression, and maladaptive defenses). We interpret this as showing that integration in this population reflects the ongoing struggle with negative self-beliefs. When a maltreated person can compartmentalize negative self-beliefs, then coping may be either more straightforward or more complete, and psychological well-being is good.

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LINKS BETWEEN SELF-ORGANIZATION AND SELF-MOTIVES Each type of self-organization (i.e., positive compartmentalization, positive integration, negative integration, and negative compartmentalization) can be understood in terms of underlying motives that may contribute to that self-structure or that may emerge when an individual with that structure experiences stressful life events. Characteristic ways of organizing self-knowledge may affect individuals’ responses to stress and their goals for effective coping. It may also affect their goals in settings in which performance will be evaluated. Here, we will consider each type of self-structure and outline the likely motivations and preferred types of goals consistent with that self-structure, emphasizing approach–avoidance motives and achievement goals, in conjunction with characteristic styles of coping for individuals with that selfstructure, as inferred from previous research.

POSITIVE COMPARTMENTALIZATION Because individuals with positively compartmentalized self-structures primarily access their positive compartments, negative attributes are characteristically avoided or ignored. One might infer that these individuals value self-enhancement over self-accuracy or realism. Consistent with this, individuals with positively compartmentalized selves report the most positive mood and highest self-esteem. However, these positive feelings may sometimes be unrealistic. Our study of romantic partners found that individuals with positively compartmentalized perceptions of their partners had more positive attitudes toward them at the outset of the study than individuals with positively integrative perceptions, but were more likely to break up over the course of 1 year (Showers & Zeigler-Hill, 2004). In addition, Zeigler-Hill and Showers (2007) found that individuals with positively compartmentalized selves had relatively unstable self-esteem and were especially sensitive to negative interpersonal events and social rejection. If individuals with positively compartmentalized selfstructures wish to avoid their negative attributes, it is likely that their motivations could be characterized as high in approach motivation and low in avoidance. Moreover, their characteristic achievement orientation could be characterized as performance-approach (cf. Elliot & Church, 1997). However, the gist of the literature on evaluative organization suggests that individuals for whom approach is the sole motivation may have hidden vulnerabilities if they cannot adopt a different

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motivational perspective in appropriate circumstances. In motivational terms, if the prospect of failure suddenly looms large, a person who is unfamiliar with the avoidance state may have difficulty harnessing their anxiety to direct effort toward avoiding feared outcomes.

INTEGRATION In contrast to individuals with positively compartmentalized selves who avoid or ignore negative attributes and experiences, integrative individuals preserve access to negative attributes, but cushion their impact on the self. This approach may be more realistic, since negative attributes are acknowledged rather than ignored. It also may require high effort or resources, because the individual may be preserving detailed self-thoughts (rather than assimilating concrete beliefs into a broader impression) and continually has to confront distressing negative self-beliefs. One advantage of this approach, however, may be that chronic access to at least some negative beliefs inoculates the individual against stress when it occurs. If people are accustomed to processing salient negative beliefs and linking them to other more positive attributes, they may be well-prepared to cope with salient negative beliefs when additional stressors arise. In other words, individuals with integrative self-structures may be more modest in their typical self-perceptions, but may show good resilience when extreme stressors occur (Showers & Zeigler-Hill, 2007). Individuals with positively integrative self-structures (i.e., integration within a basically positive self-concept) are likely to be the most realistic in their self-representations. (Most people have predominantly positive self-beliefs.) Moreover, the more positive self-beliefs one has, the easier it should be to make integrative associations between salient negative beliefs and positive attributes. Thus, these individuals are likely to be most resilient. Consistent with this, we expect that positively integrative individuals would show moderate levels of both approach and avoidance motivations. This should be an ideal motivational frame, since it affords the greatest flexibility (cf. Elliot, 2006). In terms of specific achievement goals, these individuals with their realistic perspective should prefer mastery goals. Their access to a mix of positive and negative self-beliefs gives them a realistic perspective on their current level of skill, while their approach motivation should help them set appropriate goals for self-improvement. Individuals with negatively integrative structures might best be characterized as good copers. They will have a relatively negative self-concept, which they are chronically trying to resolve. The risk for them is that the

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integration of many important negative attributes is so effortful that they wear themselves out. In many cases, negative integration may be temporary until the negative concerns are resolved or recompartmentalized. In other cases, the individual may become an expert at integration, able to think in this complex fashion with relative ease and minimal drain on cognitive resources. In some cases, the prevalence and importance of negative attributes may reflect subjective perceptions. Anxious individuals who are struggling to cope might be the prototype of negative integration. An individual who is anxious yet coping would seem to have high avoidance motivation with moderate levels of approach motivation (to spur the effort to cope). The dominant achievement goal would seem to be performance-avoidance, perhaps with performance-approach goals adopted in the service of avoidance. Thus, their goals may have a hierarchical structure, as proposed by Elliot and Thrash (2001). In their hierarchical model, Elliot and Thrash (2001) separate the different components that interact to produce an individual’s achievement motivation (cf. Elliot & Church, 1997). Specifically, their model includes a higher order construct (i.e., motive dispositions) and a midlevel construct (i.e., achievement goals). Motive dispositions describe relatively abstract motives that individuals have, including the need for achievement and the need to avoid failure, among others. These higher order motives are theorized to lead individuals to adopt more concrete achievement goals. The achievement goals then directly influence a person’s goal-related behavior. Elliot and Thrash (2001) argue that motive dispositions and achievement goals are independent constructs, a position that allows for a more flexible understanding of how general motives and specific goals can affect each other to lead to behavior. Thus, this model allows a person to have a dominant motive to avoid failure, but also to use concrete performance-approach goals to alleviate this fear of failure.

NEGATIVE COMPARTMENTALIZATION Negative compartmentalization is the alternative to negative integration. These individuals have relatively negative self-concepts, but may do little in the way of coping. They may seem overwhelmed by their negative attributes, and may be characterized by low-arousal anxiety or depression. One possibility is that negative compartmentalization represents a failed attempt to isolate or avoid one’s negative attributions via positive compartmentalization. Alternatively, negatively compartmentalized

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structures may afford stability even if they do not imply happiness. For example, in our study of romantic partners, individuals who had negatively compartmentalized perceptions of their partner showed low relationship satisfaction, but were relatively unlikely to break up (Showers & Zeigler-Hill, 2004). In other words, they appeared to have unhappy, but stable, relationships. These depressed, negatively compartmentalized individuals would likely reveal low approach and low avoidance motivation. Unlike anxious individuals who are vigilant to negative stimuli in order to avoid feared outcomes, depressed individuals are more likely simply to withdraw. In performance contexts, they should endorse neither mastery, performance-approach, nor performanceavoid goals.

DYNAMIC MODEL: CHANGE IN SELF-STRUCTURE To the extent that these four types of self-structure represent alternative strategies for managing positive and negative self-beliefs, it is reasonable to expect flexibility, that is the potential shift from one structure or strategy to another as circumstances and salient beliefs change. For example, we have suggested that healthy individuals may shift from a positively compartmentalized self-structure to the more effortful integrative style of thinking when negative attributes are salient. In a study of self-structure associated with body dissatisfaction and disordered eating in college-aged women, McMahon et al. (2003) found that participants who were relatively compartmentalized in their overall self-concept structure, but who switched to an integrative style of thinking about specific negative characteristics, also reported the least negative mood. Thus, the most adaptive form of evaluative self-organization may be one that is flexible, shifting from relative compartmentalization to relative integration depending on the salience of positive and negative attributes and one’s goals for accuracy, optimism, or resilience. Another study that examined stability and change in self-structure over the course of almost 2 years (Showers et al., 1998) obtained results that contradicted the hypothesis that individuals would shift toward a more integrative style of self-organization in times of stress. Instead, individuals who seemed to be coping well (low vulnerability to depression, but experiencing major stressful life events) were more compartmentalized when stress was high than when stress was low. We interpret this to mean that compartmentalization is more effective as a coping strategy than was previously imagined. Because of its ease and efficiency, self-organization by valence may be an effective

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strategy as long as compartmentalization is successfully maintained (i.e., as long as compartmentalization effectively isolates important negative attributes). Compartmentalization may be an especially useful strategy for college students, given the complexity of their lives. For instance, if college students tend to have multiple selves that are relatively independent and nonoverlapping, compartmentalization may be especially effective for them. Interestingly, some of the clearest evidence of shifts toward integration emerged from our study of romantic relationships (Showers & Zeigler-Hill, 2004), in which integration of partner-structure increased over the course of a year for individuals who were experiencing high relationship conflict or who described their partner in relatively negative terms (but not both). Moreover, increases in integration were associated with better relationship outcomes (i.e., ongoing status) only if the couple experienced low conflict. Thus, as suggested earlier, increased integration may reflect the effort of an ongoing struggle with negative beliefs that is not always successful in the long run. Finally, preliminary results of a psychological treatment study suggest that individuals who seek psychological treatment experience shifts toward increased evaluative integration of the self over a 2- to 3-month period. A more detailed discussion of a dynamic model of evaluative self-organization appears in Showers (2002). The present approach–avoidance systems perspective suggests the intriguing possibility that a physiological shift from approach (BAS) to avoidance (BIS) systems may accompany or even underlie or precede change in evaluative self-structure, as described above. The approach– avoidance framework inherently allows for flexibility without implying that evaluative structures need to be stable and unchanging. Moreover, the approach–avoidance goals framework emphasizes the contribution of the individual’s perspective and goal choice in accomplishing these structural shifts.

ADDITIONAL FEATURES OF SELF-STRUCTURE AND LINKS TO SELF-MOTIVES As should be clear from the previous sections, one advantage of the model of evaluative organization is its ability to make very explicit predictions about motivations. In particular, the compartmentalization model is an information processing model that specifies the cognitive processes that take place when individuals are confronted with positive or negative information or experience, as well as the long-term outcomes that these processes would predict. As outlined above, evaluative organization specifies four

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specific groups of individuals whose achievement goals, approach–avoidance motives, and likelihood of resilience can be differentiated and explained. However, evaluative self-organization is not the only feature of self-structure that can be linked to resilience and the ability to cope with stress. Whereas the content of the self-concept may represent a reasonably accurate reflection of both positive and negative attributes and experiences in individuals’ lives, structural features of the self may reflect an individual’s goals and motives; the self-structure, rather than the self-concept content, may be the source of the individual’s ability to cope (Showers et al., 1998). A variety of features of self-structure influence the attention, salience, or importance an individual gives positive or negative aspects of the self. In their most adaptive forms, these features of self-structure may enable individuals to approach negativity without aversion.

MULTIPLE SELVES PERSPECTIVES Self-complexity is one dimension of self-structure that may allow individuals to approach negative information or experience without aversion. Self-complexity has two components (1) the number of aspects a person uses to describe the self, and (2) the distinctiveness of the aspects (Linville, 1987; Rafaeli-Mor & Steinberg, 2002). (One distinction between evaluative organization and selfcomplexity is that self-complexity does not take the valence of traits into account, whereas evaluative organization does assess the valence of the self-concept). Specifically, an individual’s multiple self-aspects are said to be distinctive if the attributes contained in one aspect of the self are different from, or independent of, those in other aspects of the self-concept. Therefore, a person’s level of self-complexity increases as the number and distinctiveness of her self-aspects increase. The many distinct self-aspects of individuals with high self-complexity should buffer them from negative outcomes under conditions of stress (Koch & Shepperd, 2004; Linville, 1987; see also Showers & Zeigler-Hill, 2003). Particularly, those with higher self-complexity are less affected by negative events because this negative information is restricted to a small amount of selfknowledge, while other independent self-aspects are left unaffected. For example, a person with high complexity may have multiple self-aspects that describe her as a mother, wife, teacher, researcher, and writer, while a person with low complexity might only have two selfaspects describing her family life and work life. If the first individual receives negative teaching evaluations, this should only affect her “teaching” aspect, while her

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other self-aspects are unaffected. However, if the second person receives the same information this would relate to everything that falls within her “work” aspect, and thus affect her more broadly. Due to the buffering effect of complexity, individuals with higher self-complexity should react less strongly to stressors than those with low self-complexity. Importantly, these individuals may show lower avoidance motivation because they are able to approach negativity without an extreme aversive reaction. Individuals with high selfcomplexity may also exhibit moderate approach motives because their resilience should provide them with a greater opportunity to focus attention on and approach positive information instead of exerting their energy toward circumventing negative information. A second structural feature of the self-concept that cushions the effect of negative attributes and experience is differential importance. The model of differential importance (DI) and differential certainty attempts to explain differences in self-esteem by taking into account both the certainty and importance of positive and negative self-views (Pelham & Swann, 1989). As described above, individuals have high DI if they perceive their relatively positive aspects of the self to be more important than their relatively negative self-aspects. Pelham and Swann (1989) found that, for individuals who had many negative self-views, self-esteem was greater when they placed greater importance on their positive self-views, as compared to their negative selfviews (i.e., when they showed high differential importance). Thus, even though their self-concepts contained a great deal of negative information, these individuals still exhibited relatively high levels of self-esteem because they were able to put more emphasis on their positive attributes. This ability to minimize negative information should help those with high DI to be resilient to incoming negative information. When forced to deal with this information, these individuals have the ability to minimize its importance and shift attention and importance to the positive aspects that they have. Because of this ability, we predict that individuals with high DI should have lower avoidance motivation than those with low DI (those placing more importance on negative aspects than positive aspects). Individuals with high DI should be able to confront negative information without extreme emotional reactions or unpleasantness. Furthermore, the emphasis that they place on positive attributes should allow them to develop moderate levels of approach motivations by shifting their attention and effort to seeking additional positive information.

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SELF-CONCEPT CLARITY, SELF-STABILITY, AND CONTINGENCIES OF SELF-WORTH In addition to focusing on the multiple selves that an individual can have, researchers have begun to examine the fragility, or insecurity, of the self-concept as it relates to self-structure (Crocker & Wolfe, 2001; Kernis, Paradise, Whitaker, Wheatman, & Goldman, 2000). According to these perspectives, a self-concept is fragile if the perception of self-worth is uncertain and easily changed by external information or events. Some features of the self-concept associated with self-fragility include self-concept clarity, self-esteem instability, and contingencies of self-worth. These models share the common characteristic of measuring variability in self-descriptions and self-worth. However, each model also has its own distinct formulation and predictions. Self-concept clarity refers to having a self-concept that is clearly and confidently defined, temporally stable, and internally consistent (Campbell, 1990; Campbell et al., 1996). Thus, an individual is said to have high self-concept clarity if he knows which traits describe him, if these descriptions stay constant through time, and if these descriptions relate to specific behaviors. In contrast, those with low self-concept clarity are unsure about how to describe themselves and tend to change their self-views more easily. Empirical studies have found low self-clarity to be correlated with low selfesteem, negative affect, high neuroticism, and high levels of depression (Campbell et al.). Additionally, low selfconcept clarity has been correlated with unstable selfesteem (Kernis et al., 2000). Self-esteem instability describes a tendency for individuals to display short-term fluctuations in global self-esteem (Kernis & Goldman, 2003). These fluctuations can reflect responses to daily positive and negative events and can lead to more depressive symptoms and lower levels of self-determination. Individuals with low self-concept clarity and selfesteem instability lack definite beliefs about the traits that describe them. This lack of certain self-knowledge allows their moods and self-esteem to be greatly influenced by outside events. Although the focus on fragility has framed this self-uncertainty as a negative outcome, it is also possible to view uncertainty or instability as a source of flexibility or resilience. If we imagine a person with low self-esteem and either low self-clarity or unstable self-esteem, we can consider whether self-uncertainty might actually offer relief from an otherwise negative self-concept. These individuals may prefer self-knowledge that is uncertain but sometimes (even if only rarely) positive, over confirmed, stable negative self-beliefs. Although there may often be costs to uncertainty, the glimmers of

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hope it provides may sometimes motivate resilience in the face of threat (cf. Pelham, 1991). A study by Hannover (2002) makes a relevant argument for the usefulness of low self-concept clarity for individuals with an interdependent self-construal. For those with interdependent construals, it is particularly important to achieve group harmony and have positive relationships within different social groups. Hannover theorizes that having low self-concept clarity would be more adaptive for individuals with interdependent construals because it would give them flexibility to adjust to various social contexts. In other words, because individuals with low self-concept clarity lack a strong sense of who they are, they may actually interact more effectively with others by changing to fit the social environment. Thus, in some circumstances, having a flexible sense of self can lead to better outcomes and make a person more resilient to negativity. On the basis of the fact that low self-concept clarity and self-esteem instability have been associated with relatively negative self-concepts, we do not expect these individuals to be high in approach motivation. However, if these characteristics afford resilience, either in terms of flexibility to adjust to different social contexts or by providing glimmers of hope in the face of an otherwise negative self-concept, avoidance motivation may be lower than for individuals with clear and stable negative selfconcepts. The fact that uncertain individuals have negative self-beliefs combined with glimmers of hope may allow them to approach negative self-knowledge or experience without aversion. Thus, we would predict that these fragile individuals may show moderate levels of approach motivation and relatively low levels of avoidance motivation. This motivational structure affords them the flexibility to change their behavior as needed in response to an environment that is often adverse. Our discussion of self-concept clarity and self-esteem instability has characterized these features of selfstructure as representing strategies that a person can use when dealing with negative feedback (i.e., using one’s uncertainty of self-knowledge to defend against potentially damaging negative information). To the extent that contingencies of self-worth (CSW) also create low selfclarity or unstable self-esteem, similar outcomes may be expected. Specifically, a person is said to have contingent self-worth if he places particular importance on a certain domain of the self and stakes his self-worth on success in this area (Crocker & Wolfe, 2001). Crocker and Wolfe (2001) describe seven domains of the self for which people may construct contingencies: approval, appearance, God’s love, family support, academic competency,

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competition, and virtue. Accordingly, if college students place importance on the area of academic competency (i.e., if their self-worth is contingent on academic success) then their self-esteem may increase when they succeed and decrease when they fail in this domain. Literature on CSW has focused on the harsh implications of failure in a contingent domain. Crocker, Brook, Niiya, and Villacorta (2006) explain that, because declines in self-esteem following failure can be highly painful, contingent self-esteem can create a prevailing motivation to protect and maintain the self. This goal of protecting the self should produce vigilance toward negativity and, hence, an avoidance perspective. More specifically, in an achievement domain, this contingency might translate into a tendency to adopt performanceavoidance goals in an attempt to ensure that failure does not occur. However, it seems plausible that CSW in a domain can sometimes be accompanied by high self-efficacy, such that contingent individuals generally believe that they can succeed in that domain. More specifically, if individuals are able to attain success in their contingent domains this should allow them to exhibit high stable self-esteem (Crocker & Wolfe, 2001). In these cases, we would predict that individuals could reveal an approach motivation due to the fact that they strongly believe that they can succeed in a domain and increase their self-esteem. In a related vein, Niiya, Crocker, and Bartmess (2004) showed that the negative effects of failure for those with academic CSW can be attenuated by priming them with an incremental theory of intelligence. In this work, individuals primed to believe that they could increase their intelligence in the future showed a less severe drop in selfesteem after an academic failure. In other words, activation of incremental self-theories may mimic the hypothesized effects of high self-efficacy, and link CSW to approach rather than avoidance motives. Thus, although CSW in its prototypical form is likely associated with strong avoidance motives and performance-avoid goals, it may sometimes be associated with using self-uncertainty to one’s advantage. Moreover, if contingencies are likely to be satisfied, CSW may even be associated with approach goals, despite the inherent fragility of this self-structure.

SELF-STRATEGIES: SELF-ENHANCEMENT VERSUS SELF-VERIFICATION Most researchers would agree that people are motivated to understand themselves and the ways in which others see them (Fiske, 2004; Taylor, 1998). There are a number

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of different self-strategies that people can use to do this, depending on the type of information that is the most appealing to them (Tesser, Crepaz, Beach, Cornell, & Collins, 2000). For instance, one of the most wellresearched strategies is the self-enhancement motive (Sedikides, 1993; Kwan, John, Kenny, Bond, & Robins, 2004). Individuals use this strategy because they are interested in obtaining positive or favorable information about themselves. This could also be called an enhancement bias because individuals only receive a limited amount of information about themselves and are motivated to avoid learning about any information that could reflect negatively on them. Sedikides’s data suggest that self-enhancement is one of the most dominant strategies used to evaluate one’s self. Nonetheless, there are alternative strategies that can actually lead individuals to approach negative information. Self-verification is a strategy for understanding the self in which people are motivated to have their own selfbeliefs validated by others (Swann & Read, 1981). They seek consistency between the attributes that they believe describe them and the attributes that other people use to describe them. Importantly, these individuals may be motivated to verify negative beliefs that they hold about themselves, as well as positive beliefs. Thus, if a person believes that he is an incompetent tennis player, he will seek out others to verify this belief. Individuals guided by this motive may seek verification of negative self-beliefs from others because they would rather have others see them truthfully than have them set high expectations that they cannot meet. Knowing that others understand and accept their weaknesses alleviates the stress of wondering whether others will feel disappointed with them in the future (Swann & Read, 1981; Swann, Stein-Seroussi, & Giesler, 1992). Presumably, a self-verification motive could lead individuals to approach self-consistent information (both positive and negative) without aversion, if this information offers the benefit of validating their own beliefs about the self. To the extent that most individuals have a substantial number of both positive and negative beliefs in their repertoire of self-knowledge (cf. Schwartz & Garamoni, 1986), we would expect them to show moderate to high levels of approach motivation when positive attributes are salient and (because of the benefits of self-verification) only moderate levels of avoidance motivation with regard to salient negative attributes. Moreover, like the negatively integrative individuals, self-verifying individuals with important negative self-beliefs may adopt a mixture of approach–avoid tactics in the service of higher-level avoidance goals (e.g., I want my romantic partner to

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verify my current negative self-views in order to prevent future disaster in my relationship). Other features of self-knowledge, self-structure, and self-strategies are not addressed in detail here because they have their own chapters in the present volume. For example, self-presentation phenomena comprise strategies of portraying the self so that one relates well to others in a social group (Baumeister, 1982). Selfpresentation could reflect higher levels of avoidance motivation if individuals who self-present are unduly anxious about being accepted by others, but other forms of self-presentation may be associated with resilience. Research on self-discrepancies has already been related to promotion or prevention focus and achievement goals (Higgins, 1997). Self-discrepancies emphasize the contrast between a person’s perception of the actual selfconcept and both the self they wish they had (ideal) and the self they should have (ought). These different discrepancies can lead individuals to exhibit different achievement goals and adopt a focus on promotion versus prevention goals. Finally, Friedman and Förster (2000) have developed approach–avoidance goal manipulations using specific behaviors. These perspectives on self-knowledge and self-strategies offer additional understanding of potential resilience to negativity within an approach–avoidance framework.

CONCLUSION To summarize, this chapter has reviewed literature on evaluative organization of the self, as well as other features of self-structure, linking each feature to approach and avoidance motivation and (where appropriate) performance versus mastery goals. Specifically, we propose that the resilience of individuals who construct positively integrative structures for their self-beliefs may correspond to moderate levels of both approach and avoid motives (i.e., motivational flexibility) and a preference for mastery goals. The predominance of avoidance motives in individuals with negatively integrative self-structures may serve them well in the short-term, but may often carry long-term costs, consistent with the view that this perspective functions best as a short-term strategy. In contrast, individuals who tend toward positively compartmentalized self-structures may prefer a performance-approach framework that is optimal in benign circumstances, but which may be unrealistically positive in times of stress, especially if the self-structure and concomitant motives are rigid and inflexible. Finally, individuals with negatively compartmentalized self-structures should simply be low in both approach and avoidance motivations, given a perspective

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that allows the illusion of some positive potential with low motivation for any substantive change. Additionally, we discussed other features of self-structure that may characterize resilient individuals who can approach negative self-knowledge or experience without aversion. In addition to the positively integrative selfstructure that characterizes resilient individuals according to the model of evaluative self-organization, other features of self-structure associated with resilience may include high self-complexity; high differential importance (especially for individuals with a relatively negative selfconcept); some instances of low self-concept clarity, self-esteem instability, or even contingent self-worth; and a preference for self-verification strategies. We propose that these structural features and strategies associated with good coping may stem from moderate levels of approach motives and low to moderate avoidance motives, affording an optimal level of flexibility. This flexibility allows resilient individuals to adjust their motives and mastery/performance goals to fit the current environment. Although much of the literature tends to treat approach and avoidance motives as mutually exclusive (although see Elliot, 2006 for an exception), an interest in resilience highlights the need to examine the flexibility of individuals who display moderate levels of both approach and avoidance goals, the ability of these individuals to adapt to a range of motivational contexts, and the ways in which motivational flexibility can affect behavioral outcomes.

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Self-Access Functional Architecture of 32 The Approach and Avoidance Motivation Julius Kuhl and Sander L. Koole CONTENTS A Hierarchical Model of Personality Functioning ................................................................................ 536 Level 1: Elementary Cognition......................................................................................................... 536 Level 2: Temperament ...................................................................................................................... 538 Level 3: Affect .................................................................................................................................. 538 Level 4: Progression Versus Regression ........................................................................................... 538 Level 5: Motives ............................................................................................................................... 538 Level 6: Complex Cognition ............................................................................................................. 539 Level 7: Agency ................................................................................................................................ 539 Interactions Between Personality Systems............................................................................................ 539 Approach and Avoidance Across Seven Levels of Personality Functioning ........................................ 541 Approach and Avoidance in Elementary Personality Functioning .......................................................542 Approach and Avoidance in Elementary Cognition (Level 1) .........................................................542 Approach and Avoidance in Temperament (Level 2) .......................................................................543 Approach and Avoidance in Affect (Level 3)...................................................................................543 Approach and Avoidance in Higher Personality Functioning ..............................................................544 Approach and Avoidance in Motives (Level 5) ................................................................................544 Approach and Avoidance in High-Level Cognition and Agency (Levels 6 and 7) ..........................545 Vertical Interactions Within Approach and Avoidance Systems: Affect Modulations and Progression Versus Regression ......................................................................545 Self-Confrontational Coping .................................................................................................................547 Summary, Conclusion, and Future Directions ......................................................................................548 References .............................................................................................................................................550

When a young man marries a woman just because he cannot bear his loneliness any longer, we would not be surprised when this marriage does not bring him much happiness. Simply marrying somebody to avoid being alone does not guarantee marital happiness, common interests, personal well-being, or mutual understanding and growth, to name just a few approach goals neglected by the young man in our example. Avoidance goals, even when they are perfectly accomplished, terminate or

prevent aversive states, but they do not necessarily promote the satisfaction of needs (Elliot, chapter 1, this volume; Higgins, 1998). Instead, avoidance motivation is associated with reduced subjective well-being and impaired subjective competence (Elliot & Sheldon, 1997) and increased physical symptoms (Elliot & Sheldon, 1998). The negative consequences of avoidance motivation are intuitively compelling. But what might be the psychological mechanisms that underlie the relationship between 535

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avoidance motivation and its negative consequences? An intuitive understanding of its negative consequences does not really tell us why avoidance motivation should have those detrimental effects. In the present chapter, we therefore aim to develop a more scientifically grounded understanding of the psychology of approach and avoidance motivation. In particular, we examine the functional architecture that underlies approach and avoidance motivation. Because we assume that approach versus avoidance is a fundamental distinction to personality functioning, we highlight the connections between approach and avoidance motivation and basic personality systems. Our functional approach focuses on the psychological processes that underlie the two most fundamental achievements of personality functioning (Kuhl, 2000a, 2000b, 2001; Kuhl & Koole, 2004): The enactment of difficult intentions (volitional efficiency) and the repeated integration of new (self-alien) experiences into an ever-growing network of personal wisdom (self-development). The plan of this chapter is threefold. First, we discuss a hierarchical model of personality functioning. Second, we give a brief summary of PSI theory. In the third part, we describe in more detail how the distinction between approach and avoidance motivation is integrated by the theory of personality system interactions across different levels of personality functioning. We devote special attention to self-regulation as the highest level of personality functioning. We conclude that approach and avoidance are not, as they may appear at first glance, confined to simple forms of motivation (e.g., related to fight or flight). As we will show, approach and avoidance systems may regulate even highly complex motivational phenomena such as self-determination and free will.

with it (Rogers). Given this wide array of different personality constructs, it is a formidable challenge to arrive at an integrative theory of personality functioning. PSI theory (Kuhl, 2000a, 2001) takes a first step toward an integrative theory of personality, by proposing that leading theories of personality each focus on a different level of personality functioning. More specifically, PSI theory proposes seven levels of personality functioning, which are displayed in Table 32.1. The lowest, most basic level of personality functioning is formed by the smallest unit of motor and perceptual systems that can still be controlled by motivational or volitional processes. The highest level of personality functioning is formed by systems that support intentional action and self-determination. The lower levels of personality functioning are assumed to be both phylo- and ontogenetically older than the higher levels. Moreover, a steep gradient of increasing degrees of freedom in behavior control can be discerned across the seven levels of personality functioning, which highlights the compatibility of our taxonomy with hierarchical models of approach and avoidance motivation (Cacioppo & Berntson, 1999; Carver & Scheier, 1998; Elliot, 1997). The “gradient of freedom” starts with very few degrees of freedom at the lowest level, where behavior is determined by S-R associations that permit only one dominant response to a given stimulus. With each higher level, the degrees of freedom (or the number of possible responses to a given stimulus) increase. The highest degrees of freedom are associated with the participation of the integrated self in the guidance of decision making and action control. On this level, even goals are exchangeable as long as they are somehow compatible with a person’s needs, values, integrated social norms, and other self-aspects.

A HIERARCHICAL MODEL OF PERSONALITY FUNCTIONING

LEVEL 1: ELEMENTARY COGNITION

Over the past century or so, psychologists have developed quite a few different approaches to personality (for an overview, see Carver & Scheier, 2004). For example, whereas Skinner and Hull (and, with some elaborations, social learning theories) describe personality in terms of acquired habits, that is, response dispositions that are automatically triggered by stimuli associated with them, other theories place more emphasis on individual differences in arousal (Eysenck) or affect (Freud, Gray), and still others describe personality with higher-level constructs such as motives (Murray, Atkinson, McClelland), cognitive schemas or “constructs” (Kelly), or the need to develop an authentic self and bring behavior in accordance

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At the most basic level, PSI theory distinguishes between a system that supports the automatic control of behavior, intuitive behavior control (IBC), and a system that supports the perception of isolated objects, object recognition. The behavior that is governed by intuitive behavior control is strongly dependent on the presence of triggering stimuli. Prototypical examples of intuitive behavior control are S-R learning (Skinner, 1953), behavioral priming (Bargh, Chen, & Burrows, 1996), and the largely automatic control of behavior through specifying the exact time and place for performing an intended action (Gollwitzer, 1999). Examples of intuitive behavior control are small talk based on automatized routines of exchanging polite and culturally scripted words, the

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The Functional Architecture of Approach and Avoidance Motivation

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TABLE 32.1 Approach and Avoidance Components within Seven Levels of Personality Functioning, Related Theories of Personality (1), and Operationalizations (2) Level of Personality Approach-Related Level 1 (Low-level cognition) Habits Intuitive Behavior Control: IBC

Avoidance-Related

Theories (1) and Operationalizations (2) (1) Hull, Skinner, Witkin (2) Valence-independent enactment; behavioral priming (Bargh et al., 1996)

Objects Object Recognition: OR

Level 2 (Temperament) Motor activation Sensory arousal Opportunistic energization of motor or sensory networks

(1) Pavlov, Eysenck (2) Determinants of activation/arousal (EDA): motor activity, white noise (Lang,1995; Thayer,1978)

Level 3 (Affect) Positive and facilitating Negative and inhibiting Object conditioning of positive and negative valence

(1) Freud, Gray (2) Reward versus punishment (Gupta & Nagpal, 1978)

Level 4 (Progression versus regression) Top–down Bottom–up Degree of modulation of Levels 1–3 through Levels 5–7

(1) Freud (2) Elementary versus configurational conditioning (Schmajuk & Buhusi, 1997)

Level 5 (Instrumental versus experiential motives): Instrumental needs Experiential needs (achievement, power) (affiliation, self-growth) Motives as “intelligent needs” (networks of context-specific possible actions from autobiographical memory)

(1) Murray, Atkinson, McClelland (2) Motives (Atkinson, 1958); Motive-goal congruence (Brunstein, 2001; Baumann et al., 2005)

Level 6 (Knowing and feeling: high-level cognition) Analytical thinking (either–or) Holistic feeling (both–and) Independence of experience, affect, and need Dependence of experience, states affect, and need states

(1) Kelly, Jung (2) Summation priming (Beeman et al., 1994); Coherence judgments (Bowers et al., 1990)

Level 7 (Agency) Self-control Intention memory (IM)

(1) Rogers (Freud versus Jung) (2) Volition (Kuhl & Kazén, 1999); self-complexity (Linville, 1987; Showers & Kling, 1996); self-determination (Deci & Ryan, 2000)

Self-maintenance Extension memory (EM/Self)

intuitive exchange between mother and baby during face-to-face interaction, and a driver taking the wellknown route to his office. Object recognition is assigned to the same fundamental level of personality functioning. The primary function of object recognition is to recognize single objects independently of the context in which they appear. An “object” is defined here as a perceptual or semantic entity that can be labeled and recognized as separate from the context. For example, Witkin’s (1950) concept of field-independence can be related to the object recognition function. Examples of object recognition are recognizing a new car model on the freeway despite the fact that one has only seen this new model at an exhibition rather than on the road, or

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recognizing a single angry face among a crowd of faces with a different emotional expression (Öhman, Lundqvist, & Esteves, 2001). An example of a maladaptive use of object recognition would be a psychotherapist perceiving a patient as an exemplar of a particular clinical category rather than as a complex human being with an elaborate past and a rich life context that entails many propensities and resources beyond her particular symptoms.

LEVEL 2: TEMPERAMENT The second level of personality functioning is referred to as temperament, and controls the intensity or energization of behavior. Temperament is further divided into a

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sensory arousal and a motor activation component. For example, motor activation increases whenever a person has engaged in rigorous physical exercise, such as walking up and down a flight of stairs several times. Analogously, sensory arousal increases whenever a person has perceived a strong stimulus, such as a loud noise. Either type of temperament component intensifies processes across levels of personality. At a subjective level, it is often difficult to distinguish between arousal and affect (see Level 3), given that increases in affect often involve elevated levels of arousal. Nevertheless, psychophysiological (Lang, 1995) and even self-report (Thayer, 1978) methods for disentangling arousal and affect have been developed.

LEVEL 3: AFFECT The third level of personality functioning is affect. At this level, specific objects become linked to a specific affective valence. In agreement with other modern emotion theories (Cacioppo & Gardner, 1999), PSI theory distinguishes between positive and negative affect. The distinction between positive and negative affect is conceptually and empirically supported by various lines of research (Cacioppo & Berntson, 1999; Diener & Emmons, 1985; Higgins, 1987; Taylor, 1991; Watson, Wiese, Vaidya, & Tellegen, 1999). Positive affect is typically experienced as elated emotion, ranging from satisfaction to joy, whereas inhibited positive affect is typically experienced as dejected emotion, ranging from a “neutral” or aloof mood to listlessness, dejection, or even depression. Negative affect is typically experienced as agitated emotion, ranging from sadness to anxiety, whereas inhibited negative affect is typically experienced as peaceful emotion, ranging from calmness to deep relaxation. The third level corresponds to reward and punishment systems, and is therefore most directly linked to approach and avoidance motives. We return to this issue in the next section.

LEVEL 4: PROGRESSION VERSUS REGRESSION On the fourth level of personality functioning, a decision is made as to whether the three elementary levels (Levels 1–3), or the three higher levels of control (Levels 4–7) govern experience and behavior. When the lower levels acquire the predominant control over the person’s behavior, we speak of regression. When the higher levels acquire the predominant control over the person’s behavior, we speak of progression. The Freudian concept of regression (Freud, 1938/1989) can be related to this level

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because it describes impaired high-level control of affective responses and habitual behavior (i.e., Levels 1–3). Today, regression of experience and behavior to lowerlevel functioning (i.e., to uncontrollable habits, arousal, impulsivity, and affect-driven behavior) can be related to the stress-dependent inhibition of the hippocampus that normally mediates top–down control of emotional experience and motor behavior at lower levels through higher-order systems (Jacobs & Nadel, 1985; Sapolsky, 1992; Schmajuk & Buhusi, 1997). When the hippocampus is inhibited by excessive amounts of the stress hormone cortisol, task-oriented goals or any volitional effort cannot inhibit impulsive behavior elicited by some stimulus in the environment (e.g., when in front of a lion’s cage in the zoo, fear of wild animals cannot be inhibited by the high-level knowledge that the lion cannot leave its cage) nor can unwanted affective responses be suppressed (e.g., fear of failure although it interferes with one’s effort to concentrate on an exam): Experience and behavior regresses to and is governed by elementary response dispositions that do not obey task-motivation, higher insights, or volitional control intentions. This functional account of regression and progression can be related to the concept of threat and challenge, respectively (Blascovich & Tomaka, 1996). Whereas challenge is marked by activation of the sympatheticadrenal-medullary (SAM) axis which enhances left ventricular contractility and cardiac output, but decreases peripheral vascular resistance, threat is marked by not only activation of the SAM axis, but also by activation of the pituitary-adrenal-cortical (PAC) axis which is associated with inhibition of hippocampal activity and its dampening effects on the PAC-axis (including an inhibition of the challenge-related increase of both cardiac output and peripheral resistance).

LEVEL 5: MOTIVES At the fifth level of personality functioning, behavior is governed by motives. PSI theory’s conception of motives draws on the classic work on implicit motives by McClelland, Heckhausen, and associates (Heckhausen, 1991; McClelland, Koestner, & Weinberger, 1989). Motives are conceived as “intelligent needs.” This means that motives are assumed to be grounded in the person’s basic needs, which specify the essential nutriments that the person needs for his or her well-being. Motives connect these needs with networks of context-specific possible actions that are represented in autobiographical memory. As such, motives allow individuals to pursue their basic needs in an intelligent, context-sensitive

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manner. PSI theory distinguishes between two basic classes of motives. Instrumental motives involve a means-end perspective, that is, the enactment of these motives is based on clear-cut intentions and instrumental activities that are considered means toward accomplishing intended goals. Achievement and power motives are among the most important instrumental motives. Experiential motives are characterized by more holistic enactment that is based on integrative competence rather than dichotomies between means and ends or exclusive alternatives (such as winners or losers, success or failure, own or others’ needs). The most important examples of experiential motives are affiliation and self-growth motives.

LEVEL 6: COMPLEX COGNITION At the sixth level of personality functioning, behavior is guided by complex cognition. What makes cognition at this level complex is that it consists of configurations of elements rather than separate elements. Moreover, complex cognition is abstract and removed from the person’s immediate perceptual experience. PSI theory distinguishes two forms of complex cognition. Analytic thinking consists of logical-symbolic thought that operates in a sequential, step-by-step mode and typically takes the form of “if … then” statements. Holistic feeling consists of associative thought that considers many different elements simultaneously in computing an integrative representation. Holistic feeling is closely connected with emotion and somatic systems. It can be distinguished from intuitive behavior control (elementary intuition) because the operation of holistic feeling can be partly expressed in explicit language, whereas intuitive behavior control is completely implicit.

LEVEL 7: AGENCY The seventh and highest level of personality functioning is the level of agency. At this level, the other levels of personality functioning are co-ordinated in a manner that enables the person to control his or her thoughts, feelings, and behavior in a top–down manner. PSI theory distinguishes between two agent systems, intention memory and extension memory. Intention memory is a system that maintains symbolic representations of intentions activated in working memory, while at the same time inhibiting intuitive behavior control (to prevent premature enactment of the intention). Intention memory is thus a vital system in the regulation of intentional action (Goschke & Kuhl, 1993; Kazén & Kuhl, 2005). Extension

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memory is conceived as a huge network integrating a vast amount of personally relevant experiences abstracted from autobiographical memory. Extension memory plays an important role in detecting coherence between complex configurations of stimuli (Baumann & Kuhl, 2002) and in establishing congruence between explicit goals and more implicit needs (Baumann, Kaschel, & Kuhl, 2005; Baumann & Kuhl, 2003).

INTERACTIONS BETWEEN PERSONALITY SYSTEMS PSI theory’s hierarchical model (Kuhl, 2001) thus posits seven separate levels of personality functioning with two opposing subsystems on each level. An important implication of the model is that human behavior is determined by a complex array of personality systems. For some pathological individuals, one system or level may be sufficient to understand their behavior. For instance, highly impulsive individuals may rely predominantly on intuitive behavior control, whereas highly neurotic individuals may have a chronic activation of the negative affect system. Among fully functioning individuals, however, all seven levels with their different subsystems will be more or less relevant in understanding their personality functioning. Of course, this is especially true as circumstances vary over time. Under specific circumstances, one personality system may be sufficient in understanding human behavior. For instance, in solving a logical syllogism, most individuals will call on their analytic thinking system. With time and varying circumstances, personality functioning becomes more dynamic and needs to operate on multiple levels, switching back and forth between different systems. An important question thus becomes which principles determine the dynamic interaction between personality systems. PSI theory integrates experimental and neurobiological research that helps to illuminate the basic principles of personality system interactions (Kuhl, 2000a, 2000b, 2001). In general terms, PSI theory assumes that affective changes are critical to the interaction between low-level systems (intuitive behavior control and object recognition) and high-level systems (intention memory and extension memory). Affect is thus central to the dynamics of personality system interactions. Positive and negative affect are assumed to play distinct roles in regulating the dynamics of personality system interactions. It is important to note that this modulation function of positive and negative affect is postulated over and above the direct impact that positive and negative affect have on approach and avoidance behavior

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(Neumann, Förster, & Strack, 2003). Positive and negative affect are thus assumed to serve a dual function, which consists of (1) facilitating approach and avoidance behavior toward specific objects and (2) regulation of personality system interactions. The regulatory function of affect may have evolved because affect systems lie at an intermediate level in the hierarchy of personality systems. Due to this central position within the overall personality architecture, affect systems are well positioned to co-ordinate the interplay between lower- and higherlevel systems. According to PSI theory, positive affect plays a key role in the dynamics between intuitive behavior control (Level 1) and intention memory (Level 7). Specifically, positive affect facilitates enactment of difficult intentions (i.e., volitional efficiency) once they are loaded into intention memory, that is, after an explicit intention has been formed (Figure 32.1). Positive affect thus helps the intuitive behavior control system to get to know what the current intention is (which enables intuitive behavior control to find some routine in its repertoire that may help enact the current intention). In more technical parlance, positive affect modulates the interaction between intuitive behavior control and intention memory. The presumed modulation function of positive affect has received ample empirical support (Fuhrmann & Kuhl, 1998; Goschke & Kuhl, 1993; Kazén & Kuhl, 2005; Kuhl & Kazén, 1999). The modulation function of positive affect can also be stated in reverse form, when it is applied to inhibited positive affect. On the basis of the modulation function of positive affect, inhibited positive affect should be

associated with hesitation and “passive goal awareness” (Kuhl & Beckmann, 1994), that is, a discrepancy between actual behavior and plans, goals, or ideals activated in intention memory. Research has indeed confirmed that individuals high on hesitation display an impaired ability to upregulate positive affect (Baumann, Kaschel, & Kuhl, 2005; Jostmann, Koole, Van der Wulp, & Fockenberg, 2005; Koole & Jostmann, 2004). Research on the relationship between ideal-actual self-discrepancies (or promotion focus) and dejected emotion is thus consistent with this modulation function of positive affect (Higgins, 1987; Higgins, Shah, & Friedman, 1997). According to PSI theory, negative affect plays a key role in the dynamics between object recognition (Level 1) and extension memory (Level 7). Specifically, persistent negative affect impairs access to extension memory. Persistent negative affect presumably energizes the object recognition system, which isolates single instances of new experience (objects) and inhibits their integration into that coherent network of personal wisdom (i.e., the integrated self). As a result, individuals who have an impaired ability to downregulate negative affect (i.e., “ruminators” or stateoriented individuals) should show deficits on various functions that rely on self-access and other coherence-depending functions (such as the coherence-detection task mentioned earlier). For example, successful integration of all personally relevant autobiographical experience in extension memory is an ideal basis for integration of actual goals and behavior with a mature form of moral judgment that derives decisions as to what is good or bad behavior in a given situation from the expected consequences for both

Self-control

Self-regulation

PA–

NA–

Intention memory (IM)

lfEff

Se

icie

Object recognition (OR)

NA+

Extension memory (EM)

th

w gro

nt

wil

l

Intuitive behavior control (IBC)

PA+

FIGURE 32.1 PSI theory: Illustration of a change from low (PA−) to high (PA+) positive affect facilitating enactment of intentions (efficient will) and change from high (NA+) to low (NA−) negative affect facilitating integration of some isolated (unexpected or painful) experience into the coherent network (EM) of personal experience (self-growth).

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others and oneself (rather than from self-alien norms) integrated across a host of personal and cultural experiences. According to PSI theory, integration of personal goals into a coherent self-system is impaired when excessive negative affect inhibits self-access. The empirical relationship between negative affect (i.e., agitated emotions such as anxiety and nervousness) and the discrepancy between conscience (ought goals, duties and responsibilities) and actual goals (Higgins et al., 1997) are consistent with this implication of PSI theory. Empirical findings show such integration deficits in participants having an impaired capacity to downregulate negative affect (i.e., state-oriented participants). For example, when observed in negative mood states (either induced or reported) state-oriented participants show impaired perception of coherence among personality traits or other concepts (Baumann & Kuhl, 2002; Bolte, Goschke, & Kuhl, 2003), impaired discrimination between externally assigned and self-chosen goals (Baumann & Kuhl, 2003; Kazén, Baumann, & Kuhl, 2003; Kuhl & Kazén, 1994), and impaired disengagement from unwanted (task-irrelevant) thoughts and emotions (Baumann & Kuhl, 2003; Brunstein & Olbrich, 1985; Koole, 2004; Koole & Van den Berg, 2005; Kuhl, 1981; Kuhl & Baumann, 2000; Kuhl & Weiss, 1994). Taken together, PSI theory introduces a different type of explanation to existing theories of human motivation. Classical motivation theories heavily rely on the contents of thought, emotions, and intentions when explaining motivated behavior. By contrast, PSI theory focuses on functional effects of psychological systems and their interactions. For example, when a student repeatedly fails to sit down at home and prepare himself for the next exam, content-related explanations would refer to control beliefs (“I cannot understand this topic anyway”) or the content of his intentions (“I will go out to play baseball”). According to PSI theory, there may be an additional explanation that operates over and above possible effects of mental contents: The student may even have positive control beliefs and the intention to work, but his intention memory might not be able to make contact with intuitive behavior control (e.g., because he is stuck in dejected affect which impairs transfer of information from intention memory to intuitive behavior control). Another example illustrates the modulation function of negative affect: Learned helplessness as indicated by generalized performance deficits observed after exposure to uncontrollable failure (Hiroto & Seligman, 1975) is typically attributed to contents of beliefs or intentions (“I failed on the first task, so I will fail on any other task

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as well” and “I will not even try”). Alternatively, it may result from a functional rather than a motivational or cognitive deficit: To the extent that negative affect elicited by the failure experience cannot be downregulated when confronting a task that differs markedly from the task one failed to solve, access to extension memory and the integrated self may be impaired which would cause deteriorated performance, especially at complex tasks that draw upon this system. In accordance with this alternative account, helplessness effects are observed even when participants do not generalize their performance deficits experienced at the training task to the subsequent task and even when they do not show any motivational deficits (Kuhl, 1981; Kuhl & Weiss, 1994).

APPROACH AND AVOIDANCE ACROSS SEVEN LEVELS OF PERSONALITY FUNCTIONING From the perspective of PSI theory, approach and avoidance motivation play a very basic role in the functional architecture of personality. The fundamental importance of approach and avoidance motivation is presumably derived from its adaptive significance during the evolution of the human species. Mostly likely, the ability to efficiently approach opportunities and avoid dangers facilitated the survival of our prehuman ancestors. Accordingly, basic approach and avoidance mechanisms were built into the architecture of personality at a very early stage, probably around the time that our ancestors acquired affect systems at Level 3. However, the significance of approach and avoidance motivation extends beyond the affective level of personality functioning. A basic principle in personality architecture is that more elementary levels are encompassed by more complex levels of personality functioning (Kuhl, 2001). This principle is likely predicated on nature’s inclination to build more complex neurological structures on top of more primitive structures (Panksepp, 1998). The organization of more elementary levels of personality thus forms a groundplan for the organization of more complex levels of personality. Because of this structural organization, certain systems within the personality architecture are more likely to form connections between each other than other systems. PSI theory’s hierarchical model of personality architecture thus allows us to make predictions about the connections of approach and avoidance systems across all seven levels of personality functioning. On the basis of structural considerations, PSI theory suggests that certain

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personality systems may be more compatible with approach motivation whereas other personality systems may be more compatible with avoidance motivation. A schematic overview of the approach and avoidance components at each level is provided in Table 32.1. Notably, these hypotheses about the approach–avoidance components at each of the seven levels of personality should be taken as possible guides for future research more than as clear-cut conclusions from available research. Just because certain systems are less compatible with one type of motivation, does not mean that these systems are in reality never recruited in the service of that motivation. One reason for this difficulty derives from the operation of approach versus avoidance at multiple levels of personality functioning (Cacioppo & Berntson, 1999). To the extent that approach versus avoidance effects can dissociate across levels of personality, approach effects on one level can be counteracted by avoidance effects on another level. Another reason for the notion that we cannot expect that approach and avoidance processes are always translated into approach or avoidance behavior, respectively, may be seen in the fact that mechanisms that have evolved over millennia of evolution are often used for purposes other than the original one. An example of such an “exaptation effect” (Gould & Vrba, 1982) is the functional significance of bird feathers that originally served for thermoregulation and were later used for flying. To use a more psychological example, when people experience fear during a horror movie, they usually give a positive evaluation of this movie and might even decide to see it again on a later occasion (for empirical evidence, see Martin, Abend, Sedikides, & Green, 1997). Thus, it is possible that people sometimes learn to use negative affect for approach behavior, even though the original function of negative affect was presumably to facilitate avoidance behavior. In the present context, we refer to such exaptation effects as functional crossover. Although functional crossover adds a layer of complexity to our analysis, it is theoretically meaningful as it testifies to the inherent plasticity in personality functioning.

APPROACH AND AVOIDANCE IN ELEMENTARY PERSONALITY FUNCTIONING APPROACH AND AVOIDANCE IN ELEMENTARY COGNITION (LEVEL 1) What might be the relationship of simple habits and object perception to the approach–avoidance distinction on the first level of personality functioning? According to

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PSI theory, automatic (or intuitive) control of approach behavior does not require the conscious perception of objects to the same extent that avoidance behavior does. This claim is illustrated by neuropsychological evidence associated with object agnosia (Goodale & Milner, 1992). A patient suffering from this disease could not see an object in front of her (e.g., a glass) or describe its size, but she could spread her thumb and index finger according to the size of that object when asked to grasp it. Intuitive control of approach behavior which is organized by a brain system different from systems underlying object perception (e.g., dorsal versus ventral visual systems) contains an intuitive perceptual component that continues to work even when conscious object perception is not available, provided the relevant action is ongoing (that is, the implicit perceptual component of IBC is available only during performance). It should be noted that in PSI theory, the terms “automatic” and “intuitive” can be distinguished on the basis of the extensiveness and flexibility of habitual behavior (based on S-R learning). In line with common terminology, automatic is used to denote rather rigid habitual behavior that does not require positive valence to be elicited (e.g., daily tooth-brushing which is performed irrespective of how much fun it is). On the other hand, intuitive behavior includes a wider range of the behavioral repertoire that is typically associated with positive affect: An example of intuitive behavior is social interaction that is neither planned nor controlled, but much less rigid and confined than the S-R type of behavior performed independently of its valence. In contrast to the postulated association between approach motivation and intuitive behavior control, object perception might have a deeply rooted affinity with avoidance motivation. A plausible theoretical reason for this assumption can be seen in the generalization and decontextualization function of object perception postulated by PSI theory: When encountering a dangerous situation it seems adaptive to make sure that one will recognize the source of that danger in the future, even if it occurs in quite different contexts (Öhman et al., 2001). High certainty of context-independent recognition may be more important (even life-saving) for dangerous objects than for positive incentives. Context-independent recognition requires decontextualization, a crucial feature of object perception (cf. the construct of field-independence; Witkin, 1950) whereas approach behavior requires a great sensitivity for contextual information. Indeed, locomotion involves parallel processing of information for online control of one’s movements according to the weight, size, and position of objects

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(relative to one’s own position) in space (Berthental & Pinto, 1993; Paillard, 1991) and it places considerable demands on the integration of contextual information across modalities (Clifton, Rochat, Robin, & Berthier, 1994). Empirical evidence consistent with a special association between context sensitivity and intuitive behavior control stems from behavioral priming studies that typically involve casual or implicit primes (e.g., classifying nouns and adjectives that “happen” to be related to old age) affecting automatic behavior (Bargh et al., 1996). Nonetheless, according to the evolutionary principle of functional crossover, intuitive behavior control can also be utilized by avoidance motivation and object perception can be useful for approach purposes.

APPROACH AND AVOIDANCE IN TEMPERAMENT (LEVEL 2) Activation and arousal have been used interchangeably to denote a global energization function presumably associated with “temperament” (Duffy, 1962; Eysenck, 1967). However, research on animal and human behavior has demonstrated the separability of (motor) activation and (sensory) arousal (Pribram & McGuiness, 1975; Thayer, 1978). Conceding the possibility that both activation and arousal can affect either intuitive behavior control or object recognition, PSI theory (Kuhl, 2001) proposes an original link between activation and approach, on the one hand, and arousal and avoidance, on the other hand. Avoidance-related stimuli (e.g., unpleasant levels of noise) typically increase sensory arousal (more than motor activation) as operationalized by object recognition measures or sensory thresholds (Broadbent & Gregory, 1965; Eysenck, 1982). In contrast, approachrelated stimuli (e.g., some desired food) activate motor behavior more than sensory arousal as expressed in theories of incentive motivation and related research (Bolles, 1975; Lewin, 1935). Again, despite the possibility that approach and avoidance components may dissociate across levels of personality, we expect that links among approach and among avoidance components across levels of personality should be more likely to occur than dissociations across levels. Consistent with this reasoning, experimental induction of motor activation (e.g., stepping up and down a chair several times) facilitates perception of blurred (only implicitly perceived) objects that are hard to identify on a conscious level (recall that implicit rather than explicit perception is associated with intuitive behavior control as illustrated by Goodale and Milner’s case of object agnosia), whereas it does not affect conscious perception of clear-cut objects (Matthews, Davies, & Lees, 1990). The

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link between object recognition and arousal (expected on the basis of a common link to avoidance motivation) is difficult to investigate. This is because measures of object recognition are typically confounded with intuitive behavior control because participants typically need some form of motor behavior (e.g., pushing a key) to indicate what they have seen. However, in an experiment in which object recognition and motor behavior were unconfounded by assessing perceptual performance through a subsequent memory test, arousal (induced by white noise) facilitated object recognition (Broadbent & Gregory, 1965).

APPROACH AND AVOIDANCE IN AFFECT (LEVEL 3) Whereas the first and the second levels of personality functioning can work irrespective of the valence of objects (e.g., strong habits are performed independent of their positive or negative valence), the third level brings positive and negative valence into play. This is the level where the most clear-cut links to approach and avoidance motivation have been found (see the other chapters in this volume). According to PSI theory, valence brings incentive motivation into play which results in consistent approach or avoidance reactions to the same objects. Objects associated with positive valence elicit consistent approach and negatively valenced objects elicit consistent avoidance behavior whereas individuals who are mainly motivated from Level 2 (activation or arousal) may respond to the same object in different (even opposing) ways at different times in an opportunistic fashion. An increased level of activation may facilitate approach to an object the organism happens to be confronted with without implying consistent approach behavior toward that object on future occasions. This opportunistic feature of activation-based approach behavior is illustrated in Jung’s description of extraverts who would change their behavior according to their current mood or opportunities encountered in the here and now, without showing introverts’ high degree of “object loyality” in terms of consistent behavior toward the same object or person on future occasions. In contrast, the association of valence with an object (e.g., positive attachment to a person or the positive incentive value of a steak) presumably leads to more consistent behavior toward that object (Bolles, 1975; Freud, 1938). This increase in consistency can be explained: Affect is more easily conditioned to a stimulus than a certain level of activation or arousal. A particular form of anger can directly increase approach motivation (Harmon-Jones & Allen, 1998)

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through establishing the interaction between IM (intention memory) and IBC, which we consider the functional basis of the “invigoration of the will” through temperament (Ach, 1910). Presumably, this type of anger improves the enactment of intentions more through motor activation (Level 2: temperament) than through positive affect (Level 3).

APPROACH AND AVOIDANCE IN HIGHER PERSONALITY FUNCTIONING For the moment, we postpone the intermediate level of personality, which deals with movement between elementary and higher levels of personality functioning. Our discussion thus turns to the three higher-order levels listed in Table 32.1, that is, motives, analytic versus holistic cognition, and intentional control versus holistic self-regulation.

APPROACH AND AVOIDANCE IN MOTIVES (LEVEL 5) In PSI theory, motives are conceived of as “intelligent needs.” Their close connection with holistic feeling (Level 6), extension memory, and the integrated self (Level 7) is what enables them to find intelligent ways for need satisfaction, that is, the ways that take into account the current context (e.g., using fork and knife rather than one’s hands at a formal dinner party) and compatibility with the integrated self (which provides emotional support for motive enactment). According to PSI theory, achievement and power motives have their original roots in instrumental approach motivation (Elliot, 2005; Winter, 1996). Specifically, achievement motivation is primarily characterized by affective change along the approach dimension (McClelland, Atkinson, Clark, & Lowell, 1953; see also Kazén & Kuhl, 2005). A typical achievement-motivated episode starts with some difficult task (which initially dampens positive affect because goal attainment must be postponed) and ends with succeeding at that task (which re-establishes positive affect). Means-end analysis associated with instrumental activity is associated with left rather than right-hemispheric processing (Levy & Trevarthen, 1976). The latter evidence triangulates with studies linking left-hemispheric processing to approach (Harmon-Jones & Allen, 1998). Despite the hypothesized compatibility between achievement motivation and approach, the role of fear of failure and avoidance concerns is so obvious in the achievement domain that the postulated primacy of approach in achievement motivation may appear as a rather academic issue (Elliot, 2005).

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In fact, the elaboration of the old dichotomous (approach– avoidance) taxonomy of achievement motivation into a 2 × 2 model differentiates high- and low-level forms of motivation within both approach and avoidance orientations (Elliot & McGregor, 2001): High-level achievement motivation combines the creativity and emotional support of the self with approach or avoidance orientations, respectively (mastery motivation), whereas low-level achievement motivation is characterized by an (objectrelated) outcome rather than a self-referential focus. We recently developed a nonreactive method for fourfold assessment of achievement (as well as affiliation and power) motives resulting from this taxonomy (plus a fifth passive-avoidance category). This nonreactive measure capitalizes on the advantages of the traditional TAT by using spontaneous fantasies rather than explicit responses to questionnaire items, while being less time-consuming to score and yielding much better psychometric properties than the traditional TAT (Kazén & Kuhl, 2005; Kuhl, 2002; Scheffer, 2003). Empirical evidence for the postulated affinity between left-hemispheric processing and power motivation was recently obtained in a study confirming left-hemispheric dominance for power motivation (independent of positive or negative valence) (Kuhl & Kazén, 2007). The latter association is consistent with the notion that affiliation and intimacy in dyadic relationships involve exchange on a personal level which is tantamount to the integrated self. Findings showing empathy to be associated with right-hemispheric dominance (Adolphs, Damasio, Tranel, Cooper, & Damasio, 2000) are also consistent with our relating the affiliation motive to the operation of the right hemisphere. Less obvious seems the postulated basic association between affiliation and avoidance (Table 32.1). Indirect evidence for this link is that right-hemispheric dominance is associated with both affiliation (Kuhl & Kazén, 2006) and negative affect (Davidson, 1993). More directly to the point, there is empirical evidence for evolutionary and ontogenetic primacy of the link between avoidance motivation and affiliation (MacDonald, 1992). Both in animals as well as in human infants the primary function of the need for affiliation, attachment, and proximity seems to be protection and safety, two concerns that have a deeply rooted avoidance focus (MacDonald, 1992). Nonetheless, functional crossover opens affiliation to positive affect and approach motivation. People from independent cultures might tend to overestimate this link because there is a greater value attached to positive affect in many independent cultures compared to the majority of interdependent cultures (MacDonald, 1992).

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APPROACH AND AVOIDANCE IN HIGH-LEVEL COGNITION AND AGENCY (LEVELS 6 AND 7) Levels 6 and 7 are closely interconnected with Level 5. Achievement and power motives are more dependent on analytical thinking, explicit intentionality, and ego-control, whereas affiliation and self-growth motives are naturally more closely interacting with the vast integrative potential of extension memory and the self that develops from innumerable autobiographical episodes and receives continuous input from emotions and needs (whose level of satisfaction is indicated by emotions). The parallel processing power of extension memory is the functional basis for its ability to integrate a virtually unlimited amount of inputs and constraints: The ability of extension memory to simultaneously take in a virtually unlimited number of information units is a computational feature that results in an enormous integrative competence, that is, in the ability to find cognitive and behavioral solutions that simultaneously satisfy innumerable needs and values (own and others’), and take account of situational constraints, personal competences, and cultural norms and expectations. In contrast, the step-bystep (sequential) nature of analytical thinking cannot take account of as many different constraints which renders complex decision making very difficult when it solely relies on sequential processing (i.e., left-hemispheric processing). The self integrates the personally relevant part of extension memory. Because of its intimate interrelatedness with emotions, the self is the most potent functional basis for the recruitment of positive (intrinsic) motivation (Deci & Ryan, 2000) and for profound and permanent coping with painful experience (Linville, 1987; Rothermund & Meiniger, 2004; Showers & Kling, 1996). Up to 40 self-regulatory functions can be distinguished and assessed which range from goal formation in intention memory, generation of initiative and self-motivation, disengagement from intrusive or ruminating thoughts, and other aspects of self-relaxation, self-compatibility checking (e.g., for discovering self-alien introjects), and many more (Kuhl & Fuhrmann, 1998).

VERTICAL INTERACTIONS WITHIN APPROACH AND AVOIDANCE SYSTEMS: AFFECT MODULATIONS AND PROGRESSION VERSUS REGRESSION In addition to the “horizontal” distinction between approach and avoidance components at each level of

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personality, “vertical” interactions within approach and within avoidance orientations can be investigated across levels of personality (Table 32.1). The two modulation assumptions of PSI theory mentioned earlier focus on the vertical link between valence-related approach or avoidance components (Level 3 in Table 32.1) and corresponding high-level systems. In fact, the assumed basic association between valence-based approach (Level 3) and intentional control (Level 7), on the one hand, and valence-based avoidance (Level 3) and holistic self-representations (Level 7), on the other hand, is the basis for the two affect modulation assumptions described earlier. In light of the close connection between self-access and the avoidance axis (especially: high versus low negative affect) one might wonder how the NA-self relationship can be reconciled with findings demonstrating self-positivity (Koole, Dijksterhuis, & Van Knippenberg, 2001). One answer might be that self-positivity has a profound basis in finding positive sides of and meaning in negative experience, a process that presumably involves the self-system providing an extended network of personal experience (Frankl, 1986; Kuhl, 2000a; Linville, 1987; Rothermund & Meiniger, 2004; Showers & Kling, 1996). This would be an example of functional crossover: Despite its deeply rooted link with the avoidance axis, self-access can be utilized for direct recruitment of positive affect (self-motivation) in order to strengthen approach motivation (Koole & Jostmann, 2004). It goes without saying that the postulated functional priority of avoidance over approach in self-maintenance requires further empirical testing. Some preliminary support comes from neuropsychological research. Holistic and polysemantic processing as well as self-access are associated with the right hemisphere and analytic-instrumental processing with the left hemisphere (Craik et al., 1999; Keenan et al., 2001; Levy & Trevarthen, 1976; Rotenberg, 2004; Springer & Deutsch, 1997). In addition, right-hemispheric activation is associated with negative affect and left-hemispheric activation with positive affect (Davidson, 1993; Harmon-Jones, 2006). Taken together, these findings are consistent with PSI theory’s assumption concerning natural links between negative affect and holistic processing versus positive affect and intentional (analytical) action control. Evidence from neuropsychological studies confirms the assumption that the right prefrontal cortex is involved in both holistic processing in general and self-referential processing in particular (Beeman et al., 1994; Craik et al.; Keenan et al., 2001), and that the self-referential part supported by the right prefrontal cortex involves implicit rather than explicit self-representations (Kircher et al., 2002).

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Our approach–avoidance look at the architecture of personality is almost complete at this point. However, the role of Level 4 still requires some elaboration. In fact, the functional significance of progression and regression may help acquire an understanding of the intricate relationship between cognitive systems, affect, and approach–avoidance: At first glance, the notion that nonanalytic, holistic processing is “associated” with negative affect seems to be inconsistent with empirical evidence suggesting excessive negative affect interferes with holistic processing as assessed by coherence judgments and self-access (Baumann & Kuhl, 2002, 2003). For instance, state-oriented individuals who report having problems terminating negative affect and related ruminations do not seem to be successful in their attempts to cope with negative affect by accessing coherence-producing functions (self-related or not). An extreme case of a similar phenomenon has been observed in depressed and suicidal patients who seem to be unable to find (polysemantic or “holistic”) meaning in their lives despite their enduring attempts to activate the hemisphere that should provide all-encompassing meaning due to its holistic and polysemantic nature (as indicated by physiological arousal of right prefrontal networks; Davidson, 1993; Rotenberg, 2004; Weinberg, 2000). Empirical evidence shows that state orientation may, in fact, be regarded as a nonpathological analogue of depression (Kuhl, 1981; Kuhl & Helle, 1986). What happens to depressed or state-oriented people who undermine their attempts to seek meaning and selfcongruence to failure when exposed to excessive life stress or experimentally induced negative affect? How can we reconcile the assumed association between holistic selfmaintenance functions and negative affect with the finding that for some people (i.e., state-orientated ones) negative affect seems to be associated with impaired functioning of self-related (presumably holistic) functions? Consistent with PSI theory is the argument that the inability to cope with negative affect (typical of state-oriented or depressed individuals) causes a dissociation between physiological arousal of the holistic self-system (presumably supported by the right prefrontal cortex) and its efficiency (Rotenberg, 2004). According to this view, both action- and state-oriented or depressed and nondepressed individuals activate the holistic, self-referential system when negative affect is aroused (even more so than actionoriented individuals: Biebrich & Kuhl, 2004). However, for some reason, the failure to downregulate negative affect impairs efficient functioning of that system. This is where the fourth level of our architecture of personality deserves special attention. One of the mechanisms that explains the dissociation between physiological arousal of the right hemisphere (Davidson, 1993) and

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its malfunctioning in state-oriented or depressed people when exposed to life stress or aversive stimuli, respectively, operates on Level 4, which may be related to the Freudian concept of regression. Recall that regression may be accounted for by a stress-sensitive structure of the brain that is inhibited when the level of stress (as assessed, for example, by the concentration of the stress hormone cortisol) exceeds a critical intensity (Jacobs & Nadel, 1985; Sapolsky, 1992). The hippocampus mediates, among other things, the top–down modulation of lowlevel processing (cf. Level 1, 2, and 3 in Table 32.1) through high-level systems in humans (Jacobs & Nadel, 1985) and in animals (Schmajuk & Buhusi, 1997). Consequently, we can explain the failure of high-level systems to regulate affect by meaning-providing structures or useful personal experience (provided by selfaccess): Whenever stress exceeds a critical level and cannot be downregulated within a critical time window (which seems to happen to state-oriented more often than to action-oriented individuals), high-level systems lose their impact on low-level structures. This can result in the perseverance of unwanted habits (such as compulsive cleaning: Level 1 in Table 32.1) or unpleasant affect (such as the elicitation of strong anxiety when crossing a high bridge, despite the firm knowledge that it will not break down: Level 3 in Table 32.1). Presumably, regression is more deeply associated with avoidance because its prime function is to prepare the organism for simple forms of avoidance (e.g., fight or flight) by shutting off high-level control of behavior. This renunciation of high-level control seems especially adaptive in an environment that provides many unpredictable risks: Whenever dangerous events cannot be reliably predicted it makes sense to inhibit cognitive systems that try to make sense out of the environment by relying on prognostic attempts of the cognitive apparatus. Aligning the two modes of control (i.e., top–down versus bottom–up control) with the approach–avoidance distinction, we therefore propose that regression (i.e., the bottom–up flow of control) is associated with avoidance and the release of regression corresponds to self-confrontational coping. On the other hand, progression typically facilitates intelligent top–down approach because it puts low-level systems under the control of the current task or goal, whereas the inhibition of progression amounts to bottom–up control of behavior guided by impulses (generated on the temperament or affective level) or habits including external control. Despite this aligning of approach–avoidance with progression and regression, respectively, the crossover hypothesis permits that progression can be associated with avoidance (e.g., loading intention memory with an avoidance goal) and regression

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can serve approach purposes (e.g., when behavioral impulses toward wanted objects cannot be controlled by high-level systems). The negative affect modulation assumption of PSI theory (and its reversal) describes the intricate relationship between negative affect and high-level functioning: Excessive and persevering negative affect (presumably associated with state orientation) impairs the efficiency of high-level coping that depends on holistic processing and self-access. In other words, when negative affect exceeds a critical intensity, it becomes difficult to bring painful or anxiety-inducing events in contact with the experiential knowledge of the self which normally helps see aversive events in perspective (“despite this failure I know that I have been successful in so many other situations”) or provides meaning to them (“this loss has brought a new task to my life”). The integrated self is the ideal system for this deep and sustained coping effect because it encompasses extended networks of autobiographical experience, needs, values, options for future action, and creative solutions. Access to these extended networks (extension memory) facilitates detection of some experience, need, or behavioral option that may help cope with the aversive event (Frankl, 1986). This effect is further facilitated by another functional characteristic of the integrated self. The close connection between this (right-hemispheric) system and the autonomic (emotional) nervous system (Cacioppo, Gardner, & Berntson, 1999; Dawson & Schell, 1982; Wittling, 1990) provides a functional basis for changing affective responses associated with aversive experience. To the extent that excessive negative affect inhibits selfaccess, this form of deep and sustained coping is impaired, which gives way for the well-known self-avoiding defense mechanisms (e.g., denial, embellishment, suppression, intellectualization).

SELF-CONFRONTATIONAL COPING As a final question we may ask: Why should the self be especially suited for dealing with negative affect and avoidance (Linville, 1987; Rothermund & Meiniger, 2004; Showers & Kling, 1996), a feature that fits with neurobiological evidence for the close association between negative affect, withdrawal, and right-hemispheric activation (Davidson, 1993)? We can see one reason for this relationship in the multidirectionality of negative affect and avoidance: Avoidance motivation defines a direction of locomotion to be avoided rather than defining which way to go. In Lewin’s topological representation of psychological forces, negative valence was illustrated by arrows pointing

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away from the locus of negative valence in all directions (Lewin, 1938). We propose that this model nicely illustrates the enormous demands on parallel processing for intelligent coping with avoidance: The highest level of parallel processing (i.e., the level of the integrated self) is the best functional basis for fast processing of an extended number of possible ways (directions) of avoiding an aversive event. Finding the personally best way among this host of possible directions that promise to overcome or avoid a negative experience may be tantamount to the search for meaning that Frankl (1986) described as the most powerful and uniquely human way of coping (Kuhl, 2006). This view is largely consistent with a neurobehavioral animal model that associates anxiety (as opposed to fear) with high-level, integrative functions (hippocampal and prefrontal) that mediate inhibition of dominant responses and support cognitive search for conflict resolution (McNaughton & Corr, 2004). However, arguing more from a motivational rather than from a neurobehavioral perspective, we confine the term approach to clearcut approach motivation rather than to situations that start with avoidance motivation and lead to search activity (Rotenberg, 2004) which may eventually result in approach behavior. Nonetheless, the two terminologies are compatible with our terminology focusing on motivation whereas McNaughton and Corr’s use a behavioral criterion for defining approach and avoidance. In contrast, in the case of approach motivation, that is, when a clear-cut approach goal is available, cognitive reduction on the direct path toward that goal as performed by analytical thinking and intention memory may be more adaptive than parallel processing of many possible ways to approach it. As a result, cognitive reduction to one goal and task-related information only, which is typically provided by explicit, verbal cognition and the left hemisphere (Kircher et al., 2002; Marcel, 1983; Schore, 2003; Springer & Deutsch, 1997), should be more adaptive for approach than for avoidance motivation. As mentioned, this is consistent with neurobiological findings that demonstrate an association between left-hemispheric activation and approach motivation (Davidson, 1993; Harmon-Jones & Allen, 1998). Nonetheless, there is the possibility of functional crossover among this association of approach and avoidance with sequential and parallel processing systems, respectively (i.e., approach with analytical thinking and intention memory versus avoidance with extension memory and the integrated self). For example, even if the primary (original) purpose of the integrated self has evolved for dealing with the cognitive complexity of avoidance, the enormous computational power of its parallel processing capacity can be utilized for exploring creative ways for realizing approach

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goals, especially when important existential decisions (involving the whole person with his or her needs, values, propensities, and experience) are to be made. The parallel processing capacity of the right hemisphere (especially its prefrontal parts involved in self-representation and self-regulation) is better equipped for integration of both positive and negative emotions than the analytic and discriminative processing characteristic of the left hemisphere: According to Cacioppo et al. (1999), emotiongenerating circuits share with cognitive parallel processing systems the collapsing of multiple input dimensions (e.g., the temperature, sweetness, or texture of a gustatory stimulus). The loss of information associated with this multidimensional integration can be considered a functional prerequisite for computing instantaneous overall utility of a given situation necessary for a fast approach or avoidance response. The self-inhibiting impact of negative affect is offset by the beneficial effects of self-access on the downregulation of negative affect (reversal of the second modulation assumption): Successful activation of holistic processing and self-access helps downregulate negative affect in a more reliable way than accomplished by any other coping or defense mechanism. Empirical findings are consistent with this notion. In addition to the cited evidence for the relationship between negative affect and impaired self-access and deteriorated detection of coherence in state-oriented individuals (Baumann & Kuhl, 2002, 2003), empirical findings demonstrate that state orientation predicts the intensity and development of psychosomatic symptoms (Baumann et al., 2005; Baumann, Kaschel, & Kuhl, 2007). This particular study revealed that motives mediate the relationship between state orientation and psychosomatic illness (i.e., Levels 3 and 4 affecting Levels 6 and 7): The significant prediction of psychosomatic symptoms by the interaction of state orientation (Level 4) and negative affect (Level 3) was significantly reduced when the discrepancy between implicit motives and explicit goals was statistically controlled. Discrepancy between goals and motives is a form of self-incongruence which may be regarded as a hidden stressor. Negative affect associated with this stressor should impair self-access which in turn reduces the ability of the self-system to regulate emotions and other somatic processes that only this system has privileged access to, according to PSI theory. Loss of privileged access to emotions, needs, motives, and other somatically anchored organismic processes also explains why so-called extrinsic goals (such as status or money) do not easily bring happiness and satisfaction with life (Kasser & Ryan, 1993): Goal attainment does not really

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reach organismic needs and emotions unless goal motivation emanates from the self. According to PSI theory, the functional basis of this basic tenet of self-determination theory (Deci & Ryan, 2000) can be seen in the close connectivity between the implicit self of the right hemisphere and the autonomic nervous system of the brain (Cacioppo et al., 1999; Dawson & Schell, 1982; Schore, 2003; Wittling, 1990).

SUMMARY, CONCLUSION, AND FUTURE DIRECTIONS In the present chapter, we have situated approach and avoidance motivation within the functional architecture of personality. We first discussed the personality architecture as postulated by PSI theory (Kuhl, 2000a, 2001). PSI theory distinguishes seven levels of personality functioning, which include elementary cognition, temperament, affect, progression and regression, motives, high-level cognition, and agency. At each of these levels, our analysis distinguished two personality systems, which include intuitive behavior control versus object recognition, motoric activation versus perceptual arousal, positive versus negative affect, progression versus regression, instrumental versus experiential motives, knowing versus feeling, and self-control versus self-maintenance. To become a fully functioning person, high- and lowlevel systems need to interact with each other. According to PSI theory, these personality system interactions are regulated by affect: Changes between low and high positive affect regulate the interaction between intention memory and intuitive behavior control, which is necessary for volitional action. Changes along the negative affect dimension regulate the interaction between extension memory and object recognition, which is necessary for personal growth. We then related approach and avoidance motivation to the framework of PSI theory. At first glance, approach and avoidance motivation relate primarily to positive and negative affect systems. This straightforward relation, however, probably underestimates the broad and fundamental significance of approach and avoidance motivation. Indeed, we proposed that the functional significance of approach and avoidance motivation cuts across the entire spectrum of personality functioning, thereby implicating all seven levels of the functional architecture of personality. Because the organization of higher personality systems tends to subsume that of lower personality systems, it is possible to delineate which personality systems are particularly compatible with approach and avoidance motivation. Approach motivation is particularly compatible with the axis of

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personality systems that support intuitive behavior control, motor activation, positive affect, progression, instrumental motives, analytic thinking, and self-control. Avoidance motivation is particularly compatible with the axis of personality systems that support object recognition, perceptual arousal, negative affect, regression, experiential motives, holistic feeling, and self-maintenance (Table 32.1). Our review of the literature found some initial empirical support that related approach versus avoidance motivation to the hypothesized profile of compatible functional systems. At the same time, it is apparent that approach versus avoidance motivation do not conform rigidly to the hypothesized profiles. Indeed, our review yielded several examples of functional crossover, in which approach versus avoidance motivation were linked to systems that should be theoretically less compatible with the respective motivation. These examples of functional crossover highlight the inherent flexibility and plasticity in personality functioning. As we suggested, this flexibility may arise either because of the complex hierarchical nature of approach versus avoidance motivation (Elliot, 2005) or because people find ways to recruit personality systems for motivations for which these personality systems were not originally “designed” during the course of evolution. Whenever functional crossover occurs, it may give rise to forms of behavior regulation that are inherently somewhat unstable. This is because functional crossover involves the collaboration of personality systems that were not originally designed by nature to collaborate with each other. For instance, functional crossover may break down more easily under high demands or stress or require special kinds of executive control to ensure the smooth collaboration between the inherently less compatible systems. It is thus likely that behavior that results from functional crossover still differs in subtle ways from behavior that results from inherently compatible personality systems. For future research, the approach–avoidance distinction is especially intriguing within the highest level of personality functioning. Theoretical and empirical research is especially needed to spell out the far-reaching implications of the functional connection between avoidance and self-determination. Suffice it to say, in concluding, that according to our hypothesis concerning a special link between negative affect and the integrated self, avoidance motivation should be even more deeply involved in free self-determination than approach motivation. This notion is in accordance with existential philosophy, according to which there is a deep link between freedom of choice and anxiety (Heidegger, 1927/1996). Moreover, this notion is also consistent with empirical evidence that the self plays a major role in coping with existential

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threats such as mortality salience (for an overview, see Greenberg, Koole, & Pyszczynski, 2004). Our argument concerning the multidirectionality of avoidance motivation can be regarded as a functional account of Heidegger’s claim of existential anxiety emanating from the virtually unlimited range of existential possibilities associated with “Da-Sein,” his philosophical term for the totality of subjective representations relevant for one’s existence. At the outset of this chapter, we introduced our readers to a young man who chose to get married because he could not bear his loneliness. At the end of this chapter, we are in a position to shed some more light on the intuition that getting married to avoid being alone is unlikely to bring someone happiness. To the extent that negative affect associated with avoidance motivation is strong enough to inhibit extension memory, experiential motives (especially the affiliation motive), and the integrated self, our young man might have difficulties developing a satisfying relationship on a personal level, which would require functions associated with the right hemisphere such as affiliation motivation and empathy, holistic processing, and self-access. Unlike local affect associated with an isolated event (e.g., positive affect associated with a single success), happiness requires an overall positive evaluation of a variety of life events on the basis of their relevance for personal (i.e., self-related) needs (Deci & Ryan, 2000). Without access to the integrative function of the self-system, it will be difficult to even experience overall happiness (irrespective of the objective amount of happy events occurring). Our functional-design analysis of approach and avoidance motivation is admittedly more abstract than traditional motivational theories. Nevertheless, unraveling the functional architecture of approach and avoidance motivation can be extremely useful in understanding the basic psychological mechanisms that underlie the effects of approach and avoidance motivation. A deeper understanding of these basic mechanisms, in turn, can be of great practical use in providing motivational support to people in everyday life situations (Kuhl, Kazén, & Koole, 2006). For instance, the present analysis may suggest some grounds for hope for our lonely young man: Once his self-growth would permit him at some point of his development to downregulate the negative affect associated with his avoidance motivation through self-confrontation, his weakness may be turned into a source of strength. Successful self-confrontation may help to turn the inhibiting aspects of excessive avoidance motivation into facilitating resources for a mutually satisfying relationship, further personal growth and overall well-being.

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Lewin, K. (1938). The conceptual representation and the measurement of psychological forces. Durham, NC: Duke University Press. Linville, P. W. (1987). Self-complexity as a cognitive buffer against stress-related illness and depression. Journal of Personality and Social Psychology, 52, 663–676. MacDonald, K. (1992). Warmth as a developmental construct: An evolutionary analysis. Child Development, 63, 753–773. Marcel, A. J. (1983). Conscious and unconscious perception: Experiments on visual masking and word recognition. Cognitive Psychology, 15, 197–237. Martin, L. L., Abend, T., Sedikides, C., & Green, J. D. (1997). How would I feel if…? Mood as input to a role fulfillment evaluation process. Journal of Personality and Social Psychology, 73, 242–253. Matthews, G., Davies, D. R., & Lees, J. L. (1990). Arousal, extraversion, and individual differences in resource availability. Journal of Personality and Social Psychology, 59, 150–168. McClelland, D. C., Atkinson, J. W., Clark, R. A., & Lowell, E. L. (1953). The achievement motive. New York: Appleton-Century-Crofts. McClelland, D. C., Koestner, R., & Weinberger, J. (1989). How do self-attributed and implicit motives differ? Psychological Review, 96, 690–702. McNaughton, N., & Corr, P. J. (2004). A two-dimensional neuropsychology of defense: Fear/anxiety and defensive distance. Neuroscience and Biobehavioral Reviews, 28, 285–305. Neumann, R., Förster, J., & Strack, F. (2003). Motor compatibility: The bidirectional link between behavior and evaluation. In J. Musch & K. C. Klauer (Eds.), The psychology of evaluation: Affective processes in cognition and emotion (pp. 371–391). Mahwah, NJ: Lawrence Erlbaum. Öhman, A., Lundqvist, D., & Esteves, F. (2001). The face in the crowd revisited: A threat advantage with schematic stimuli. Journal of Personality and Social Psychology, 80, 381–396. Paillard, J. (1991). Motor and representational framing of space. In J. Paillard (Ed.), Brain and space (pp. 163–182). New York: Oxford University Press. Panksepp, J. (1998). Affective neuroscience: The foundations of human and animal emotions. New York: Oxford University Press. Pribram, K. H., & McGuiness, D. (1975). Arousal, activation, and effort in the control of attention. Psychological Review, 82, 116–149. Rotenberg, V. S. (2004). The peculiarity of the right-hemisphere function in depression: Solving the paradoxes. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 28, 1–13. Rothermund, K., & Meiniger, C. (2004). Stress-buffering effects of self-complexity: Reduced affective spillover or self-regulatory processes? Self and Identity, 3, 263–282. Sapolsky, R. M. (1992). Stress, the aging brain, and the mechanism of neuron death. Cambridge, MA: MIT Press.

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Part VIII Social Context

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Culture and Avoidance Motivation 33 Approach Across Cultures Takeshi Hamamura and Steven J. Heine CONTENTS Cultural Variation in Self-Enhancement Motivation ............................................................................ 558 Summary of Section ......................................................................................................................... 559 Cultures and Self-Regulation: Approach and Avoidance Motivation .............................................. 559 Summary of Section .........................................................................................................................562 Cross-Cultural Research of Phenomena Implicated in an Approach–Avoidance Framework .............562 Regulatory Fit ...................................................................................................................................562 Temporal Construal ..........................................................................................................................563 Anticipating Future Events ...............................................................................................................563 Motivated Information Processing ...................................................................................................563 Emotional Consequences .................................................................................................................564 Summary of Section .........................................................................................................................565 Mechanisms Underlying Cross-Cultural Variation in Approach–Avoidance Motivation ....................565 Summary of Section .........................................................................................................................566 Conclusion .............................................................................................................................................566 References .............................................................................................................................................567

The distinction between approach and avoidance motivation has been of enormous value for understanding the functioning of the mind. It has also been of much use in aiding cultural psychologists to better understand the interplay between culture and mind. Cultural psychology has primarily been concerned with how culture and mind influence each other (Shweder, 1991). In particular, much research has been conducted exploring how individuals from different cultures vary in terms of how they evaluate themselves (Cousins, 1989; Markus & Kitayama, 1991). Various findings about cultural differences in the self-concept have led to a number of different accounts for why people view themselves in the ways that they do (Cohen, Hoshino-Browne, & Leung, in press; Heine, Lehman, Markus, & Kitayama, 1999; Kitayama, Markus,

Matsumoto, & Norasakkunkit, 1997). It is the thesis of this chapter that the framework of approach and avoidance motivation can integrate many of the findings from the cross-cultural exploration of the self-concept. This chapter first introduces how the approach and avoidance distinction fits with cross-cultural research on self-evaluation. Then, we discuss how the approach and avoidance framework can be utilized in developing a number of novel hypotheses in cross-cultural research. Last, we review how cross-cultural research can, in turn, be utilized to inform the mechanisms underlying approach and avoidance motivation. As the majority of this research has contrasted East Asians and Westerners, our focus for the review is also on research with these cultures. 557

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CULTURAL VARIATION IN SELF-ENHANCEMENT MOTIVATION How do individuals from different cultures vary in their self-evaluations? At one level, it would seem that there should be much universality with respect to how people evaluate themselves. For example, people everywhere should be motivated to view themselves as living up to the cultural norms with respect to what it is to be a good person (Norenzayan & Heine, 2005). At the same time, however, to the extent that the nature of social relations varies across cultures, what constitutes a culturally valued person should also vary across cultures (Heine et al., 1999). In individualistic cultures such as much of the West, people learn (via their socialization, participating in cultural institutions, interaction with others) that it is valued to think of themselves as a unique and selfsufficient entity. Towards this objective, individuals come to focus on their positive self-characteristics in order to positively distinguish themselves from others, that is, they come to have high self-esteem. According to this view, strategies which help enable individuals to have high self-esteem should be favored in individualistic cultures. Self-enhancement, defined as the motivation to elaborate on positive self-characteristics relative to negative ones, is a motivation that should thus serve to bring one closer to the culturally shared ideals of a good person in such cultural contexts. In contrast, in hierarchical collectivistic cultural environments such as East Asia, where the self is embedded in a social network, being a culturally valued person importantly entails maintaining one’s “face.” Face has been defined as “the respectability and/or deference which a person can claim for himself from others by virtue of the relative position he occupies in his social network and the degree to which he is judged to have functioned adequately in that position” (Ho, 1976, p. 883). Being a good person in East Asian contexts is associated with being a person with a successfully maintained face. We submit that concepts such as face and self-esteem are universally accessible (they can be seen as existential universals) (Norenzayan & Heine, 2005), however, we argue that self-esteem is prioritized more in the West whereas face is prioritized more in East Asia (Hamamura & Heine, in press; Heine, 2005). In the following sections, we explore some of the psychological implications of the notion that the conception of a “good person” held commonly among East Asians differs from that typically held among Westerners. If the motivation to view the self in a positive light is prioritized to a greater extent among Westerners than it is

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for East Asians, it follows that there should be cultural variation in the extent to which Westerners and East Asians self-enhance (Heine et al., 1999). This rationale is supported by many studies. A recent meta-analysis of all published cross-cultural self-enhancement studies (k = 46) showed a striking absence of self-enhancement among East Asians (d = −.01) compared to strong evidence for self-enhancement among Westerners (d = .87) (Heine & Hamamura, 2007). The conclusion we draw from these findings is that self-enhancing motivations are more prevalent among Westerners than among East Asians. There are three objections that are commonly made regarding this conclusion: (1) cross-cultural self-enhancement research does not take account the fact that different cultures value different characteristics. People everywhere self-enhance on those characteristics that are important to them, and the cultural differences would be greatly reduced if East Asians were asked to evaluate themselves in domains that are of much concern to them (Kobayashi & Brown, 2003; Sedikides, Gaertner, & Toguchi, 2003); (2) collectivistic East Asians self-enhance by enhancing their group selves (Brown & Kobayashi, 2002; Muramoto & Yamaguchi, 1997); and (3) the cultural differences reflect different self-presentation norms across cultures, not differences in people’s motivations (Kobayashi & Greenwald, 2003; Kurman, 2003). We discuss each of these alternative accounts below. The first account predicts universal self-enhancement on those characteristics that an individual views to be important, and it suggests that this pattern should hold across cultures. A few studies have indeed found this pattern (Brown & Kobayashi, 2002; Sedikides et al., 2003) although the opposite pattern (i.e., East Asians show less self-enhancement for more important traits) has been found in other studies (Heine & Lehman, 1995; Heine & Renshaw, 2002; Kitayama et al., 1997). A meta-analysis of all cross-cultural studies on this topic reveals that cultures differ significantly on the correlation between traits importance and self-enhancement in that East Asians do not exhibit the pattern of greater self-enhancement for traits that are especially important to them (r = −.01) whereas Westerners do (r = .18) (Heine, Kitayama, & Hamamura, in press; note that a meta-analysis with different inclusion criteria conducted by Sedikides, Gaertner, & Vevea, 2005, concluded that East Asians do self-enhance more for important traits; also see Sedikides, Gaertner, & Vevea, in press. We invite readers to compare the different meta-analyses and draw their own conclusions). Furthermore, the few studies that do identify tendencies among East Asians to self-enhance more on especially important domains do so almost exclusively with measures of the

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Approach and Avoidance Motivation across Cultures

“better-than-average effect,” a measure that is compromised by a person positivity bias (Klar & Giladi, 1997; Sears, 1983). When this bias is circumvented, the betterthan-average effect no longer reveals self-enhancement among East Asians for especially important traits (Hamamura & Heine, 2007; Heine et al., in press). Hence, although this alternative account benefits from a certain intuitive appeal, overall, the data do not support it. The second account, that East Asians direct their selfenhancing motivations to their groups, has also been explored in a number of different studies. Two cross-cultural studies have found no difference between Westerners and East Asians in their group-enhancing tendencies (Brown & Kobayashi, 2002; Endo, Heine, & Lehman, 2000). These two studies are in support of this alternative account. On the other hand, eight studies have found that Westerners enhance their groups more than East Asians. This cultural difference has emerged for people’s evaluations of their romantic relationships (Endo et al., 2000), their family members, universities, and social groups (Heine & Lehman, 1997), their evaluations of their countries (Rose, 1985), their cities (Kitayama, Palm, Masuda, Karasawa, & Carroll, 1996), their children (Stevenson & Stigler, 1992), their sports teams (Snibbe, Kitayama, Markus, & Suzuki, 2003), their gender (Bond, Hewstone, Wan, & Chiu, 1985), and in their collective self-esteem (Crocker, Luhtanen, Blaine, & Broadnax, 1994). In contrast, we are not aware of any published studies that have found greater group-enhancing tendencies among East Asians compared with Westerners which would be expected if this alternative account was correct. In sum, a consideration of the cross-cultural research on this topic finds that, overall, group-enhancing tendencies are stronger among North Americans than among East Asians. Hence, the observed cultural variation in self-enhancement cannot be explained in terms of any purported East Asian group-enhancing motivations. The third alternative account for cultural variation in self-enhancement is that the differences arise from selfpresentational norms and not from genuine cultural differences in motivations. That is, either East Asians are feigning modesty or Westerners are feigning bravado, and this is preventing us from having an accurate view of each culture’s self-enhancing motivations. This is a very difficult question to assess with confidence as our ability to assess the private thoughts of individuals is limited by our methods. Nonetheless, two studies that sought private behavioral measures of self-enhancement found that whereas Westerners showed a self-enhancing pattern of responses, East Asians showed an overall self-critical pattern of responses (Heine, Kitayama, Lehman, Takata,

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Ide, & Leung, et al., 2001; Heine, Takata, & Lehman, 2000). That the East Asian responses were, if anything, more self-critical in these studies than in questionnaire studies would argue against the account that East Asians are feigning modesty. Furthermore, a number of other studies have also found clear evidence for a lack of East Asian self-enhancement using measures that would seem protected from self-presentational concerns (Oishi & Diener, 2003; Ross, Heine, Wilson, & Sugimori, 2005; White & Lehman, 2005). However, research conducted with implicit measures of self-esteem, such as the Implicit Associates Test and the birthday-number effect, reveal that East Asians have as positive views of themselves as do Westerners (Kitayama & Karasawa, 1997; Kitayama & Uchida, 2003; Kobayashi & Greenwald, 2003). We submit that these latter findings might indicate that cultures do not differ in the extent to which people come to have warm feelings about themselves. Rather, the cultural differences primarily lie with respect to how positively people assess their own competence (cf., Tafarodi & Swann, 1996). The question of what cross-cultural comparisons of implicit measures of selfesteem are telling us will be further illuminated once we have a better understanding of what these measures are assessing (Bosson, Swann, & Pennebaker, 2000; Hofmann, Gawronski, Gschwendner, Le, & Schmitt, 2005).

SUMMARY OF SECTION The available evidence converges to indicate a pronounced cultural discrepancy in tendencies to self-enhance. Whereas Westerners consistently show evidence for strong self-enhancing motivations, East Asians do not (Heine & Hamamura, 2007). The relative absence of evidence for self-enhancing motivations among East Asians calls into question the ways that East Asians evaluate themselves. As the next section discusses, the distinction of approach and avoidance motivation is of much utility for illuminating how East Asians and Westerners work towards becoming a good person in their respective cultures.

CULTURES AND SELF-REGULATION: APPROACH AND AVOIDANCE MOTIVATION Self-regulation coordinates cognitions, emotions, and behaviors and is essential for the attainment of goals and the adherence to social norms (Baumesiter & Heatherton, 1996). To the extent that social norms and goals which govern psychological processes are importantly influenced by culture, patterns of self-regulation should also differ across cultures.

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Self-esteem and face are two ways to instantiate the motivation to be a culturally valued person, and their relative prioritization varies across cultures. These two conceptions of being a good person can be distinguished from each other in a number of ways. One important distinction is with respect to their ease of management. On the one hand, self-esteem is something that is relatively easy to manage as individuals have at least some control over it. People have a variety of self-deceptive tactics at their disposal by which they can interpret self-relevant information in a way that is flattering to themselves. For example, they can attend to and elaborate more on positive informative, they can exaggerate the positivity of their self-assessments, or they can make attributions for their performance in a self-serving way (see Taylor & Brown, 1988, for a review). In Western contexts these can be viewed as adaptive strategies, as they bring the self closer to the culturally valued goal of having a positive view of one’s self. These various self-deceptive tactics can be seen as examples of an approach motivation, as they are all consistent with the goal of securing positive information about the self. People who are self-enhancing work towards securing a positive self-view and largely ignore, or discount, information that would threaten this conception. According to this view, approach motivation is integral in Westerners’ attempts to build upon the self-resource that they tend to prioritize: namely, self-esteem. In contrast, compared to self-esteem, face is considerably more difficult to manage. On the one hand, there are few opportunities for people to increase their face because the amount of face that people can claim is determined by their position in the social hierarchy. Such opportunities are limited to occasions in which one moves up the social hierarchy (e.g., a graduate student becomes a professor). On the other hand, face is chronically vulnerable for loss because it is successfully managed only to the extent that the individual is able to live up to the expectations of others—expectations that are often unknown to the individual and that vary depending on the audience. In other words, unlike self-esteem, the fate of one’s face is largely determined by relevant others’ evaluations. For example, if a teacher is perceived as incompetent by students, his or her face as a teacher may be in jeopardy. Hence, face is something that is difficult to gain but easy to lose. To the extent that East Asians are concerned about this inherently vulnerable resource, their self-regulation should be oriented more towards avoiding the loss of face. In other words, an avoidance orientation should be more adaptive for East Asians in their quest to become a culturally valued person (Hamamura & Heine, in press; Heine, 2005). In sum, we propose that different conceptions of what it entails to be a good person and an inherent asymmetry

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between the ease of acquiring self-esteem and of not losing face, give rise to cultural variation in self-regulation. An approach focus is more adaptive and should be more common among North Americans, whereas an avoidance focus is more adaptive and should predominate more among East Asians. This rationale is confirmed by a growing corpus of cross-cultural research. First, there is evidence that people are socialized to develop particular motivational styles in culturally distinct ways from a very young age. For example, in their investigation of Japanese and American mothers’ behaviors, Caudill and Weinstein (1969) identified a strong positive correlation between the frequency of American mothers’ chatting with their babies and their infants’ “happy vocals.” In contrast, there was no correlation between the mothers’ chatting and the babies’ “unhappy vocals.” The American mother thus appears to elicit and reinforce her baby’s happy vocalizations, reflecting an approach orientation in her mothering style. In contrast, the chatting of Japanese mothers was significantly correlated with their babies’ unhappy vocals and not with their happy vocals. Caudill and Weinstein argued that the Japanese mothers’ chatting served to soothe their babies—an effort to eliminate their problems, rather than to approach happy states. Similar findings have been documented from a set of studies in which parents in Taiwan and the United States were interviewed regarding their attitudes towards child rearing (Miller, Wang, Sandel, & Cho, 2002; Miller, Wiley, Fung, & Liang, 1997). The researchers explored the stories that parents often used about the child’s past behaviors to socialize them. European-American parents more frequently described telling stories that focused on a past success of the child. In contrast, the Taiwanese parents were more likely to tell stories about past transgressions of the child (Miller et al., 1997; also see similar findings by Wang, 2004). East Asians thus appear to be socialized to adopt a predominantly avoidance outlook, whereas Westerners are socialized more towards an approach orientation. These cultural differences in socialization are paralleled by many findings for cultural differences in approach– avoidance motivation later in life. For example, Elliot, Chirkov, Kim, and Sheldon (2001) found that AsianAmericans and Koreans were more likely to embrace avoidance personal goals relative to European-Americans. Quite often, for many participants of Asian background, important concerns are to avoid not living up to others’ expectations. Likewise, Lee, Aaker, and Gardner (2000) found that Americans rated a tennis game that was framed as an opportunity to win as more important than one that was framed as an opportunity to avoid a loss, whereas the reverse pattern was observed among Chinese participants.

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Winning is thus not necessarily the name of the game, in some cultures it may be better labeled “not losing.” Similarly, Lockwood, Marshall, and Sadler (2005) found that negative role models—someone that people want to ensure they do not become like—are more motivating for Asian-Canadians, whereas positive role models are more motivating for European-Canadians. The findings of these studies converge across methods to demonstrate that a concern with not failing is of greater motivational significance among East Asians than Westerners. Cultural variation in approach and avoidance motivation is also evident in studies that have explored people’s reactions to successes and failures. On the one hand, successes are diagnostic of one’s strengths and they thus should be particularly motivating for individuals with an approach focus (Idson & Higgins, 2000). Moreover, in Western cultural contexts where motivations to positively distinguish the self from others are prioritized, individuals would fare better by adopting an approach focus to reveal their strengths. According to this reasoning, Westerners who succeed on a task should be more motivated to continue working on the task relative to East Asians. In contrast, failures are diagnostic of one’s shortcomings and these should be especially motivating for those with an avoidance focus (Idson & Higgins, 2000). The identification of shortcomings is particularly informative for the purpose of self-improvement and face management as shortcomings indicate where one’s face might be vulnerable to loss. It follows, then, that East Asians who have failed on a task and have identified a shortcoming should be more motivated to continue working on that task, in an effort to correct the shortcoming, compared to Westerners. This rationale has been confirmed in a number of studies. In one series of studies, Canadians and Japanese participants received either success or failure feedback on a task (Heine et al., 2001). When they were subsequently given an opportunity to work again on that task in private, Canadians who received success feedback persisted longer compared to those receiving failure feedback (replicating a pattern that has been identified in a number of Western studies) (Feather, 1966; Shrauger & Rosenberg, 1970), indicating an approach orientation. In stark contrast, Japanese who received failure feedback persisted longer than those receiving success feedback, indicating an avoidance orientation. Similarly, Oishi and Diener (2003) found that whereas European-American participants who performed well on a task tended to choose the same task over a different task 2 weeks later, such a pattern was not observed among Asian-Americans; that is their successful performance did not affect AsianAmericans’ subsequent choice of which task to choose.

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Again, this is evidence for cultural variation in approach– avoidance motivation. Similarly, much research finds that East Asians tend to view negative feedback as more useful to them, whereas Westerners are more likely to show the opposite pattern (Heine et al., 2000; White & Lehman, 2005). To the extent that cultural differences in approach and avoidance motivation underlie this observed difference, an experimental procedure that manipulates one’s motivation should reverse this pattern. Indeed, when an approach motivation is experimentally induced to Japanese participants (by reading a scenario of someone receiving a bonus for good performance), positive feedback was evaluated as equally useful as negative feedback eliminating the pattern observed in a control as well as in an avoidance condition (a scenario of a salary reduction for poor performance) in which participants evaluated negative feedback to be more useful than positive (Ozaki, 2005). In other words, Japanese evaluations of positive and negative feedback became more similar to Western norms when they explicitly adopted an approach orientation. This suggests that a key reason for cultural differences in the perceived utility of positive feedback relates to chronic cultural differences in approach motivation. Furthermore, manipulations that prime East Asian identity have also been shown to affect approach– avoidance motivation in ways that are parallel to the findings from cross-cultural studies. For example, in one study, Briley and Wyer (2002) gave Hong Kong Chinese a questionnaire that was written either in English or Cantonese. The rationale was that the language should prime bilingual participants’ respective networks of cultural information (Ross, Xun, & Wilson, 2002). They found that those participants who answered the questionnaires in English were more approach focused as indicated by their greater endorsement of approach-oriented proverbs (e.g., “try any doctor when critically ill”), compared to those who answered the questionnaire in Cantonese, who showed greater endorsement of avoidance proverbs (e.g., “ponder your faults and you will avert misfortune”; also see conceptually similar findings from Briley, Morris, & Simonson, 2005). That is, bilingual participants would switch between motivational states depending on the language that they spoke, indicating that their two languages were each associated with motivational states that paralleled the cultural differences. The above studies provide convergent evidence that East Asians are more likely to adopt an avoidance outlook compared with Westerners. However, there is one area of research that consistently reveals the opposite pattern of results. When it comes to taking risks in financial ventures, a number of studies indicate that, relative to Westerners,

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East Asians are more likely to prefer pursuing more risky, although potentially lucrative, strategies. For example, Hsee and Weber (1999) compared the financial decision making of Chinese and Americans in response to a number of hypothetical scenarios. In these studies, when participants were asked to choose between an uncertain loss of a large amount of money (e.g., 50% chance of losing $2000) and a certain loss of a smaller amount of money (e.g., losing $1000 for sure), the Chinese were less risk averse (i.e., they were more willing to take a risk and choose the uncertain option) in comparison with Americans. This pattern of cultural differences was replicated by Mandel (2003) with a prime of independence–interdependence, which suggests that financial risk seeking is associated with feelings of interdependence. Hsee and Weber (1999) explained these findings in terms of a “social cushion” that protects interdependent individuals from financial misfortune. If times go bad, the reasoning goes, people with a stronger social network have a greater social cushion (e.g., friends, extended family) that can help absorb the blow of their misfortune. However, this kind of cushion should only be able to mitigate the impact of financial misfortunes. A social network is of less utility for absorbing the negative consequences of risky behavior that makes one’s health or social reputation vulnerable (Mandel, 2003). Hence, there appears to be an important boundary condition regarding cultural variation in terms of an avoidance focus. In domains, such as making investment choices, where one’s interdependent network can potentially cushion the harmful effects of a loss, East Asians do not show more of an avoidance orientation compared to Westerners.

SUMMARY OF SECTION A growing body of cross-cultural research on approach– avoidance motivation yields a converging set of findings. East Asians tend to adopt more of an avoidance outlook compared with Westerners. These cultural differences have been identified with a number of different East Asian and Western samples, with a wide variety of different experimental methods, and for a number of domains, with the important exception of investment choices.

CROSS-CULTURAL RESEARCH OF PHENOMENA IMPLICATED IN AN APPROACH–AVOIDANCE FRAMEWORK The distinction of approach–avoidance motivation is an integral aspect of many psychological theories (Cacioppo, Gardner, & Berntson, 1999; Elliot & Church, 1997;

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Higgins, 1997). As such, the observed cultural variation in approach and avoidance motivation allows for the generation of a number of novel hypotheses regarding cultural differences in a variety of psychological phenomena. We discuss some of these below.

REGULATORY FIT Much recent research has suggested that regulatory fit, or the concordance between one’s chronic regulatory focus (approach or avoidance focus) and the regulatory strategy that is demanded by a particular task at hand (e.g., trying to win or trying to prevent a loss) serves to boost one’s motivation (Aaker & Lee, 2006; Higgins & Spiegel, 2004). To the extent that there are cultural differences in chronic regulatory focus, it follows that the framing of tasks will affect East Asians and Westerners differently. For example, when Canadian and Japanese participants were instructed that performance on a puzzle was to either be monetarily rewarded for each correct response (approach condition) or punished for each incorrect response (avoidance condition), Canadians were able to perform better on the puzzle in the approach condition relative to the avoidance condition. In contrast, Japanese tended to perform better in the avoidance condition compared to the approach condition (Hamamura & Heine, 2006). This demonstrates that regulatory fit is associated with positive motivational consequences across cultures although Canadians and Japanese differ in terms of what kinds of strategies tend to fit better with their chronic orientations. In contrast, situations where one’s chronic regulatory focus is mismatched with the demands of a task may give rise to negative consequences. One such potential negative consequence is in terms of health outcomes. Much prior research conducted in North America reports a link between having an avoidance focus and poor physical and mental health (Elliot & Sheldon, 1997; Elliot & Sheldon, 1998). One possible conclusion is that this relation reflects some universal disadvantages associated with an avoidance focus. However, another possibility is that this relation reflects the consequences of having a mismatch between culturally encouraged approach orientations among Westerners and an individual-level avoidance focus. Perhaps having goals that are at odds with dominant cultural values leads to negative outcomes because of a lack of regulatory fit. This latter alternative suggests that the negative health consequences that have been observed among Western individuals with an avoidance focus should not be as prevalent among East Asians. A few studies find evidence that is consistent with this

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reasoning. For example, Elliot et al. (2001) found that an avoidance orientation was not a negative predictor of subjective well-being for Asian-Americans or Koreans, although it was for Americans. Likewise, Takagi (2005) found that whereas avoidance personal goals were predictive of greater loneliness and worse health outcomes among Canadians, they actually predicted lower levels of loneliness and better health among Japanese. Furthermore, Heine and Lehman (1999) found that a correlation between an actual-ideal self-discrepancy (which indicates the extent to which one is failing at an approach goal) and depression was significantly weaker among Japanese compared to Canadians, suggesting that unsatisfied approach motivation was less of a problem for Japanese individuals. In sum, these studies indicate that negative mental and physical health outcomes of particular kinds of regulatory focus that are found among North Americans are largely absent among East Asians. These findings suggest that such negative outcomes might arise from a lack of regulatory fit rather than being due to an avoidance orientation per se.

TEMPORAL CONSTRUAL Approach and avoidance motivations have also been linked to temporal construals. Temporal construal theory states that future events are construed differently depending on their temporal distance, that is, distant future events tend to be represented in an abstract, general, and decontextualized manner, whereas, in contrast, nearfuture events tend to be represented in a concrete and contextualized manner (Trope & Liberman, 2003). A recent study has demonstrated that an approach focus is more common when a distant future perspective is taken, whereas an avoidance focus comes to predominate when a near future perspective is adopted (Pennington & Roese, 2003; see also Forster & Higgins, 2005). The rationale is that the concern with security that characterizes an avoidance focus is better achieved when people direct their attention to concrete aspects of events where potential threats might lie. On the other hand, the concern with growth which characterizes an approach focus is better achieved; people concentrate on abstract aspects of events where opportunities for growth can be more commonly found. This line of research suggests that there may be potential cultural differences in temporal construals. It follows that East Asians, with their relatively more dominant avoidance orientation, should tend to be more near-future oriented in their construal of future events. In contrast, Westerners, with a more pronounced approach orientation,

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should be relatively more distant-future oriented. A few preliminary studies have found evidence for such a pattern. For example, Hamamura and Heine (2006) found that the personal goals of Japanese tend to be of a shorter time frame relative to the personal goals of Canadians (i.e., goals that can be achieved in days and weeks as opposed to months and years). Likewise, Lee (2006) reported that when Asian-Americans and Koreans were asked to imagine an event that they would be responsible for organizing, they tended to assume that it would occur nearer in the future (e.g., the event will take place in 2 weeks) compared to European-Americans who tended to have more distant future orientations (e.g., 2 years from now). Hence, preliminary findings suggest that temporal construal is another phenomenon that is implicated by cross-cultural research on approach–avoidance motivation.

ANTICIPATING FUTURE EVENTS Cultural differences in approach–avoidance motivation also have implications for how people from different cultures anticipate future events. Whereas anticipating positive events should enhance the motivation of those with an approach focus, anticipating negative events should be more motivating and lead to more productive outcomes among those with an avoidance focus (Grant & Higgins, 2003). Consistent with this rationale, cross-cultural research has found greater optimism for Westerners relative to East Asians (Lee & Seligman, 1997). For example, Heine and Lehman (1995) found that, compared to Canadians, Japanese were less optimistic in that they were much less likely to believe that positive events (e.g., living past the age of 80, owning a home sometime in the future) would happen to them. Furthermore, Japanese were more pessimistic than Canadians in that they were more likely to believe that negative events (e.g., have a heart attack before the age of 50, drop out of university) would happen to them. Other studies have found further support for this cultural difference (Chang & Asakawa, 2003; Hamamura, Heine, & Takemoto, 2007). In sum, North Americans and East Asians differ in terms of the kinds of future events they anticipate as cultural variation in approach–avoidance motivation would predict.

MOTIVATED INFORMATION PROCESSING Another area where the application of the approach– avoidance motivation distinction has been fruitful is the field of information processing. Prior research has identified that a chronic motivational orientation sensitizes one to stimuli that are consistent with their orientation

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(i.e., approach focused individuals should become more sensitive to stimuli that are framed in terms of the presence or absence of positive outcomes). Moreover, research shows that this pattern extends even to stimuli that are not relevant to the self. For example, Higgins and Tykocinski (1992) found that when chronically approach and avoidant oriented participants read a list of events that a stranger had experienced, approach-oriented individuals recalled more events pertaining to the presence or absence of positive outcomes (e.g., finding a $20 bill on street, or finding that a movie one wanted to see was no longer showing) whereas avoidance oriented individuals recalled more events pertaining to the presence or absence of negative outcomes (e.g., getting stuck in the subway, or having an unpleasant class canceled). Attending to the approach–avoidance distinction provides a foundation for predicting cultural variation in information processing. Specifically, Westerners with a more chronic approach focus should be more sensitive to information pertaining to positive rather than negative outcomes whereas East Asians, with a more chronic avoidance orientation should show the opposite preference. A few studies support this rationale. For example, in a study of autobiographical memory, Endo and Meijer (2004) found that, among Americans, memories of successes were more accessible relative to memories of failures. In contrast, among Japanese, memories of successes and failures were equally accessible. In addition, Endo and Meijer (2004) found that Americans perceived the positive impact of their success memories to be greater than the negative impact of their failure memories, whereas Japanese showed the opposite pattern. This difference in information processing may even affect people’s evaluations of their subjective well-being. Oishi (2002) found that European-Americans’ overall satisfaction ratings across a week were better predicted by the level of satisfaction that was reached in their happiest day of the week. In contrast, for Asian-Americans, their overall satisfaction was better predicted by the level that was reached in their unhappiest day of the week. In a crosscultural replication of Higgins and Tykocinski (1992), Meijer, Heine, and Yamagami (1999) found that after studying a list of events that happened in a stranger’s life, Japanese participants better recalled information pertaining to negative outcomes, whereas Americans had better recall for information regarding positive outcomes. Likewise, Hamamura and Heine (2006) extended this research by investigating people’s recall of movie reviews. They found that Japanese participants recalled movie reviews that were framed in terms of the presence or absence of negative information relatively better. In

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contrast, Canadians tended to have better recall of reviews framed in terms of the presence or absence of positive information. Similarly, Aaker and Lee (2001) found that Hong Kong Chinese had better recall for the details from a tennis match when the game was framed as preventing a loss whereas European-Americans exhibited better recall when the game was framed as an opportunity to win. In sum, these studies provide converging evidence that cultural variation in approach–avoidance motivation orientation affects memory in predictable ways.

EMOTIONAL CONSEQUENCES Much research has revealed that approach and avoidance motivations are associated with different emotional states. Specifically, emotional experiences associated with approach motivation tend to be located along a dimension that ranges from cheerfulness to dejection (e.g., happy, disappointed). In contrast, the emotional experiences that are associated with an avoidance focus tend to fall along a dimension that runs from relaxation to agitation (e.g., calm, uneasy) (Carver and Scheier, 1998; Higgins, Shah, & Friedman, 1997; Mowrer, 1960). The different emotional consequences of approach and avoidance motivation predict that there should be cultural variation in the kinds of emotions that people experience and seek. For example, Lee et al. (2000) found that when Americans reacted to a scenario of a tennis match, they more strongly experienced emotions that were associated with an approach motivation (i.e., happiness, dejection) compared with those associated with an avoidance focus (i.e., relaxation, agitation). In contrast, Chinese participants showed the precise opposite pattern, and experienced avoidance related emotions more strongly than they did approach related emotions. This proposed cultural difference in emotional experience has also been observed in recent research by Tsai and her colleagues (Tsai, Knutson, & Fung, 2006a; Tsai, Louie, Chen, & Uchida, 2006b; Tsai, Miao, & Seppala, 2007). They propose that cultures vary in the kinds of emotional states that people are motivated to pursue something which they term “ideal affect.” Westerners, they argue, are more likely to seek out high arousal positive (HAP) emotional states, such as feeling enthusiastic, or excited. These states would seem to parallel those achieved through the successful completion of approach goals. In contrast, East Asians, they argue, strive to attain low arousal positive (LAP) emotional states, such as feeling calm and relaxed. These parallel those states achieved by successfully completing avoidance goals.

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Evidence for these cultural differences has been found in several studies. For example, Chinese were found to value LAP emotions more and HAP emotions less compared with Americans (Tsai et al., 2006a). Furthermore, these preferred emotional states appear to be learned through socialization. An investigation of best selling children’s storybooks in Taiwan and the United States revealed that Taiwanese storybooks contained more characters with calm expressions, and who were engaged in less arousing activities, compared to American storybooks, and children preferred those characters who demonstrated the culturally appropriate emotions (Tsai et al., 2006b). Further evidence for this cultural difference has been identified in the dominant religious teachings and practices of the respective cultures. A content analysis of classic Christian and Buddhist texts (e.g., the Gospels of the Bible and the Lotus Sutra), as well as contemporary Christian and Buddhist self-help books, revealed that high arousal states were encouraged more in the Christian texts whereas the low arousal states were more encouraged in the Buddhist texts. Moreover, Tsai and colleagues noted that some Christian sects include enthusiastic religious practices such as jumping, shouting, and applause, whereas Buddhist religious practices more often emphasize meditation and the calming of one’s mind (Tsai et al., 2007). In sum, these studies indicate that different emotional states are preferred across cultures, and these are consistent with predictions that are derived from cultural variation in approach–avoidance motivation.

SUMMARY OF SECTION Approach–avoidance motivation has been found to implicate a number of psychological phenomena. Given the cultural variability that has been documented with respect to approach and avoidance orientations, it follows that East Asians and Westerners should also differ in terms of the various phenomena that are influenced by different motivational outlooks. Convergent cross-cultural differences have been documented for studies of regulatory fit, temporal construal, optimism and pessimism, motivated informational processing, and emotional consequences.

MECHANISMS UNDERLYING CROSS-CULTURAL VARIATION IN APPROACH–AVOIDANCE MOTIVATION As reviewed above, many studies have found evidence for cross-cultural variation in approach–avoidance motivation and in psychological phenomena that are implicated by the respective motivations. However, it is important to

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underscore that these cultural differences do not suggest that either type of motivation is absent across cultures. Indeed, the distinction between approach and avoidance motivation is evident across species, even for the most basic organisms (e.g., amoebas), underscoring the fundamental role both modes of motivation play for many, if not all, living organisms (Elliot, 1999). It seems reasonable to assume that the two modes of motivation are functional universals, or mental process that universally serve the same function, although their accessibility may differ importantly across cultures (Norenzayan & Heine, 2005). To the extent that approach–avoidance motivation is universally available, it suggests that observed cultural differences could be reduced or even reversed with appropriate experimental manipulations. Cross-cultural studies that investigate how the correlates of approach and avoidance motivation are influenced by various manipulations are critical for identifying the mechanisms that underlie these motivations. This is one way that cultural variation can be used to inform the nature of universal theories: it serves to spotlight where one should more effectively target the search for mechanisms. Whatever variables underlie observed cultural differences in motivations likely play a key role in the manifestation of the motivations in other contexts as well. For example, one way to consider why East Asian and Western cultures differ in their reliance on approach and avoidance motivation is to explore another variable for which East Asians and Westerners have been shown to reliably differ: lay theories of achievement (Dweck & Leggett, 1988). Many studies have found evidence for heightened entity theories of achievement among Westerners compared with East Asians (Norenzayan, Choi, & Nisbett, 2002; Stevenson & Stigler, 1992). How might entity theories of achievement be associated with an approach motivation? To the extent that people view abilities as largely fixed and entity-like, it follows that they should not devote much effort towards tasks in which they perform poorly. Entity theorists would fare better by avoiding tasks in which they fail, as future efforts would be unlikely to lead to successes. In contrast, entity theorists should focus their effort on tasks in which they perform well, as they will likely continue to succeed on those tasks in the future. Hence, entity theorists are able to approach positive outcomes by devoting effort to tasks at which they are especially talented. On the other hand, incremental theorists would seem to fare better by devoting their effort to those tasks for which there is the most room for improvement. Future failures can be avoided if one is able to improve one’s abilities on the tasks by making sufficient efforts. If this reasoning is correct,

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entity theorists should be more likely to demonstrate an approach motivation and incremental theorists should evince more of an avoidance motivation. One study tested this hypothesis by manipulating American and Japanese participants’ theories of achievement (Heine et al., 2001, Study 3). Participants in one condition were led to believe that a task had an incremental basis (i.e., trying harder would improve one’s performance), whereas those in another condition were led to believe the task had an entity basis (i.e., performance was largely unrelated to efforts). A third condition, a control group, received no manipulation. Participants’ persistence on a task following failure was then assessed. For Americans, the entity manipulation had no effect on their performance: they persisted as long on the task if they had received entity instructions as they did in the control group. Apparently, the entity instructions were redundant with most American participants’ lay theory of achievement regarding this task. In contrast, Americans who received incremental instructions persisted significantly longer on the task, suggesting that the incremental instructions heightened American participants’ avoidance focus. On the other hand, Japanese who received incremental instructions persisted as long as those who were in the control group; these instructions did not appear to contain novel information to them. In contrast, Japanese who received the entity instructions persisted less than those in the other conditions, suggesting that the instruction heightened their approach focus. In sum, manipulations of lay theories yield parallel findings as those from previous cross-cultural studies, and suggest that entity theorists should be more likely to demonstrate approach motivations, whereas incremental theorists should be more likely to demonstrate avoidance motivations. Cultural differences in approach and avoidance orientations have also been explained in another way. The most commonly discussed psychological difference between East Asians and Westerners is that East Asians tend to view the self as part of an interdependent network, whereas Westerners more commonly view the self as an independent agent (Markus & Kitayama, 1991). Could these cultural differences in self-concept help make sense of the observed cultural differences in approach–avoidance motivation? In one study, Lee et al. (2000, Study 3) contrasted how Americans viewed a tennis game depending on whether it was described as a team event (which should prime thoughts of interdependence) or as a solo event (which should prime thoughts of independence). When Americans received the interdependence prime, they viewed tennis games framed as an

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opportunity to avoid a loss as more important than those games framed as opportunities for victories—the precise pattern that Lee et al. had demonstrated among Chinese. Another source of evidence that cultural differences in the self-concept underlie differences in approach–avoidance motivation comes from research on regulatory fit. Regulatory fit theory, as discussed earlier, suggests that a fit between regulatory focus that a particular task at hand demands (i.e., approaching a success or avoiding a failure) and people’s chronic motivation focus (i.e., approach or avoidance) serves to intensify emotional and motivational reactions (Aaker & Lee, 2006; Higgins & Spiegel, 2004). To the extent that independence and interdependence are associated with approach and avoidance motivations, respectively, it follows that when independence is primed people should experience regulatory fit with approach stimuli, whereas when interdependence is primed people should experience regulatory fit with avoidance stimuli. This rationale was tested in a study by Aaker and Lee (2001). They had participants evaluate a product that was presented to them either in approach or avoidance terms (i.e., participants were asked to focus on the presence or absence of positive or negative qualities) after they were primed with independence or interdependence. The participants had a more favorable evaluation of the product presented in approach terms under the independence priming whereas the product presented in avoidance term was evaluated more favorably in the interdependence condition. These studies suggest that self-concept is importantly related to approach–avoidance orientation.

SUMMARY OF SECTION Cultural variation in psychological processes can serve to spotlight the underlying mechanisms of those processes. Knowing that East Asians are more likely to adopt an avoidance orientation compared with Westerners has led to research that demonstrates that avoidance orientations are facilitated by other variables which are more characteristic of those from East Asian cultures: namely, incremental theories of abilities and interdependent self-concepts.

CONCLUSION The distinction of approach and avoidance orientations provides new insight into cross-cultural research on motivations. We suggest that cultural differences exist in approach–avoidance motivation because cultures shape the kinds of self-resources that people come to prioritize.

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In Western contexts, people come to prioritize a self-view that includes the sense that one is an autonomous and self-sufficient entity; a view that is fostered by having high self-esteem. Furthermore, self-esteem is a resource that is accumulated relatively easily given people’s abilities to selectively attend to information that bolsters it. For this reason, a chronic approach focus is favored. In contrast, in East Asian contexts, people come to favor a self-view that includes the sense that one maintains a valuable position within a social network; a view that is fostered by successfully maintaining one’s face. Because face, in comparison with self-esteem, is a resource that is always vulnerable as it is subject to the whims of others in one’s social network, a habitual avoidant outlook is more functional. These different ways of evaluating the self importantly shape the relative predominance of approach and avoidance motivation across cultures. Approach and avoidance motivations are fundamental and universal psychological processes. It is precisely these kinds of core psychological processes which should provide some of the most interesting vistas from which to observe how the mind is shaped by culture. As the research reviewed in this chapter reveals, many of the identified differences in the ways of thinking between East Asians and Westerners can be better understood by considering them from the perspective of approach–avoidance motivation. Although approach and avoidance motivations are universally available, that they are prioritized differently across cultures leads to an array of different psychological consequences that cut across a number of topics of research that are typically viewed as largely unrelated. East Asians are more likely to chronically take on an avoidance perspective than are Westerners, and this increasingly well-documented fact can help to explain why a wide variety of other psychological differences emerge between the two cultures.

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Stereotyping Interactions: Approach 34 Interracial and Avoidance E. Ashby Plant and Patricia G. Devine CONTENTS Approach and Avoidance Motivation ....................................................................................................572 Majority Group Perspective ..................................................................................................................572 Choosing to Approach or Avoid Interracial Interactions .................................................................572 Within Interracial Interactions: Approach and Avoidance Goals .................................................... 574 Internal and External Motivation to Respond Without Prejudice .................................................... 574 Self-Reported Goals and Strategies for Interracial Interactions ........................................................... 575 Activation of Approach and Avoidance Upon Exposure to Black Faces ..............................................577 Implications of Approach and Avoidance Orientation for Interracial Interactions .............................. 578 Minority Perspective .............................................................................................................................579 Choosing to Approach or Avoid Interracial Interactions .................................................................579 Within Interracial Interactions: Approach and Avoidance Goals ....................................................580 Bringing It Together: Dynamic Interactions ......................................................................................... 581 References .............................................................................................................................................582

In today’s increasingly diverse society, people have the opportunity to interact with individuals from many different racial and ethnic groups. Historically in the United States, society was segregated, which effectively limited interracial contact. When interracial contact occurred, it was often not by choice (e.g., African Americans forced to serve Whites) and almost always involved clear roles and scripts for how to behave in the interaction. In contemporary society, however, not only are interracial interactions likely more frequent, people typically have at least some choice as to whether or not they interact with outgroup members. That is, people may choose to approach interracial interactions or avoid them. Of course, there are also times that, regardless of whether one would choose to interact, interracial interactions are unavoidable. Furthermore, interracial interactions are less often scripted in contemporary society, though at the same time, strong norms discouraging expressions of prejudice exist. With no clear scripts to guide interactions and no way to divine

others’ intentions or attitudes, interracial interactions in contemporary society create new challenges to interactants, often making the road to intergroup interactions rocky and difficult to traverse (Devine & Vasquez, 1998). Recent years, however, have witnessed an everburgeoning literature addressing the nature of these challenges from the perspective of majority as well as minority group members. In reviewing and synthesizing this literature, we have found the distinction between approach and avoidance motivation to provide a useful framework for identifying the nature and consequences of these new challenges. Hence, in the current chapter, we consider how approach and avoidance motivations play out in interracial contexts in determining (1) whether people chose to interact and (2) how they regulate their behavior in interracial contexts. In exploring these issues, we consider the experiences of White people interacting with racial and ethnic minority group members as well as the experiences of people from ethnic and racial minority groups interacting with White 571

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people. Although we believe that many of the same factors influence the experiences for both groups (e.g., expectations concerning the quality of the interaction, anxiety about the interaction), we believe there are also some important differences in the self-regulatory challenges members of these groups face in interracial interactions (e.g., being the historic target vs. perpetrator of racial bias). In what follows, we first consider general issues of approach and avoidance motivation in the context of selfregulation. We then review relevant research on interracial interactions using the framework of approach and avoidance motivation. We first consider interracial interactions from the majority group perspective and then consider the minority group perspective. Although we review these literatures separately, ultimately the implications of approach and avoidance motivations play out in the context of intergroup settings in which people have to interact with each other. Therefore, we conclude by considering the implications of approach and avoidance for dynamic interactions.

APPROACH AND AVOIDANCE MOTIVATION As reviewed in the introductory chapter of this volume (Elliot, 2008), an important distinction is made in classic and contemporary motivation and self-regulation theories between motivational systems that focus on approaching desired end-states and those that focus on avoiding undesired end-states (Atkinson, 1964; Carver & Scheier, 1998). The motivation to approach a desired end-state produces interest in and the active pursuit of the end-state and the adjustment of behavior to reduce the discrepancy between current behavior and the desired end-state. As such, people motivated to achieve a desired end-state tend to pursue success-related behaviors, such as persistence in the face of failure and setting realistic, approach-related goals (Atkinson & Litwin, 1960; Elliot & Church, 1997; Elliot & Harackiewicz, 1996; Feather, 1967; Hembree, 1988; Mahone, 1960). The motivation to avoid an undesired end-state, in contrast, produces the tendency to avoid performing actions that are expected to produce the undesired end-state and the adjustment of behavior to amplify the discrepancy between current behavior and the undesired end-state. People who are motivated to avoid an undesired end-state tend to set avoidance-related goals and to pursue behaviors that are likely to provide an excuse for failure, presumably in an attempt to avoid negative implications for the self-concept (Atkinson & Litwin, 1960; Elliot & Church, 1997; Feather, 1967; Hembree, 1988; Mahone, 1960). We believe that conceptualizing interracial interactions in terms of approach and avoidance motivations

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provides a useful approach for understanding challenges faced by majority and minority group members in such interactions. These motivational concerns are reflected, we posit, in people’s decisions about whether to enter into intergroup interactions and, if they engage in interracial interactions, their goals and primary concerns for these interactions. People’s decision to engage in or avoid interracial interactions can be framed as the decision to approach a positive end-state or avoid a negative endstate. Further, in considering whether people possess approach or avoidance motivation when they engage in interracial interactions, it is important to reflect upon what people are likely trying to accomplish in interracial interactions. For example, in regulating their responses in intergroup interactions, some people may be primarily focused on having a positive interaction. To this end, they pursue the goal of treating their interaction partner in a fair, friendly manner (i.e., approach a desired end-state). Others, however, may be primarily concerned with preventing a negative interaction and therefore, may be focused on the potential for a negative interaction. In interracial interactions, the concern with bias or prejudice (either being the perpetrator or target of bias) may be a salient undesired end-state. As a result, people focused on the potential for a negative outcome may pursue the goal of avoiding negative outcomes during the interaction (i.e., avoid an undesired end-state). Such concerns could have implications for a variety of issues beyond whether people enter interracial interactions, including for example, their perceived quality of the interaction, the interaction partner’s perceived quality of the interaction, the dynamics of ongoing interactions, and whether people wish to pursue subsequent interracial interactions. With these considerations as a backdrop, we now review some of the literature on interracial interactions using this approach and avoidance motivation framework. For both the majority and minority group perspective, we first reflect upon the decision of whether or not to enter interracial interactions and then the implications of approach and avoidance motivations for responses within the context of an interaction.

MAJORITY GROUP PERSPECTIVE CHOOSING TO APPROACH OR AVOID INTERRACIAL INTERACTIONS As noted above, in contemporary society people often have the choice whether or not they want to participate in interracial interactions. For White people, there seem to be two key factors that are likely to contribute to a desire

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Interracial Interactions: Approach and Avoidance

to avoid interracial interactions, racial antipathy and a concern that the interaction will not go well. Not surprisingly, there is some evidence that White people who possess more negative attitudes toward Black people (either implicitly or explicitly) tend to report having less contact with Black people (Brigham, 1993; Levin, van Laar, & Sidanius, 2003; Towles-Schwen & Fazio, 2001, 2006). Similarly, White, non-Hispanic people who report negative attitudes toward Hispanic people also report a greater desire to avoid interacting with Hispanic people than those with less negative attitudes (Plant, Butz, & Tartakovsky, in press). As for the impact of implicit prejudice, Towles-Schwen and Fazio (2006) found that automatically activated negative attitudes among Whites were associated with a shorter duration of roommate relationships with Black roommates. Thus, negative attitudes toward outgroup members are likely to be one factor that contributes to the avoidance of interracial contact. However, negative attitudes toward the outgroup are not the only source of outgroup avoidance. A major factor in determining whether White people report that they want to avoid interracial interactions is their expectations about the likely outcome of such interactions. If White people anticipate that interracial interactions will go poorly and be unpleasant, these negative outcomes can be a salient negative end-state that White people may desire to avoid. Consistent with this idea, White people who are concerned that interracial interactions will not go well tend to report a heightened desire to avoid interracial interactions (Britt, Boniecki, Vescio, Biernat, & Brown, 1996; Gudykunst, 1993; Plant, 2004; Plant & Butz, 2006; Plant & Devine, 2003; Plant & Devine, 2007; Shelton & Richeson, 2005; Vorauer, 2006; Vorauer, Main, & O’Connell, 1998) and given the chance, will actually avoid such interactions (Plant & Devine, 2003). Further, there is some evidence that this influence of expectancies on avoidance is due to the impact of negative expectancies on interracial anxiety (Plant & Devine, 2003). White people who anticipate that interracial interactions will go poorly tend to report heightened anxiety about these interactions which, in turn, predicts the tendency to avoid them. Anxiety is related to avoidance of intergroup interactions even when controlling for intergroup attitudes, indicating that attitudes and expectancies/anxiety have independent contributions to the decision to approach or avoid intergroup contact (Plant et al., in press). It is also worth noting, however, that not all who are anxious will avoid interracial contact. There is some evidence that White people who are personally, internally motivated to respond without prejudice will not avoid interracial interactions even if they are anxious about them (Plant, 2004).

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In identifying the nature of the negative expectations that White people have regarding interracial interactions, recent work has begun to clarify the types of negative endstates that White people may be trying to escape when avoiding interracial interactions. In general, these negative expectancies revolve around concerns about the likelihood that the interaction will end poorly and that the outgroup member will view the person in a negative manner. Vourauer and colleagues have identified the importance of concerns among White people that outgroup members will stereotype them based on the negative stereotype of Whites as prejudiced (i.e., the meta-stereotype; Vorauer, 2006; Vorauer et al., 1998). Such evaluative concerns have a range of negative implications for intergroup interactions including avoidance. Shelton and Richeson (2005) found that White people explained their avoidance of interactions with Black people as being due to fear of rejection, indicating that interracial avoidance may serve the purpose of averting the highly negative experience of being socially rejected. Plant and Butz (2006; also see Butz & Plant, 2006) demonstrated that low levels of selfefficacy regarding one’s ability to respond in a nonbiased manner during interracial interactions predicted avoidance. Specifically, being concerned that they would come across as racially biased during interracial interactions caused White people to both desire to avoid an upcoming interaction with a Black person and, after having participated in the interaction, wish to avoid future interactions with that outgroup member. For these people, the potential of being viewed in a racially biased manner likely represented a highly negative end-state that they were driven to avoid even if it meant cutting off contact with the outgroup member. There is somewhat less evidence regarding what increases White people’s tendency to approach interracial interactions. Presumably, low levels of those factors that contribute to avoidance would likely lead to a higher likelihood of approach (e.g., positive attitudes toward outgroup members would increase approach), but the absence of avoidance does not necessarily lead to active approach of interracial contact. There is some evidence, however, that White people with more positive expectations about the outcome of interactions reported having more positive interracial contact during the subsequent 2 weeks than those with more negative expectations (Plant, 2004). Thus, expecting positive outcomes from interracial interactions can lead people to approach them. Plant (2004) also found that people who reported that it is personally important for them to respond without prejudice (i.e., the internally motivated) were more likely to have positive interactions with Black people over the following 2 weeks

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and were less interested in avoiding interactions with Black people. Moreover, for those who are internally motivated, interracial interactions may represent a chance to respond consistently with their personal standards and approach their nonprejudiced identity (Brodish & Devine, 2007).

WITHIN INTERRACIAL INTERACTIONS: APPROACH AND AVOIDANCE GOALS The complexities of interracial interactions do not end with the decision to engage in an interaction or avoid it altogether. After choosing to engage in an interaction with an outgroup member or being required to interact if the situation does not permit avoiding it, White people must decide how to manage the interracial interaction. That is, they must determine their goal for the interaction (e.g., make a new friend, avoid angering the new boss) and how best to respond during the course of the interaction to meet the interaction goal. If White people are motivated to have a positive interaction or simply to avoid a negative interaction, they must decide how best to bring the outcome to fruition. The research on approach and avoidance motivation suggests that whether people chose to focus on approaching a positive interaction or avoiding a negative interaction is likely to have a range of implications for their self-regulatory choices within the interracial interaction as well as the likelihood of meeting their goal. In considering whether White people possess an approach or avoidance motivation when regulating behavior in interracial interactions, it is important to reflect upon what they are likely trying to accomplish in interracial interactions. To the extent that White people are primarily focused on having a positive interaction, they may pursue the goal of treating their interaction partner in a pleasant, egalitarian manner (i.e., approach a desired end-state). In contrast, to the extent that White people are primarily concerned with preventing a negative interaction and, therefore, may be focused on the potential for a negative interaction, responding with racial bias is likely to be a highly salient undesired end-state. As a result, they may pursue the goal of avoiding negative outcomes and prejudiced behavior during the interaction (i.e., avoid an undesired end-state). We suggest that in interracial interactions, whether White people are primarily concerned with approaching a desired end-state of a pleasant interaction or avoiding an undesired end-state of overt bias in the interaction depends the reasons underlying their motivation to respond without prejudice. Plant and Devine (1998)

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argued that in examining the regulation of prejudice, it is important to consider not only whether people are motivated, but also the reasons why they are motivated to respond without prejudice. For example, some people are strongly motivated to respond without prejudice in interracial interactions because they possess personally important nonprejudiced beliefs (Devine, 1989; Devine & Monteith, 1993, 1999; Devine, Monteith, Zuwerink, & Elliot, 1991; Plant & Devine, 1998). It is also possible to be strongly influenced by social norms discouraging the expression of bias in interracial interactions and to be motivated to control the expression of prejudice to avoid negative reactions from others (Crandall, Eshleman, & O’Brien, 2002; Dunton & Fazio, 1997; Plant & Devine, 1998). We posit that these distinct reasons for responding without prejudice will have important implications for regulatory behavior in interracial settings. More specifically, our emerging program of research leads us to suggest that these different reasons for responding without prejudice lead to regulatory efforts that reflect approach and avoidance orientations. It should be noted that because we are arguing that individual differences in the reasons underlying people’s motivation to respond without prejudice has implications for their motivational tendencies (approach or avoidance) in the context of interracial interactions, the language can become awkward (motivation resulting in motivation). As a result, throughout this chapter, we frequently refer to approach and avoidance motivational tendencies as orientations. In what follows, we first review some of the previous work on internal and external motivation to respond without prejudice and then outline how they may map onto approach and avoidance orientations for the regulation of racial bias.

INTERNAL AND EXTERNAL MOTIVATION TO RESPOND WITHOUT PREJUDICE In order to capture these distinct reasons for responding without prejudice, Plant and Devine (1998) developed and validated two scales, the internal (personal) motivation to respond without prejudice scale (IMS) and the external (normative) motivation to respond without prejudice scale (EMS) (Plant & Devine, 1998). Plant and Devine demonstrated that the IMS was highly correlated with traditional measures of prejudice, such that higher levels of internal motivation were associated with lower prejudice scores. The EMS, in contrast, was only modestly correlated with traditional prejudice measures such that high levels of external motivation were associated with high prejudice scores. In addition, only a small

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correlation was found between the EMS and measures of social evaluation (e.g., Leary, 1983, Interaction Anxiety Scale), suggesting that the EMS assesses a specific concern with how prejudiced responses will be evaluated rather than a general concern with social evaluation. Also providing evidence of the discriminant validity of the scales, neither the IMS nor the EMS was related to measures of social desirability (Crowne & Marlowe, 1960) or self-monitoring (Snyder & Gangestad, 1986). Moreover, the IMS and EMS were found to be largely independent (average r = −.14). Thus, people can be motivated to respond without prejudice primarily for internal reasons, primarily for external reasons, for both internal and external reasons, or they may not be particularly motivated for either type of reason. We propose that internal motivation to respond without prejudice results in an approach orientation in interracial interactions whereas external motivation to respond without prejudice results in an avoidance orientation. Consider that highly internally motivated people want to respond without prejudice in order to respond consistently with personally important nonprejudiced values. That is, they want to approach a desired end-state of pleasant, egalitarian responding. People externally motivated, in contrast, want to respond without prejudice in order to avoid negative reactions from others. Their primary concern is with avoiding an undesired end-state of biased responding that would result in social disapproval. These distinct approach and avoidance motivational tendencies should have implications for White people’s goals in interracial interactions (Carver & Scheier, 1998; Elliot, Gable, & Mapes, 2006; Higgins, 1997). In addition, people should be particularly drawn to strategies for interracial interactions that address their motivational concerns (Elliot, 2006; Shah, Higgins, & Friedman, 1998). Consistent with this argument, Plant and Devine (2008) explored people’s efforts to regulate their racial bias for an upcoming interracial interaction and the intentions underlying their self-regulatory efforts. White participants were presented with an opportunity to work on a computer program that they were led to believe would help them to respond without prejudice during the interaction. When participants were led to believe that the program would reduce detectable, overt racial bias that would be apparent to their Black partner in an upcoming interracial interaction, White participants who were highly externally motivated to respond without prejudice spent more time on the program than those less externally motivated. Such efforts are consistent with a desire to avoid an undesired end-state of racial bias and the

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resulting social sanction for the upcoming interaction. In contrast, when the program was framed as eliminating bias that would be unlikely to be detected by others but could still result in a subtle bias, only highly internally motivated participants who anticipated that bias was a possibility in the interaction spent extensive time working on the program. This type of response is consistent with the intention of being free of all bias and thereby, approaching true egalitarian responding. Brodish and Devine (2006) further demonstrated that among individuals who are externally motivated, those who were also internally motivated were more likely to endorse, activate, and pursue the goal to reveal their nonprejudiced identity in interracial interactions. Thus, they seemed to be focused on approaching an impression in the interaction consistent with their egalitarian selfconcept. In contrast, participants who were primarily externally motivated to respond without prejudice were more focused on pursuing the goal of concealing their prejudice; that is, avoiding a prejudiced impression. These previous findings are consistent with our suggestion that internal motivation to respond without prejudice results in an approach orientation for interracial interactions and external motivation to respond without prejudice results in an avoidance orientation for interracial interactions. However, the previous work does not provide a direct link between our individual difference measures and approach and avoidance motivations. Moreover, the previous work does not demonstrate how these motivational approaches to interracial interactions play out in people’s goals and strategies for the interactions. Below, we provide some initial evidence linking internal motivation to an approach focus and external motivation to an avoidance focus for interracial interactions (Plant & Devine, 2007). The first study examines whether White people’s source of motivation to respond without prejudice is related to their self-reported goals and strategies in interracial interactions with Black people. The second study examines the extent to which approach and avoidance goals are automatically activated upon exposure to Black and White faces as a function of White people’s source of motivation to respond without prejudice.

SELF-REPORTED GOALS AND STRATEGIES FOR INTERRACIAL INTERACTIONS As a first step in exploring these issues, Plant and Devine (2008) explored White people’s self-reported goals and strategies for an anticipated interaction with a Black person. Of particular interest was whether these goals

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and strategies reflected an approach or avoidance focus and whether the tendency to report goals and strategies reflecting an approach or avoidance focus varied as a function of their source of motivation to respond without prejudice. Participants who were highly internally motivated were expected to be more likely to generate goals and strategies for the interaction that focused on approaching egalitarianism (positive end-state) compared to those less internally motivated to respond without prejudice. In addition, participants who were highly externally motivated were expected to be more likely to generate goals and strategies for the interaction that focused on avoiding racial bias (negative end-state) than those less externally motivated to respond without prejudice. White introductory psychology students who had completed the IMS and EMS as a part of a mass testing session early in the semester were invited to participate if their scores fell in the top or bottom 30% of the IMS and EMS distributions. Participants completed open-ended questions assessing their anticipated goals and strategies when interacting with a Black person. For the assessment of participants’ goals, they were asked the following open-ended question: “Think about having an interaction with a Black person you have never met before in a social setting. What would your goal be in the interaction?” For the assessment of the participants’ strategies, they were asked to list the strategies they would use in interactions with Black people to be nonprejudiced. Two independent judges, who were blind to the participants’ IMS and EMS scores, coded participants’ responses to the goal and strategy questions in order to determine whether participants generated approach themes (i.e., focused on approaching a positive, egalitarian interaction) and avoidance themes (i.e., focused on avoiding overt bias) in their goals and strategies. If participants generated a goal that reflected the desire to treat the hypothetical Black interaction partner without bias and, thereby, approach the desired end-state of egalitarian responding (e.g., “treat the person as I would anyone else”; “get to know them and become friends”), they were coded as having an approach goal. If participants generated a goal that reflected the desire to avoid overtly biased responses and, thereby, avoid the undesired end-state of overt bias (e.g., “avoid having a bad interaction”; “wouldn’t want to look uncomfortable”), they were coded as having an avoidance goal. If participants generated a strategy that reflected behaviors likely to result in a positive interaction (e.g., “smile”; “be friendly”), they were coded as having an approach strategy. If participants generated a strategy that reflected the avoidance of overtly biased behaviors likely to result in a negative interaction (e.g., “avoid

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making racist jokes”; “not make offensive statements”), they were coded as having an avoidance strategy. Analysis of the presence or absence of approach themes in participants’ goals revealed the anticipated effect of IMS, such that high IMS participants were more likely to generate goals with an approach theme than low IMS participants. Table 34.1 presents percentages and frequencies for the approach and avoidance goals and strategies as a function of IMS and EMS separately. Although participants rarely generated goals with avoidance themes, the analyses of the presence or absence of avoidance themes revealed an effect of EMS, such that, as expected, high EMS participants were more likely to generate goals with an avoidance theme than low EMS participants. For the analysis of the strategies, consistent with expectations, the analyses of the presence or absence of approach themes revealed an effect of IMS, such that high IMS participants were more likely to generate approach strategies than low IMS participants. The analyses of the presence of absence of avoidance strategies revealed an effect of EMS, such that, as expected, high EMS participants were more likely to generate avoidance strategies than low EMS participants. TABLE 34.1 Percentage of Goals and Strategies That Reflected Approach and Avoidance Themes Approach goals Avoidance goals Approach strategies Avoidance strategies

Approach goals Avoidance goals Approach strategies Avoidance strategies

Low IMS (N = 50) 34%a (17) 10% (4) 40%a

High IMS (N = 61) 56%b (34) 5% (4) 59%b

(20) 36% (18)

(36) 34% (21)

Low EMS (N = 52) 50% (26) 2%a (2) 44% (23) 21%a (11)

High EMS (N = 59) 42% (25) 12%b (6) 56% (33) 48%b (28)

Note: Percentages with different superscripts on the same row differ with p < .05. The frequencies for each group are presented in parentheses below the percentages.

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Plant and Devine’s (2008) findings were highly consistent with the idea that internal motivation to respond without prejudice results in an approach orientation for interracial interactions. Specifically, those who were motivated to respond without prejudice because it is personally important (i.e., high IMS) were more likely than those low in internal motivation to generate goals and strategies for the interaction that focused on approaching a pleasant, egalitarian interaction. In addition, the findings supported the proposition that external motivation was related to an avoidance orientation for interracial interactions. High EMS people were more likely than those low in external motivation to generate goals and strategies for the interaction that focused on avoiding overt bias.

ACTIVATION OF APPROACH AND AVOIDANCE UPON EXPOSURE TO BLACK FACES The findings from Plant and Devine’s (2008) first study suggest that whether White people’s self-reported goals and strategies for interactions with Black people focus on approaching egalitarianism or avoiding overt bias is influenced by their motivation to respond without prejudice. To the extent that participants’ reports of their goals for interracial interactions reflect chronic regulatory tendencies, then these concerns are likely to become automatically activated upon exposure to relevant cues (Bargh, 1990; Bargh & Barndollar, 1996). To the extent that people who are highly internally motivated to respond without prejudice are chronically concerned with approaching egalitarianism in interracial interactions, then we would expect that general approach-related concepts would be highly accessible when exposed to Black people. Further, to the extent that people who are highly externally motivated are chronically concerned with avoiding overt bias for interracial interactions, then we would expect that general avoidance-related concepts would be highly accessible when they are exposed to Black people. To explore this possibility, Plant and Devine (2008) examined whether concepts conceptually related to approach and avoidance goals are automatically activated upon exposure to Black people as a function of the source of participants’ motivation to respond without prejudice. Specifically, the accessibility of approach- and avoidance-related goals was examined by assessing the speed of response to these concepts following exposure to Black versus White faces. Previously, researchers have shown that when environmental cues relevant to a chronic goal are primed (i.e.,

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activated), people respond more quickly to words related to that goal (Bargh & Barndollar, 1996; Bargh, Raymond, Pryor, & Strack, 1995). To the extent that exposure to a Black person activates approach- or avoidance-related goals for White people, then responses to approach and avoidance concepts reflecting these goals should be facilitated (i.e., made more quickly) following exposure to a Black face as compared to a White face. To examine these possibilities, Plant and Devine (2008) had White participants complete a lexical decision task, in which they indicated as quickly as possible whether a string of letters was a word or nonword. Prior to each decision, participants were presented with either a White or Black face prime. Of particular interest was the speed of response to approach- and avoidance-related words following exposure to Black faces, controlling for the speed of response to these words following White faces. White introductory psychology students who completed the IMS and EMS as a part of a mass testing session early in the semester were considered eligible for the study if their responses fell into the top or bottom 30% of the IMS and EMS distributions. The design of the study was a 2 (IMS: high vs. low) × 2 (EMS: high vs. low) × 2 (Face Prime: Black vs. White) × 2 (Letter String: approach vs. avoid) mixed-model factorial, with face prime and letter string as repeated measures. Of interest was participants’ speed of response to the approach and avoidance words following a Black face prime controlling for the speed of response to similar words following a White face prime (Table 34.2). Specifically, participants completed a computer task where they were primed with Black and White faces prior to being presented with approach- and avoidance-related words and nonwords (SOA 450 ms). The average speed of response in seconds was then computed for the approach- and avoidancerelated words following the Black and White faces separately (e.g., approach words following Black faces; avoidance words following White faces). Analyses were conducted on participants’ speed of response to the approach and avoidance words following Black face primes with the average speed of response to the corresponding words following White face primes as the covariate in each analysis with IMS and EMS as factors. The analysis of the speed of response to approachrelated words following Black face primes revealed the predicted main effect of IMS, such that high IMS participants responded more quickly to the approach-related words following Black faces than low IMS participants. The analysis of the speed of response to avoidance-related words following Black face primes, consistent with expectations, revealed a main effect of EMS, such that

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TABLE 34.2 Latency to Respond to Words Following Black Face Primes Controlling for Speed Following White Face Primes

Approach words Avoidance words

Low IMS (N = 46)

High IMS (N = 52)

992.94a

853.87b

(36.86)

(34.46)

1121.10

1089.00

(37.82)

(35.47)

Low EMS (N = 48) Approach words Avoidance words

High EMS (N = 50)

910.39

936.43

(35.99)

(35.04)

1165.61a

1044.49b

(37.18)

(36.16)

Note: Means with different superscripts on the same row differ with p < .05. The standard errors are presented in parentheses below the means.

high EMS participants responded more quickly to the avoidance-related words following Black faces than low EMS participants. These findings indicate that internally motivated people have approach goals automatically activated upon exposure to Black faces and externally motivated people have avoidance goals automatically activated upon exposure to Black faces. Drawing upon Bargh’s (Bargh, 1990; Bargh & Barndollar, 1996) automotive theory, these findings suggest that for internally and externally motivated people, approach and avoidance regulatory concerns are likely to be chronically activated in relevant situations (e.g., exposure to a Black person). These findings lend further support to the utility of conceptualizing people’s source of motivation to respond without prejudice in terms of its implications for their orientation (approach or avoidance) for interracial interactions. Taken together, the findings from Plant and Devine’s (2008) work demonstrate that highly, internally motivated White people are more likely to anticipate pursuing goals and strategies that focus on approaching egalitarianism during an interaction with a Black person and to have their approach-related goals automatically activated upon exposure to a Black person than are less internally motivated White people. In addition, highly externally motivated White people are more likely to anticipate pursing goals and strategies that focus on avoiding overt bias during such

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interactions and to have their avoidance-related goals automatically activated upon exposure to a Black person than are less externally motivated White people. We now turn to the implications of approach and avoidance concerns for the quality of interracial interactions.

IMPLICATIONS OF APPROACH AND AVOIDANCE ORIENTATION FOR INTERRACIAL INTERACTIONS Plant and Devine’s (2008) findings provided insight into who among White people is likely to possess approach or avoidance motivation for interracial interactions and the implications of these motivational concerns for people’s goals and strategies for such interactions. This foundation is an essential step to understanding interracial interactions and it leaves us better prepared to take on the challenges of exploring ongoing, dynamic interactions. However, thus far, the work does not speak to the likely implications of possessing approach or avoidance motivation for the perceived quality of interracial interactions. There is reason to suspect that having avoidance motivation may be less beneficial for the course of interracial interactions than possessing an approach orientation. We anticipate that in an interracial interaction, a White person who pursues strategies such as smiling and being friendly is likely to have a far more pleasant interaction than someone who pursues strategies such as avoiding the use of stereotypes (Reis & Shaver, 1988). Further, actively trying to avoid or suppress the use of a stereotype causes the stereotype to become highly accessible in the person’s mind and influence the treatment of outgroup members (Macrae, Bodenhausen, Milne, & Jetten, 1994). Thus, some avoidance strategies may actually backfire and result in a more biased response. In addition, focusing on the undesired end-state of bias in interracial interactions may result in heightened anxiety in these interactions, which may lead to avoidance behaviors and more negative attitudes about the outgroup (Devine, Evett, & Vasquez-Suson, 1996; Islam & Hewstone, 1993; Plant & Devine, 2003; Stephan & Stephan, 1985). Focusing on a positive outcome, in contrast, may lead to the pursuit of success-related behaviors, such as persistence in the face of failure and setting realistic goals (Atkinson & Litwin, 1960; Elliot & Church, 1997; Elliot & Harackiewicz, 1996; Feather, 1967; Hembree, 1988; Mahone, 1960). In addition, there is some evidence that taking on an approach-focus for an interracial interaction (i.e., seeing it as an opportunity for intercultural dialogue) results in less depletion of self-regulatory strength following the interaction than pursuing an

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avoidance focus (i.e., avoiding the appearance of prejudice; Trawalter & Richeson, 2006). Further, Shelton (2003) found that when White people tried not to be prejudiced (i.e., took on an avoidance orientation), they experienced more anxiety and enjoyed an interaction with a Black person less than if they were not trying to avoid prejudice. Interestingly, though they enjoyed the interaction less, participants trying to avoid prejudice were liked more by their Black partner than control group participants who were not told to avoid prejudice, which may indicate that some motivation to respond without prejudice is better than none. In the Shelton (2003) work, however, there was not a group that worked to approach a good interaction, so it is difficult to know how that would have influenced the partner’s experience. In addition, although Vorauer and Turpie (2004) also found that heightened evaluative concerns had positive implications for how White participants responded to outgroup members, it was only for participants higher in prejudice. Such concerns were actually disruptive for those low in prejudice who may typically respond positively in interracial interactions. It is also worth considering that in Study 2, as summarized previously, externally motivated participants responded with the automatic activation of avoidancerelated concepts, such as “withdraw” and “escape” when exposed to Black faces. The activation of such concepts in interracial interactions may lead to avoidance behaviors (e.g., standing further away, making less eye contact). In addition, it may mean that externally motivated people are more likely to choose to avoid interracial interactions all together. One highly effective way to avoid coming across as biased in an interracial interaction is to avoid that interaction altogether (though, of course, avoiding interactions could be perceived as bias de facto). In contrast, the automatic activation of approach-related concepts, such as “embrace” and “unite,” among internally motivated people may result in intimate and warm interactions and possibly the active pursuit of interracial interactions. It will be important to examine such implications of possessing approach or avoidance concerns in interracial interactions for behavior in actual ongoing interactions. As a final note, although the focus for this section was on motivation to respond without prejudice, there are likely other factors that also predict approach and avoidance responses within intergroup interactions for majority group members. For example, Dovidio et al. (2002) found that White participants’ implicit prejudice was associated with less nonverbal friendliness (less approach) in their interactions with a Black compared to White partner.

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These processes could complicate matters in that one’s intentions (e.g., to approach) could be inconsistent with implicit biases that are known to be difficult to control (Devine et al., 1996; Devine, Plant, Amodio, HarmonJones, & Vance, 2002).

MINORITY PERSPECTIVE We now consider the experiences of minority group members with a focus on both their decisions to approach or avoid interracial interactions and their approach and avoidance orientation within interracial interactions. Historically, far less research has been conducted examining minority group members’ responses and behaviors in intergroup settings (Shelton, 2000), assuming, at least implicitly, that minority group members are passive targets of prejudice. This perspective has been challenged in recent years (Devine et al., 1996; Shelton, 2003) and, indeed, one of the exciting developments in intergroup relations research is a focus on minority group members’ experiences (i.e., their attitudes, expectancies, goals) and the role they play in intergroup interactions (Brigham, 1993; Butz & Plant, 2006; Livingston, 2002; MendozaDenton, Downey, Purdie, Davis, & Pietrzak, 2002; Monteith & Spicer, 2000; Plant, 2004; Shelton & Richeson, 2006). The vast majority of the existing work tends to focus on minority group members’ (and particularly Black people’s) experiences in interactions with majority group members, specifically White people. As a result, the focus of this review will be on minority group members’ experiences in interactions with White people. As with the review of the majority group perspective, we first summarize the work examining the decision to approach or avoid interactions with White people and then consider the implications of being approach or avoidance oriented for responses in interactions with White people.

CHOOSING TO APPROACH OR AVOID INTERRACIAL INTERACTIONS For minority group members, the decision of whether to enter interracial interactions with White people or avoid them may be more restricted than for majority group members. By virtue of being in the numerical minority, minority group members may often have little choice whether to interact with White people (e.g., in work, retail, educational settings). Further, because historically, White people have held positions of power more often than minority group members and in some cases this has not changed, minority group members may be compelled

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to interact with and get along with majority group members or be put at a disadvantage (e.g., professionally). Indeed, even among college students, there is some evidence that Black students have far more contact with White people than White students have with Black people, which may in part reflect having little choice whether to interact with Whites in some situations (Brigham, 1993). When minority group members do have a choice whether or not to interact with White people, the factors that predict whether minority group members want to approach or avoid interactions with White people are in some cases similar to those factors that influence majority group members’ decisions to interact with minority group members. However, there are also some important differences. Similar to the situation for White people, minority group members’ negative attitudes toward White people are associated with the avoidance of interracial contact (Brigham, 1993; Johnson & Lecci, 2003; Levin et al., 2003; Livingston, 2002; Plant, 2004; Shelton & Richeson, 2006). For example, Hispanic participants who reported more negative attitudes toward White people both reported less previous contact with White people and a greater desire to avoid an upcoming interaction with a White person (Plant et al., in press). Brigham (1993) also found that for Black people, negative attitudes toward White people were associated with low levels of contact with White people. Further, longitudinal work by Levin et al. indicates that ethnic minority group members’ negative attitudes may lead to decreased outgroup contact. Thus, negative attitudes may be an important factor in contributing to the avoidance of contact with White people for minority group members. Also, consistent with the experience of majority group members, minority group members are likely to approach interracial interactions if they possess positive expectations regarding the outcomes of these interactions and avoid them if they anticipate negative outcomes. However, the types of outcomes that are most salient to minority group members in deciding whether to engage in interracial interactions differ somewhat compared to those for White people. One salient negative outcome that minority group members experience in the context of interracial interactions with White people is that they will be the target of bias and stereotyping from White people, which can contribute to the avoidance of intergroup contact (Livingston, 2002; Mendoza-Denton et al., 2002; Monteith & Spicer, 2000; Pinel, 1999; Plant, 2004; Steele, 1997; Tropp, 2003). For example, Plant (2004) demonstrated that Black participants who were concerned about being the target of bias in interactions with White people

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had fewer interracial interactions during the subsequent 2 weeks and were more interested in avoiding interactions with White people. Interestingly, Black participants who expected less bias from White people had more previous experience with White people, suggesting that contact may decrease negative expectations regarding interracial interactions. Unfortunately, since negative expectations breed avoidance, it may be difficult to alleviate negative expectations of bias once formed. Consistent with the experiences of White people in interracial interactions, Black participants report that they would avoid interracial interactions out of fear of rejection from White people (Shelton & Richeson, 2005). However, it is possible that the reasons Black and White people anticipate being rejected differ somewhat. For example, Black people may fear being rejected because of White people’s prejudice toward them. White people may fear being rejected because of Black people’s frustration at being the targets of racial bias. Unlike for White people, self-efficacy concerns and fears of coming across as biased generally may be less prominent for minority group members because of more chances for interracial contact over the course of their lives (cf. Plant et al., in press).

WITHIN INTERRACIAL INTERACTIONS: APPROACH AND AVOIDANCE GOALS Once in an interaction with a majority group member, minority group members must decide what outcome they desire for the interaction. Within the context of the interaction, minority group members may choose to approach a positive interaction or avoid a negative interaction. As discussed in the previous section, for minority group members, the concern that they may be the target of prejudice is likely to loom large in interactions with White people (Feagin, 1991; Crocker et al., 1991; MendozaDenton et al., 2002; Pinel, 1999). This concern may take the form of constantly being “on guard” for signs of bias on the part of majority groups members and culminate in low feelings of trust in being treated fairly by the other. In many ways, this could complicate the unfolding dynamics of interracial interactions such that they may see signs of bias when none are intended or present (Devine et al., 1996). Moreover, to prevent the possibility for the other to view them in light of their group membership, minority group members may adopt an avoidance motivation, whereby they specifically focus on avoiding behavior that might be seen as confirming stereotypes about their group and behaviors that may elicit prejudice. However, when minority group members anticipate the possibility of prejudice, the cause of the negative

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outcome is external to the self (i.e., the prejudice of the majority group member). As a result, minority group members may feel that their best tactic for interracial interactions is to focus on approaching a good interaction as opposed to focusing on avoiding a negative outcome that they may not be able to control (i.e., the outgroup member’s bias). Consistent with this idea, Shelton, Richeson, and Salvatore (2005) found that stigma consciousness can lead Black people to pursue compensatory behaviors that encourage a positive interaction, such as increased engagement and self-disclosure. These behaviors would seem to reflect more of an approach than avoidance motivation, as they would move the actor toward a positive interracial interaction. Indeed, these compensatory strategies were found to improve the experience of White people in the interracial interaction (Shelton et al., 2005). Interestingly, these behaviors did not lead to a better experience for the Black people, which may have been due to the behaviors making the Black people feel inauthentic in the interaction. These findings are an interesting parallel to Shelton’s (2003) work showing that White people who tried to appear nonprejudiced made a better impression on their Black interaction partner but enjoyed the interaction less. Clearly efforts to improve the experience of outgroup interaction partners can come at a cost. Similar to concerns about being the target of bias, minority group members experience concerns about confirming stereotypes about their group (Steele, 1997; Steele & Aronson, 1995). Previous work on stereotype threat supports the idea that, in some contexts, minority group members may focus on avoiding the confirmation of a stereotype about their group, which can have negative implications for performance in those arenas (Steele, 1997; Steele & Aronson, 1995). For example, concerns about confirming the stereotype that minority group members are less intelligent and academically inclined than White people may lead minority group members to focus on avoiding stereotype confirmation. The negative implications of focusing on avoiding the stereotype confirmation as opposed to focusing on approaching success may account for the negative performance implications of stereotype threat (Smith, 2006). Similar to the implications of stereotype threat in performance settings, it is possible that concerns about confirming stereotypes in interpersonal interactions may also result in an avoidance focus in intergroup interactions. That is, one could speculate that concerns about being perceived as behaving consistently with the stereotype of one’s group may lead minority group members to focus on not behaving in ways that are consistent with the stereotype of their group

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(e.g., not seeming unintelligent or lazy, not being too into athletics or music). As a result, they may be less likely to focus on behaviors that may result in a positive interaction (e.g., finding common interests, actively gathering information about the interaction partner). Such a focus on avoiding a stereotypic impression in interracial interactions could result in less pleasant interactions for all involved.

BRINGING IT TOGETHER: DYNAMIC INTERACTIONS Thus far, we have focused primarily on the majority and minority group members’ responses to interracial interactions in isolation. However, interactions are by definition dynamic interchanges. It seems inescapable that the behaviors and responses of one interactant will influence the experiences of the other interactant (Devine et al., 1996). To date, the research exploring ongoing interactions where neither interactant is a confederate are extremely limited (but see Shelton et al., 2005; Shelton, 2003). Whether an individual decides to approach or avoid interracial interactions will certainly have an impact on the outgroup member. For example, deciding to avoid an interracial interaction can lead to the outgroup member feeling rejected (Shelton & Richeson, 2005). Such feelings of rejection could certainly contribute to negative expectations and attitudes about future intergroup interactions. Further, if people want to avoid interactions but cannot escape them, they are likely to respond in an awkward, avoidant manner in the interaction (Plant & Butz, 2006). These responses come across as avoidant may be interpreted as intergroup bias (Plant & Butz, 2006), and could contribute to negative expectations and attitudes for the interaction partner. Of course, it is also possible that interracial interactions can go well, particularly if the interaction partners have an approach motivation for the interaction. Such positive interactions can have a range of implications including improving intergroup attitudes and expectations for future interactions (Allport, 1954; Pettigrew & Tropp, 2006). It will be important in future work to identify those factors that create an approach motivation for both majority and minority group members. For those who avoid intergroup interactions out of concerns that they will go poorly, breaking the cycle of avoidance will be a critical first step to moving forward. Simply getting people to engage in intergroup interactions may help to improve negative expectancies at least in most situations. Further, once people engage in interactions, perhaps if one interactant has an approach orientation for the

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interaction, it can help the other person to overcome any negative expectancies and shift to an approach orientation as well. In general, getting people to shift their focus from what can go wrong in intergroup interactions to what can go right may be an important advance in encouraging approach motivation. Our hope is that the framework of approach and avoidance motivations for intergroup interactions that we have introduced here can help identify promising avenues to encourage positive intergroup contact.

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Social Comparison Reunion for Approach–Avoidance 35 AMotivation and Social Comparison Jerry Suls and Ladd Wheeler CONTENTS Historical Background ..........................................................................................................................586 Level of Aspiration ...........................................................................................................................586 Social Comparison Theory...............................................................................................................587 Connections Between Social Comparison and LOA .......................................................................587 Bringing Approach and Avoidance Back Home ...................................................................................588 “Can I Do X?”: Comparison Selection and Motives ........................................................................588 Motives and Reactions to Social Comparison ..................................................................................590 The Selective Accessibility Model ...................................................................................................590 The Role of Motives .........................................................................................................................592 The Approach–Avoidance Model of Comparison ............................................................................592 Relevant Empirical Evidence ...........................................................................................................594 Approach and a Highly Superior Target (Scenario A) ................................................................594 Approach and a Slightly Superior Target (Scenario B) ...............................................................594 Approach and a Slightly or Extremely Inferior Target (Scenarios C & D) .................................595 Avoidance and a Highly Superior Target (Scenario E) ...............................................................595 Avoidance and a Slightly Superior Target (Scenario F) ..............................................................596 Avoidance and a Slightly Inferior Target (Scenario G) ...............................................................596 Avoidance and a Highly Inferior Target (Scenario H) ................................................................596 Coda .............................................................................................................................................596 The Case of the Similar Comparison Target ...............................................................................597 Conclusions and Implications................................................................................................................597 Acknowledgments .................................................................................................................................597 References .............................................................................................................................................597

Leon Festinger was a student or colleague of Kurt Lewin from 1939 until Lewin’s death in 1947, and Lewin’s theorizing about positive and negative valences led to the distinction between approach and avoidance motivation (Elliot, 1997; see Elliot, chapter 1, this volume; Higgins, 2000). However, there is no mention of approach–avoidance or positive–negative valence in social comparison theory (Festinger, 1954a,b). Festinger had used these concepts in the classic paper on level of aspiration (LOA)

(Lewin, Dembo, Festinger, & Sears, 1944) and had in fact previously published on the “resultant valence theory” (Festinger, 1942b). We would guess that these notions of positive and negative valence would be deeply embedded in Festinger’s mind. Their apparent absence in his subsequent work is surprising. However, we show that Festinger (1954a,b) borrowed important elements of the LOA paper for his formulation of comparison theory. Also, by formally reintroducing 585

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social comparison to approach–avoidance motivation, we hope to provide more clarity about the current state of knowledge concerning comparison processes for ability and trait evaluation. In this chapter, we first briefly describe the LOA and classic social comparison theories, noting their connections and what Festinger borrowed from earlier research by himself and colleagues. Appreciation of these connections leads us to a reconceptualization of social comparison and its positive and negative consequences for self-evaluation. Specifically, we describe responses to social comparison and selection of comparison information in a new approach–avoidance framework. For our purposes, approach will refer to those situations in which the person wants to excel on the comparison dimension. Conversely, avoidance will refer to the desire to avoid failure on the comparison dimension. The other dimension in this framework is the actual status of the comparison target relative to the person, whether the target is inferior or superior to the person and by how much.

HISTORICAL BACKGROUND LEVEL OF ASPIRATION In the 1930s, Lewin and his students, Dembo (1931) and Hoppe (1930), turned their attention to the question of how people set goal levels. LOA was defined as the degree of difficulty of the goal toward which a person is striving and was seen as relevant when there is a range of perceived difficulty to attain goals. It also was recognized that there is variation in valence among goals differing in difficulty. Succeeding at a task known to be difficult should be particularly satisfying; failing at a simple task should be particularly unsatisfying. In a representative LOA experiment, a subject performs a task to obtain a score. Following the first trial, the subjects learn about their performance and then are asked what score they will try to make the next time. The task is attempted again and the subject receives another score. Prior to each trial, the subject is asked to report what score he/she is aiming for next (i.e., level of aspiration). This sequence continues over a series of trials. In this paradigm, a common observation is that doing better versus doing worse across trials influences the LOA set by the subjects. By the mid-1940s, an appreciable amount of research had been conducted by Lewin and his colleagues and by others to understand factors that affect LOA. The purpose of Lewin et al.’s (1944) review paper was to evaluate the state of evidence and propose a general theory of

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LOA. Three factors were identified as important contributors to LOA: (a) the valence of seeking success; (b) the valence of avoiding failure; (c) the probability of success/ failure. “The strength of these forces and values corresponding to the subjective probability depend on many aspects of the individual…particularly on the way he sees his past experience and on the scales of reference which are characteristics of his culture and his personality” (Lewin et al., p. 376). These factors were implicated by several sources of empirical evidence. For example, researchers noted that the vast majority of research subjects reported LOA’s which were above their previous performance score (Gould, 1939). This was seen as a manifestation of the cultural emphasis on improvement. In the theory of LOA, past experience was seen as acting on the perceived probability of future success or failure. The valence of success or failure was seen to follow a general rule–as the difficulty of the task increases so does the valence of success (while the valence of failure decreases). This general tendency was modifiable, however, by other factors, including the performance standards of relevant social groups. The valence of failure should be high and valence of success low at a performance level below the group’s standard (or average). Conversely, the valence of success should be high and valence of failure low at a performance level at or above the group standard. There can be, however, group standards that prohibit either low or high levels of performance. True Gentlemen should not receive an academic grade either higher or lower than a “C.” Departure in either direction would entail a high negative valence and a low positive valence. Direct evidence of the role of social reference standards was provided by Festinger (1942a). Using the LOA experimental protocol, Festinger manipulated the source and nature of performance norms that subjects received about other groups. He found that undergraduates would lower their aspirations if they found themselves performing above the group average and raise their aspirations if they scored below the group average. Thus, subjects changed their aspirations to be in agreement with their peers. The status of the group also made a difference. The undergraduates raised their aspirations the most when they were told they scored below high school students and lowered their aspirations the most when told they scored above graduate students. The most direct legacy of LOA was for theories of achievement motivation where valence and probability figured importantly, as well as personality (Atkinson, 1959, 1964). But LOA also informed Festinger’s (1954a,b) Social Comparison Theory.

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A Reunion for Approach–Avoidance Motivation and Social Comparison

SOCIAL COMPARISON THEORY In the mid-to-late 1940s, Festinger, Lewin, and their associates turned their attention to the study of group dynamics. In his Informal Social Communication theory, Festinger (1950) emphasized the action of social pressures, such as communication between group members and the rejection of deviates, to attain agreement or uniformity in the group. Uniformity of opinion was desirable, Festinger thought, because it provides confidence in one’s opinion or facilitates group goals. A short time later, when Festinger was asked to review and integrate empirical findings about social influence in groups (which resulted in two papers describing social comparison theory; 1954a,b), his thinking had shifted from an emphasis on the power of the group over the individual to how individuals use groups to evaluate themselves. In the new theory, Festinger carried over the idea about people wanting to know whether their opinions were correct, but also extended it to the evaluation of abilities. That is, people also want to know what their abilities allow them to do. He proposed that comparisons with others could provide this information when objective standards were unavailable or nonexistent. His idea about pressures toward uniformity from informal social communication was extended to the comparison process. Finding agreement with others should make us feel more confident. In the case of abilities, observing those with similar abilities allows us to know what our own possibilities for action are; “if they were successful at ‘X,’ probably I can be too.” In social comparison theory, the emphasis was on accurate self-evaluation—for opinions, “Am I correct?” and for abilities, “Can I do X?” For both questions, the “similarity hypothesis” was a key element. As Festinger (1954b) noted, “There is a tendency to stop comparing oneself with others who are very divergent. This tendency increases if others are perceived as different from oneself in relevant dimensions” (p. 217). In other words, people who are similar are especially useful in generating accurate evaluations. Festinger, however, did not clearly specify the basis of similarity. Subsequent researchers clarified that the similarity was on characteristics correlated or predictive of an ability or opinion (Goethals & Darley, 1977; Martin, Suls, & Wheeler, 2002; Suls, Martin, & Wheeler, 2000; Wheeler, Martin, & Suls, 1997). These characteristics are referred to as related attributes by social comparison researchers. In his 1954 statements, Festinger almost completely ignored the valence of comparison information; whether the comparison would make the recipient feel worthwhile

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or worthless was irrelevant. In fact, the theory allowed for the possibility that someone may purposely not perform their best so they can be similar and “fit in” with other group members (Radloff, 1966). However, valence crept into the theory via the unidirectional drive upward, a legacy of the LOA work. For abilities, Festinger observed there is a value set on doing better and better (“a unidirectional drive upward”), which does not normally apply to opinions. This means there is an inherent conflict between pressures to uniformity for purposes of accurate selfevaluation and the need to be superior (see discussion of Hypothesis V; Festinger, 1954a). We would add, however, that this also applies to other personal attributes and many kinds of opinions because some opinions and personal attributes are seen as better than others to possess (Jones & Gerard, 1965). For Festinger (1954a), “The implication is that, with respect to the evaluation of abilities, a state of social quiescence is never reached.” In other words, in a social group there will be a continuous attempt to be better, or at least think one is better, than everyone else.

CONNECTIONS BETWEEN SOCIAL COMPARISON AND LOA Festinger borrowed at least two important themes from LOA. The first was the idea that similar others serve as a critical reference standard. He had shown this in his earlier LOA research. After learning they had performed above or below other undergraduates, subjects moved their aspiration level closer to their peer group’s performance. The second idea he adapted was the unidirectional drive upward, which he observed might apply only in Western culture which stresses individual achievement and competition. This was suggested by empirical evidence with the LOA paradigm demonstrating that subjects typically set higher goals on each succeeding trial. People want to improve. LOA also may have been influential in another way. Festinger’s idea that ability self-evaluation works the same way as opinion, evaluation probably seemed surprising to initial readers of his theory. In the 1950s, group processes, opinions, and persuasion were the popular social psychology topics. But Festinger’s introduction of ability is understandable in the context of his earlier LOA research, which presumed that aspirations are based partly on ability self-assessment. Still, the absence of discussion of the affective consequences of social comparisons (only touched on in the unidirectional drive upward) seems like an oversight for a researcher who had been previously studied how people select goals to maximize feelings of success and minimize feelings of failure. Our speculation is that the oversight

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might be the result of Festinger’s well-known disdain for bubba (commonsense) psychology and his predilection for empirical demonstrations of counter-intuitive behavior. The affective effects of social comparison might have seemed too obvious–people should feel better about themselves when they are superior and worse when they are inferior to others. As subsequent research has demonstrated (Buunk, Collins, Taylor, VanYperen, & Dakof, 1990), however, the outcomes of comparison are not so simple, but Festinger did not wait to find out. He dropped social comparison theory and moved to his theory of cognitive dissonance, the last research he did in social psychology. For nearly a decade and a half, researchers studying social comparison focused mainly on the striving for accurate self-evaluation and tests of the similarity hypothesis (see Latane, 1966). The emphasis shifted after publication of Wills’ (1981) downward comparison theory, which posited that people who feel threatened should compare with others who are worse-off, thereby boosting feelings of subjective well-being. Subsequent research, consistent with Wills’ theory, showed that medical patients seemed to benefit from strategic downward comparisons (Wood, Taylor, & Lichtman, 1985). The idea that social comparisons could be self-enhancing or self-protective rather than self-evaluative became a major research topic, which continues to the present day. Also, empirical support for another motive—directing comparison in the interest of improving the self—also appeared (see Wood, 1989). With the recognition of these additional motivations for social comparison, the relevance of valence was clearly appreciated. But the accumulated research from the 1980s to the present day has presented a wide range of findings across different kinds of outcomes (Collins, 1996; Wheeler & Suls, in press). A number of theories have been presented (see Suls & Wheeler, 2000; Stapel & Suls, 2007), but none seem to subsume all of the data and none have formally incorporated approach and avoidance. With regard to the latter, this seems important because the desire to attain success (i.e., self-enhancement) may operate differently in social comparison than the desire to avoid failure (i.e., self-protection). Later in this chapter, we describe our approach–avoidance model and assess how well it handles the empirical evidence.

BRINGING APPROACH AND AVOIDANCE BACK HOME The legacy of LOA theory, particularly its emphasis on achieving success and avoiding failure, has considerable relevance when we are uncertain about choosing a goal or a course of action (as in the LOA paradigm). Similarly,

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distinguishing between approach toward success and avoidance of failure has utility for understanding the affective reactions to unbidden forced or spontaneous comparisons. We begin with the general premise that we want to find out we are worthwhile people. To accomplish this, people want to excel on the comparison dimension—this can be conceptualized as approach. Conversely, people want not to fail on the comparison dimension— avoidance. One can feel worthwhile as a person either by excelling or by not failing. In the social world, these general tendencies are played out among an array of superior, similar, and inferior comparison targets. The distinction between approach and avoidance motivation has not been fully appreciated in social comparison (but see Lockwood, 2002). We described earlier how downward comparison was believed to serve selfenhancement. However, the empirical literature tends to lump self-protection with self-enhancement and assume they work similarly. This may be in error because selfenhancement represents the desire to excel; self-protection is quite different because it represents a desire to avoid failure (see Elliot & Mapes, 2005). In the next section, we describe how approach and avoidance influence the selection of appropriate comparisons to evaluate ability. After describing the role of these motives for comparison selection, we will describe the affective responses that result from being exposed to superior or inferior comparison targets.

“CAN I DO X?”: COMPARISON SELECTION AND MOTIVES To understand the role of approach and avoidance in comparison selection, we first must describe how the process by which people make comparisons to evaluate their abilities is understood currently. The proxy comparison model (Martin, 2000; Martin et al., 2002; Wheeler et al., 1997) builds on Festinger’s theory and the attributional reformulation (Goethals & Darley, 1977) that clarified his similarity hypothesis. The model focuses on the selection of comparison information in situations where someone must decide whether to undertake a novel and consequential task where failure would have costs. Should a college graduate accept admission at a prestigious medical school where the receipt of a degree confers future benefits but the flunk-out rate is high? Does someone have the ability to swim to a lovely island across a wide bay? Serious consequences may occur if people miscalculate about their capabilities in attempting a novel task. If the person has not tried this before, there is no objective standard available, but certain kinds of social comparisons can help to make the decision.

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According to the proxy model, one can find out whether he/she can do “X,” if there is a person who already has undertaken the unfamiliar task—that is, a proxy. Not every person who has tried “X” is an informative choice, however. The proxy model describes the configuration of variables—similarity to self, effort expended, and related attributes—that make a proxy appropriate. These variables are defined by three premises. If one finds someone else who has succeeded at “X” (e.g., medical school or swimming the bay successfully), this proxy is a good indicator of one’s own likely future performance if both self and proxy performed similarly on a prior related task and the proxy is known to have exerted maximal effort on that prior occasion. If it is unclear that proxy exerted maximum effort then he/she may not be an appropriate index (e.g., if proxy was fatigued when performing comparably to self), his/her prior performance might be an underestimate of proxy’s actual ability, making his/her success at “X” a poor prognosticator for the self. In the absence of information about proxy’s maximum effort, proxy can still be informative if self and proxy share characteristics that are predictive of performance (i.e., related attributes). If, however, it is known that proxy performed at maximum effort, then standing on related attributes is irrelevant. Unpacking this argument with an example: if Stan knows that he and Gus ran 25 laps in 10 min and he was confident that this represented Gus’ best or maximal effort, then Stan can infer he should be able to match Gus’ subsequent performance in a marathon. Whether Gus runs several times a week (i.e., a related attribute) should not change Stan’s expectation of matching proxy-Gus’ performance on the new task. In sum, the proxy model predicts that related attribute information should be disregarded when there is information that proxy performed at maximal effort on the prior related task. Lacking that, related attributes similarity can serve as a substitute and establish that proxy’s performance indicates whether self can do X. The proxy model predictions have received support in several experiments. In an important study that inspired the formulation of the proxy model, Jones and Regan (1974) found that subjects preferred to affiliate with someone who performed similarly to them on an initial test of ability and who had already attempted the task at issue. Smith and Sachs (1997) reported that confidence in performance predictions was highest when the proxy’s score was similar. Martin et al. (2002) reported the results of several lab experiments using a physical strength paradigm to test

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the three main predictions. Consistent with the model, subjects used a proxy’s success on a novel task (Task 2) to predict their own performance if both had performed similarly on a prior related task and proxy was known to have exerted maximal effort on that occasion. In another study, whether proxy had performed at maximum effort was ambiguous, but information about a related attribute (hand size) was manipulated. Subjects used related attribute information about hand width to make their performance predictions about task 2. The third premise was tested by manipulating information about proxy’s prior performance (maximum, ambiguous) and related attribute information. When subjects did not know whether proxy’s performance was their maximum, subjects used the related attribute information as a basis for their predictions. When proxy’s performance represented maximum effort, subjects predicted that they would perform at the same level as proxy did on task 2, regardless of related attributes. Comparable support was found for these predictions in a paradigm involving a novel intellectual task. Where do approach and avoidance motivations play a role? They were not discussed in the proxy model or experiments, but they are implicitly part of the basic premises. As stated earlier, the theory is assumed to apply in cases where the task is novel (hence, there is uncertainty about the outcome) and successful performance would lead to personal rewards, but failure would be costly. People want to know whether they “can do X?” so that they maximize the possibility of success (approach) and minimize the possibility of failure (avoidance). If there were no rewards for succeeding, then there is no reason to consider trying “X.” The question is asked precisely because there is something important to be gained. But because failure is costly, there also is strong motivation not to fail. Lacking other information about a novel challenge, finding an appropriate proxy—someone who has attempted it previously—is critical. By comparing with a proxy (defined by similar prior performance under best effort or related attributes), the person maximizes the informational potential and balances the desire for success versus fear of failure. The proxy model has a clear connection to approach and avoidance motivation because it applies to novel situations where there are both incentives for succeeding and serious costs for failing. Festinger (1954a) also recognized that inaccurate evaluation was costly: “The holding of … inaccurate appraisals of one’s abilities can be punishing or even fatal in many situations,” (p. 117). There is a need for research that manipulates rewards of success and costs of failure to assess how selection of

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the proxy may change. Earlier work indicated that offering appreciable monetary incentives did not affect performance prediction accuracy (Martin et al., 2002), but this is different from effects of the gains or costs associated with performance quality. In social comparison research, the rewards of success and costs of failure have not been manipulated. Also, individual differences in approach or avoidance motivation have not been directly measured so we do not know much about the interplay of the motives and comparison selection. We speculate that inordinate focus on success may cause people to focus on proxy superstars who are wholly inappropriate and lead them to attempt tasks that exceed their capabilities. Conversely, too much focus on fears of failure may cause people to rely on proxies who lead them to be overly cautious in choosing their goals.

MOTIVES AND REACTIONS TO SOCIAL COMPARISON Contemporary researchers find that comparison with a target can produce self-evaluations that are displaced toward the comparison target (i.e., assimilation) or evaluations that are displaced away from the target (i.e., contrast). Recognition that assimilation might be a consequence of comparison represented a change in thinking because the assumption in the 1980s and 1990s was that contrast was the main outcome of social comparison (Suls, Martin, & Wheeler, 2002). An illustrative study is Morse and Gergen’s (1970) “Mr. Clean–Mr. Dirty experiment” where the self-esteem of subjects increased after being exposed to a disheveled, disorganized student but decreased after being exposed to a well-dressed, very competent college student. More recent evidence, however, demonstrates that comparison also can lead to assimilation. For example, Brown, Novick, Lord, and Richards (1992) found that low self-esteem females who had the same birthday as an attractive comparison target female assimilated their own attractiveness ratings toward that target. However, if they did not have the same birthday, they contrasted their attractiveness ratings away from her. Since the recognition that social comparisons can lead to contrast or to assimilation, social psychologists have been actively studying what conditions lead to one or the other outcome and have developed a number of conceptual models. By now, several variables have been identified. Some contemporary theories of assimilation-contrast emphasize how different kinds of information are made accessible by the comparison target or by surrounding conditions (Markman & McMullen, 2003; Mussweiler, 2003; Stapel & Koomen, 2001b). We find these cognitive

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explanations to be interesting but incomplete. When motives, such as self-enhancement or self-improvement, are discussed, they seem tacked-on rather than fully incorporated into the theory. (In fairness, the Markman and McMullen model considers affect more explicitly than the other models, but mainly as an outcome of comparison; Markman, McMullen, & Elizaga, 2007.) But we think that an appreciation of the interplay of approach and avoidance motivation has the potential for a satisfying integration that acknowledges both cognitive and affective influences (see also Lockwood, 2002; Higgins, 2000). To advance our arguments, first we must describe a contemporary cognitive assimilation-contrast theory that we find attractive. We chose the selective accessibility model (SAM; Mussweiler, 2003) as the vehicle from which we launch our approach–avoidance comparison model because of its parsimony and preference for absolute rather than subjective rating outcomes. However, Stapel’s (2007; Stapel & Koomen, 2000; Stapel & Suls, 2004) interpretation-comparison model probably might just as readily have been used. In the interests of space and complexity, we have focused on SAM. After reviewing SAM, we describe our approach–avoidance perspective.

THE SELECTIVE ACCESSIBILITY MODEL Mussweiler (2003; see also Mussweiler & Strack, 2000a,b) proposes that whether assimilation versus contrast occurs depends on the information that is accessible and used during the comparison. The process is guided by an initial, holistic assessment of the similarity between the target and the self. This rapid initial screening results in a general judgment of “similar” or “dissimilar.” Cognitive psychologists who have studied object recognition note that people rapidly consider a small number of salient features to determine whether an object and a target are generally similar or dissimilar. For social comparison, this might comprise salient characteristics or category membership, such as gender or age. Once the initial assessment is made, retrieval tends to focus on hypothesis-consistent evidence (Klayman & Ha, 1987). In the context of comparison, a general impression of similarity with the target sets in motion a process of “similarity testing” (e.g., “We both like history”). Because there are many facets of the self, people can recall or construe self-knowledge in such a way that accessible knowledge is consistent with the initial holistic impression. The consequence is that the selfevaluations are drawn closer to the target after selective search for similarity—leading to assimilation. An initial, general impression of dissimilarity, however, should prompt selective retrieval of target-inconsistent

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knowledge about the self (e.g., “He likes barbershop quartets, but I like bebop”). There, too, information can be recalled or construed consistently with the impression of difference. After dissimilarity search, self-evaluations are displaced from the comparison target—leading to contrast. Empirical support for the SAM has taken several forms. In a representative experiment, Mussweiler (2001) used a procedural priming task (Smith, 1994) with a picture comparison task to induce subjects to focus on either similarities or differences. Specifically, subjects were assigned either to find the similarities or the differences between two scenes. This manipulation was used to prime the subjects to engage in similarity versus dissimilarity testing. Then, in a supposedly unrelated experiment, subjects read about another college student who was described either adjusting well or poorly to college. After making their impressions of the other student, subjects evaluated their own adjustment to college by answering such questions as, “How often have you typically gone out per month?” and “How many friends do you have at the university?” Consistent with predictions from SAM, subjects who had been primed earlier to focus on similarities named more social activities and friends after comparison with a well-adjusted target than a poorly adjusted target. Conversely, subjects primed to focus on differences, contrasted self-evaluations away from the high standard; that is, reported their adjustment to college was worse after comparison with a well-adjusted target than a poorly adjusted target. Thus, assimilation versus contrast with a comparison target occurred depending on whether subjects had been primed to focus on similarities or differences. Other research has found evidence, consistent with SAM, that priming social standards makes certain kinds of standard-consistent or standard-inconsistent information more cognitively accessible and hence faster to access in a lexical priming task (Mussweiler & Strack, 2000b). One of the strengths of SAM is that selective accessibility provides a parsimonious cognitive explanation for the moderating factors reported to influence whether assimilation or contrast with a comparison target occurs. Lockwood and Kunda (1997) found that subjects would assimilate to a superior target if they believed the likelihood of reaching the same success was possible for them. Thus, the likelihood of attaining better standing is important. This is also related to Stapel and Koomen’s (2000) idea that assimilation to the target is facilitated when the person thinks that the relevant attribute is mutable, that is, can be changed. Major, Testa, and Blysma (2001) also proposed that perceived control was important in determining

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responses to comparisons. If the target was superior, subjects should assimilate if they thought they had control over the attribute. In these empirical examples, the likelihood of improvement to the comparison target was high; assimilation with the target was the outcome. Another moderator that strengthens assimilation is psychological closeness to the comparison target, such as sharing related attributes with another person. In the study by Brown et al. (1992), described earlier, assimilation presumably occurred for the subjects who shared a birthday with the target because psychological closeness was salient. Sharing a social category, increasing the feeling of “we-ness,” should also increase psychological closeness and is associated with assimilative outcomes (Stapel & Koomen, 2001a), as should comparison with ingroup rather than outgroup members (Mussweiler & Bodenhausen, 2002). Mussweiler (2003) notes that each of these factors should lead to a holistic impression of similarity leading to further testing for similarity. If information about the self is retrieved that is consistent with the target then assimilation should result. Conversely, contrast should occur in the absence of psychological closeness, when people think they do not share the same likelihood for future success, or do not have the same related attributes. Researchers also find that a highly distinct or extreme comparison target (e.g., Albert Einstein for intelligence, Mother Teresa for charity) produces contrast (Stapel & Koomen, 2000). Such extreme exemplars, according to SAM, should create an initial impression of dissimilarity with the target and prompt testing for dissimilarity, thereby resulting in contrastive self-evaluations. In SAM, similarity testing frequently operates as the default. Research indicates that people initially tend to focus on similarities rather than differences in comparisons. Festinger’s (1954a) theory and its extensions (Goethals & Darley, 1977; Wheeler et al., 1997) also are consistent with this idea. Whether similarity is a default because it is well practiced (Smith, 1994) or follows attributional logic (see description of proxy model) are not mutually exclusive possibilities. But the search for similarity should be short-circuited when a target initially perceived as extreme or distinct does not share related attributes or has some salient attribute suggesting the self and target are probably quite different. Then the holistic impression of dissimilarity should set in motion a search for differences that leads to contrast. There are other models, with origins in psychophysics, that do not account for contrast with selective accessibility (Biernat, Manis, & Nelson, 1991; Manis & Paskewitz,

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1984; Ostrom & Upshaw, 1968; Manis, Biernat, & Nelson, 1991).* In these alternative accounts, a comparison target serves as a judgmental anchor that changes the meaning of the scale of evaluation. For example, in the company of Yao Ming (7¢6²), the authors might rate themselves as “very short” though objectively we both are of average height. In this case, Ming serves as a reference point that influences the interpretation of the points on the rating scale. As a consequence, “average” and “short” take on a different meaning for us as raters than if Earl Boykins (5¢5²) was the reference point. The SAM acknowledges that both selective accessibility (via difference seeking) and the change of meaning induced by reference points can produce contrast. But SAM views the latter as only affecting the language or ratings that people use to describe their judgments and not the underlying cognitive or perceptual process. Selective accessibility is thought to directly affect the mental representation of the self-evaluation. Moreover, if the similarity default is operating, then there is always a battle between assimilation (via selective accessibility) and use of the target as a contrastive standard when a subjective rating is the measure of self-evaluation (because of the change in scale interpretation). This means, with a few exceptions, that both reference points and selective accessibility (via difference search) may account for contrast outcomes. On the other hand, an assimilative outcome on a subjective rating scale is strong evidence that the influence of selective accessibility (via similarity testing) was greater than any effect of reference point. For these reasons, Mussweiler (2003) prefers to demonstrate comparison effects on absolute judgments rather than on subjective rating scales. But, to date, there is more research available that reports rating scale outcomes. This will be a relevant consideration when we review the relevant evidence.

seemingly disinterested in whether the comparison outcome reflects positively or negatively on the self. Mussweiler, Epstrude, and Ruter (2005) note, however, that people motivated to preserve a positive self-image when confronted with a low standard may focus more on dissimilarity testing. Stapel and Schwinghammer (2004) have shown that defensiveness may prompt construal of comparison targets in ways that protect self-esteem (also see Stapel & Van der Zee, 2006). But a systematic approach to personal motivations is missing in SAM, which does not differentiate between the motivation to succeed versus that to avoid failure. When self-enhancement is considered, approach and avoidance motivations are lumped together. We propose that people should be interested in the outcome of social comparisons because they want to find out and confirm that they are worthwhile. This means that people are always oriented upward whether they want to approach success or avoid failure. The central question is “How close am I to those people up there?” When the approach motive is high, the person wants to know this so he can get there. When avoidance is high, they hope the gap is not so great that it makes them feel and look bad. Translated into approach–avoidance terms, people should want to excel on the comparison dimension and avoid failure on the comparison dimension. We assume, however, that situational factors and individual differences determine whether approach or avoidance is salient. (Much of this volume is devoted to these topics.) The approach–avoidance distinction is represented by the two levels of the first factor in the 2 × 4 scheme that we propose (see Table 35.1). The second factor refers to the status of the comparison target, which considers both direction—upward/downward—and extremity: from extremely superior, slightly superior, and slightly inferior to extremely inferior.

THE ROLE OF MOTIVES

THE APPROACH–AVOIDANCE MODEL OF COMPARISON

Neither the selective accessibility or reference point theories have formal mechanisms addressing the role of motives on responses to comparisons with superior or inferior others. The cognitive mechanisms grind away

In our scheme, the comparison effects of features identified in research, such as closeness, related attributes, attainability, mutability, and extremity, are considered in light of the approach or avoidance tendencies. This is best explained by describing how approach–avoidance should work in assimilation-contrast terms in each cell of the 2 × 4 matrix. In Scenario A, the desire to excel (approach) is difficult to satisfy with someone who is highly superior, such as Einstein, Gandhi, or a fashion model. In the case of a superstar, the likelihood of psychological closeness, attainability, or related attributes also is probably low and immediately apparent; thus, selective search for differences

* Changes in reference point interpretation do not account for assimilation phenomena as easily (Wedell, Hicklin, & Smarandescu, 2007). Some related models posit an inclusion process leading to assimilation when the comparison other has attributes that are potentially relevant to the self-representation. Under such circumstances, the person and the comparison target are assigned to the same category— assimilation (Schwarz & Bless, 1992; Stapel & Koomen, 2001b).

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TABLE 35.1 Comparison Responses as a Function of Approach–Avoidance Motivation and Target Direction and Extremity Target Direction and Extremity Motivation

Highly Superior

Slightly Superior

Slightly Inferior

Highly Inferior

Approach

A Contrast

B Assimilation

C Contrast

D Ignore or maybe contrast

Avoidance

E He/she is a noncomparable genius.

F Derogate (lower) the target to your level.

G Emphasize your differences from that person to avoid possibility of assimilation.

H Contrast

should commence. Of course, in the interest of selfenhancement, it would be optimal to cease comparison with such targets or find someone not quite so brilliant. But the target’s extremity probably engages dissimilarity search, leading to contrast. We doubt, however, that the self-evaluation is repelled so far that it shifts to the negative side of the continuum. For Scenario B, exposure to a slightly superior other, combined with a personal desire to excel (approach), should yield assimilation. This possibility was first explicitly recognized by Collins (1996), but was implied by earlier evidence (Wheeler, 1966). According to SAM, the similarity search default contributes here, the distance from the target also is not too large, and any other relevant feature (e.g., closeness, related attributes, attainability) will further engage retrieval or construal of similarity with the target. Self-evaluations, therefore, should move closer to the superior other. Any initially detected feature that seems to negate the possibility of attainment or similarity, however, should terminate similarity seeking and discourage assimilation. If the person is motivated to excel (approach) and exposed to a slightly inferior target then contrast should be the result (Scenario C). Although the distance from the target is not great, the person should be motivated to reject similarity testing. Also, if there are any features that might suggest similarity with the target, it is in the person’s interest to ignore them. If the target is highly inferior, however, then either it is ignored or contrast occurs because of the initial impression of dissimilarity (Scenario D). We assume the target’s extreme (inferior) status will frequently imply that there is a difference in related attributes between them. Selective retrieval of other differences should only reinforce that impression.

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When avoidance is high and the target is highly superior, the simplest strategy to “save face” is to consider them a noncomparable genius (Scenario E). If the person is only slightly better, derogation of the target to your level is the best option (Scenario F). This is probably the scenario where pressure for selective construal of the comparison target or sabotage is the greatest (Scenario F). To avoid failure when confronted with a slightly inferior target (Scenario G), it is best for the person to emphasize differences (i.e., dissimilarity search leading to contrast) because the person is not far from them. This tendency to find dissimilarity should be most intense, however, if the target is highly inferior, producing contrast (Scenario H). It is noteworthy that contrast is considered more likely whenever the person compares with an inferior target (regardless of how different the target is; scenarios C, D, G, & H). Whether a person wants to excel (approach) or avoid failure (avoidance), downward assimilation is an unlikely outcome. This prediction is consistent with the empirical literature where instances of downward assimilation have rarely been documented (Wheeler & Suls, in press). Another point concerns the unavoidable looseness of some predictions. Things work like this in general, but there are probably circumstances where a single salient attribute could create the opposite outcome. For example, a person might be extremely avoidant about academic situations and tend to derogate those who are more academically successful (Scenario F). But if the target happens to be a sibling then psychological closeness might become very salient and induce selective retrieval that results in (upward) assimilation. Or, for an aspiring student, assimilation toward a slightly better classmate might be

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short-circuited in the absence of an expectation about improving. There are, however, a wide variety of factors (extremity, related attributes, attainability, mutability, psychological closeness) that may effect the initial holistic impression of the comparison target. Because these features may not be highly correlated, the exact outcome may be difficult to predict; this looseness in the model seems necessary to remain true to the complexities and subtleties of comparison in social life. (Researchers, however, should manipulate all of these factors independently or keep some constant while manipulating others.)

RELEVANT EMPIRICAL EVIDENCE Our approach–avoidance comparison model requires systematic empirical testing, but some tentative support for the predictions can be found in previous experiments that will be briefly described below. Before describing this evidence, a few issues should be noted. With a few exceptions, approach and avoidance have not been measured or manipulated in past comparison research (but see Lockwood, 2002). But our reading of the empirical literature suggested that certain situational or individual difference variables in some experiments can plausibly be considered as approach or avoidance. Also, we made some judgments about the extremity of the comparison target. A successful peer seemed to us to be slightly superior; figures like Einstein, Mother Teresa, or professional fashion models to be extremely superior. Second, inclusion of no-comparison control groups or pre and post comparison self-evaluative ratings is atypical in the literature (Wheeler, 2000; Wheeler & Suls, in press). This is unfortunate because, in the absence of such information, it is not possible to unambiguously determine whether the upward target or downward target is attracting or repelling, or both are acting on self-ratings. For example, there may have been contrast with an upward target leading to lower self-ratings that nonetheless still are in the positive range. Alternatively, the self-ratings may have been repelled to the negative side of the continuum. Finally, the outcomes of most relevant research are in the form of subjective rating scales, so these were the focus of our review. But for some scenarios, relevant data using self-evaluation were unavailable. In those cases, we had to rely on studies with different kinds of outcomes, such as mood, self-esteem, and motivation. This is not our preference because we have previously shown that self-evaluations, affect, and behavior do not necessarily respond in the same way to upward/downward comparisons (Suls & Wheeler, 2007; Wheeler & Suls, in press). In fact, we have strongly advocated for defining

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assimilation and contrast in social comparison as displacements in self-evaluations toward or away from targets. For the present, however, we had to deviate from our preference. Approach and a Highly Superior Target (Scenario A) Cash, Cash, and Butters (1983) exposed women to photographs of very physically attractive women (taken from magazines), but described as other college students. Subjects’ self-ratings of attractiveness decreased—producing a contrast effect. Brown et al. (1992) also found contrast effects, except when the target shared a similarity with the subject (such as a birthday or similar attitudes). In the latter condition, we assume that the shared attribute increased the similarity search and produced assimilation, as predicted for Scenario B. In Cash et al. (1983), there was also a condition that attached a label (Calvin Klein or Cover Girl) to the photo to emphasize the stimulus person’s status as a professional model. Subjects’ selfattractiveness ratings were unaffected (i.e., no contrast) in the “model condition.” This suggests that subjects ceased comparing with the photos because the models were perceived to be irrelevant to them (see Scenario E). Thornton and Moore (1993) also examined effects of exposure to very physically attractive targets on selfevaluations. Two experiments collected self-ratings after exposure to attractive targets versus a no-comparison control group. Both men and women rated themselves lower in attractiveness after exposure to same-sex attractive photographs—a negative contrast effect. In an experiment mentioned earlier, Morse and Gergen’s (1970) subjects were recruited with the cover story of applying for a summer part-time job; therefore we assume they were oriented toward success. Although the comparison target was a college student, the experiment was conducted in the 1960s in a midwestern university town. “Mr. Clean” was a job applicant who was well groomed, dressed in a suit and with an attaché case. Thus, we think Mr. Clean probably created a very high (i.e., extreme) standard. When subjects were exposed to Mr. Clean, self-esteem ratings decreased from baseline, suggestive of a (negative) contrast effect. In a supplementary analysis (based on the experimenter’s ratings of the subject’s appearance and demeanor), those who resembled Mr. Dirty showed the largest contrast effect after being exposed to Mr. Clean. Approach and a Slightly Superior Target (Scenario B) This case should produce assimilation, an outcome reported by Lockwood and Kunda (1997) who had firstyear and senior college student subjects read a description

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of a very successful senior of matching major and gender. We assume that college students in general are motivated to succeed and read the materials about another student with that set. First-year students were inspired and made higher self-ratings on traits relevant to career success (i.e., assimilation) than subjects not exposed to any target. However, subjects who also were seniors (like the target), and therefore no longer had time to attain the same success (i.e., low attainability), did not show any more positive reaction than those subjects in the no-comparison control condition. In an experiment that shares many features with Lockwood and Kunda (1997), Stapel and Schwinghammer (2004; Study 1) had college students who were psychology majors read a (fictitious) newspaper article about another student who was described in either very positive or very negative terms. Subsequently, the subjects completed ratings about themselves. A reliable contrast effect was found; inclusion of a no-comparison control showed that the upward comparison lowered and downward comparison increased self-evaluations. Of course, this conflicts with our prediction and Lockwood and Kunda’s finding of assimilation. However, Stapel and Schwinghammer’s target was simply described as a psychology student, whether the target was a senior should not have been clear to the subjects. Also, the attributes on which the target excelled or was deficient were relatively enduring (intelligent, well liked, and friendly vs. unintelligent, not liked, and unfriendly). We speculate that the absence of salient clues for similarity and low likelihood of attainability prompted difference search. But this does suggest that the occurrence of assimilation versus contrast in Scenario B is temperamental. Nosanchuk and Erickson (1985) conducted a study of social comparison among experienced bridge players, who should have been motivated to win given their commitment to team playing. Although respondents claimed to compare with players of similar ability, often those named were objectively superior according to lifetime playing records. The results suggest that average players assimilated their ability to the higher level. This is not surprising as the subjects still had the possibility of getting better. Testa and Major (1990) led subjects to believe their performance on a test could improve or not and then they learned about an upward comparison target who performed slightly better. When subjects believed they could improve, they felt more positively and were more persistent than those who believed improvement was impossible. The downward comparison had no differential effects in this study.

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Approach and a Slightly or Extremely Inferior Target (Scenarios C & D) In these cases, the comparison target is worse-off than the subject. Morse and Gergen’s (1970) results are relevant to C & D, but it is difficult for us to decide whether Mr. Dirty represents an instance of slight or extreme inferiority. In the 1960s, Mr. Dirty was probably a more common sight on college campuses (one of us was encouraged to “Get clean for Gene [McCarthy]!” in the 1960s’; we declined!) and probably did not stand out as much as Mr. Clean. Fortunately, contrast is predicted for both Cells C and D; however, when the target is very extreme, the subject might also ignore the target as irrelevant. With these considerations in mind, it is noteworthy that after being exposed to Mr. Dirty, subjects’ self-esteem increased from baseline—a (positive) contrast effect. The smallest change was seen in “neat” subjects suggesting they found Mr. Dirty to be highly inferior (more like Scenario D) or irrelevant to them. But those subjects who resembled Mr. Dirty (and therefore were closer in reality to him) actually showed the largest increase in selfesteem—a (positive) contrast effect (Scenario C). Lockwood (2002) examined the role of perceived vulnerability in response to downward comparisons. First-year college students read about another fi rst-year student who was doing poorly in the transition to college. Lockwood posited subjects would not feel vulnerable to another’s predicament because they were doing OK in their first year of college. We also assume that low vulnerability should have oriented the student subjects toward success rather than avoidance of failure. Lockwood predicted and found that subject’s self-ratings became more positive (vs. no-comparison target)— a contrastive self-evaluation, which is consistent with our analysis of scenario C. (To obtain the contrast effect, it was also necessary for Lockwood to instruct subjects to think about how they might become like the other student.) Avoidance and a Highly Superior Target (Scenario E) When avoiding failure is salient (whether because of situational or chronic needs), people should try to find a way to make their distance from the top irrelevant. Hoffman, Festinger, and Lawrence (1954) had subjects work in three-person competitive bargaining tasks. When subjects were falsely told that one of the players (an accomplice) was clearly superior, they competed considerably less with him and more against each other. Since the task was difficult (probably raising concerns about losing points) and competition is one way to acquire comparison information, this result is consistent with our prediction

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that comparison ceases with a very superior other when avoidance motivation is strong. More definitive evidence comes in the form of the socalled “genius effect,” demonstrated by Alicke, LoSchiavo, Zerbst, and Zhang (1997). They found that when subjects did not perform well on difficult problems compared to an accomplice—which should have made avoidance salient— they tended to aggrandize the superior performer’s abilities. That is, subjects rated him/her as much more intelligent. Alicke et al. (1997) proposed that seeing the superior performer as a genius allowed the subject to reduce self-esteem threat. Observer-subjects who learned about the relative performance of the subject and the accomplice did not make differential ratings of ability. These results are quite consistent with the idea that a salient desire to avoid failure after being exposed to a highly superior other prompts perception of the other as a “noncomparable genius.” Cash et al.’s (1983) finding no contrast when female subjects were exposed to photographs labeled as professional models may also be relevant to Scenario E. Although we think most young people are motivated to be seen as attractive (approach in cells A and B), learning that they are comparing to a model might make avoidance salient. Putting the models in the “noncomparable beauty category” makes them irrelevant to self—hence, there was no contrast in that condition. Avoidance and a Slightly Superior Target (Scenario F) Our analysis suggests that exposure to a slightly superior target, combined with a motive to avoid failure, should lead to derogation of the target to one’s own level. After all, the target is not so superior that this is impossible at least in one’s own mind. Unfortunately, subjective construal of comparison targets or sabotage is not frequently measured, but a study by Tesser and Smith (1980) has relevance. They found that when subjects were outperformed by a friend on a self-relevant task, the subjects subsequently provided fewer clues to help the friend, presumably to lower his/her performance and make him more comparable to the self. Avoidance and a Slightly Inferior Target (Scenario G) Some studies have shown that depressed students (Gibbons, 1986; Study 2) and students in a negative mood (Aspinwall & Taylor, 1993) report more positive affect after exposure to a worse-off peer. This has also been found among persons low in self-esteem (Aspinwall & Taylor, 1993). If we assume that these subjects were very concerned about avoiding failure then the changes in affect suggest they saw differences with the target. Admittedly, this must be considered speculative.

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More direct evidence can be found in an experiment conducted by Lockwood (2002). First-year college students read a description of a graduate who was having great difficulty obtaining employment and making the transition from college. In this case, Lockwood thought the subjects could perceive that they were vulnerable to the same predicament, thus their wanting not to fail should have been strong. Relative to a no-comparison control group, subjects rated themselves less positively. This might be indicative of assimilation—contrary to our prediction. In this scenario, our model predicts people should try to distance themselves to avoid possibility of assimilation. It should be noted, however, that subject’s mean ratings were above the midpoint so subjects still saw themselves in relatively positive terms. A different dependent variable showed results more consistent with our prediction. Lockwood also measured the degree to which subjects planned to act in ways to prevent failure. Consistent with the idea that people would try to emphasize their differences with a slightly inferior target to avoid assimilation, subjects exposed to the unsuccessful graduate reported thinking of more specific strategies they would use in the future to avoid failure. Avoidance and a Highly Inferior Target (Scenario H) The effects of extreme comparison targets have been studied. For example, Stapel and Blanton (2004) found that subjects primed with “Clown” made more positive selfevaluations than those primed with Einstein. But to our knowledge, no experimental studies have looked at comparisons with highly inferior targets in situations that manipulated or measured approach–avoidance motivation. According to our model, this scenario should produce contrast. Some indirect support for this prediction comes from Wood et al.’s (1985) study of cancer survivors who we assume wanted to avoid thoughts about negative outcomes (i.e., disease recurrence, coping difficulties). The fact that the vast majority of them reported that they were doing much better than most cancer patients is consistent. We think that the appeal of gossip about celebrities might also fall into this category (Brickman & Bulman, 1977; Suls, 1977). Famous actors, musicians, and politicians can serve as foils for the rest of us when we learn about the terrible predicaments to which they fall victim. The most “trashtastic” current celebrity can serve as an extreme negative standard for contrast, which may account for the high level of interest in gossip. Coda For some scenarios, the evidence we reviewed is somewhat thin. Perhaps the biggest limitation of the review,

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however, concerns whether the upward or downward target is attracting or repelling, or both are acting. As noted above, we cannot always ascertain whether contrast with an upward target repels the subject below a psychological midpoint or whether the subject hovers at or somewhat above the midpoint. Conversely, the evidence does not indicate whether contrast with a downward comparison leads to a self-evaluation above the midpoint or only slightly distanced from the inferior target. Our view, however, is that because people want to feel worthwhile, their self-evaluations should be somewhat positive even if their self-ratings are displaced (i.e., contrasted) from someone who is superior. Exposed to a downward comparison, people also probably try their best to see themselves on the positive side of the dimension, not just as less inferior. The Case of the Similar Comparison Target The 2 × 4 table does not address responses to similar targets. It might be imagined that comparison with others of similar standing would not produce any shifts in selfevaluation because the person should be satisfied to find a fellow to share the same rung on the social ladder. Often, in the case of opinions, finding such agreement is satisfying (Festinger, 1954a,b; Suls et al., 2000). The present approach, however, concerns comparison of personal attributes that are relevant to success and failure. Earlier, we described the unidirectional drive upward and how it prevents a state of “social quiescence” (Festinger, 1954a). If we are to learn about someone who has performed at the same level, there will be an upward drive to outdo him/her. There may be cultural constraints on this tendency. Festinger (1954a) observed that non-Western cultures that de-emphasize competitive and achievement may not exhibit the unidirectional drive. But in the societies most extensively studied to date by comparison researchers, the striving to be better and do better seems prevalent. Thus, people are oriented toward targets who are somewhat better than themselves. Evidence for preferred upward comparison choices (Blanton, Buunk, Gibbons, & Kuyper, 1999; Huguet, Dumas, Monteil, & Genestoux, 2001; Suls & Tesch, 1978; Thornton & Arrowood, 1966; Wheeler, 1966; Wheeler et al., 1969) consistently documents this tendency.

CONCLUSIONS AND IMPLICATIONS To show how they are relevant to contemporary issues, we wanted to reacquaint the reader with elements of LOA research that Festinger used in his classic social comparison theory. The integration of these motivational concepts

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with contemporary theory and research provides a better understanding of how people select comparison information to evaluate their capabilities. Furthermore, distinguishing between approach and avoidance motives provides a more comprehensive way to predict when upward or downward comparisons lead to assimilation versus contrast. Previous writers and researchers have emphasized how self-enhancement can affect both the search for comparison information and comparison responses (Wills, 1981; Wood, 1989). However, selfenhancement lumps together two very different motives— the need to excel and the need to avoid failure. Our approach–avoidance model shows how these motives can produce different outcomes depending on the direction and extremity of the comparison target. Contemporary social cognitive theories of assimilation contrast (Mussweiler, 2003; Stapel & Koomen, 2001a,b) informed our analysis, but motives previously have not been systematically or formally included as an integral component of these cognitive models. The relevant evidence that we found provides support for our approach– avoidance model although the available evidence is admittedly limited and rests in some instances on plausible but unverified assumptions. Nonetheless, we think the 2 × 4 model has sufficient support to serve as a generative framework to pose more refined questions, to conduct studies with more informative results, and to provide a common ground for self-evaluation researchers and motivation researchers. Finally, we hope this chapter can serve as a trustworthy map to encourage the next explorers to approach, rather than avoid, this challenging territory.

ACKNOWLEDGMENTS Preparation of this chapter was partially supported by grants from National Science Foundation BCS-9910592 and National Science Foundation BCS-SGER 0634901 to JS and by the Australian Research Council DP0449717 to LW. Also, we are grateful to Majorie Seaton for her splendid comments and suggestions and to Bryan Koestner for his excellent questions.

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Social Exclusion Approaching the Decision 36 ItoAm Avoid You: An Approach and Avoidance Perspective on Research on Social Exclusion and Rejection Roy F. Baumeister and Seth Gitter CONTENTS The Need to Belong...............................................................................................................................601 Rejecting Strangers ...............................................................................................................................603 Rejecting Current Relationship Partners...............................................................................................605 Responses to Exclusion Threats ............................................................................................................606 Responses to Actual Rejection ..............................................................................................................608 Conclusion ............................................................................................................................................. 611 References ............................................................................................................................................. 611

As cultural animals, humans live by rules set up by the community. Government, religions and, on a more micro level, local community and social groups have developed rules and laws that guide and direct behavior. Those who abide by society’s rules are rewarded for their behavior. Those who disobey face severe punishments. Quite possibly the most used and oldest form of punishment is social rejection/ostracism. Although the practices of banishment and exile, so readily used by early humankind, have fallen out of favor in recent years, people still rely on rejection in some form or another to encourage appropriate behavior in social contexts. Rejection looms large and one simple slip can lead an individual to lose relationships that are so important to him or her. With rejection being such a looming threat in the social world across evolutionary history, one would expect strong motivational responses to the threat and occurrence of social exclusion. For early humans, rejection was likely to lead to death. As a result, people should

have developed a strong predisposition to avoid the occurrence of rejection and to react quickly after rejection. Recently, there has been an increased interest in studying appetitive/approach and aversive/avoidance motives with regard to the social domain (Elliot, Gable, & Mapes, 2006; Gable, 2006). Although research is currently being devoted to the motivational factors that draw people together, little, if any, research has been directed to identifying similar motivational factors that pull people apart. To address this disparity in the literature, our aim in this chapter is to present supportable evidence to suggest how motivational systems allow individuals to navigate the tortuous waters between acceptance and exclusion.

THE NEED TO BELONG Baumeister and Leary (1995) suggest that humans have a fundamental motivation to form groups and relationships and to sustain these connections (see also Bowlby, 1969, 601

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1973; Maslow, 1968). It is even suggested that many of the other motivations that people have (e.g., need for achievement) are driven by or derived from a need to belong to a social group (Baumeister & Leary, 1995)—as the attainment of these goals would facilitate being perceived as a good relationship partner. Belonging to groups could therefore be considered to be one of the most important positive outcomes that motivate and guide human behavior. Yet belongingness seems to serve the purpose of attaining other outcomes as well. In this next section we look to the relevant literature presented by Baumeister and Leary (1995) on the need to belong. We focus on the distinction between specific approach and avoidance motivation factors associated with this need. The need to belong likely developed over human evolutionary history, as individuals who had a strong motivation to form social bonds with others would have survived and reproduced better than individuals who lacked this need. Many positive outcomes can be acquired through striving to affiliate with others, suggesting that the need to belong is driven by a strong approach motivation. Group members would be more successful than individuals at procuring food—through hunting and food-sharing. Individuals might also find it much more difficult than group members to acquire a mate (a necessary condition for reproduction). Individuals who are motivated to affiliate would also be much more successful at raising children to reproductive age than individuals who would be less motivated to stay with the child. Additionally, groups can benefit by sharing vigilance duties, thereby improving avoidance of predators and other enemies. This might be suspect as a twinge of avoidant motivation present in the need to belong as the individual is attempting to avoid some negative outcome. Yet research by Rofe (1984) suggests that people are driven to be with others under the threat of possible danger elicited by such cues as illness, danger, nightfall, and disaster. Essentially, individuals seek out others for protection rather than simply trying to avoid the threat of danger. Therefore, the threats to survival drive individuals to affiliate with others, suggesting avoiding threat leads to approaching allies. Belonging to groups therefore appears to function to a great degree to ensure the attainment of outcomes necessary to survive in a harsh environment. This drive is likely elicited by approach motivation. Modern life has obviated some of the pragmatic need for belongingness. If nothing else, the meteoric rise in single-person households demonstrates this. We no longer need to have somebody watching out for marauding tigers. Individuals still depend on others to provide resources for them (e.g., food, protection), but there is a

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reduced need to interact with others to acquire these resources. For example rather than relying on group members to engage in cooperative hunting, today an individual can simply pick up a filling and tasty and slightly nutritious meal by passing through a drive-through. But evolution has done its work, and people still crave social connection regardless of whether they absolutely need it for survival. The relationship between an individual and those he or she relies upon for certain resources is decidedly reduced compared to the relationships our ancestors forged to ensure survival, and indeed the global economy allows people to have mutually beneficial interactions with far-off strangers they will never meet. Evolution likely did not select for people who sought out relationship partners merely to obtain resources. Rather it is more likely that those individuals who had a strong motivation to seek out relationship partners, and consequently suffered when alone, were more likely to survive due to the benefits of engaging in relationships. One of the most widely supported findings in the behavioral sciences is that individuals who lack relationships suffer from decrements in health, adjustment, and well-being (see Berscheid & Reis, 1998 for review). Although the modern day environment may seem to reduce the need to associate with others for the direct procurement of resources, affiliating with others remains an important need that can produce substantial benefits over being alone. Indeed individuals today retain similar needs to develop relationships as those suggested to be prevalent in our ancestors. The ease with which individuals form relationships with others implies a strong approach motivation. This is evident in research showing proximity (or the mere experience of interacting with another) to be one of the biggest factors in predicting whether a relationship will occur between two people (Festinger, Schachter, & Back, 1950)—even overcoming the role that similarity plays in forming social bonds (Nahemov & Lawton, 1975). Research on minimal group paradigms has also shown the ease with which cohesive groups form (Brewer, 1979). Relationships can even develop in the presence of adverse circumstances (Latane, Eckman, & Joy, 1966) and with individuals who were once disliked (Sherif, Harvey, White, Hood, & Sherif, 1961/1988; Wilder & Thompson, 1980). It appears that people are willing to start a relationship with just about anyone that they encounter, suggesting a strong approach orientation to the development of relationships. Even individuals who appear, at least on the surface, to lack this persistent need to form relationships still desire them. Individuals who suffer from social anxiety

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Rejection and Approach and Avoidance Motivation

disorder (SAD) and those who are shy are very resistant to engaging others in social interaction. Yet this seems to be more a result of fears concerning evaluation than a lack of a need to form relationships. When shy individuals interact with others, they engage in a large degree of “innocuously sociable” behavior (Leary, 1983) such as smiling and nodding, as well as verbally reinforcing those they are interacting with. Schlenker and Leary (1982) suggest that the reactions of individuals suffering from SAD seem to stem from the discrepancy between the strong desire to make a positive impression and the worry or expectation that they will be unable to do so. For shy and SAD individuals the concern with belonging seems to remain pervasive. Rather, their dissociation from interaction seems to stem from a low self-efficacy to form the desired impression rather than a lack of desire to form relationships. Forming relationships does not seem to be enough to satiate the need to belong as people seem to benefit little by simply having relationships. Rather these relationships need to consist of strong bonds of mutual caring (Baumeister & Leary, 1995). Individuals should therefore also be motivated to further the development of their relationships with others. Seemingly, those individuals who engage in approach-oriented behavior toward developing their current relationships benefit greatly. Elliot et al. (2006) found that individuals who espoused strong approach goals with their current friendships benefited more than individuals who espoused avoidance social goals. Individuals with strong approach social goals (e.g., “I am trying to deepen my relationships with my friends”) reported greater relationship satisfaction, lowered perceptions of loneliness, and a greater number and impact of positive relationship experiences compared with individuals who espoused a more avoidant stance to their friendships (e.g., “I am trying to avoid disagreements and conflicts with my friends”) who experienced more loneliness and a greater number and impact of negative relationship events. In the long-term, individuals who scored higher in friendship approach goals showed an increase in subjective well-being, whereas individuals who scored higher in friendship avoidance goals showed an increase in physical symptomology. Seemingly, individuals benefit by continually devoting time and resources to their current relationship partners. The need to belong is such a strong motivation that it would likely make individuals reluctant to reject others. Indeed, individuals seem disinclined to sever ties that they have formed with others, including relationships that are based on loosely established ties, and even abusive relationships (see Baumeister & Leary, 1995 for review).

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Anecdotally, many of our research assistants express great difficulty at having to tell research participants that they have been rejected by someone else. They feel pained at the possibility of a distraught or surprised look on the face of the participant upon hearing this. The saving grace of this experience is to see the look of relief on the participant’s face upon learning of the deception of the experiment during the debriefing. Experimental evidence confirms that people are at least reluctant to reject others outright. Folkes (1982) compared women’s real reasons for rejecting a potential date to the reasons they told the luckless men. Although most women explained the rejection as based on some factor external to the requestor (e.g., she was busy on the evening he picked), the true reason tended to involve something internal to him, such as that he was unattractive, unintelligent, or poor. Converging evidence comes from research on unrequited love. People who have to reject would-be-lovers often experience extreme guilt over having to reject someone they once considered a close friend (Baumeister, Wotman, & Stillwell, 1993; Baumeister & Dhavale, 2001). Even though the experience is almost always negative for them, rejectors are reluctant to exclude the would-be-lovers entirely. Unfortunately this often results in the would-be-lover doubling his or her efforts, likely resulting in an even more stressful situation for the rejector. Seemingly rejection is something that is not taken lightly, experienced as very aversive, and often avoided until all other options have been exhausted. In the modern environment, it is likely impossible for an individual to accept all others. As humans are incredibly social animals, individuals may occasionally confront others who are vying for their affection—affection that may already be tied up with other relationship partners. Devoting time and resources to new relationship partners limits the amount of time and resources an individual can devote to already established ties. Humans therefore should have developed specific parameters with which to discriminate between the possible relationship partners within the environment—seeking out the most advantageous relationships to devote time and resources to. Although rejecting people may be an aversive experience, some individuals will need to be rejected in favor of others.

REJECTING STRANGERS Although it may seem paradoxical, satiation of the need to belong may actually be one factor that results in the exclusion of some individuals. Individuals have a limited

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amount of time and resources to devote to their relationships (Audy, 1980; Leary, 2001; Tooby & Cosmides, 1996). In order to devote the requisite time and resources to relationships of high importance, individuals need to exclude others. Research has shown that individuals do prefer a small group of intimate relationships to a large number of loosely established ties (Caldwell & Peplau, 1982; Reis, 1990). Even when an individual is immersed in a highly social environment and has access to a large number of possible relationship partners, he or she will tend to devote the majority of his or her time to the same five or six individuals (Wheeler & Nezlek, 1977). Parker and Asher (1993) found that the quality of one’s relationships is more important for producing positive psychological outcomes than the sheer quantity of relationships. The findings of Elliot et al. (2006) also attest to the benefits acquired by being motivated to approach those relationships that one has already established. Individuals with strong approach goals have much more satisfactory relationships with others and show greater increases in subjective well-being over time compared to individuals with low approach goals and those with a strong avoidance goals—who seemed to suffer as a result of their relationships. Seemingly, a strong approach motivation to continually engage in current relationships appears to result in the by-default rejection of others. Other more direct forms of stranger rejection have also been identified and seem to result from stigmatization—the process of ascribing negative global evaluations to a person based on a single defining negative characteristic (Goffman, 1963). Several different theories have been presented to explain processes of stigmatization each with its own interpretation of what is likely to be stigmatized as well as the process through which stigmatization occurs (Crocker, Major, & Steele, 1998; Elliot, Ziegler, Altman, & Scott, 1982; Goffman, 1963; Jones et al., 1984; Kurzban & Leary, 2001). Regardless of the process, however, the major function of stigma is to identify individuals to be avoided or excluded from social interaction (Kurzban & Leary, 2001). The basic premise of functional stigma avoidance (Kurzban & Leary, 2001) is that humans, over the course of evolutionary history, would likely develop specific adaptations to identify and avoid other individuals who could pose threats to survival, reproduction, and resource acquisition. If an individual is assessed to be a threat to any one of these factors, he or she would be more likely than individuals who do not exhibit these characteristics to be rejected from group interaction. Insofar as these stigmas identify an individual as unfit for social interaction, it is likely that stigma serves largely as an avoidance

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cue. For example, parasite avoidance is indeed a factor that should result in the avoidance of an individual to facilitate survival and reproduction. Due to the possibility of contagion when interacting with someone who is ill, those of our ancestors who were sensitive to and readily avoided anyone with a marker of parasitic infection would have been more likely to survive than those who didn’t. In some instances clear markers (such as infested sores and a higher incidence of coughing) are present that would suggest an individual is infected. Other identifying features are much more subtle however. The ability to withstand environmental and genetic stressors in both humans and animals is reflected in facial/bodily symmetry, as the presence of parasites usually leads to asymmetrical features (see Grammer & Thornhill, 1994; Kurzban & Leary, 2001 for review). Humans and other animals have been shown to have a preference for facial and bodily symmetry (Bruce & Morgan, 1975; Gangestad & Thornhill, 1997). These systems become especially sensitive at key times. Specifically, women become more sensitive to facial symmetry, even detecting it through scent, when they are able to become pregnant (Thornhill & Gangestad, 1999). Parasitic avoidance therefore seems to have partly risen from a motivation to avoid reproduction with unhealthy partners. There may be some question as to whether sensitivity to symmetry is an approach or avoidance motivation. Researchers often frame their findings to suggest a preference for symmetrical faces over asymmetrical faces. Preferences motivate an individual to attain things that provide resources and benefits needed for reproduction (Orians & Heerwagen, 1992). Therefore, the preference for symmetrical faces may be an approach motivation to attain healthy partners. Nevertheless, this preference is only in a relative sense in that individuals rate symmetrical others as more attractive than asymmetrical others. Rather, parasitic avoidance mechanisms are likely similar to other evolutionary avoidance systems that are overly sensitive to the possibility of a negative outcome (e.g., fear; Haselton & Buss, 2000). The costs of mating with someone who appears to be healthy, but is not (miss), is much greater than the cost of not mating with someone who appears unhealthy, but is actually healthy (false positive)—oversensitizing the system to false positives. Therefore, it seems more likely that our preference for symmetrical faces arose from avoidance of parasites rather than to approach individuals free from parasites. Another function of stigmatization is to avoid relationships that could lead to unfair reciprocal exchange (Kurzban & Leary, 2001). One of the suggested reasons for the development of the need to belong is that individuals who belonged to groups would benefit by engaging in

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exchange with one another (Baumeister & Leary, 1995). There are certain restrictions that limit an individual’s ability to benefit from dyadic cooperation however. For a person to benefit from exchange, he or she should (1) readily cooperate with others—but only when reciprocation is likely, (2) be especially sensitive to individuals who violate social contracts, and (3) quickly reject any person who is unwilling to engage in fair exchange (Cosmides & Tooby, 1992). If reciprocal exchange were guided only by approach motivation and an individual were indiscriminately prosocial with others, he or she would be more likely than an individual that followed these rules to give resources to others and not receive anything in exchange. Avoidance motivation should therefore guide decisions to exclude others who appear unable or unwilling to reciprocate. Indeed, humans have developed specific adaptations to identify cheaters—those individuals who take more than they give. Cosmides (1985) reviewed the literature examining performance on the Wason selection task. The Wason selection task is widely used to assess an individual’s ability to detect conditional rules (Wason, 1966). Normally individuals perform quite poorly on these tasks. Most of the errors on this task are errors of omission in which participants fail to identify disconfirming information (Chapman & Johnson, 2002). When these tasks are framed as social contract violations, however, such as taking benefits without paying costs, individuals solve them much more easily and accurately, with approximately 75% of participants correctly solving the problem (Cosmides, 1985). Crucially, performance increased because participants’ sensitivity to disconfirming information increased on these social contract problems compared to standard conditional logic problems. In social contract problems the disconfirming instance is one in which an individual might be cheating by receiving some benefit without meeting the criteria necessary to receive that benefit. Individual increases in performance on social contract problems appear to result from a strong sensitization to the possibility of being cheated on and the desire to avoid this outcome. Cheater detection is only one avoidance motivated function in dyadic cooperation. Kurzban and Leary (2001) also proposed that the predictability of a potential relationship partner will influence whether he or she is selected as an exchange partner. Individuals who associate with those who are unpredictable cannot be sure that they will receive resources in exchange. Basically, successful exchange requires coordination between individuals (Cosmides & Tooby, 1992). In order to coordinate exchange, an individual needs to be able to infer the intentions of his or her exchange partners. People generate expectations about

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individuals based on societal norms. When individuals violate these norms, they break from expectations. This break from expectations leads observers to evaluate them as unpredictable and results in the norm-violating individual being evaluated more negatively than individuals who follow social norms (Kiesler, 1973). Humans appear to have developed systems sensitized to identify individuals who appear unwilling and unable to engage in fruitful, mutually beneficial exchange.

REJECTING CURRENT RELATIONSHIP PARTNERS Undoubtedly it is harder to reject a partner from an ongoing relationship than to reject a stranger before any relationship starts. Indeed the research attests to the resistance of committed relationships to dissolution (see Baumeister & Leary, 1995 for review). Although it would be expected that extreme negative experiences, such as abuse, would result in relationship dissolution, a great number of people are reluctant to end abusive relationships (Roy, 1977; Strube, 1988). Similarly, the experience of infidelity might be expected to be a deal-breaker in romantic relationships, yet a goodly proportion of individuals who experienced infidelity in a former relationship suggest that the infidelity was not the cause of the break-up (approximately 25%; Hall & Fincham, 2006). People even seem reluctant to end relationships with people that they have little interest in. Studies of unrequited love have shown that although the experience is more negative for the would-be-loved individual, these people are very reluctant to completely reject their would-be-lovers (Baumeister et al., 1993; Baumeister & Dhavale, 2001). Interdependence theory (Kelley & Thibault, 1978) and investment model theory (Rusbult, 1980a) suggest that individuals consider more than just the negative experiences associated with their relationships. Rather, an individual’s satisfaction with his or her relationship is a result of a comparison of the rewards (e.g., perceived similarity, attractiveness of partner) and costs (e.g., time and monetary costs) present in the relationship compared to the expectations that one has for his or her partner. If a relationship partner continues to produce more rewards and fewer costs than his or her comparison level, satisfaction will be high and the relationship will continue. If costs rise or rewards decline to the point that an individual is not meeting his or her comparison level however, satisfaction will be low and the relationship is at threat of termination. Indeed the relative weight of rewards and costs compared to a relationship partner’s comparison level influences an individual’s level of satisfaction and

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commitment for both friendships (Rusbult, 1980b) and romantic relationship partners (Rusbult, 1980a). A direct corollary can be drawn between relationship satisfaction and approach and avoidance motivation. Approach-oriented systems are attuned to seeking out situations in which rewards exceed costs, whereas avoidanceoriented systems are attuned to avoiding situations high in costs (Gable, Reis, & Elliot, 2003). Therefore, individuals who are currently satisfied with their relationship should engage in approach-oriented behavior toward sustaining the relationship due to the relatively high proportion of rewards compared to costs. Individuals in unsatisfactory relationships on the contrary should be motivated by avoidance forces due to the relatively high proportion of costs compared to rewards. Besides satisfaction level, other competitive forces appear to push and pull at relationships. People today live in a socially rich world with many alternative partners available. Interdependence theory (Kelley & Thibault, 1978) and Rusbult’s investment model (1980a) posit that the comparison level of alternative partners will also influence decisions to stay or leave current relationship partners. This is very similar to the comparison level of one’s current relationship partner, except that it refers to the attractiveness of alternative partners. Even if a person is moderately satisfied with his or her current relationship partner, if there are more attractive alternatives available in the environment, relationship dissolution may still occur. Kenrick, Neuberg, Zierk, and Krones (1994) showed men and women pictures of either attractive or dominant opposite sex individuals. Women shown dominant male faces and men shown attractive female faces rated lower satisfaction with their current partner. Approach forces toward external sources (in this case attractive alternative partners) therefore also function in decisions to maintain or dissolve a relationship. Earlier, however, we suggested that a strong approach motive serves to encourage continued engagement in current relationships. This presents a difficult barrier to new potential partners vying for someone’s affection. The strong motive to maintain current relationships should make it difficult for a new potential partner to be considered as a replacement—even if this new potential partner is perceived to have a slightly higher comparison level. This is because individual members of a long-term relationship have a large number of resources (such as time, effort, and mutual possessions) tied to their relationship (Rusbult, 1980a). These could be considered as “sunk costs” of the relationship that cannot be retrieved if the relationship is ended. This should make individual members averse to relationship dissolution, insofar as these

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lost resources cannot be fully reclaimed. The avoidance of losing resources therefore plays a key role in sustaining long-term relationships. Rusbult (1983) tested the influence of these factors (rewards/costs, comparison level, comparison level for alternative partners, and investment) on one another as well as their role in influencing stay/leave decisions in romantic relationships in a longitudinal study. Most important for this chapter are those factors that influenced stay/leave decisions. Of those relationships that ended, rewards increased less and costs grew more than those who stayed in the relationship. It is likely that approach forces were considerably less and avoidance forces to leave the relationship greater because of the shift in rewards and costs, respectively, for those who left compared to those who stayed. Additionally for those who left the relationship, alternative quality of attractive partners increased over time, and individuals invested less in their partners. In this case the approach motivation to leave the partner may have increased, whereas the avoidance motivation to maintain resources was reduced by investing less in the relationship. As the decision to end a relationship is influenced by both approach and avoidance motivation, it could be expected that the course of relationship dissolution might also wax and wane as a result of approach and avoidance forces. Using a script generation procedure, Battaglia, Richard, Daterri, and Lord (1998) developed a script of relationship dissolution processes. The script reflected a long lasting process of indecisiveness that fluctuated between decisions aimed at ending the relationship and decisions aimed at trying to repair the relationship. These fluctuations appeared to shift between approach and avoidance tendencies during which “Characteristic approach behaviors, for instance ‘try to work things out’, ‘communicate feelings’ and ‘get back together’, alternate with typical avoidance behaviors, such as ‘act distant’, ‘physical distance/ avoidance’ and date other people’ throughout the 16 step script” (Battaglia et al., 1998, p. 841).

RESPONSES TO EXCLUSION THREATS Inclusion is such an important and pervasive need (Baumeister & Leary, 1995) that threats to this need result in negatively affective states such as guilt, anxiety, jealousy, depression, and loneliness (Baumeister, Stillwell, & Heatherton, 1994; Baumeister & Tice, 1990; Leary, 1990). The general association between exclusion threats and negatively affective states suggests that threats to inclusion will result in motivated cognition and behavior to avoid exclusion from current relationship partners.

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This places a potentially powerful tool in the hand of relationship partners. Insofar as it can be expected that individuals will engage in behavior to avoid exclusion, relationship partners may be able to use exclusion threats to encourage motivated behavior to avoid relationship dissolution. Indeed, individuals appear to induce guilt (Baumeister, Stillwell, & Heatherton, 1995) and jealousy (Vangelesti, Daly, & Rudnick, 1991) to elicit more appropriate relationship-regulation behaviors on the part of their partners. For example, Baumeister et al. (1995) found that guilt induction appears to be a frequently used and moderately successful tactic to redistribute power and resources within a relationship. Guilt is an important weapon of the weak in the sense that it enables people with little or no objective power to exert influence over others who have more power. Additionally, Baumeister et al. found that individuals who felt guilty, whether induced or not, for a past transgression against their partner were more likely to change their behavior, apologize for the transgression, and/or say that they learned a lesson than individuals who did not feel guilty. Individuals who induce guilt in their partners therefore seem motivated by both approach forces to attain positive outcomes in relationships, and avoidance forces to reduce the likelihood of future transgressions by their partner. Individuals induced to feel guilty on the other hand are motivated by forces to avoid relationship dissolution. Similarly, jealousy is quite effective at encouraging motivated cognition and behavior to avoid relationship dissolution. Jealousy has been shown to elicit compensatory behaviors in which the jealous individual expends more attention and resources to the relationship partner (Fleischman, Spitzberg, Andersen, & Scott, 2005) as well as specific attentional biases directed at detecting possible threats from worthy competitors in an effort to avoid losing the relationship (Maner, Gailliot, Rouby, & Miller, 2007). Because of the specific threat of jealousy that one’s relationship partner will reallocate his or her attention to another potential partner, jealousy motivates individuals to engage in behavior directed at the partner and to potential rivals to reduce the threat of rejection. Other forms of negative affect seem important in reducing the threat of rejection. Anxiety and depression are negative affective states that co-occur with real or imagined threats to social exclusion (Schlenker & Leary, 1982; Baumeister & Tice, 1990; Allen & Badcock, 2003). The relationship between these negatively affective states and threats to exclusion has led many to suggest that they function to ward off exclusion threats. Specifically, anxiety functions to encourage regulated behavior to fulfill

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self-presentational concerns (Schlenker & Leary, 1982), whereas depression functions to elicit socially cautious behavior (Allen & Badcock, 2003). Feelings of anxiety can aid individuals in appropriate self-regulatory and self-presentational behaviors. When an individual engages in social interaction it is important for him or her to act in a socially desirable manner and to be perceived positively by others (Schlenker, 1980). Individuals who do not follow normative standards fail to contribute to the group, or are perceived as unattractive by the group are at threat of exclusion (Baumeister & Tice, 1990). In response to such threats, anxiety causes people to focus attention on potentially threatening social evaluations and to reassess their current behavior as appropriate or inappropriate (Smith, Ingram, & Brehm, 1983). If the behavior may lead to a negative evaluation, the individual can then cease that behavior in favor of more socially desirable responses (Schlenker & Leary, 1982). Anxiety therefore appears to function as a warning system to weed out behavior that would result in negative evaluations from others. Similar to anxiety, feelings of sadness or depression can occur in response to exclusion threats (Leary, 1990). According to the social risk hypothesis (Allen & Badcock, 2003), depression evolved to elicit a risk-averse response predisposition for those individuals who may be currently at risk for social exclusion. In that perspective, due to the threat of exclusion faced by individuals experiencing depression, depressed individuals should favor cautious, low-risk social behavior. High-risk social behaviors may benefit the depressed individual greatly, as success could quickly restore his or her relationships. These big risks carry with them a high cost however, because failure could result in complete exclusion from social relationships. Taking smaller social risks should therefore be the optimal strategy for individuals suffering from depression. Success may only slightly raise an individual’s social standing, yet these smaller risks carry with them a lower likelihood of failure resulting in exclusion. Indeed individuals experiencing moderate levels of depression seem especially attentive to socially relevant information (Badcock & Allen, 2003; Matthews, Ridgeway, & Williamson, 1996), are more likely to over-perceive the risks in social endeavors (Allen & Badcock, 2003), and are less likely to engage in socially risky behavior (Forgas, 2002). Although interpersonal regulation may be guided by anxious and depressed states, it can also lead to selfdefeating social behaviors (Allen & Badcock, 2003; Baumeister & Tice, 1990; Schlenker & Leary, 1982). The chronic experience of rejection can lead to strong feelings of anxiety that preclude individuals from engaging

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in social interactions in the first place (Baumeister & Tice, 1990; Downey & Feldman, 1996; Schlenker & Leary, 1982). Shy individuals and those who suffer from SAD are constantly concerned with the evaluations of others. The result is often a complete avoidance of social interaction. Similarly, although moderately depressed individuals benefit from being averse to social risks, clinical levels of depression can hamper an individual’s social relationships. Risk-averse behavior can become so pervasive that it results in individuals becoming dysregulated and avoiding social contact (Gilbert, 2001). Additionally, although individuals at moderate levels of depression can elicit care from close-relationship partners through signaling behaviors (Clark, Ouellette, Powell, & Milberg, 1987; Biglan et al., 1985), these behaviors can become so pervasive that the relationship partners of severely depressed individuals will begin to distance themselves from the relationship (Coyne, 1976). Emotion is not the only function that can reduce relationship threats. Several have suggested that an individual’s perception of his or her social standing is monitored by cognitive systems that fluctuate with varying levels of inclusion and exclusion (Leary, Tambor, Terdal, & Downs, 1995; Allen & Badcock, 2003). According to sociometer theory (Leary et al., 1995), self-esteem serves this function. Through a series of experiments the authors showed that high self-esteem individuals have higher perceptions of inclusion compared to individuals with low self-esteem. State ratings of self-esteem also seem to decrease with increasing levels of rejection (Buckley, Winkel, & Leary, 2004). Self-esteem may therefore function like a gas gauge of social acceptance, lighting up to warn people when their level of social inclusion is reaching critically low levels (Leary et al.). The major functional difference between self-esteem and emotional response systems to rejection is that selfesteem systems can result in both avoidant and approach social motives. At high levels of self-esteem, individuals feel secure in their relationships and as a result engage in self-enhancement strategies, whereas at low levels of self-esteem, individuals are less secure in their relationships and tend to engage in more self-protective strategies (see Baumeister, Tice, & Hutton, 1989; Sommer, 2001 for reviews). Individuals high in selfesteem seem to buffer themselves against rejection threats by affirming other relationships (Murray, Holmes, MacDonald, & Ellsworth, 1998), terminating the threatened relationship (Rusbult, Morrow, & Johnson, 1987), and seeking out new relationship partners (Sommer, Williams, Ciarocco, & Baumeister, 2001). Individuals low in self-esteem who perceive

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threats of exclusion on the other hand tend to devalue the source of the possible exclusion (Murray et al., 1998), to neglect and ignore threatened relationships (Rusbult et al., 1987), and to engage in “defensive ostracism” (Sommer et al., 2001). In response to exclusion threats, high self-esteem individuals appear to be motivated by approach forces aimed at developing other relationships, whereas low self-esteem individuals are motivated to avoid information that threatens their relationships, often resulting in relationships falling apart.

RESPONSES TO ACTUAL REJECTION Much human behavior appears to be motivated at defusing rejection threats before they occur. Yet even these attempts can fail and ironically can sometimes increase the person’s likelihood of being rejected. If an individual is unsuccessful at avoiding threats to exclusion, one expected reaction might be behavior motivated to establish new relationships. After rejection, however, many individuals appear to engage in a host of self-defeating behaviors such as increased levels of aggression, decreased prosocial behavior, and a reduction in the motivation to engage in self-regulatory behaviors important for engaging in social interactions (see Blackhart, Baumeister, & Twenge, 2006 for review). On the surface these behaviors appear maladaptive and would likely result in a continued lonely existence. But new work has begun to elucidate the reasons why rejected individuals fail to engage in the self-regulation necessary for social success (DeWall & Baumeister, 2006) as well as to show that, under the right conditions, rejection can cause people to approach new relationships (Maner, DeWall, Baumeister, & Schaller, 2007). Self-regulation is crucial for functioning in a social world, so one might expect that individuals faced with a lonely future would be more than willing to engage in motivated behavior aimed at repairing those relationships. Much evidence points to the contrary however. When rejection is experienced, individuals appear to fail to monitor and correct their behavior (Baumeister, DeWall, Ciarocco, & Twenge, 2005). Self-awareness is an important component of selfregulation (Carver & Scheier, 1981). For an individual to regulate his or her behavior, attention must be directed at the self to identify whether the current behavior being enacted is meeting evaluative standards. Individuals appear motivated to avoid self-awareness when they are faced with negative evaluative feedback however. If an individual has received negative information about his or her character, having to direct attention at the self

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would result in the individual having to confront this apparent shortcoming. Self-awareness after rejection would likely be an aversive experience of analyzing one’s character flaws to identify the reason one was rejected. Indeed, research shows that when rejected, individuals avoid self-awareness (Twenge, Catanese, & Baumeister, 2003). Why? Introspection following rejection might be profitable for the future and long-term success, but it would be fairly unpleasant. After the experience of social exclusion, rejected individuals may perceive that future attempts at affiliation are unlikely to result in the desired outcome. Avoiding a negative self-perception may have much more drastic consequences in the here and now. Therefore, the monitoring system necessary for engaging in effective self-regulation is avoided momentarily to defuse the effect of negative feedback on an excluded individual’s self-perception. Recent research on the emotions experienced (or not experienced) after exclusion suggests one other reason why rejected individuals fail to engage in motivated behavior. It might be expected that rejection, considered by most to be a distressing experience, would decrease positive affect and increase negative affect. Nevertheless, when examined in the laboratory, rejection experiences seem to have little effect on mood (Baumeister, Twenge, & Nuss, 2002; Gardner, Pickett, & Brewer, 2000; Twenge, Baumeister, Tice, & Stucke, 2001). Even when rejection is found to decrease mood, the change in mood does not seem to mediate the behavioral responses to social exclusion (Buckley et al., 2004; DeWall & Baumeister, 2006; Williams, Cheung, & Choi, 2000). Rather it seems that rejection results in a numbing to both emotional and physical pain, both in the ability to experience one’s own pain as well as the emotional and physical pain of others (DeWall & Baumeister, 2006; Twenge, Baumeister, DeWall, Ciarocco, & Bartels, 2007). Emotional and physical insensitivity may be an adaptive response to social exclusion, insofar as it would effectively reduce the distress that is assumed to occur after social exclusion. It may however have drastic consequences for social interaction. Positive and negative affective systems have been shown to be inherently linked to both approach and avoidance motivation, respectively (Cacioppo & Gardner, 1999; Depue & Iacono, 1989). People generally want to avoid experiences that would lead to negative affect and approach experiences that result in positive affect. The apparent lack of emotional sensitivity may however leave the rejected individual unable or unwilling to engage in motivated behavior to avoid these states.

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Recently, DeWall (in preparation) and Twenge et al. (2007) have produced studies identifying the lack of empathy as a mediating factor in the disinhibition of aggressive responses and inhibition of prosocial responses by excluded individuals. The results of these studies suggest that the maladaptive behavior of excluded individuals arises due to a lack of empathic emotion that normally results in more socially appropriate behavior. In these situations, normal or included individuals would respond with emotional distress and a corresponding motivation to avoid this distress through prosocial behavior and inhibiting the urge to engage in aggressive behavior. Those who have been excluded however lack the emotional systems that would distress the individual in the first place (DeWall & Baumeister, 2006). Lacking these feelings of associated distress disengages the normal motivational propensity to avoid empathic distress through engagement of prosocial behavior and inhibition in aggression. The emotional numbness of excluded individuals therefore appears to reduce avoidance motivation by wiping away the crucial signal to engage in effective self-regulation. It is entirely possible that the emotional numbness experienced after social exclusion may stifle approach behavior as well. DeWall and Baumeister’s (2006) findings showed excluded individuals lack the ability to experience both negative and positive affect. As positive affect is inherently linked to approach motivation, it could be assumed that the inability for excluded individuals to experience positively affective states may reduce this motivational propensity as well. Although a rejected individual may be unable to experience positive affect, it is entirely plausible that he or she will still seek it out. Indeed, when enticed by a tangible reward (such as cash), excluded individuals appear to retain the ability to engage in self-regulation (Baumeister et al., 2005). Approach motivation may therefore be sustained in the behavior of rejected people. A likely place to identify approach motivation is in the domain where it is currently thwarted— specifically redeveloping social relationships. Recent findings by Maner et al. (2007) suggest that excluded individuals will continue to engage in self-regulated behavior toward attaining positive social experiences, but only when the outcome is highly likely. Early research on rejection suggested rejected individuals were unwilling to engage in behavior that would increase the likelihood of reconnecting with others. If the need to belong is a fundamental human motive (Baumeister & Leary, 1995) it would be expected that rejected individuals would engage in behaviors to reduce their thwarted belongingness. Nevertheless, rejected

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individuals engage in a host of behaviors that would not be beneficial to building new social relationships (Blackhart et al., 2006). Several studies have shown that rejection and ostracism lead to aggressive responses, not only to the source of the rejection, but also to individuals completely unrelated to the rejection experience (Buckley et al., 2004; Twenge et al., 2001; Twenge & Campbell, 2003; Warburton, Williams, & Cairns, 2006). Additionally, Twenge et al. (2007) have shown that individuals who have been rejected engage in less prosocial behavior compared to those who have been included or did not receive acceptance/exclusion feedback. Being highly aggressive and refusing to engage in prosocial behavior would likely not result in an individual being a highly valued candidate for social interaction. This evidence of antisocial tendencies among rejected persons seems inconsistent with other findings showing that exclusion can sometimes lead to behavior that could be seen as aimed at fostering reconnection. Williams and Sommer (1997) found that ostracized women (but not men) put forth increased effort toward a group task, which could be considered a promising strategy to make oneself attractive to the group. Williams et al. (2000) found that ostracized individuals were more likely than accepted individuals to conform to others’ opinions, which could be seen as an ingratiation strategy (though it could also reflect mere passivity). Rejected individuals have also been shown to have better memory for information regarding other people’s affiliation and rejection experiences, which may function to encourage more appropriate social behavior in future interactions, although it may simply reflect greater sensitivity due to being primed by one’s own rejection (Gardner et al., 2000). In an attempt to resolve the contradiction between these findings and the findings of others showing that rejected individuals engage in antisocial behaviors, Maner et al. (2007) proposed that rejected individuals will engage in affiliative behaviors only when the perceived possibility of forming a relationship is high. Through several studies, Maner and colleagues showed that individuals who experienced or imagined social exclusion were more interested in joining a group to form new friends (Study 1), were more likely to choose to work with others (Study 2), perceive others as more friendly and less hostile (Studies 3 & 4), and were more rewarding of a new interaction partner who was not an initial source of the exclusion experience (Studies 5 & 6). These studies seem to confirm the social reconnection hypothesis in that excluded individuals appear to be optimistic about future social interactions and take the opportunity to engage in social reconnection opportunities.

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What then could result in the findings of previous studies showing that individuals who had been rejected were less than willing to engage in affiliative behavior? Maner and colleagues suggest that the degree to which an individual perceives social interaction to lead to actual social connection will alter affiliative responses to rejection. Specifically, three boundary conditions were tested and supported. The first factor is simply whether the individuals are engaging in interactions with the individual who had previously rejected them, or a novel potential relationship partner. Although rejected individuals, compared to control, rated novel relationship partners as friendlier and less hostile (Studies 4 & 5) and assigned greater rewards to these novel relationship partners— even though giving less rewards to their partner would result in a greater sum of money they could win in a raffle (Study 5)—they rated the individual who had rejected them as less friendly and more hostile (Studies 4 & 5) and were less benevolent toward this individual (Study 5). Another boundary condition was tested and identified in Study 6. Specifically participants were led to believe that they would either later meet their novel interaction partner or not. Those who were rejected and expected to meet their new interaction partner later were much more rewarding to this novel partner than those who did not expect to meet their partner and those who were not rejected in the first place. Apparently then excluded individuals seem to retain the motivation to seek out new relationship partners, but only if doing so is likely to result in future interaction. Besides suggesting that individuals who have been excluded appear to continue to engage in approach-motivated behavior, the research of Maner et al. (2007) seems to suggest that at least a modicum of avoidance motivation remains intact after social exclusion. Specifically, many of the findings in these studies were moderated by a crucial individual difference, evaluation anxiety. Those individuals who had been excluded and scored high on a measure of anxiety showed no evidence of a desire to reconnect with others. Even when highly anxious excluded individuals interacted with a new partner (unrelated to the initial rejection experience) and had been led to expect that they would meet this person later, they seemed reluctant to engage in prosocial behavior. This suggests that for some individuals, the experience of rejection may lead to fears about future rejection. High anxious individuals who had faced a previous rejection may have expected a similar result of interacting with a new partner. The pervasive fear of negative evaluation and future rejection from others may therefore stifle even the strongest of motivations.

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CONCLUSION The purpose of this chapter has been to examine the effects of social rejection and exclusion in terms of approach and avoidance. Rejection is itself generally the result of a sort of avoidance, in the sense that rejection means that others have elected to avoid the person. But the rejected person’s responses include a rich mixture of approach and avoidance tactics. The decision to reject someone seems inherently to be a matter of avoidance, but this appearance can be misleading. For example, in modern societies, people are legally allowed to have only one spouse at a time, and most premarital romantic relationships follow the same dyadic rule, and so a person might reject one potential partner simply because of a stronger (approach) desire to affiliate with someone else. Even during the processes of rejecting someone and breaking off a romantic attachment, people may be ambivalent and thus torn between their lingering attraction to the partner and their various reasons for wanting to separate — thus, a classic approach/ avoidance conflict. The rejected person tends to avoid the people who rejected him or her. There is some wish to form new relationships to replace the lost one, and that wish is essentially an approach motivation (i.e., to approach new partners and relationships), but this is tempered by the painful sensitivity that makes the rejected person eager to avoid being rejected again. The reluctance to risk another rejection entails an avoidance of some possible interactions and partners. Rejected people avoid selfawareness, presumably because it is highly aversive to dwell on what faults or flaws in themselves may have contributed to the rejection, and this lack of selfawareness curtails learning and introspection and may interfere with self-regulation. The threat of rejection seems to evoke powerful and deeply rooted motivations, most likely because the need to belong is very basic to the human psychological makeup insofar as belongingness was essential to human biological strategies for survival and reproduction. The threat of rejection generally evokes a variety of negative affective and emotional responses, and people wish to avoid these. Many behaviors are thus indirectly shaped by the wish to avoid anxiety and other negative emotions that are associated with the possibility of rejection. For example, shy people may avoid social settings because they fear rejection, but this very avoidance conflicts with their often quite strong desire to approach others so as to form relationships and thereby escape from loneliness. Self-esteem may also be threatened by possible rejection,

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and people may therefore engage in a variety of behaviors to protect or enhance their self-esteem. Within relationships, too, approach and avoidance dynamics may be affected by the fear of rejection. One destructive pattern occurs when a partner who fears rejection seeks to preempt the devastating blow by distancing himself or herself from the relationship (e.g., devaluing the partner or the relationship), thereby contributing to its demise. The novelist E.M. Forster once wrote, “Only connect!” but such advice is impractical, especially in a world where time is limited and monogamy is enforced. Human beings have a deeply rooted set of impulses to approach others to form relationships, but the complications of human social life lead to a great many avoidance impulses as well. Analyzing the phenomena of belongingness and rejection in those terms offers a fresh set of insights into how humans relate to each other.

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Sexual Behavior Perspective on Approach 37 AandDyadic Avoidance Motives for Sexual Behavior M. Lynne Cooper, Amelia E. Talley, Meli S. Sheldon, Ash Levitt, and Lindsay L. Barber CONTENTS What Motives Underlie Sexual Behavior? ............................................................................................ 616 Does Having Sex to Satisfy Different Motives Matter?........................................................................ 618 Approach Motives for Sex ................................................................................................................ 618 Avoidance Motives for Sex ............................................................................................................... 619 Summary ..........................................................................................................................................620 Limitations of Studying Individuals as Opposed to Couples................................................................620 Dyadic Analyses of Approach and Avoidance Motives ........................................................................ 621 To What Extent Is an Individual’s Sexual Experience Influenced by His or Her Partner’s Approach and Avoidance Motives for Sex? ..........................................................................................622 Are There Synergistic (i.e., Couple Level) Effects of Approach and Avoidance Motives? ..................624 Do Male and Female Partner Motives Interact? If So, Are These Synergistic Effects Equally Common Among Men and Women, Across Sexual Behaviors, and Across Specific Motives? ......624 What Is the Nature of These Synergistic Effects?............................................................................624 Summary ..........................................................................................................................................627 Concluding Thoughts and Future Directions ........................................................................................627 The Relational Context .....................................................................................................................628 Gender Specificity of Motive Effects ...............................................................................................629 References .............................................................................................................................................629

The notion that people use sex strategically to achieve different goals, and that these differences shape the experience and expression of their sexuality, is central to a motivational perspective. According to this view, the key to understanding behavior lies in the needs and purposes served by the behavior. Regardless of outward similarities, behaviors undertaken in service of different needs are thought to be psychologically distinct, and should therefore exhibit unique patterns of antecedents, correlates,

and consequences. This perspective suggests that sexual behaviors motivated by different needs (e.g., to strengthen a bond vs. avoid rejection) should be triggered by unique antecedents, characterized by qualitatively different styles of behavior and emotions, and ultimately result in distinct consequences. Thus, according to this view, human sexual behavior cannot be adequately understood without taking into account the nature of the underlying needs that motivate it. 615

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Although needs or motives* vary along many dimensions, a fundamental distinction can be drawn between approach and avoidance motives. Past research indicates that sexual behavior motivated by approach versus avoidance concerns is associated with distinctive styles of behaving and distinctive outcomes in both cross-sectional and longitudinal studies. In general, this body of research suggests that having sex for avoidant reasons (e.g., to escape or avoid negative moods, to avoid disapproval from one’s partner or peers, to allay insecure feelings) is linked to negative feelings about sex and lower satisfaction, along with higher rates of casual sex, sexually transmitted infections (STIs), and unplanned pregnancies. In contrast, having sex for approach reasons (intimacy, enhancement) is associated with positive feelings about sex, higher satisfaction, and more adaptive behaviors overall, though certain approach motives also appear to foster sexual risk taking. Although this body of research attests to the importance of approach–avoidance motives for understanding patterns and consequences of sexual behavior, it has been limited by an almost exclusive focus on the individual and his or her motives in isolation. The fact that sexual behavior is shaped by the needs and motives of two people has received little systematic attention. In this chapter, we use this observation as a jumping-off point for exploring how the approach–avoidance motives of intimate partners individually and jointly shape the nature and quality of sexual experiences within their relationship. We begin this chapter with a review of existing research on approach–avoidance motives for sexual behavior, conducted exclusively on individuals rather

* Throughout this document, we use the term motive to refer to the underlying dynamics that drive or “energize” sexual behavior. The sex motives measure used in our research (developed and described in Cooper, Shapiro, & Powers, 1998) assesses the motivated use of sexual behavior to achieve, maintain, avoid, or escape different desired or undesired end states. As such, this measure assesses a mid-range, hybrid construct that is part motive, part goal. Indeed, it is similar to what Elliot (2006) has called a “goal complex,” because it specifies both the source or energization of behavior (what motivates or gives rise to the behavior; e.g., the desire to strengthen a relationship), as well as how the individual “directs” his or her efforts to satisfy the need or motive (in this case, via sexual behavior). However, because our measure refers to a relatively stable tendency to use sex to achieve certain ends (see Cooper et al., 1998, Study 4, for information on the temporal stability of this measure), whereas goals most often refer to more time-bound, situation specific behaviors, we believe that the term, motive or motive disposition, best captures the nature of the construct under review in the present chapter.

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than couples. We then review several lines of evidence from prior studies based on individuals that, nevertheless, suggest that individual-level analyses of highly interdependent behaviors, such as sexual behavior, are limited in important ways. Using data from a community sample of 299 young adult couples, we then summarize evidence showing (a) that the effects of approach–avoidance motives on sexual behavior are highly sensitive to a relationship context; (b) that both one’s own motives and one’s partner’s motives shape individual sexual experience (particularly among men); and (c) that partner motives combine in synergistic ways (i.e., interact) to shape the sexual outcomes of both male and female relationship partners. We conclude by highlighting several new insights gained by moving to a dyadic level of analysis to examine the nature of approach–avoidance motives in the sexual arena.

WHAT MOTIVES UNDERLIE SEXUAL BEHAVIOR? In our earlier work, we (Cooper, Shapiro, & Powers, 1998) hypothesized that two primary motivational dimensions underlie human sexual behavior. The first dimension distinguishes behaviors that involve the pursuit of positive or pleasurable experiences (appetitive or approach behaviors) from those that involve the avoidance of, or escape from, negative or painful ones (so-called aversive or avoidance behaviors). According to Gray (1970, 1987), approach and avoidance behaviors are regulated by neurologically distinct motivational systems. The behavioral inhibition system (BIS) regulates avoidance motivation and controls the experience of negative emotions, whereas the behavioral activation system (BAS) regulates approach motivation and controls the experience of positive emotions. Gray further hypothesized that individuals differ in a stable, trait-like manner in the relative sensitivity of the two systems. Consistent with this hypothesis, people who are high in BIS are especially responsive to threat and punishment cues, which predispose them to experience negative affect and respond in an avoidant or fearful manner. Conversely, individuals who are high in BAS are especially responsive to reward cues, which predispose them to experience positive affect and engage in reward-seeking behaviors (see Carver & White, 1994; Larsen & Ketelaar, 1991, for supporting evidence). Indeed, the stable personality traits of neuroticism and extroversion are thought to derive from the BIS and BAS systems, respectively (Gray, 1970; Larsen & Ketelaar, 1991). When applied to sexual behaviors, this distinction suggests that people can have sex to pursue or maintain

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A Dyadic Perspective on Approach and Avoidance Motives for Sexual Behavior

positive outcomes, such as physical pleasure or excitement, or to avoid or escape negative ones, such as rejection by socially significant others. The second motivational dimension hypothesized to underlie human sexual behavior concerns the extent to which behavior is motivated by an intraindividual or selffocused concern versus an external, interpersonal, or social concern. This distinction is closely related to distinctions between agency versus communion (Bakan, 1966), autonomy/competence versus relatedness (Skinner & Wellborn, 1994), and exploration versus attachment (Bowlby, 1970). Thus, sexual behaviors motivated by self-focused concerns might serve agentic, identity, or autonomy/competence needs, such as having sex to affirm one’s sense of identity or attractiveness, or to manage one’s internal emotional experience. The latter can be thought of as an agentic striving to the extent that it involves mastery and control of one’s emotional experience (McAdams, 1984). In contrast, sexual behavior motivated by social concerns might serve attachment or communal needs, such as having sex to achieve intimacy and communion in a relationship, or to gain another’s approval. Thus, although intrapersonal motives can be pursued in an interpersonal context (as when one uses sex to self-affirm), and both intrapersonal and interpersonal motives can be seen as ultimately originating from a desire to manage one’s emotions (either by direct manipulation of feeling states or indirectly by obtaining a valued outcome from a socially significant other), these motives nevertheless can be differentiated by the degree to which the outcomes sought are primarily self-focused or internal to the individual versus other-focused or external to the individual (i.e., social). We hypothesized that these two dimensions combine to yield four broad classes of motivations for sexual behavior: (a) self-focused approach motives, such as having sex to enhance physical or emotional pleasure (i.e., enhancement motives); (b) self-focused avoidant motives, such as having sex to cope with threats to selfesteem or to minimize negative emotions (i.e., coping motives); (c) social approach motives, such as having sex to bond with socially significant others (i.e., intimacy motives); and (d) social avoidant motives, such as having sex to avoid social censure or rejection (i.e., peer- and partner-approval motives). We validated this framework in a series of studies (Cooper et al., 1998, Studies 1–3). First, to determine how well people’s spontaneously generated motives fit the hypothesized framework, we asked undergraduates to list the most important reasons why they had sex on a recent occasion of intercourse. Ninety-two percent of the

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resulting responses involved approach motives, both enhancement (49%) and intimacy (43%), whereas only 8% involved avoidant motives, including having sex to escape or cope with negative internal states (e.g., “So I could relieve stress”) and to avoid rejection by one’s peers or partner (e.g., “I felt that I had to because he was my boyfriend”). Thus, people spontaneously generated reasons within all hypothetical motive classes identified by our model, though their reasons were not equally distributed across these classes. Factor analytic work carried out in three independent samples provided further support for the validity of this model, while at the same time suggesting a potentially important refinement. Using a set of Likert-type items intended to measure the four-motive constructs, we obtained six instead of four factors: two approach motive factors (intimacy, enhancement), as hypothesized, but four (instead of two) avoidant motive factors (coping, self-affirmation, partner approval, and peer approval). Despite this deviation from expectation, higher-order factor models showed that the correlations among the six factors could be explained by a four-factor structure in which intimacy and enhancement were treated as indicators of discrete factors (i.e., other- and self-focused approach factors, respectively); affirmation and coping motives were treated as indicators of a single, higherorder self-focused, avoidant factor; and peer- and partnerapproval motives were treated as indicators of a single, higher-order social, avoidant factor (see Cooper et al., 1998, Study 3). These data suggest that although multiple, specific manifestations of avoidance motives exist, the four-motive typology is nevertheless a useful heuristic device for understanding the major distinctions among motive types. Additional factor analytic work showed that nesting the four avoidant motives under a higher-order avoidance factor and the two approach motives under a higher-order approach factor provided a better fit to the data than nesting the three intrapersonal motives (enhancement, coping, self-affirmation) under a higher-order intrapersonal factor and the three social motives (intimacy, partner approval, peer approval) under a higher-order interpersonal factor (Cooper et al., 1998, Study 2). Although both two-factor models provided a significantly worse fit to the data than the four-factor model, these findings nevertheless indicate that the approach–avoidance distinction better accounts for the structure of sexual motivations than the self versus social distinction. In this sense then, the approach–avoidance distinction appears to be the more fundamental of the two to the psychological structure of sex motives.

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Subsequent validation studies using the Cooper et al. (1998) measure of sexual motivations showed that rates of endorsement in both college (Cooper et al., Study 2) and community (Study 3) samples varied across motive type in a manner similar to that observed in the initial open-ended elicitation study: Enhancement and intimacy were by far the most commonly endorsed reasons for having sex followed by sex to affirm ones’ self-worth, to cope with negative emotions, and for partner or peer approval. Moreover, this rank order was largely invariant across gender, race, and age groups (Study 3). In sum, findings from this research indicate that people use sex to pursue a relatively small number of different goals, and that these goals can be parsimoniously characterized in terms of underlying differences in approach– avoidance motivation and self/internal versus social focus. At the same time, these dimensions and the specific motives that derive from them appear to differ in their importance; the approach–avoidance distinction better accounts for the underlying latent structure of sex motives and, within this dimension, approach motives are much more common, at least among young adults, than avoidance motives.

DOES HAVING SEX TO SATISFY DIFFERENT MOTIVES MATTER? In the foregoing section, we characterized the nature and distribution of sexual motives among young adults. However, the larger question of whether these differences are consequential remains. Do the nature and quality of outcomes differ, for example, among individuals who use sex primarily to achieve intimacy with their partner compared with those who use sex primarily to cope with their insecurities? Consistent with a core assumption of the motivational perspective, existing research (reviewed below) suggests that they do.

APPROACH MOTIVES FOR SEX People who have sex for approach reasons are, by definition, seeking a positive or rewarding outcome, be that a closer connection with their partner or a physically enjoyable and exciting experience. Accordingly, sexual behavior among such individuals should be seen as a way to obtain benefits and achieve important life goals—expectations that in turn should create positive emotional responses to sex (i.e., high erotophilia, low erotophobia; Fisher, Byrne, & White, 1983), and lead to more frequent and satisfying sexual experiences. At the same time, however, the contexts in which these experiences occur

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should differ markedly for people who have sex to build intimacy versus enhance. Having sex within the context of a close emotional relationship should facilitate satisfaction among those who are primarily motivated to seek intimacy, whereas having sex with any attractive person may provide a suitable context for satisfaction of pleasure-seeking motivations. Indeed, to the extent that enhancement motives are partly driven by excitement and novelty seeking, as their hypothesized roots in the BAS suggest, a casual sex partner may even be preferred to a more intimate one among individuals who are primarily motivated by hedonic concerns. Consistent with the above analysis, research indicates that both intimacy and enhancement motives are positively associated with need for sex and erotophilia, but negatively associated with erotophobia (Cooper et al., 1998, Study 3). Also as expected, individuals who have sex for intimacy and enhancement reasons report higher relationship satisfaction (which has been strongly linked to sexual satisfaction; Christopher & Sprecher, 2000; Rusbult & Van Lange, 2003) and more frequent intercourse (Cooper et al.; Impett, Peplau, & Gable, 2005). On the whole then, these data suggest that both intimacy and enhancement motives reflect a strong approach orientation to sex. These similarities notwithstanding, the two motives are linked to distinct partner and risk profiles, as hypothesized. Whereas intimacy motives have been consistently associated with fewer and less risky, better-known sexual partners, enhancement motives have been associated with permissive attitudes toward casual, uncommitted sex, more sex partners (especially casual ones), and more risky sex practices (Browning, Hatfield, Kessler, & Levine, 2000; Cooper et al., 1998; Hill & Preston, 1996; Levinson, Jaccard, & Beamer, 1995). Intimacy motives have also been associated with more effective birth control use, fewer unplanned pregnancies, as well as lower rates of condom use (Cooper et al.; Gebhardt, Kuyper, & Dusseldorp, 2006; Hill & Preston, 1996). This pattern of findings appears to be directly attributable to the more committed relationship contexts in which people who use sex to achieve intimacy are likely to have sex (Cooper et al.; see also Schachner & Shaver, 2004). Finally, and in contrast, enhancement motives have been associated with both higher rates of STIs and unplanned pregnancies (Cooper et al.). Together these data suggest that although intimacy and enhancement motives are associated with positive feelings about sex, as their shared roots in the approach motivation system predict, sex motivated by these two concern, is nevertheless characterized by highly distinctive relational contexts, as well as distinctive patterns of behavior and associated consequences.

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AVOIDANCE MOTIVES FOR SEX People who have sex for avoidant reasons are, by definition, having sex to escape from, minimize, or avoid aversive states or anticipated negative outcomes, including generalized negative mood states, feelings of insecurity or inadequacy, or rejection by socially significant others. According to Elliot and colleagues (Elliot, Gable, & Mapes, 2006), the negative orientation characteristic of avoidance goals is thought to evoke a set of processes that undermine the quality of social interactions and the development of social bonds, including negatively valenced perceptions (e.g., interpreting partner behaviors in the worst possible light), attentional biases (e.g., heightened attention to negative partner qualities), memories (e.g., biased search for and recall of negative information), emotions (e.g., fear, mistrust), and behaviors (e.g., stonewalling one’s partner). As a result, people who are primarily motivated by avoidance goals are more likely to associate sex with painful or unpleasant experiences and to experience negative emotional responses to sex (i.e., high erotophobia). As a result of these intervening processes, such individuals are also more likely to engender negative sexual situations. For all of these reasons, we expect less frequent, satisfying, and rewarding sex among individuals who are primarily motivated by avoidance goals. Sexual behaviors motivated by avoidance concerns should also be riskier. This expectation rests on at least three different lines of reasoning. First, negatively valenced stimuli have been shown to garner more attention, to create stronger emotional reactions, and to more reliably elicit behavioral responses than comparable positively valenced stimuli (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001; Carver & Scheier, 1998). Because avoidant motives focus attention on negative rather than positive situations and possibilities, they may take precedence over other goals and considerations. Under such circumstances, if having sex is seen as an effective way to escape from or avoid an undesirable situation, then sex seems more likely to occur regardless of its advisability on that particular occasion or with that particular partner. A second and related point: risky behaviors are typically thought to involve a trade-off between short-term gains and long-term costs. According to Baumeister and Scher (1988), the propensity to choose immediate pleasure or relief is exacerbated under the influence of negative emotional states in part because being in a negative mood increases the attractiveness of immediate relief. Thus, individuals who use sex to escape negative emotional states may weigh the immediate

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benefits of having sex more heavily than potential longerterm costs, thereby shifting the balance in favor of riskier sexual decisions. Finally, even though avoidance goals can assume a prepotent role in decision-making situations, they are nevertheless thought to provide a suboptimal structure for self-regulation (Carver & Scheier, 1998; Heimpel, Elliot, & Wood, 2006). As Carver and Scheier (1998) point out, avoidance goals provide something to move away from but nothing to move toward. In the absence of a concrete path for moving forward, individuals who are primarily focused on avoidance concerns may lack clear guidelines for evaluating behavioral alternatives and thus have greater difficulty regulating their behavior in line with their goals and values. Thus, through a variety of processes, we expect individuals who are primarily motivated by avoidant concerns to engage in less adaptive, riskier sexual behaviors. A review of the existing literature reveals patterns of association that are largely consistent with these expectations. Consistent with the notion that avoidant motives are rooted in the BIS, all four avoidance motives have been linked to higher levels of neuroticism and erotophobia (Cooper et al., 1998). Interestingly, however, coping and affirmation motives have also been associated with higher levels of sexual desire and erotophilia (Cooper et al.; Hill & Preston, 1996), thus suggesting an approachavoidant or ambivalent orientation toward sex among those who use sex to cope or affirm. However, because ambivalence is widely experienced as aversive (Priester & Petty, 1996), these findings can also be seen as consistent with the contention that both motives reflect BIS-driven, avoidant motivational processes. Unlike the pattern observed for coping and affirmation motives, individuals who are high (vs. low) in peer- and partner-approval motives do not differ in need for sex or in erotophilia (Cooper et al.), thus suggesting a predominantly negative (as opposed to ambivalent) orientation to sex among those who have sex for approval reasons. Finally, although specific associations between avoidant motives and sexual satisfaction have not been tested, avoidance motives have been linked to lower relationship satisfaction (Impett et al., 2005), which, as previously indicated, is strongly associated with sexual satisfaction. Although these four motives appear to share a core set of negative emotional responses to sex, they have nevertheless been associated with distinctive behavioral patterns. For example, individuals who are high in sex to cope report more frequent masturbation (Hill & Preston, 1996), more casual sex partners (Cooper et al., 1998; Hill & Preston, 1996), but better birth control use and fewer unplanned pregnancies (Cooper et al.). This promiscuous

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but “safe” pattern suggests a certain calculated quality to the sexual behavior of individuals who use sex to cope (cf., Gold & Skinner, 1993). Individuals who are high in partner-approval motives also show greater involvement in risky sexual practices, but less birth control use and higher rates of unplanned pregnancies (Cooper et al.)—a pattern that is thought to reflect reluctance to assert oneself and risk partner disapproval in sexual situations (cf., Harlow, Quina, Morokoff, Rose, & Grimley, 1993; Jemmott & Jemmott, 1991). Having sex for peer approval, a phenomenon observed primarily among young adolescent males (Cooper et al., Studies 3 and 4) has been associated with a relative lack of sexual experience. Such individuals reported fewer lifetime intercourse experiences, fewer lifetime sex partners, less frequent sex in the past 6 months, and older age at first intercourse. These individuals also, however, showed steeper increases in sexual risk taking over time, thus suggesting that they eventually “catch-up” with or even exceed their peers, possibly as other motives supplant their initial reasons for having sex (Cooper et al., Study 4). Finally, having sex to affirm has been linked to an inconsistent pattern of sexual risk behaviors, perhaps owing at least in part to its statistical overlap with coping motives (Cooper et al.).

SUMMARY The foregoing review provides strong support for the idea that the reasons why people have sex are important for understanding sexual outcomes. Indeed, different motives for sex are characterized by distinct patterns of behaving and by distinct consequences. Moreover, although approach and avoidant sex motives have been related in a uniform and consistent manner to positive and negative emotional responses to sex, respectively, the distinctive pattern of behaviors associated with individual motives suggests that motives cannot be reduced to a simple approach–avoidance dichotomy. Instead, it appears that whether one is trying to use sex to address internal, selffocused needs, or social needs also matters, perhaps by selectively directing the individual to more impersonal versus intimate relational contexts.

LIMITATIONS OF STUDYING INDIVIDUALS AS OPPOSED TO COUPLES As previously discussed, past research on sexual motivations has focused on one partner’s goals and motives in isolation, essentially ignoring the fact that sexual behavior is intrinsically dyadic and thus involves the goals and motives of two people. As Kenny and Cook (1999) point

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out, individualistic approaches such as this assume, without ever testing, that there are actor but not partner effects—in other words, that one’s behavior is caused by his or her own standing on important predictors, but not by the partner’s. In such studies, the partner is effectively deemed irrelevant. Interestingly, however, even research using individuals (as opposed to couples) points to the fallacy of this position. Cooper, Agocha, and Sheldon (2000), for example, found that approach and avoidance motives for alcohol use accounted for 27% of the variance in alcohol outcomes on average, whereas approach and avoidance motives for sex accounted for only 6%, on average, of the variance in sexual behavior outcomes—a more than fourfold difference. Although it is possible that these differences stem from the differential validity of the two motive measures, there is no psychometric evidence to support this interpretation (cf., Cooper, 1994; Cooper et al., 1998). Rather we suspect that the observed differences reflect the fact that intrapersonal motives are less predictive of highly interdependent behaviors like sex than they are of largely individually determined behaviors like drinking. Evidence from our earlier study on sex motives (Cooper et al., 1998) lends additional support to this interpretation. Specifically, we found a consistent pattern of relationship status × sex motive interactions in both cross-sectional (Study 3) and longitudinal (Study 4) analyses showing that individual motives (especially enhancement) more strongly predicted sexual behavior among uncoupled individuals than among those in steady or exclusive relationships. Indeed, in some cases motives only predicted behavior among uncoupled individuals, thus implying that sexual behavior enacted in some relationship contexts may be even more interdependent and hence jointly determined than in other contexts. In our earlier sex motives study (Cooper et al., 1998, Studies 3 and 4), we also found a strong and consistent pattern of relationship status versus motive interactions predicting precautionary behaviors (i.e., birth control and condom use). Intimacy motives, for example, were significantly positively related to birth control and condom use in the context of an ongoing or exclusive relationship, but significantly negatively related in more casual relationship contexts (see Gebhardt, Kuyper, & Greunsven, 2003, for similar results). This pattern, though not specifically predicted, is consistent with evidence that condom and birth control use in casual relationship contexts are thought to convey advance planning for sex and, by extension, sexual permissiveness (Morrison, 1985)—an impression that people seeking intimacy in their sexual encounters would surely want to avoid conveying to their

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partner. In contrast, intimacy motives in a committed relationship context should encourage communication and cooperation between partners (Reis & Shaver, 1988), which in turn has been shown to facilitate precaution adoption (Sheeran, Abraham, & Orbell, 1999). Interestingly, the reverse pattern of effects was found for enhancement motives—that is, enhancement was significantly positively related to condom use with casual sex partners, but significantly negatively related with committed sex partners (Cooper et al., 1998, Study 3). Moreover, in prospective analyses, enhancement motives were related to discontinuation of condom use among those who were stably partnered, but with maintenance of use among those who were not (Study 4). Thus, in a context where the need to protect oneself against STI/AIDS was likely perceived as low (i.e., in a stable relationship), those with high-enhancement needs were quick to abandon any protective measure that interfered with their pleasure. In contrast, taking pleasure in the physical aspects of one’s sexuality appeared to facilitate (or at least, not undermine) protective measures in the context of more casual liaisons (cf., Gerrard, 1982). Taken together, the cross-over interaction patterns observed for intimacy and enhancement motives suggest that precaution adoption is facilitated when the relationship context provides a good match to the individual’s motives and needs, but may be impeded in the presence of a mismatch. More broadly and more important for the present chapter, they show that the effects of sex motives on sexual behaviors depend strongly on the relationship context and therefore cannot be understood in a decontextualized framework. Evidence that motives are systematically linked to the probability of being in different relationship contexts provides yet more support for the importance of adopting an explicit dyadic perspective. In cross-sectional analyses, for example, we (Cooper et al., 1998, Study 3) found that mean levels of all motives, except enhancement, differed as a function of relationship status. Indeed, intimacy motives were higher among individuals who were either in an exclusive or nonexclusive sexual relationship, whereas all four avoidant motivations were higher among individuals who were not in any relationship. Although cross-sectional data such as these cannot address the issue of differential selection versus environmental influence, longitudinal data from our earlier study (Cooper et al., Study 4) suggest that at least some of the observed differences reflect the effects of selection into relationship environments that ostensibly foster need satisfaction. Indeed, we found that high-intimacy-motive individuals were, over a 1 1/2 year period, more likely to stay in

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committed relationships if already in one at baseline or, if not, to move into a committed relationship. In contrast, people who were high in enhancement and coping motives were more likely to leave a committed relationship if they were in one at baseline or, if not, to stay unattached. Moreover, patterns of change and stability in relationship status were found to mediate, at least in part, the prospective effects of sex motives on sexual behavior. Together these data suggest that failure to consider the relationship context in which sex occurs can lead to systematic underestimation of the predictability of sexual behavior from sex motives, particularly in committed relationships, as well as inaccuracies and distortions in the characterization of the motive–behavior relationship. Moreover, the fact that people appear to seek relationship environments partly on the basis of the environment’s ability to satisfy their sexual needs and that these environments in turn mediate motive effects on behavior suggests that partner and relationship effects play a consequential role in shaping the nature and quality of sexual experience. Nevertheless, simply demonstrating that relationship context matters, as these data do, does little to inform us about how or why this context matters.

DYADIC ANALYSES OF APPROACH AND AVOIDANCE MOTIVES In the remainder of this chapter, we begin to address these issues by reviewing findings from two studies (Cooper, 2008; Cooper et al., 2006) that illustrate important ways in which both partners’ approach and avoidance motives shape sexual experiences within intimate relationships. The data for both studies were drawn from the same community sample of 299 Black and White young adult couples (average age = 24 years for men and 22 years for women). To participate, couple members had to be at least 18 years old and involved in a heterosexual, sexual relationship. Couples were interviewed face-to-face, separately and in private by a same-sex interviewer; more sensitive questions were self-administered to encourage honest responding. Relationships ranged in length from 1 month to 9 years, with a mean of nearly 3 years. Sixty-two percent of couples described their relationship as an “exclusive dating relationship,” 47% were living together, and 43% were raising at least one child (see Collins, Cooper, Albino, & Allard, 2002, and Cooper et al., 2006, for details). The primary outcomes examined in these studies included six different aspects of sexual experience, rated by both partners. These were the frequency of affectionate gestures (kissing, hugging, cuddling) initiated by both

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partners; frequency of sex (with one’s primary partner) in the past 6 months; overall satisfaction with the sexual relationship; the use of verbal or physical coercion by the male partner; a dichotomous measure of cheating, defined as having one or more extrapair partners in the past 6 months when one’s primary partner thought the relationship was monogamous; and a quantitative measure of the riskiness of these extrapair sex partners. Individuals with no extrapair partners (about 75% of the sample) were scored 0 on the latter two measures. On the basis of patterns of association with sexual satisfaction, affectionate gestures and frequency of sex were viewed as markers of positive sexual experience, whereas coercion and both measures of extrapair sex were viewed as markers of poor sexual functioning.* Finally, both partners completed the Cooper et al. (1998) sex motives measure. For all analyses, an internal avoidant motive composite was created by averaging the coping and affirmation subscales, which were correlated in the low .60s among both men and women. Thus, four male and four female motive measures (viz., intimacy, enhancement, internal avoidance, and partner approval) were used in all analyses, one reflecting each of the hypothesized quadrants in our original model.

TO WHAT EXTENT IS AN INDIVIDUAL’S SEXUAL EXPERIENCE INFLUENCED BY HIS OR HER PARTNER’S APPROACH AND AVOIDANCE MOTIVES FOR SEX? Questions regarding the nature and extent of actor (influence of one’s own motives on one’s behavior) and partner (influence of partner motives on one’s behavior) effects on sexual outcomes were examined in a series of regression models in which both self- and partner-motives were entered simultaneously. Results for the four measures of sexual experience within the relationship are displayed graphically in Figure 37.1. (Results for extrapair sex are discussed later.) As shown in Figure 37.1, a number of interesting patterns emerged in the data. First, the quantity and quality of sexual experience among women was determined

* Interestingly, however, the correlations between sexual satisfaction and coercion were modest in magnitude (rs = −.15, p < .05, for both genders), suggesting that the nature of the coercion used by men in the present sample was most likely mild. Consistent with this analysis, only 5% of males and 7% of females reported that the male partner had ever used any type of physical force to coerce his partner.

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almost exclusively by their own motivations. Indeed, only one significant partner effect was found among women— male intimacy motives, somewhat surprisingly, negatively predicted female reports of sex frequency. In contrast, the quantity and quality of male sexual experience was determined by both his own and his partner’s motivations. In fact, for two of the four outcomes, male sexual experience was influenced solely by his partner’s motives. Second, the direct effects of avoidance motives on sexual experience were relatively few in number, but uniformly negative. Female avoidance motives were negatively related to both male and female partner reports of affectionate exchanges, and to female reports of sexual satisfaction. In addition, female partner-approval motives were positively related to both male and female reports of sexual coercion enacted by the male partner, as were male avoidance motives to his own reports of coercion. Thus, consistent with prior research using individuals (as opposed to couples), avoidant motivations appear to be detrimental to sexual functioning in romantic relationships. In contrast, the pattern for approach motives was both more complex and less consistent with results of earlier studies using individuals. For example, although enhancement motives have been associated in past research with a pattern of high risk, promiscuous sex, female enhancement motives were associated with largely positive effects for both men and women, including increased frequency of sex and increased satisfaction. In contrast, male enhancement motives were unrelated to sexual functioning, as reported by both male and female partners. Similarly, the effects of pursuing intimacy in the context of an intimate relationship also appeared more mixed than findings obtained in prior studies of individuals would suggest. For example, and as expected, female intimacy motives were related to higher perceived levels of affectionate exchange and higher sexual satisfaction among women, as were male intimacy motives to sexual satisfaction among men. At the same time, however, high-intimacy-motive women perceived their partners to use more coercive tactics, whereas women with high-intimacy-motive partners reported less frequent intercourse. Motive effects on extrapair sex were examined in our earlier study (see Cooper et al., 2006, for details). These results showed that men whose sexual behavior was motivated by avoidance (including coping, self-affirmation, and partner-approval motives) had more risky extrapair partners, whereas women who used sex to affirm their attractiveness and self-worth (one of the measures in our

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RT6019X_C037.indd 623

.16 ∗

−.14∗

∗∗

9 −.1

1†

−. 1

.26 ∗∗∗

MR Sex Freq

FR Sex Freq

MR Affection

FR Affection

∗∗

.37∗∗∗

.08

R 2 = .02

.54∗∗∗

R 2 = .08∗∗

R 2 = .02

R 2=

(b)

M Part Appr

M Int Avoid

M Enhance

M Intimacy

F Part Appr

F Int Avoid

F Enhance

F Intimacy

M Part Appr

M Int Avoid

M Enhance

M Intimacy

F Part Appr

F Int Avoid

F Enhance

F Intimacy

†

−.22

∗∗∗

−.12

.14 ∗

∗

.16 ∗∗ .20

.11 †

∗∗∗

.23

.15 ∗

.15 ∗

.14 ∗

.16 ∗

∗

.15

MR Male Coercion

FR Male Coercion

M Satisfaction

F Satisfaction

R 2 = .13∗∗∗

.10∗

R 2 = .11∗∗∗

R 2 = .05∗

.28∗∗∗

R 2 = .11∗∗∗

FIGURE 37.1 Actor-partner models predicting male and female sexual outcomes. Note: F = female; M = male; Int Avoid = internal avoidant; Part Appr = partner approval; FR = female report; MR = male report; Freq = frequency. † p < .10; * p < .05; ** p < .01; *** p < .001.

(a)

M Part Appr

M Int Avoid

M Enhance

M Intimacy

F Part Appr

F Int Avoid

F Enhance

F Intimacy

M Part Appr

M Int Avoid

M Enhance

M Intimacy

F Part Appr

F Int Avoid

F Enhance

F Intimacy

A Dyadic Perspective on Approach and Avoidance Motives for Sexual Behavior 623

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avoidant composite) had more risky extrapair partners. Perhaps most important for the present chapter, however, men with partners high in approval motives for sex were more likely to both cheat and have high-risk extrapair partners. In contrast, but consistent with the pattern described above, male partner motives did not predict extrapair sex among women. Together these data indicate that the sexual experiences of men in relationships are profoundly shaped not only by their own motivations but also by their partner’s. Men whose female partners were high in enhancement appeared to have more positive sexual experiences, whereas men whose female partners were high in partnerapproval motives reported less adaptive sexual behaviors. Women’s experiences, on the other hand, were almost entirely shaped by their own motivations, possibly reflecting women’s role as the arbiter of sexual activity in relationships (Baumeister & Tice, 2001). Finally, comparing these results to results from earlier studies using individuals indicates that pursuing avoidance goals is associated with largely detrimental outcomes across relationship contexts, whereas the effects of pursuing approach goals depend more heavily on relationship context.

ARE THERE SYNERGISTIC (I.E., COUPLE LEVEL) EFFECTS OF APPROACH AND AVOIDANCE MOTIVES? In the prior section, we showed that the sexual motivations of both partners, but particularly of the female partner, make unique contributions to sexual experience in intimate relationships. However, the presence of additive effects alone does not mean that the couple functions as a synergistic system in which the relationship “whole” is greater than the sum of its parts (i.e., the two partners’ motivational strivings). To demonstrate synergy, the two partners’ motives must interact to predict important outcomes. This possibility was recently examined using measures of sexual experience both within and outside the relationship (Cooper, 2008). Because little is known about how partner motives combine to shape sexual outcomes, we wanted to allow for a wide range of plausible interaction patterns in our analyses. We therefore tested all possible male partner × female partner motive interactions and then examined both the pattern of significant effects (e.g., across motives, across dependent measures) and the shape of significant interactions to determine if they conformed to any of several plausible models of synergistic effects. Interactions were tested in blocks involving all possible

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interactions for each of the four motives (e.g., all possible interactions involving male and female intimacy motives). Accordingly, a total of 48 blocks of interactions were tested (6 sexual outcomes × 4 motive classes × male and female reports).

DO MALE AND FEMALE PARTNER MOTIVES INTERACT? IF SO, ARE THESE SYNERGISTIC EFFECTS EQUALLY COMMON AMONG MEN AND WOMEN, ACROSS SEXUAL BEHAVIORS, AND ACROSS SPECIFIC MOTIVES? At the most general level, results of the interaction analyses showed that motives combine in a synergistic fashion to shape sexual experience among both men and women. Indeed, nearly half (21 of 48) of the interaction blocks tested were significant at p < .10, more than four times the number expected by chance alone. Examining results for male and female outcomes separately suggested that synergistic effects may be stronger among women than men: 54% of the blocks of interactions tested significantly predicted female outcomes, compared with only 33% of the blocks predicting male outcomes. Examining the pattern of effects by dependent measure raised the possibility that some sexual behaviors are more interdependent than others. Cheating was strongly determined by the interaction of partner motives among both men (3 of 4 blocks, p < .05) and women (3 of 4 blocks, p < .05), thus suggesting that straying from one’s primary relationship reflects an interactive dynamic between properties of the person and of the relationship. In contrast, other patterns of effects differed across men and women. In particular, more consistent interaction effects were found for risky extrapair sex (4 of 4 blocks, p < .05) and for reports of male sexual coercion (3 of 4 blocks, p < .10) among women, and for sexual satisfaction (4 of 4 blocks, p < .10) among men. Examining the pattern of significant effects by motive suggested that the effects of enhancement motives on sexual outcomes were highly conditional among both men (3 of 6 blocks, p < .10) and women (4 of 6 blocks, p < .10). Among women only, the effects of intimacy motives (4 of 6 blocks, p < .10) and internal avoidant motives (3 of 6 blocks, p < .10) also appeared to depend heavily on the male partner’s motivational pursuits.

WHAT IS THE NATURE OF THESE SYNERGISTIC EFFECTS? Although these data clearly indicate that male and female partner motives combine in a synergistic fashion to shape at least some sexual outcomes, the nature of these

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synergisms can be understood only by examining the form of the interactions. Accordingly, significant (p < .10) interactions (n = 43) were plotted and examined to determine the extent to which they conformed to several plausible patterns of synergistic effects. We first considered a set of possibilities based loosely on exchange theory (Clark & Reis, 1988). This approach argues that sexual experiences should be most rewarding and functional in relationships where couple members contribute socially valued attributes—attributes that provide significant rewards but have minimal associated costs (Schmitt, 2002). In the context of a close romantic relationship, intimacy motives would be expected to serve as a positive or adaptive attribute and avoidance motives as negative or maladaptive attributes. However, it is less clear whether enhancement motives can be seen as unequivocally adaptive or maladaptive; thus, this perspective may not apply in any simple or straightforward way to enhancement motives. The general notion that sexual functioning will be sensitive to the balance or combination of adaptive (intimacy) versus maladaptive (avoidance) motives could play out in a number of different ways. For example, couples in which both individuals are high in adaptive motives might experience unusually positive sexual outcomes, whereas couples in which both individuals are high in maladaptive motives might experience unusually negative outcomes. Similarly, couples in which both members are low in adaptive motives would be expected to experience poor sexual outcomes, whereas couples in which both members are low in maladaptive motives might experience less negative outcomes (though the mere absence of maladaptive motives might not be sufficient to foster high levels of adaptive functioning and positive outcomes). Alternatively, the presence of an adaptive motive in either partner might buffer the adverse effects of a maladaptive motive on sexual experience. Examining the subset of significant interactions relevant to the exchange theory approach (i.e., intimacy × intimacy [n = 2], intimacy × avoidance [n = 10], and avoidance × avoidance [n = 7] interactions) revealed modest support for this perspective. Of the 19 relevant interactions examined, 6 interactions could be interpreted within this framework: three conformed to the buffering model, and 3 conformed to the notion that the cumulative effects of either low quantities of positive attributes or high quantities of negative attributes lead to particularly poor outcomes. Figure 37.2 provides an example of both patterns of synergistic effects.

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As shown in the top panel of Figure 37.2, women who were high in internal avoidant motives coupled with a low intimacy partner were prone to have risky extrapair sex, perhaps in an effort to cope with negative emotions stemming from insecure feelings about their self-worth. In contrast, no such effect was observed among highinternal-avoidant-motive women coupled with highintimacy men who may provide more effective support to their female partners. As shown in the bottom panel, low intimacy among men predicted elevations in the use of coercive strategies by the male partner only if the female partner was also low in intimacy. We also considered the possibility that matching on motives might lead to superior outcomes, regardless of the adaptive nature of the motives involved. For example, couple members might be more satisfied because of the relative equality of their attributes (Hatfield, Walster, & Berscheid, 1978), or because similarity is self-validating (Swann, 1992). Alternatively, similarity in motives might lead to patterns of thoughts, feelings, and behaviors that are familiar and comfortable, even if maladaptive (cf., repetition compulsion; Freud, 1920). Or relatedly, similarity in motives might lead to less conflict or more easily managed conflict (cf., Gottman, 1994). However, little support was found for this perspective. Only a small number of interactions (6 of 48 tested) were obtained between like motives (e.g., male and female intimacy) and, of these, only one suggested that couples who shared similar motives (in this case, enhancement) experienced more adaptive outcomes (i.e., more affectionate gestures). In addition, we examined the possibility that one partner’s motives and preferences might disproportionately drive the couple’s sexual outcomes to the extent that the other partner has sex for approval reasons (cf., the motivation to comply component of subjective norms in the theory of reasoned action; Ajzen & Fishbein, 1980). For example, we might expect male enhancement motives to more strongly determine intercourse frequency in relationships where the female partner is high versus low in partner-approval motives, or in other words, where the female partner has sex to please or appease her partner. We found strong support for this notion, with more than half of the significant partner-approval interactions (10 of 19) conforming to this pattern. Interestingly, however, this pattern held primarily for female partner-approval motives, with 8 of the 10 conforming interactions involving female approval motives. Figure 37.3 illustrates this pattern for female partner approval × male enhancement predicting female reports of sex frequency (top panel) and of sexual satisfaction (bottom panel). Consistent with

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Female risky extrapair sex

0.45

Hi F Int Avoid

0.4

Lo F Int Avoid

0.35

b = −.083∗∗

0.3 0.25 0.2 0.15

b = .023

0.1 0.05 0 Low

High Male intimacy

0.6

Hi F Intimacy b = −.104∗

0.55

Lo F Intimacy

MR male coercion

0.5 0.45 0.4 0.35 0.3 0.25

b = .010

0.2 0.15 Low

High Male intimacy

FIGURE 37.2 Illustrative interactions consistent with the exchange model. Top panel: Male intimacy × female internal avoidance predicting female risky extrapair sex. Bottom panel: Male intimacy × female intimacy predicting male reports of male coercion. Note: F = female; MR = male report; Int Avoid = internal avoidant. * p < .05; ** p < .01.

expectation, both plots indicate that male motives more strongly shaped sexual experience in couples where the woman was high as opposed to low in partner-approval motives. Finally, given that more than half of all significant interaction coefficients (24 of 43) involved male enhancement, female enhancement, or both, we thought it important to examine these interactions to see what could be learned about the role of enhancement in intimate sexual relationships. Not surprisingly, a complex pattern of results was found in which enhancement motives were associated with harmful effects (especially increased infidelity and use of coercive tactics among men), but also with beneficial ones (increased frequency of physical and sexual contact), depending on the motivational context in which they were pursued. For example, high-enhancement men were more likely to use coercive tactics and to cheat when they were partnered with high-enhancement women (see Figure 37.4, top panel), and women with

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high-enhancement partners were also more likely to cheat when they were low in either intimacy or partner-approval motives or high in internal avoidance (see Figure 37.4, bottom panel). In addition, both men and women were more likely to cheat in relationships where the woman was high in enhancement and the man was low in internal avoidance motives. On the more positive side, both men and women reported more frequent intercourse when the male partner was high (vs. low) in enhancement and the female partner was high in partner-approval motives (see Figure 37.3, top panel), and high-enhancement men reported more kissing, hugging, and cuddling when they were partnered with women high in enhancement or in intimacy motives. Finally, although female enhancement was primarily associated with positive effects on sexual satisfaction among both men and women (see Figure 37.1), the effects of male enhancement motives on satisfaction were for the most part negligible. Indeed, only two interactions were obtained predicting sexual satisfaction from

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FR of sex frequency

7.7

627

b = −.089

7.5 7.3 7.1

b = . 297†

6.9 Hi F Part Appr Lo F Part Appr

6.7 6.5 Low

Male enhancement

High

5.8 b = −.037

Female satisfaction

5.4 5 4.6

b = .354∗∗

4.2 3.8

Hi F Part Appr Lo F Part Appr

3.4 3 2.6

Low

High Male enhancement

FIGURE 37.3 Illustrative interactions involving female partner-approval motives. Top panel: Male enhancement × female partner approval predicting female reports of intercourse frequency. Bottom panel: Male enhancement × female partner approval predicting female sexual satisfaction. Note: F = female; FR = female report; Part Appr = partner approval. † p < .10; ** p < .01.

male enhancement, and the effects were in one case negligible to positive (see Figure 37.3, bottom panel) and in the other, negligible to negative (not shown).

SUMMARY At the most general level, these analyses indicate that male and female partner motives combine in a synergistic fashion to determine sexual experience within intimate relationships, that the expression or satisfaction of some motivations is particularly dependent on the nature of the partner’s motivational pursuits, and that some behaviors are more synergistically determined than others. Examining the form of the interactions between male and female partner motives revealed a complex variety of forms, the overwhelming majority of which were readily interpretable. Nevertheless, the multitude of forms suggests that multiple distinct processes underlie and give rise to these interactions, and therefore that no single theoretical model will be adequate to understand the nature of these synergisms.

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CONCLUDING THOUGHTS AND FUTURE DIRECTIONS The present chapter highlights the utility of the approach– avoidance framework for understanding human sexual motivation. In this chapter, we showed that the structure of discrete sexual motivations can be usefully understood within the approach–avoidance framework, and indeed that this two-dimensional structure is superior to other plausible two-dimensional representations. Not surprisingly, this framework also provides important insights into the nature and meaning of different motivational strivings in the sexual domain, particularly their emotional valence. The approach–avoidance framework also provides broadly useful insights into the probable consequences of using sex to pursue approach and avoidance goals, although the straightforward expectation of positive effects accruing from approach pursuits and negative effects accruing from avoidant pursuits is clearly inadequate. This is particularly true for enhancement motives which may be considered a prototype of an approach

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Probability male cheating

628

Hi F Enhance Lo F Enhance

0.5 b = 1.175∗∗

0.4 0.3 0.2

b = −.228

0.1 0 Low

Male enhancement

High Hi F Int Avoid Lo F Int Avoid

Probability female cheating

0.2

b = .564†

0.1

b = −.161

0 Low

High Male enhancement

FIGURE 37.4 Illustrative interactions involving male enhancement motives. Top panel: Male enhancement × female enhancement predicting probability of male cheating. Bottom panel: Male enhancement × female internal avoidance predicting probability of female cheating. Note: F = female; Int Avoid = internal avoidance. † p < .10; ** p < .01.

motive, yet are associated with a complex pattern of both harmful and beneficial effects. Indeed, the evidence in this chapter strongly suggests that understanding how these motives play out in the lives of individuals and couples to shape sexual experience will require going beyond a simple approach–avoidance dichotomy to more carefully consider the relational context in which one’s sexual goals are pursued, as well as the role of gender-specific dynamics that can transform the meaning of sexual behaviors for men and women. In the remainder of this chapter, we briefly explore several implications of these notions for understanding approach–avoidance sexual goals and their contributions to human sexual experience.

THE RELATIONAL CONTEXT At the most basic level, evidence presented in the present chapter indicates that whether sexual goals are pursued within or outside the context of a committed or exclusive relationship matters greatly and that failure to

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take relationship status into account risks underestimating the predictability of sexual behavior from sexual motives, as well as mischaracterizing or distorting these relationships. Thus, at a minimum, even studies of individuals need to take relationship status (e.g., committed vs. casual) into account. Beyond this basic consideration, our dyadic analyses indicate that both partner’s motives shape sexual experience in at least two important ways. First, all behaviors in the present analyses are, in part, determined by partner motive effects. Specifically, our findings reveal partner (but not actor) motive effects for two (male) outcomes, and both actor and partner motive effects (i.e., additive effects) for five (4 male, 1 female) additional outcomes. Thus, for the majority of outcomes, focusing solely on one partner’s motives would substantially underestimate the predictability of sexual experience from approach and avoidance sex motives, particularly among men. Second, we showed that all of the outcomes considered in the present chapter are jointly shaped by specific

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combinations of partner approach and avoidance motives among both men and women. From a psychological viewpoint, such findings indicate that the effects of one’s own motivational pursuits on sexual experience within a close relationship cannot be understood in a vacuum, but rather depend importantly on the context provided by one’s partner’s goal pursuits. Despite the meaningfulness of the individual interactions examined, the set of interactions as a whole do not lend themselves to parsimonious generalizations about the adaptive significance of specific motive combinations for individuals and couples. Although the form of various interactions can be seen as conforming to different models of how partner attributes combine to determine outcomes in a relationship (e.g., similarity, exchange), many do not conform to any of the common models. We suspect that this diversity of form reflects the inherent complexity of sexual behavior, and of the many functions it can serve and meanings it can assume in the context of an ongoing committed relationship. Alternatively or in addition, meaning and organization may reside at a higher, more complex level of analysis. For example, the entire configuration of motives of one partner may interact with the other partner’s configuration. This, we believe, represents an important direction for future research.

GENDER SPECIFICITY OF MOTIVE EFFECTS Human sexual behavior is strongly gender specific, both biologically and culturally. Thus, it is not surprising that we find pervasive gender differences in the effects of approach–avoidance motives on sexual behavior. These differences manifest in at least three important ways. First, the pattern of actor and partner effects in Figure 37.1 illustrates what might be called a “female dominance effect” in which the woman’s, but not the man’s, motivations drive the sexual experience of both partners. This asymmetrical pattern of influence suggests that sexual outcomes are more interdependent among men than women, at least within the context of a committed relationship, possibly due to the disproportionate power women are thought to hold in the sexual arena (cf., Baumeister & Tice, 2001). There is, however, an important exception to this pattern: The sexual outcomes of both women and men in couples where the woman is high in partner-approval motives are more strongly determined by male partner motives. The converse is not true, however: In four of eight significant interactions involving male partner-approval motives, female motives more strongly determined outcomes when the male partner was low (not high) in approval motives. These data not

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629

only provide additional evidence of the gender specificity of motive effects on sexual behavior, but also raise questions about what partner-approval motives assess among men if not the motivation to comply with or defer to their partner’s sexual preferences. Finally, the data in the present chapter also indicate that the effects of pursuing approach and avoidance goals depend importantly on whose motivational agenda—the man’s or the woman’s—we are talking about. In the actorpartner models (Figure 37.1), only three actor effects replicate across men and women (viz., intimacy motives → satisfaction, partner approval → coercion by the male partner, internal avoidant → risky extrapair sex), and no partner effect replicates. Although such findings may be partly attributable to methodological limitations of selfreport measures, we suspect that these asymmetrical findings also reflect meaningful differences in how men and women pursue sexual goals, or in what specific sexual goals or specific sexual behaviors signify to men and women. Indeed, unless we are willing to write off all observed differences as methodological artifacts—an interpretation that we believe would be difficult to justify in the face of the many statistically reliable and psychologically meaningful results—we are faced with the conclusion that the effects of approach and avoidance sex motives on sexual behavior cannot be understood at a general or abstract level, but rather must take into account the highly gender specific nature of behaviors enacted in the sexual arena. In this chapter, we presented evidence showing that individuals use sex to pursue a range of approach and avoidance goals in their relationships and that sexual outcomes are shaped to a nontrivial extent by the nature of these motivational pursuits. Specifying whether, or under what conditions, these pursuits lead to positive or negative sexual outcomes proved highly complex, however, owing to the gender specificity of sexual behaviors and to synergisms between partners’ motivational pursuits. These findings point to the need to develop more complex models of approach and avoidance motives in the sexual domain, as well as a deeper understanding of the individual and dyadic processes by which people seek to meet these needs in various relational contexts.

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Schachner, D. A., & Shaver, P. R. (2004). Attachment dimensions and sexual motives. Personal Relationships, 11, 179–195. Schmitt, D. P. (2002). Personality, attachment and sexuality related to dating relationship outcomes: Contrasting three perspectives on personal attribute interaction. British Journal of Social Psychology, 41, 589–610. Sheeran, P., Abraham, C., & Orbell, S. (1999). Psychosocial correlates of heterosexual condom use: A meta-analysis. Psychological Bulletin, 125, 90–132. Skinner, E. A., & Wellborn, J. G. (1994). Coping during childhood and adolescence: A motivational perspective. In D. L. Featherman, R. M. Lerner, & M. Perlmutter (Eds.), Life-span development and behavior (Vol. 12, pp. 91–133). Hillsdale, NJ: Erlbaum. Swann, W. B. (1992). Seeking “truth,” finding despair: Some unhappy consequences of a negative self-concept. Current Directions in Psychological Science, 1, 15–18.

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Author Index A Aaker, J. L., 421, 478, 560, 562, 564, 566 Aarts, H., 296 Abelson, R. P., 352, 387 Abend, T., 542 Abercrombie, E. D., 94 Aberman, J. E., 29 Abi-Dargham, A., 121 Abraham, C., 621 Abramowitz, J. S., 448 Abramson, L. Y., 409 Abramson, L. Y., 337, 523–524 Achille, N. M., 155 Ach, N., 544 Ackerman, B. P., 373 Ackerman, J., 275, 279, 281–282 Adamec, R., 6 Adams, L. F., 110 Adams, M. S., 258 Adams, R. B. J., 403 Adolphs, R., 313–314, 544 Afarian, H., 42 Affleck, G., 388 Agnati, L. F., 91 Agocha, V. B., 620 Agrati, D., 137 Ahadi, S., 422 Ahadi, S. A., 190, 470 Ahern G. L., 35 Ahrens, A. H., 360 Aiken, K. J., 299 Aiken, L. S., 196 Ajzen, I., 223, 300, 332, 346, 421, 625 Akers, K. G., 44 Akil, H., 194 Aksan, N., 156, 188 Akwa, Y., 111 Albano, A. M., 379 Albarracín, D., 289–291 Alberts, S. C., 204 Albino, A., 621 Alburges, M. E., 100 Alcaro, A., 71, 77, 81 Alcock, J., 274 Aleman, D. O., 95 Alessandri, S. M., 400, 402 Alexander, G. E., 279 Alexander, M. P., 463 Algom, D., 157 Alicke, M., 596 Alicke, M. D., 336 Allan, S., 373, 377 Allard, L., 621 Allen-Arave, W., 257 Allen, J. J. B., 35–39, 237, 244, 404–405, 543–544, 547 Allen, K., 444

Allen, N. B., 607–608 Alloy, L. B., 337, 380, 451 Allport, G., 307 Allport, G. W., 229, 289–290, 307, 441, 581 Allsopp, J. F., 159 Alnwick, K. A., 110 Alpert, N., 418 Altman, B. M., 604 Altmann, J., 204 Alvarez-Pelaez, R., 55 Amaral, D. G., 61, 313 Amaral, E., 136 Amat, C., 129 Ambady, N., 403 Ames, C., 224–225, 227 Amodio, D. M., 579 Amo, L., 176 Amorapanth, P., 23, 25, 29 Amsel, A., 358 Anagnostaras, S. G., 129 Anderman, E. M., 227 Andersen, P. A., 392 Andersen, S. M., 346 Anderson, A. K., 314 Anderson, C., 277 Anderson, M. C., 236, 242 Anderson, N., 432 Anderson, R., 6 Anderson, R. C., 167, 174, 178–179, 221 Andréen, L., 112 Andrew, R., 41 Andrews, M. W., 43 Anglada-Figueroa, D., 23 Angleitner, A., 195 Annas, P., 61–62 Anokhin, A. P., 39 Ansfield, M., 454 Antes, J. R., 237 Antone, C., 477 Anton, G., 96 Antoniou, A. A., 351 Antony, M. M., 451 Aono, T., 137–138 Apanovitch, A. M., 477, 480 Apiolaza, L. A., 174 Appley, M. H., 9, 344 Araneda, R. C., 129 Arbisi, P., 38 Archer, J., 137, 225, 227 Arcuri, L., 293 Aristotle, 353, 359 Arkes, H. R., 369 Armitage, C. J., 483–484 Armitage, K., 6 Armony, J. L., 20, 24 Arndt, J., 448, 512

Arneson, C. L., 190 Arnold, H. M., 131 Arnold, M., 7–8 Arnold, M. B., 293, 358 Aron, A., 62, 208, 393 Aronson, J., 443, 581 Arrowood, A. J., 597 Arseneault, L., 193 Arvanitogiannis, A., 83 Asakawa, K., 563 Ascher, J. A., 138 Asendorpf, J. B., 299 Asher, E. R., 211 Asher, S. R., 604 Ashton, H., 353 Ashton, M. C., 155 Aspinwall, L., 596 Aston-Jones, G., 91 Atkinson, J., 10 Atkinson, J. W., 8, 204–205, 217–218, 220–221, 223, 346, 352, 466, 521, 536–537, 544, 572, 578, 586 Atthowe, J. M., 352 Audy, J. R., 604 Augelli, R. W., 373 Auger, A. P., 138 Augustine, A. A., 151–161, 174 Aunger, R., 368, 375, 378 Avena, N., 99 Avena, N. M., 89–102 Averill, J. R., 345 Avila, C., 211 Avivi, Y. E., 385–394 Avnet, T., 494 Axelrod, R., 257 Ayduk, O., 207, 471, 500 Ayers, G., 138 Ayton, P., 369 Aziz, N., 207

B Babinsky, R., 314 Bachman, J. G., 510 Bachnick, L., 480 Bachorowski, J., 464 Bach, P., 456 Back, K., 602 Backstrom, T., 110, 112 Badcock, P. B. T., 607–608 Baer, A., 495 Baer, L., 455 Baeyens, F., 327 Bailey, J. M., 282 Bakan, D., 617 Baker, C., 455

633

RT6019X_C038.indd 633

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634

Baker, C. A., 454–455 Baker, L. A., 153 Bakowska, J. C., 136 Bakshi, V. P., 197 Bak, T. H., 95 Balakrishnan, R., 137 Baldo, B. A., 90 Baldo, M. V., 136 Bale, T. L., 138 Balleine, B., 27 Balleine, B. W., 27–28, 90 Ball, S. A., 159 Balthazart, J., 111 Banaji, M. R., 291–293 Bancroft, J., 110 Bandler, R., 60, 462 Bandura, A., 300, 332, 348, 422–423 Banks, S. M., 476 Bannerman, D. M., 90 Banse, R., 299 Baram, T. Z., 132 Barbaccia, M. L., 111 Barber, L. L., 615–629 Bardo, M. T., 80–82, 134 Barfield, R. J., 402 Bargh, J., 7 Bargh, J. A., 7, 241, 289–301, 345–346, 392, 536–537, 543, 577–578 Barkai, E., 132 Barker, J. L., 112 Barker, R., 346 Barlow, D. H., 352, 379 Barndollar, K., 296, 346, 577–578 Barnhardt, T. M., 237 Baron, R. A., 402 Barrett, D., 130 Barrett, H. C., 252, 278–279 Barrett, L. F., 352–354, 392, 439 Barrett, P., 159 Barrett, T. R., 454 Barr, G. A., 134–135 Barrot, M., 83 Barsh, G. S., 94 Barta, W. D., 477 Bartels, A., 208 Bartels, J. M., 609 Bartels, M., 197 Bartels, R., 475, 477, 482 Bartels, R. D., 475–484 Bartmess, E. N., 531 Barto, A. G., 327 Bartussek, D., 37–38, 408 Baskin, D. G., 94 Bass, A. H., 111 Bassareo, V., 28, 92 Basso, M. R., 236 Bates, D. E., 452 Bates, J. E., 188, 190, 464 Bateson, M., 335 Batra, R., 282 Battaglia, D. M., 606 Bauer, E. P., 24 Baulieu, E. E., 111 Bauman, M. D., 313–314

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Author Index

Baumann, N., 222–223, 244, 537, 539–541, 546, 548 Baumeister, R., 297, 509 Baumeister, R. F., 204, 223, 301, 317, 334, 336, 352–353, 360–361, 392–393, 448, 453, 466, 500, 506–508, 510–513, 532, 559, 601–611, 619, 624, 629 Baxter, L. R., 156, 237 Bayon, L. E., 118 Beach, F. A., 113–114 Beach, S. R. H., 392, 532 Beamer, L., 618 Beattie, J., 352 Beauchaine, T. P., 378 Bechara, A., 313–315 Beck, A. T., 37, 451–452 Becker, D. V., 279, 281–282 Becker, E., 506 Becker, E. S., 452 Becker, J. B., 371 Beck, J. E., 471 Beck, J. G., 449–450 Beckmann, D., 40 Beckmann, J., 540 Beck, S. G., 113 Bedell, B. T., 477 Beeman, M., 245, 537, 545 Beer, J. S., 353 Behar, E., 452 Beidel, D. C., 376 Beiderbeck, D. I., 138 Beilharz, R., 6 Bekkedal, M., 207 Bell, A., 181 Bell, A. M., 181 Bellgowan, P. S. F., 23 Bell, M. A., 39, 158 Bem, D. J., 241, 336 Benes, F. M., 130 Benjamin, J., 176 Benjamin, L., 195 Bennett, M. R., 71 Bentall, R. P., 454–455 Bentham, 293 Bentham, J., 4 Berdel, B., 130 Berger, S. M., 515 Berglas, S., 513 Bergum, B. O., 235 Berkman, E. T., 203–213 Berkman, L. F., 207 Berkowitz, L., 347, 354, 359, 400–402, 409 Bernabeu, R., 132 Bernardi, F., 111 Berndt, J. D., 130 Berns, G. S., 99 Bernston, G. G., 204, 334 Berntson, G., 5–8, 324 Berntson, G. G., 57, 207, 235, 241, 307–318, 352, 354, 368, 370, 389, 407, 536, 538, 542, 547, 562 Bernzweig, J., 471 Berrettini, W. H., 110

Berridge, C. W., 463 Berridge, K., 8 Berridge, K. C., 29, 69, 71, 73–75, 77–79, 81–82, 92, 94, 96, 99, 137, 238, 291, 311–313, 315, 351 Berry, A., 440 Berscheid, E., 204, 280, 335, 392, 602, 625 Berthental, B. I., 543 Berthier, N., 543 Berthoud, H. R., 90 Best, A. R., 128, 130 Bettini, E., 113 Bevins, R. A., 82 Bhattacharyya, S., 130 Bianco, A. T., 494 Biebrich, R., 546 Biederman, L., 6 Bielsky, I. F., 138 Biernat, M., 573, 591–592 Biglan, A., 608 Bindra, D., 71 Birbaumer, N., 57 Birch, D., 8, 466, 521 Birney, R. C., 220–222, 346 Bitran, D., 112 Bittles, A., 258 Bjork, R. A., 448 Blackhart, G. C., 608, 610 Blackmore, S., 368, 374 Blackwell, K. C., 279 Blaine, B., 559 Blair, H. T., 19, 24 Blair, I., 298 Blanchard, D. C., 20–21, 55, 60, 96, 134, 402 Blanchard, R. J., 20–21, 55, 60, 96, 134, 402 Blander, D. S., 93 Blank, A., 335 Blanton, H., 515, 596–597 Blascovich, J., 370, 431–444, 512, 514, 538 Blass, E. M., 131–132, 134 Blavet, N., 96 Bless, H., 592 Bloch, B., 100 Block, J., 228 Blonigen, D. M., 193 Bloom, F. E., 96 Blumberg, S. J., 454 Blundell, P., 28 Blysma, W., 591 Bocarsly, M. E., 99–100 Boccia, M. L., 135, 138 Bodenhausen, G., 591 Bodenhausen, G. V., 454, 578 Boehmelt, A. H., 58 Boergers, J., 453 Bogardus, E., 7, 293 Bohlig, A., 402 Bohner, G., 292 Boholm, A., 326 Boissy, A., 402 Bokhorst, C. L., 189 Bolger, N., 495 Bolles, R. C., 20–21, 71, 130, 312, 543 Bolte, A., 541

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Author Index

Bolton, D., 192 Bond, M. H., 532, 559 Boniecki, K. A., 573 Boomsma, D., 190 Boomsma, D. I., 193, 197 Bordi, F., 23 Boring, E. G., 9 Borkovec, T. D., 237, 451–453 Born, L., 110 Bornovalova, M. A., 20 Bosch, O. J., 138 Bossard, J. H. S., 281 Bosson, J. K., 559 Both, C., 166, 169, 172, 174, 177, 181–182 Boucher, J. D., 354 Boudreau, G. S., 102 Bouissou, M. F., 402 Boulton, M. J., 370 Bouret, S., 130 Bouwmeester, H., 130 Bower, G. H., 452 Bowers, K. S., 537 Bowlby, J., 5, 206–207, 278, 492, 601, 617 Bowles, R., 467 Bowser, R., 454 Boyatzis, R. E., 205–206 Boyce, K. L., 521–533 Boyd, R., 257 Boysen, S., 6 Boysen, S. T., 309 Bozarth, M. A., 75 Bracha, H. S., 354 Brackbill, R., 27 Bradbury, T. N., 393 Bradley, B. P., 374, 424 Bradley, M., 6–7, 9, 522 Bradley, M. M., 51–63, 294, 313, 390 Bradley, S. J., 376, 380 Brady, J. V., 20 Brake, S. C., 131 Brandt, M. E., 354 Bratslavsky, E., 317, 334, 352, 392–393, 466, 509, 619 Braun, J. J., 55 Brechmann, M., 244 Breckler, S. J., 294 Breedlove, S. M., 371 Breer, H., 129 Brehm, J. W., 402, 406 Brehm, S. S., 607 Breitenbecher, D. L., 336 Brendl, C. M., 241, 289, 292, 493 Brennan, K. A., 207 Brennan, P., 132, 138 Brennan, P. A., 129, 136 Brewer, M. B., 297, 602, 609 Brickman, P., 336, 596 Bridges, R. S., 136, 138 Brigham, J. C., 573, 579–580 Briley, D. A., 561 Britton, J. C., 373 Britt, T. W., 573 Broadbent, D. E., 543 Broadnax, S., 559

RT6019X_C038.indd 635

635

Brodish, A., 408 Brodish, A. B., 574–575 Bronson, F. H., 114 Brook, A. T., 531 Broome, A., 454 Brosh, I., 132 Browning, J. R., 618 Brown, J. D., 289, 508–509, 515, 558–560, 590–591, 594 Brown, J. S., 347, 493 Brown, K. L., 130 Brown, L. L., 62 Brown, L. M., 573 Brown, M. Z., 453 Bruce, J. C., 132 Bruce, V. G., 604 Brudzynski, S. M., 82 Brug, J., 479 Bruner, J. S., 290, 297 Brunner, F. P., 350 Brunner, R. L., 70 Brunstein, J. C., 220–223, 228, 388, 419, 422, 537, 541 Brush, F. R., 20 Bryant, R. A., 450 Buchanan, T. W., 314 Buchsbaum, M. S., 237 Buck, L. B., 129 Buckley, K. E., 608–610 Buckley, M. E., 40 Buckmaster, C. L., 44 Buck, R., 351 Budaev, S., 6, 166–167, 172, 174, 178, 181–182 Budziszewska, B., 100 Bugental, D. B., 276 Bugental, D. P., 204 Buhusi, C. V., 537–538, 546 Bull, F. C., 479 Bulman, R. J., 596 Bunce, S. C., 154 Bunge, S. A., 207 Buonviso, N., 129 Burdick, H., 220, 346 Burgdorf, J., 76–77, 81–82 Burghardt, G. M., 6 Burke, A., 235 Burke, M. C., 282 Burkhardt, R. W., 73 Burleson, M. H., 207 Burns, L. H., 27 Burrows, L., 536 Burton, P. C., 293 Burt, S. A., 193 Busch, D. E., 402 Bush, D. E., 23 Bush, D. E. A., 43 Buss, A. H., 223, 403, 409 Buss, D., 152, 252 Buss, D. M., 256, 276–277, 284, 371–373, 604 Buss, K. A., 188 Buswell, B. N., 284 Butner, J., 276, 279

Butters, J., 594 Butz, D. A., 573, 579, 581 Buunk, A. P., 278, 284 Buunk, B. P., 282, 515, 588, 597 Bylsma, W. H., 442 Byrne, D., 280, 618

C Cabanac, M., 300 Cabeza, R., 313–314, 500 Caceres, A., 113 Cacioppo, J., 5–7, 324 Cacioppo, J. T., 57, 158–159, 203–204, 207, 235, 241, 307–318, 334, 352, 354, 368, 370, 389–390, 407, 479, 536, 538, 542, 547–548, 562, 609 Cador, M., 26 Caffe, A. R., 138 Caggiula, A. R., 94 Cahill, L., 134, 282, 314 Cain, C. K., 17–30 Cairns, D. R., 610 Cairns, K. J., 508 Calamari, J. E., 450–451 Caldwell, J. D., 138, 371 Caldwell, M. A., 604 Calkins, S., 188 Calkins, S. D., 35, 39–41 Callahan, E. C., 136 Calu, D. J., 129, 133 Campbell, A., 267 Campbell, B. A., 59, 130, 132 Campbell, J., 516 Campbell, J. D., 507, 530 Campbell, J. S., 113 Campbell, K. A., 83 Campbell, M., 403 Campbell, P., 450, 454–455 Campbell, S. B., 40 Campbell, W. K., 610 Campeau, S., 23 Camp, L. L., 131, 133 Campos, B., 283, 389 Campos, J. J., 188 Campos, L. D., 284 Camras, L., 389 Canli, T., 152, 154, 156, 160–161, 312 Cannon, W. B., 348 Canteras, N. S., 136 Cantor, N., 206, 417, 420–421, 490, 522–523 Capitanio, J. P., 175, 313 Carbary, T. J., 134 Cardinal, R. N., 26–30, 314 Cardon, L. R., 189–190, 194 Carelli, R. M., 92 Carere, C., 169, 172, 174–175 Carey, G., 189, 198 Carey, W. B., 377 Carlezon, W. A. Jr., 101 Carlson, B. B., 80 Carlson, N. R., 345, 350

4/16/2008 5:52:25 PM

636

Carlston, D. E., 336 Carmichael, S. T., 61 Caron, M. G., 83 Carpenter, V., 221 Carr, G. D., 115 Carrillo, C. A., 99 Carr, K. D., 94–95 Carroll, B. J., 403 Carroll, J., 559 Carroll, J. M., 315, 387 Carruthers, P., 279 Carter, C. S., 139, 207–208, 394 Carter, S., III., 448 Carter, W. R., 237 Caruso, E. M., 298 Carver, C., 5, 521 Carver, C. L., 38 Carver, C. S., 156, 158–159, 212–213, 238, 301, 345, 349–352, 356, 360, 369, 378, 385–394, 403–404, 417–420, 424, 470, 478, 490, 492, 500, 511–512, 536, 564, 572, 575, 608, 616, 619 Cash, D., 594, 596 Cash, T., 594, 596 Caspi, A., 161, 192, 196 Cassidy, F., 403 Castanon, N., 169, 174, 176, 179 Castelli, L., 293 Castner, S. A., 121 Catalani, A., 139 Catanese, K. R., 609 Cater, J., 403 Cattarelli, M., 129 Cattell, R., 5 Caudill, W., 560 Caughlin, J. P., 208 Caulliez, R., 93 Cavender, J., 405 Centerbar, D., 241 Cesa, I. L., 153 Cesario, J., 478 Chaiken, S., 7, 289–291, 293–294, 352, 476–477, 479 Chajut, E., 157 Chambers, W., 356 Champagne, F. A., 137 Chance, S., 256 Chang, E. C., 563 Chang, F. C., 93 Chang, I. S., 197 Chang, K. D., 377 Chanowitz, B., 335 Chapman, A. L., 453 Chapman, G. B., 605 Charlesworth, W. R., 354 Chartrand, T., 7 Chartrand, T. L., 296 Chasiotis, A., 222 Chassin, L., 294 Chau, D., 96–97 Chau, D. T., 96–97 Chau, P. M., 313 Cheatle, M. D., 132

RT6019X_C038.indd 636

Author Index

Chee, P., 136 Chen, E. E., 313, 564 Chen, J., 290 Chen, M., 7, 241, 293–294, 298, 536 Chen, W. R., 129 Cherny, S. S., 199 Cheslock, S. J., 131 Chess, S., 376 Cheung, C. K. T., 609 Cheung, P. C., 225 Chiba, A. A., 129 Chien, B. Y., 158 Chirkov, V. C., 421 Chirkov, V. I., 560 Chiu, C., 224 Chiu, C.-K., 559 Chiu, C. Y., 422 Cho, G. E., 560 Choi, I., 565 Choi, W., 609 Chorpita, B. F., 379 Christensen, P. R., 241 Christ, M., 112 Christopher, F. S., 618 Churchill, L., 30 Church, M. A., 5, 7–8, 218, 225–227, 387, 417, 420, 490, 494, 499, 527–528, 562, 572, 578 Cialdini, R. B., 223, 281, 515, 517 Ciarocco, N. J., 608–609 Cicchetti, P., 23 Cioe, J., 130 Cioffi, D., 454 Ciompi, L., 71 Cirrito, J., 136 Clancy, S., 136 Clark, A., 6 Clark, C. L., 207 Clark, D. A., 449–451 Clark, D. M., 156, 455 Clarke, A. S., 169, 172, 174, 182 Clark, E. M., 479 Clark, L. A., 37, 198, 204, 376, 379, 404, 409, 464 Clark, M. S., 526, 608, 625 Clark, R., 10 Clark, R. A., 205, 217, 221, 544 Clark, R. D., 277, 282 Clark, R. N., 389 Clifton, R., 543 Cloninger, C. R., 159, 386 Clore, G., 236 Clore, G. L., 53, 241, 280, 291, 389, 401 Clugnet, M. C., 23 Coan, J. A., 35–36, 38–39, 237, 244, 404–405 Coates, D., 336 Coats, E. J., 418 Codispoti, M., 56, 59 Cofer, C. N., 9, 224, 344 Cohen, D., 557 Cohen, J., 196 Cohen, J. D., 91 Cohen, L. B., 129

Cohen, S., 207 Cohn, F., 40 Cohn, J. F., 40 Colantuoni, C., 99–100 Colas, A. E., 113 Colasante, C., 96 Colby, S. M., 453 Cole, M., 98 Coleman, J. R., 23 Coleman, K., 6 Collier, A. C., 130 Collier, G., 354 Collins, A., 53, 389, 401 Collins, D. R., 23 Collins, J. C., 532 Collins, M. E., 336 Collins, N. L., 207, 621 Collins, P. F., 83, 159, 180, 208, 386, 462, 464 Collins, R. L., 515, 588, 593 Collins, W. A., 204 Colwill, R. M., 27 Combs, B., 324 Comings, D. E., 195 Conley, J. J., 156 Conley, M., 27 Connell, D., 40 Connolly, J., 121 Connor, J. A., 42 Connor, T. M., 28 Conrad, D., 20 Conroy, D. E., 220, 222, 227 Consedine, N. S., 354 Constantian, C. A., 206 Constantini, A. F., 352 Conway, M., 451 Cook, E. W., 58 Cook, E. W., III, 56 Cook, M., 371 Cook, W., 620 Cooper, A., 154 Cooper, D. C., 76 Cooper, G., 544 Cooper, J., 513 Cooper, M. L., 360, 615–629 Cooper, P. J., 40 Coopersmith, C., 113 Coopersmith, R., 132 Cooper, T. B., 121 Coplan, R. J., 40 Coppeta, J. S., 136 Corbit, L. H., 28 Cornelius, J., 284 Cornell, D., 532 Cornell, D. P., 346, 440 Cornish, J. L., 82 Corodimas, K. P., 23, 136 Correa, A., 132 Correa, M., 28, 75, 80, 92 Corrigan, B. S., 189 Corr, P. J., 157, 378, 547 Cortina, K. S., 227 Corwin, G., 7–8, 293 Corwyn, R. F., 514

4/16/2008 5:52:25 PM

Author Index

Cosmides, L., 5, 251–270, 275, 277, 282, 284, 348, 368–369, 604–605 Costa, E., 121 Costa, P. T., 153, 160 Costa, V. D., 62 Costigan, K. A., 41 Cothran, D. L., 477 Cotman, C., 130 Courneya, K., 477 Cousins, S. D., 557 Covington, M. V., 5 Cox, A. D., 476 Cox, D., 476 Cox, V. C., 74 Coy, K. C., 471 Coyne, J. C., 608 Cozzarelli, C., 360 Craig, A. D., 313 Craig, W., 9, 351 Craik, F. I. M., 291, 545 Crain, B., 130 Crandall, C. S., 574 Crary, W. G., 508, 511 Crawford, C., 275 Crawford, M., 52 Crenshaw, T., 371 Crepaz, N., 532 Cresswell, W., 173–174, 181 Crews, D., 371 Critchley, H. D., 313 Crites, S., 7 Crites, S. L. Jr., 57, 235 Crocker, A., 90 Crocker, J., 336, 443, 508, 511–512, 530–531, 559, 580, 604 Crombez, G., 290 Cronbach, L. J., 151, 276 Crook, J. H., 279, 284 Crook, S. J., 279, 284 Crowe, E., 238–240, 418, 490, 496–497 Crowne, D., 6 Crowne, D. P., 575 Croyle, R. T., 477 Cruz, M., 154 Cubells, J. F., 195 Cummings, D. E., 94 Cummings, E. M., 40 Cummings, J. L., 406 Cunningham, G. R., 113 Cunningham, M. G., 130 Cunningham, M. J., 113 Curb, D., 197 Cury, F., 226 Cuthbert, B., 7, 9, 522 Cuthbert, B. N., 56–59, 294, 390

D Da Fonseca, D., 226 Dakof, G. A., 588 Dale, K., 223 Daley, M. J., 182 D’Alfonso, A. A. L., 407

RT6019X_C038.indd 637

637

Dalgleish, T., 157, 451 Dalley, J. W., 28–29 Dall, S. R. X., 181 Dally, M. R., 175 Dalrymple-Alford, J. C., 129 Daly, J. A., 607 Daly, M., 256, 267–268, 278, 280 Damasio, A., 18 Damasio, A. R., 290–291, 294, 544 Damasio, H., 314–315, 544 D’Amato, F. R., 134 Danaceau, M. A., 110 Daniels, D., 189 Darby-King, A., 132 Dardou, D., 129 Darley, J., 587–588, 591 Darwin, C., 368, 370, 400, 402 Darwin, C. R., 350 Daterri, D. L., 606 Datiche, F., 129 Daubman, K. A., 236–237 Davalos, M., 39 Davé, P. N., 221 David, A. S., 455 Davidson, K., 94 Davidson, R., 9, 290–291, 353 Davidson, R. J., 9, 35–43, 155, 158, 160–161, 237, 291, 312–313, 345, 369, 371, 385–386, 390, 404–405, 419, 544–547 David, S. P., 62 Davies, D. R., 543 Davis, A., 579 Davis, A. M., 138 Davis, D., 207 Davis, M., 20, 23, 54–55, 58, 60, 133–134 Davis, T. L., 58 Davitz, J. R., 354 Dawes, R. M., 189 Dawkins, R., 368, 380 Dawson, M. E., 58, 547–548 Dayan, P., 99 Day, H. E., 43 Day, J. R., 113 Dean, W., 198 Dearing, M., 6 Dearing, M. F., 52 Dearstyne, T., 6 Debener, S., 39 DeBold, J. F., 112 DeCharms, R., 205, 221–222 Deci, E. L., 217, 222–223, 300, 387, 392, 416–417, 421, 537, 545, 548–549 DeCola, J. P., 23 DeFries, J. C., 190, 193 De Gelder, B., 351 Degenetais, E., 42 De Geus, E. J., 197 De Goede, P., 166 De Haan, E., 407 De Haan, E. H. F., 407 De Houwer, A., 291 De Houwer, J., 291–292, 327 Delaney, M. A., 403

Delespaul, P. A., 121 Delfs, J. M., 26 Delgado, J. M., 94 DelParigi, A., 350 Delton, A. W., 282 Demaree, H. A., 354 Dember, W. N., 224, 236 Dembo, T., 217, 346, 585–586 De Montes, L. G., 481 De Moor, P., 113 Denenberg, V. H., 42 Dennett, D., 254, 374 Denny, M. R., 20 Denzler, M., 237, 240–241 De Oca, B. M., 23 De Oliveira Siqueira, J., 284 De Olmos, J. S., 90 DePascalis, V., 152 Depue, R. A., 38, 83, 159, 180, 207–208, 378, 380, 386, 393, 402–403, 462, 464, 609 Der, G., 514 De Rivera, J., 353 Dermen, D., 240 Derryberry, D., 157, 188, 211, 235–237, 239–240, 243–245, 461–472 Derry, P. A., 508 Descartes, R., 353 Deschamps, S., 139 De Silva, P., 450 Desjardins, C., 114 Desmond, J. E., 312 Detke, M. J., 96 Detweiler, J. B., 477 Deutsch, G., 545, 547 Deutsch, J. A., 74 Deutsch, M., 336 Deutsch, R., 346 Devine, P. G., 299, 335, 408, 571–582 Devlin, M. J., 102 Devos, T., 354 De Vries, G. J., 136–137 De Vries, H., 479 De Vries, N. K., 352 De Waal, F., 277 DeWall, C. N., 608–609 Dhavale, D., 603, 605 DiCara, L., 55 Di Chiara, G., 28, 77, 80–82, 91–92, 97–98 Dichter, G. S., 58 Dick, D. M., 193 Dickerson, S. S., 204, 207 Dickinson, A., 6, 28, 52, 90, 138 Diego, M., 40–41 Diego, M. A., 41 Diener, C., 336 Diener, C. I., 224 Diener, E., 152–153, 155, 160, 203, 336, 415–425, 538, 559, 561 Dienstbier, R. A., 433, 434 Dietvorst, R., 472 DiFrischia, D. S., 94 Digman, J. M., 152, 160 Dijksterhuis, A., 292, 545

4/16/2008 5:52:25 PM

638

Dijkstra, P., 278, 282 Dindo, L., 379 Dingemanse, N. J., 182 Dingemanse, N. L., 166 Diorio, J., 44 DiPietro, J. A., 41 Di Scala, G., 132 Distin, K., 368 Ditto, P. H., 477 Dizadji, D., 298 Doelger, L., 190 Doerr, H. K., 135 Dolan, C. V., 193 Dolan, P., 324 Dolan, R. J., 128, 313–314 Dolcos, F., 500 Dollard, J., 10, 385, 400 Domjan, M., 175 Donaldson, D., 453 Dong, E., 121 Doob, L., 7, 400 Doob, L. W., 290, 293 Dorsa, D., 113 Dorsa, D. M., 113, 138 Dose, J. M., 134 Doss, R., 404 Doss, R. C., 9, 35 Doty, R. L., 128 Dougherty, D. D., 406 Douglas, A. J., 138 Douglas, M., 326 Dovidio, J. F., 292, 298–299, 579 Downey, G., 207, 500, 579, 608 Downhill, J. E., 36, 404, 407 Downs, D. L., 506, 608 Doyere, V., 24 Dragoin, E., 283 Drent, P., 6 Drent, P. J., 166, 174, 182 Drevets, W. C., 81, 90, 208 Dringenberg, H. C., 60 Driscoll, D. M., 441 Duchamp, A., 129 Duchamp-Viret, P., 129 Duckworth, K. L., 294, 298 Duenas, M., 113 Duff, K. J., 448 Duffy, E., 543 Dufresne, M. M., 42–43 Dulawa, S. C., 169, 174, 176, 180 Dumas, F., 354, 597 Dunbar, M., 514 Duncan, G. E., 121 Dunn, E., 110 Dunton, B. C., 293, 574 Durante, K. M., 373 Durbin, C. E., 40 Durkheim, E., 204 Durner, M., 197 Dusseldorp, E., 618 Dutton, K., 467 Dweck, C., 224, 235 Dweck, C. S., 217, 224–225, 227, 229, 346, 565

RT6019X_C038.indd 638

Author Index

Dweck, D. S., 217 Dworkin, L. P., 81 Dykman, B., 451 Dykman, B. M., 511 Dziewiatkowski, J., 130 Dzokoto, V., 422

E Eagly, A. H., 289–291, 352, 479 Easterbrook, J. A., 235–236 Easting, G., 159 Eaves, L., 190 Eaves, L. J., 192, 196 Ebbesen, E. B., 508 Ebert, C., 174 Ebstein, R. P., 176, 195 Eckman, J., 602 Eddington, K. M., 500 Edell, J., 282 Edgley, S. A., 309 Edinger, K. L., 120 Edstrom, G. H., 235 Edwards, A. L., 222 Eelen, P., 290, 292 Egloff, B., 223, 299 Eibl-Eibesfeldt, I., 277–278, 354 Eich, E., 448 Eichenbaum, H., 133 Eid, M., 422 Eisenberg, A. R., 452 Eisenberger, N. I., 156, 207 Eisenberg, N., 406, 471–472 Eiser, C., 324 Eiser, J. R., 245, 323–338 Ekman, P., 35–36, 158, 284, 350, 353–354, 369–370, 373, 402 Ekstrom, R. B., 240, 242 Eley, T., 192 Elias, L. J., 318 Eliot, G., 399 Elizaga, R., 590 Elizalde, G., 93 Elliot, A., 224–225, 269 Elliot, A. J., 3–11, 18, 63, 160, 166, 180, 188, 192, 204, 208, 210, 217–218, 220, 222–229, 235, 274, 326, 344–345, 350–351, 353, 368, 370, 374, 379, 387, 389–390, 392–394, 417–418, 420–422, 424, 432, 440, 462, 470, 478, 489–490, 492, 494, 499, 512–515, 522, 527–528, 533, 535–536, 544, 549, 560, 562–563, 565, 572, 574–575, 578, 585, 588, 601, 603–604, 606, 616, 619 Elliot, E. S., 217, 224–225 Elliot, G. C., 604 Ellis, B. J., 253, 371 Ellsworth, P. C., 408, 608 Ely, T. D., 314 Emerich, D. F., 130 Emerson, M. J., 240 Emery, G., 452

Emery, R., 374, 376 Emler, N., 510 Emmons, R. A., 155, 227, 416–417, 419–420, 499, 538 Endo, Y., 559, 564 English, J. B., 136 Ennis, M., 129 Enters, E. K., 130 Entwisle, D. R., 222 Epley, N., 298 Epping-Jordan, M. P., 98 Epstein, A. N., 94 Epstein, S., 493 Epstrude, K., 592 Erbaugh, T., 37 Erber, R. E., 448, 453–454 Erb, S., 82 Erdelyi, M. H., 448 Erickson, B. H., 595 Erickson, E., 5 Ericson, K. A. J., 62 Erlenmeyer-Kimling, L., 196 Ernst, J. M., 370, 434 Erskine, M. S., 113 Escalona, S. K., 218 Escher, A. D. M. A. C., 455 Eshleman, A., 574 Espana, R. A., 90 Essex, M., 156 Essex, M. J., 196 Estes, W. K., 27 Esteve, M. R., 454 Esteves, F., 317, 537 Estourget, Y., 481 Etgen, A. M., 112 Etheridge, J. B., 454 Etienne, M. A., 38, 239 Evdokas, A., 347, 360 Everhart, D. E., 354 Everitt, B. J., 19, 26–30, 72, 77, 80, 90, 314 Evett, S. R., 578 Eysenck, H., 5 Eysenck, H. J., 151–153, 157, 159, 464, 543 Eysenck, M. W., 152–153, 464, 543 Eysenck, S. B., 159 Eysenck, S. B. J., 159

F Fabbricatore, A. T., 282 Fabes, R. A., 471 Faccidomo, S., 112 Factor, E. M., 136 Fahey, J. L., 207 Fahrbach, S. E., 138 Faig, H. G., 197 Fairbanks, L. A., 167, 169, 174, 180, 182 Falconer, D. S., 189 Falkenstein, E., 112 Falke, R., 455 Fan, J., 192 Fannon, S. A., 112 Fanselow, M., 133

4/16/2008 5:52:25 PM

Author Index

Fanselow, M. S., 20, 23, 60, 129, 346 Fantino, E., 26 Farnham, S. D., 293 Farrar, A., 92 Fazio, R., 7 Fazio, R. H., 245, 290–294, 298–299, 323–338, 441, 526, 573–574 Feagin, J. R., 580 Fearn, M., 406 Feather, N., 561 Feather, N. T., 346, 572, 578 Federenko, I., 197 Federenko, I. S., 197 Feeney, B. C., 207 Feenstra, M. G., 130 Fehr, E., 208 Feigon, S. A., 192 Fein, S., 235 Feldman, S., 207 Feldman, S. I., 608 Feldon, J., 29 Feld, S. C., 223 Felicio, L. F., 136 Felzenberg, E., 113 Fenton, H., 80, 96 Ferguson, E., 478 Ferguson, M. J., 289–301 Fernandez de Molina, A., 55 Fernández-Dols, J. M., 400 Ferreira, A., 113, 137 Ferris, C. F., 138 Ferry, B., 133 Fessler, D. M. T., 351 Festa-Bianchet, M., 174 Festinger, L., 217–218, 442, 508, 515, 585–587, 589, 591, 595, 597, 602 Fetchenhauer, D., 282 Feuring, M., 112 Fidalgo, A. M., 455 Fields, H. L., 20 Field, T., 39–41 Fincham, F. D., 392, 605 Finkenauer, C., 317, 334, 352, 466, 509, 619 Fink, G. R., 313 Finney, L., 476–477 Fiorino, D. F., 70 Firestein, S., 129 Fischbacher, U., 208 Fischer, A. H., 354, 356, 359 Fischer, G. W., 477 Fischhoff, B., 477 Fischoff, B., 324 Fishbach, A., 241, 296–297 Fishbein, M., 223, 625 Fisher, E. B., 159 Fisher, H., 62 Fisher, P., 190 Fisher, W. A., 618 Fish, E. W., 112 Fiske, A. P., 276–277 Fiske, S., 7 Fiske, S. T., 292, 531 Fitzsimmons, J. R., 62, 313

RT6019X_C038.indd 639

639

Fitzsimons, G. M., 296, 392 Flannelly, K. J., 60 Fleeson, W., 155–156 Fleischer, J., 129 Fleischman, A. A., 607 Fleming, A., 136 Fleming, A. S., 135–136, 138–139 Fletcher, M. L., 130 Fliers, E., 138 Flint, J., 197 Flores, C., 83 Foa, E. B., 456 Fockenberg, D., 540 Fodor, J., 252, 279 Foerster, J., 332 Folkes, V, S., 603 Folkman, S., 348, 434 Ford, C. E., 515 Ford, C. S., 113 Ford, G., 514 Fordyce, G., 6 Fordyce, M. W., 155 Forest, K., 403 Forgas, J., 291 Forgas, J. P., 282, 607 Forkman, B., 180 Forlano, P. M., 111 Fornal, C. A., 90 Forster, J., 7, 235–245, 423, 483, 493–494, 497, 499, 532, 540, 563 Forthman, D. L., 93 Fossella, J., 192 Fowler, J. S., 81 Fowles, D. C., 378–379, 386, 389–390, 403, 470–471, 491 Fox, E., 467 Fox, N. A., 35–44, 158, 188, 405, 467 Francis, D., 44 Francis, E. L., 337 Francis, J., 20 Frankel, A., 513 Frankel, C. B., 389 Franken, R., 9 Frank, J. D., 218 Franklin, B., 323 Franklin, K. B., 81 Frankl, V. E., 545, 547 Franz, C. E., 223 Fraser, D, F., 182 Frederick, S., 350 Fredrickson, B. L., 18, 153, 156, 348, 374 Fredrikson, M., 61–62 Freitas, A. L., 423, 494–495, 499–500 Freitas, B. L., 207 French, J. W., 240 Frenkel-Brunswik, E., 228 Fresco, D. M., 380 Freud, S., 4, 72, 219, 385, 490, 536–538, 543, 625 Fridel, Z., 23 Friedman, R., 235, 238, 241, 296–297, 360, 418, 494, 540, 564 Friedman, R. S., 235–245, 332, 423, 482, 495, 497, 532, 575

Friedrich, R. W., 129 Friesen, W. V., 35–36, 158, 284, 354, 369–370, 402 Frijda, N., 7, 293 Frijda, N. H., 56, 160, 282, 293, 346–347, 349–351, 353, 359, 388–389, 400–401, 408, 416, 424 Froming, W. J., 356 Frye, C., 121 Frye, C. A., 109–121 Frye, N. E., 393 Fryer, J. W., 226, 228–229 Fudge, J. L., 90 Fugelstad, P., 483 Fuhrmann, A., 540, 545 Fujita, K., 300, 498 Fulker, D. W., 199 Fung, H., 560 Fung, H. H., 352, 422, 564 Fuxe, K., 91 Fyall, A. M., 99

G Gable, P., 404 Gable, P. A., 399–410 Gable, S. L., 155, 160, 203–213, 374, 392, 418, 423, 490, 492, 499, 575, 601, 606, 618–619 Gabrielidis, C., 284 Gabrieli, J. D., 312 Gabriel, M., 25 Gabriel, R., 256 Gaertner, L., 506, 558 Gaertner, S. L., 292, 298 Gailliot, M. T., 607 Gainetdinov, R. R., 83 Gainotti, G., 36 Galanter, E., 490 Galef, B. G. Jr., 130 Gale, G. D., 20–21, 23 Gallagher, M., 20, 27–28, 129 Gallant, B. Y., 174 Gallistel, C. R., 83 Gallistel, R., 28 Galosi, R., 92 Gandelman, R., 74 Ganellen, R. J., 356 Gangadhar, N., 91 Gangestad, S., 223, 575 Gangestad, S. W., 198, 278, 280, 282–284, 604 Garamoni, G. L., 532 Garcia, J., 93, 283 Garcia, M., 294 García-Montes, J. M., 455 Garcia-Sevilla, L., 6, 174, 178–179 Gardner, W. L., 57, 158–159, 204, 312, 315, 334, 389, 421, 538, 547, 560, 562, 609–610 Garris, P. A., 80 Gartside, I. B., 177 Garver, C. E., 282

4/16/2008 5:52:25 PM

640

Gash, D. M., 177 Gasper, K., 236 Gatz, M., 153 Gawronski, B., 291, 559 Geary, D. C., 278 Gebhardt, W. A., 618, 620 Gee, K. W., 113 Gelb, A., 313 Gelernter, J., 195 Genazzani, A. R., 111 Genestoux, N., 597 George, L. J., 208 Georges, F., 100 Gerard, G., 351 Gerard, H. B., 587 Gergen’s, K. J., 590, 594–595 Gerhardt, G. A., 91 German, T., 256 Gerrard, M., 621 Gervais, R., 129, 133 Gessa, G. L., 96 Geyer, M. A., 174 Ghera, M. M., 43 Ghitza, U. E., 282 Giannopoulos, C., 451 Giardini, V., 26 Giardino, N. D., 129 Gibbons, F. X., 515, 596–597 Gibb, S. J., 129 Gibbs, R. B., 113 Giesler, R. B., 532 Gigerenzer, G., 325, 369 Giladi, E. E., 559 Gilbert, D. T., 336 Gilbert, P., 373, 377, 608 Gillath, O., 207 Gilles, E. E., 132 Gilliam, J. F., 182 Gilliland, K., 378–379 Gilliom, M., 471 Gilmore, J. H., 121 Gingrich, B. S., 138 Gioanni, Y., 42 Girvin, J. P., 313 Gitter, S., 601–611 Giuliano, T. A., 154 Glascher, J., 314 Glaser, D., 311 Glaser, J., 352 Glassman, B., 478 Glassman, N. S., 346 Glatz, A. C., 92 Glazier, B. S., 97 Glickman, S. E., 73 Glick, P., 299 Globisch, J., 58 Glover, G., 282, 312 Glowacki, T., 155 Glowa, J. R., 92 Glowinski, J., 42 Goddard, M., 6 Goddard, M. E., 6 Goethals, G., 587–588, 591 Goffman, E., 443

RT6019X_C038.indd 640

Author Index

Goffman, I., 604 Goldberg, J. P., 371 Goldman, B. M., 530 Goldman, B. N., 530 Goldman-Rakic, P. S., 78, 121 Goldman, S. L., 154 Gold, M. R., 324 Gold, R. S., 620 Goldsmith, H., 290 Goldsmith, H. H., 156, 187–199, 345 Goldstein, D. G., 369 Goldstein, N., 281 Gollwitzer, P. M., 235, 295–296, 345–346, 417, 421–422, 484, 536 Gomez, A., 154 Gomez, C., 129 Gomez, R., 154, 157 Gomita, Y., 83 Gonsalkorale, K., 278 Gonzaga, G. C., 353 Gonzalez, J., 40 Gonzalez-Lima, F., 130 Gonzalez-Mariscal, G., 136 Goodale, M. A., 542–543 Goodwin, G. A., 134 Goosens, K. A., 20, 23 Gordon, S., 392 Goschke, T., 539–541 Gosling, S. D., 161, 165–183 Gosnell, B. A., 99 Gotlib, I. H., 35, 38 Gottesman, I. I., 193, 197 Gottfried, J. A., 128–129, 314 Gottman, J. M., 208, 374, 625 Gould, R., 218, 222, 228, 586 Gould, S. J., 542 Gould, T. D., 197 Govender, 290 Govindan, R., 159 Govorun, O., 292 Grabner, C. P., 80 Grace, A. A., 71 Graham, F., 6 Graham, F. K., 59, 61 Graham, J. M., 114 Graham, M. D., 139 Graham, S. M., 526 Grammer, K., 604 Grandy, D. K., 174 Granjon, L., 129 Grant, D. M., 450 Grant, H., 229, 478, 494–496, 499, 501, 563 Grant-Pillow, H., 479, 495 Grässmann, R., 222, 388 Grassman, R., 419 Gratton, A., 41–42 Gratz, K. L., 453 Grau, J. W., 310 Graybiel, A., 26 Gray, J. A., 38, 157, 159, 161, 204, 206, 326, 352, 354, 378, 386, 389–390, 392, 400, 402, 404, 419, 462, 464, 466, 490–491, 512, 536–537, 616 Gray-Little, B., 514

Graziano, M., 90 Greenberg, B. D., 176 Greenberg, D. A., 197 Greenberg, J., 448, 505–506, 510, 512, 517, 549 Green, E. J., 350 Green, J. D., 542 Green, K. W., 373 Greenstein, Y. J., 79 Greenwald, A. G., 290–294, 307, 508, 558–559 Greenwald, M. K., 56, 58 Greer, C. A., 129 Gregory, M., 543 Greunsven, G., 620 Greve, D., 351 Griffin, L. D., 121 Grill, H. J., 93, 311 Grillon, C., 58 Grimley, D. M., 620 Grimm, J. W., 99 Griskevicius, V., 281–283 Grob, A., 160 Grodsky, A., 153 Groenewegen, H. J., 137 Groothuis, G. G., 174 Grossberg, S., 461, 463, 466 Gross, J. J., 188, 347, 352, 354, 422, 452 Gross, J. N., 471 Groth, G., 277 Grudman, M., 79 Gruenewald, T. L., 207 Gruenfeld, D. H., 277 Gschwendner, T., 291, 559 Gudmundsdottir, B., 450 Gudykunst, W. B., 573 Guerin, S., 282 Guerrero, L. K., 392 Guidolin, D., 91 Guidotti, A., 121 Guilford, J. P., 241 Guldenaar, S. E., 138 Gullickson, G., 313 Gupta, B. S., 537 Gu, Q., 463 Gurewitsch, E. D., 41 Gurney, K., 80 Gur, R. C., 507 Gursky, K., 175 Gurven, M., 257, 264 Guthrie, R., 450 Gutierres, S. E., 278

H Haaga, D. A. F., 360 Haberly, L. B., 130 Haber, S. N., 90–91, 100 Haberstick, B. C., 193 Hachinski, V. C., 313 Hacker, P. M. S., 71 Haddock, G., 454 Hadjikhani, N., 351

4/16/2008 5:52:26 PM

Author Index

Hafer, C. L., 241 Hagemann, D., 37–38, 408 Haidt, J., 282–283, 298, 351 Hailey, B. J., 477 Hajnal, A., 92, 102 Hakoyama, H., 175 Halberstadt, J. B., 522 Hall, G., 28 Hall, J., 27–28 Hall, J. H., 605 Hall, W. S., 299 Hamamura, T., 557–567 Hamann, S. B., 314 Hamburg, M. D., 74 Hamer, D., 176 Hamer, D. H., 176 Hamilton, W. D., 256–257, 259 Hamm, A. O., 56, 58 Hammerstein, P., 257, 259, 264 Hampson, E., 373 Hamrick, N., 207 Hancock, T. D., 514 Handa, R. J., 113 Hane, A. A., 41, 44 Han, J. S., 19, 27 Hannover, B., 531 Hansen, S., 137, 168, 170, 174, 179 Hanson, K. N., 373 Harackiewicz, J. M., 225, 494, 572, 578 Harbaugh, C. R., 138 Harley, C. W., 132–133 Harlow, A., 440 Harlow, L. L., 620 Harman, H. H., 240 Harmon-Jones, C., 313, 399–410 Harmon-Jones, E., 35–38, 313, 399–410, 419, 543–545, 547, 579 Harney, J. P., 117–118 Haroutunian, V., 132 Harrison, D. W., 354 Harrison, J., 450 Harrison, N. L., 112 Harro, J., 72, 76, 83 Hart, C. W., 284 Harter, S., 421, 514 Harthon, C., 137 Hartlage, S., 451 Hartmann, E., 455 Hart, P. J. B., 176 Harvey, A. G., 450, 452–453 Harvey, O. H., 602 Harvey, P. H., 280 Haselton, M. G., 277, 284, 604 Hashash, A., 113 Hasselmo, M. E., 130 Hassin, R., 296 Hass, R. G., 292 Hastings, L., 70 Hatch, M. C., 41 Hatfield, E., 277, 282, 618, 625 Hatfield, T., 27 Hawilo, M. E., 311 Hawkins, M., 41 Hawkins, R., 53

RT6019X_C038.indd 641

641

Hawkley, L. C., 204, 207 Hawk, L. W., 58 Hawlena, D., 176 Hayar, A., 129 Hay, D. A., 192 Hayden, E. P., 40 Hayes, S. C., 456 Hay, J., 76 Haynes, N. B., 114 Haynes, O. M., 374 Ha, Y.-W., 590 Hazan, C., 278 Haze, R. A., 472 Headey, B., 155 Healy, B., 377 Healy, S., 206 Hearst, E., 26 Heath, A. C., 39 Heatherton, T. F., 352, 559, 606–607 Heath, I., 377 Heath, R. G., 69–70 Hebb, D. O., 4, 166–167, 172, 174 Heckhausen, H., 221–223, 235, 421, 538 Heerwagen, J., 6 Heerwagen, J. H., 604 Heidegger, M., 549 Heider, F., 5, 346, 352 Heien, M. L. A. V., 80 Heimer, L., 90 Heimpel, S. A., 513, 517, 619 Heine, S. J., 284, 507, 557–567 Heinrichs, M., 208 Heiser, N. A., 376 Hejmadi, A., 353 Helle, P., 546 Heller, W., 35, 38, 239, 244 Hellhammer, D. H., 110, 197 Helm, K. A., 102 Helmstetter, F, J., 23 Helson, H., 337, 350 Hembree, R., 572, 578 Hemenover, S. H., 155 Henderson, H. A., 35, 39, 43 Henderson, M., 300 Hennessy, M. B., 135 Henriques, J. B., 37–38, 158, 313, 404 Herbert, C., 318 Herman, J. P., 169, 177, 179 Hermans, D., 290 Hermans, E., 403, 407 Hermans, W., 222 Hernandez, L., 91–92, 96–97, 99 Hernandez-Reif, M., 40–41 Hershey, K. L., 190, 470 Hersh, L. B., 113 Hertel, A., 475 Hertel, A. W., 417 Hertenstein, M. J., 283 Herz, A., 101 Herzberg, F., 8 Herz, L. R., 369 Herzog, H. A. Jr., 6 Hetherington, E. M., 191

Hettema, J. M., 192 Heuer, F., 235 Hewig, J., 38, 408 Hewitt, J, K., 193, 199 Hewstone, M., 559, 578 Heyman, R. E., 208 Heyns, R. W., 205 Heyns, W., 113 Hicklin, S. K., 592 Hicks, B. M., 193 Higgins, E., 7 Higgins, E. T., 5, 206, 213, 235, 238–240, 245, 289, 292, 298, 326, 332, 344, 360, 386, 389, 417–418, 423, 478–483, 489–501, 512, 535, 538, 540–541, 561–564, 566, 575, 585, 590 Higgins, T. E., 423, 521, 532, 575 Higuchi, T., 138 Hill, C. A., 618–619 Hill, C. R., 129 Hill, K., 257, 264 Hill, S. E., 372 Hilton, S. C., 41 Himmelfarb, S., 289 Hiroto, D. W., 541 Hirt, E. R., 237 Hitchcock, J., 23 Hitt, S. K., 39 Hjelmstad, G. O., 91 Hmaidan, Y., 96 Hodgson, R. J., 275 Ho, D. Y., 558 Hoebel, B. G., 89–102, 312 Hofer, J., 222 Hofer, M. A., 131 Hoffman, J. M., 314 Hoffman, L. W., 190 Hoffman, P. J., 595 Hoffman, S., 41 Hofmann, W., 291, 559 Hogan, M. E., 523–524 Holland, P. C., 20, 26–28 Hollerman, J. R., 92, 469 Holloway, J., 454 Holmes, A., 177 Holmes, J. G., 608 Hólmsteinsson, H. E., 451 Holmstrom, E., 155 Holsboer, F., 112 Ho, L. T., 197 Holt, E. B., 219 Holt-Lunstad, J., 204 Honda, K., 113 Hong, Y., 224 Honig, A., 455 Hood, W. R., 602 Hooks, M. S., 92 Hopkins, J., 40 Hoppe, F., 218, 586 Hopwood, M. J., 36 Horney, K., 4 Hornschuh, G., 135 Horvitz, J. C., 79, 81

4/16/2008 5:52:26 PM

642

Hoshino-Browne, E., 557 Hospers, H., 479 House, J. S., 204, 207 Houston, A. I., 181 Houts, R. M., 208 Hoving, K. L., 352 Hovland, C. I., 10 Howard, A., 292 Howell, A., 451 Howes, S. R., 28 Hrdy, S. H., 277–278 Hsee, C. K., 387, 562 Hsiung, C. A., 197 Huber, R., 71, 81 Hudziak, J. J., 193 Huguet, P., 597 Hull, C., 4, 10 Hull, C. L., 21, 312, 344 Hull, E. M., 114 Hunter, B. A., 299 Hunter, G. A., 92 Hunter, S., 443 Hunter, S. B., 436, 439, 442–444 Huntingford, F. A., 257, 259 Hunt, K., 514 Hunt, P. S., 130 Hunt, W., 58 Hurd, Y. L., 97 Hurst, A. L., 217–229 Hurtado, M., 257 Huston, T. L., 208 Hutton, D. G., 512, 608 Hyland, B. I., 76 Hyman, S. E., 81 Hymes, C., 7, 239, 418, 490

I Iacono, W., 609 Iacono, W. G., 38, 192, 378, 389, 402–403 Iancono, W. G., 193 Iannoti, R., 476–477 Iannotti, R. J., 40 Ickes, W., 392 Ide, E., 559 Idson, L., 7 Idson, L. C., 238, 423, 493–494, 561 Igarashi, K. M., 129 Iguchi, K., 175 Ikemoto, S., 26, 28–29, 69, 76–77, 79–81, 84, 97 Illingworth, K. S., 522 Imbrie, M., 155 Imperato, A., 91, 97 Impett, E., 210 Impett, E. A., 211, 618–619 Ingjaldsson, J. T., 453 Ingram, R. E., 373, 452, 607 Innes-Ker, A. H., 522 Insel, T. R., 135, 138–139, 207–208, 371 Inz, J., 452 Irizarry, R. A., 41 Irwin, J. R., 353

RT6019X_C038.indd 642

Author Index

Irwin, M. R., 207 Irwin, W., 43, 313 Isen, A. M., 236–237, 347, 469 Islam, M. R., 578 Isaacson, R., 205 Iswari, S., 113 Ito, R., 28 Ito, T., 79 Ito, T. A., 354 Ivkovich, D., 130 Ivy, G., 129 Iwata, J., 19, 23, 55 Iwata, N., 390 Izard, C. E., 347, 350, 353–354, 367–381, 400, 403 Izquierdo, A., 177 Izquierdo, I., 90

J Jablonka, E., 374 Jaccard, J., 618 Jackendoff, R., 254 Jackson, D. C., 35, 37, 160 Jackson, D. N., 222 Jackson, J. H., 308 Jackson, J. R., 293 Jacobs, B. L., 90 Jacobs, G. D., 404 Jacobs, W. J., 546 Jagalska-Majewska, H., 130 Jalfre, M., 96 James, W., 4, 8, 53, 449, 512–513 James, W. J., 56 Jamison, K. R., 377 Janeck, A. S., 450–451 Janet, P., 449 Janoff-Bulman, R., 336, 418 Jarcho, J. M., 207 Jeffery, R. W., 417, 483 Jemmott, J. B., 620 Jemmott, L. S., 620 Jensen, K., 96 Jetten, J., 454, 578 Jirikowski, G. F., 371 John, O. P., 283, 317, 354, 532 Johnsen, B. H., 453 Johnson, B. A., 132 Johnson, B. T., 289, 293 Johnson, C., 292 Johnson, D. A., 113 Johnson, D. J., 608 Johnson, E., 469 Johnson, E. J., 605 Johnson, J. C., 181 Johnson, J. D., 580 Johnson-Laird, P. N., 353, 424 Johnson, M., 80 Johnson, M. C., 237 Johnson, M. M. S., 236 Johnson, R. A., 372 Johnson, R. J., 477 Johnson, S. L., 380, 390 Johnstone, K. A., 454

Johnstone, T., 350, 357 Joh, T. H., 110 Joireman, J., 157 Jones, E. E., 604 Jones, A. C., 165–183 Jones, D. L., 90 Jones, E. E., 292, 513, 587 Jones, L., 477 Jones, N. A., 39, 41, 158 Jones, S., 589 Jordan, C. H., 293 Jordan, V. C., 112 Jorgensen, R. S., 35 Jose, P. E., 351, 360 Jost, J. T., 444 Jostmann, N., 540 Jostmann, N. B., 540, 545 Joy, V., 602 Judd, C. M., 289, 293 Jung, C., 4 Junghofer, M., 318 Jung-Testas, I., 111 Justice, J. B. Jr., 80, 96

K Kaba, H., 132, 138 Kaczynski, K. J., 393 Kadohisa, M., 128, 133 Kadokawa, T., 79 Kagan, J., 6, 39, 371, 374, 376 Kahneman, D., 238, 328, 332, 352, 416, 466, 476, 498 Kahn, J. H., 450 Kaiser, S., 135 Kajantie, E., 110 Kakolewski, J. W., 74 Kalin, N. H., 35, 41, 197 Kalivas, P. W., 28–30, 81–84, 92 Kallin, N. H., 160 Kandel, E. R., 291 Kaner, H. C., 130 Kaplan, H., 264 Kaplan, H. S., 280 Kaplan, J. M., 93 Kapp, B. S., 23, 60 Kapur, S., 72, 81 Karasawa, M., 559 Karavolas, H. J., 113 Kardes, F., 7 Kardes, F. R., 290, 526 Kardum, I., 154 Karney, B. R., 393 Karnup, S., 129 Kaschel, R., 222, 539–540, 548 Kasimatis, M., 155 Kasser, T., 548 Katkin, E. S., 223 Katulak, N., 478 Katz, I., 292 Kauer, J. S., 129 Kaufman, M., 282 Kawakami, K., 292, 298 Kazdin, A. E., 376

4/16/2008 5:52:26 PM

Author Index

Kazén, M., 235, 243–244, 537, 539–541, 544, 549 Kazlauckas, V., 166–167, 173 Keay, K. A., 462 Kedem, P., 237 Keefe, K. A., 94 Keefe, R. C., 277, 284 Keenan, D. M., 110 Keenan, J. P., 545 Keener, A. D., 35, 405 Kegeles, L. S., 121 Kehoe, P., 134 Kehr, H. M., 222 Kehr, J., 97 Keil, A., 57 Keir, R., 371 Keller, M., 134, 137 Kelley, A. E., 26, 71, 77, 90, 97, 99–101 Kelley, H. H., 280, 605–606 Kelly, A. E., 450 Kelly, K. M., 475, 477 Kelsey, R. M., 434, 438 Kelsoe, J. R., 194 Keltner, D., 277, 282–284, 351, 353–354, 356, 403 Kemble, E. D., 134 Kemeny, M. E., 204, 207 Kendler, K. S., 192, 198 Kendrick, K. M., 129, 136 Kenny, D. A., 532, 620 Kenrick, D. T., 273–285, 606 Kensinger, E. A., 314 Keough, K., 477 Kerker, E., 138 Kernis, N. H., 440, 513, 530 Kessler, D., 618 Kessler, R. C., 373 Ketelaar, T., 153–154, 616 Ketter, T. A., 377 Keverne, E. B., 132, 138 Kevlyn, S. B., 523–524 Khouri, H., 207, 500 Kibler, J., 370, 434 Kidd, J. R., 195 Kidd, K. K., 195 Kiecolt-Glaser, J. K., 203, 207 Kieffer, B. L., 134 Kiene, S. M., 477–478 Kiersted, G., 298 Kiesler, S. B., 605 Kihlstrom, J. F., 352, 490, 522–523 Killcross, S., 27–28 Kilner, J. M., 314 Kilts, C. D., 314 Kim, J. H., 130 Kim, J. J., 19 Kim, S., 35 Kimura, D., 110 Kim, Y., 421, 560 Kingdon, D. G., 455 King, L. A., 154 Kinney, L., 37, 404 Kinsbourne, M., 313 Kinsley, C. H., 138 Kirby, L. D., 347, 351, 359

RT6019X_C038.indd 643

643

Kircher, T. T. J., 545, 547 Kirkpatrick, L. A., 253 Kirschbaum, C., 110, 197 Kirsch, I., 360 Kirson, D., 53, 352, 401 Kissler, J., 318 Kitayama, S., 422, 507, 556–559 Kiyatkin, E. A., 74 Klar, Y., 559 Klasmeyer, G., 350 Klauer, K. C., 290, 293 Klayman, J., 590 Kleck, R. E., 403, 443 Klein, A. A., 448, 453 Klein, D. A., 102 Klein, D. N., 40 Kleinginna, A., 344–345 Kleinginna, P. Jr., 344–345 Kleinman, B. M., 393–394 Klein, S., 256 Klein, S. B., 346, 451 Klem, A., 494 Klinger, E., 203, 417 Klinger, M. R., 290, 293 Kling, K. C., 524, 537, 545, 547 Klos, K. L., 197 Klotz, M. L., 336 Knafo, S., 129 Knuston, B., 77 Knutson, B., 76, 81–82, 282, 352, 422, 454, 564 Kobak, R., 346 Kobayashi, C., 558–559 Kochanska, G., 40, 470–471 Koch, E. J., 529 Koch, K., 294 Koch, M., 313 Kocsis, B., 79 Koehler, E., 138 Koelling, R. A., 283 Koenig, H., 111 Koenis, S., 515 Koestner, R., 221–222, 538 Kolakowska, L., 93 Kolb, B., 91, 130 Konner, M., 371, 376–377 Konorski, J., 6, 52, 385 Koob, G. F., 81, 96, 98–99, 101, 208 Koo, J. W., 19, 23 Koole, S. K., 292 Koole, S. L., 535–549 Koolhaas, J. M., 174 Koomen, W., 590–592, 597 Kosfeld, M., 208 Kosloff, R. A., 96–97 Koven, N. S., 239 Kowai-Bell, N., 443 Kowianski, P., 130 Kow, L. M., 113 Kozak, M., 455 Kraemer, P. J., 134 Kraepelin, E., 380 Kral, P., 283 Kratl, M., 157 Krause, J., 176

Krause, S., 206 Krauss, S. P., 386 Krebs, E. G., 113 Kremen, I., 53 Kreuter, M. K., 478 Kreuter, M. W., 479 Krishnan, K. R. R., 500 Kristjánsson, K., 352 Kroes, R. A., 76 Krohne, H. W., 223 Krones, J. M., 606 Krosnick, J. A., 289, 294 Krueger, J. I., 507 Krueger, R. F., 193 Kruglanski, A. W., 235, 296–297 Kruk, Z. L., 91 Krull, D. S., 440 Ksionzky, S., 205 Ksir, C., 96 Kubos, K. L., 36 Kubovy, M., 416 Kucharski, D., 132 Kudielka, B. M., 110 Kuhilan, D. M., 157 Kuhl, J., 7, 222, 235, 243–244, 535–549 Kuhn, C., 40 Kuiper, N. A., 508 Kuipers, P., 401 Kukla, A., 217, 224 Kunda, Z., 235, 591, 594–595 Kuppens, P., 403 Kupper, N., 197 Kurman, J., 558 Kurumaji, A., 121 Kurzban, R., 208, 278–279, 604–605 Kuyper, H., 515, 597 Kuyper, L., 618, 620 Kwan, V. S. Y., 532

L Laakso, A., 83 LaBar, K. S., 313–314 Laberg, J. C., 453 Lacey, E. H., 120 Lagerspetz, K. M. J., 402 Laham, S. M., 278 Lai, M., 96 Lalor, K. M., 477 Lambert, A. J., 298 Lamb, M. J., 374 Lamoreaux, R. R., 21 Lander, E. S., 194 Landers, M., 131 Landgraf, R., 138 Landis, C., 58 Landis, K. R., 204, 207 Lane, M. V., 136 Lane, R., 90 Lane, R. D., 61, 313, 453 Langer, E. J., 335 Lang, P., 5–7, 9–10, 351, 522 Lang, P. J., 51–63, 134, 293–294, 298, 313, 390, 399, 419, 490, 537–538

4/16/2008 5:52:27 PM

644

Lansing, J. B., 205 Larsen, J. T., 188, 192, 308, 315, 352, 354 Larsen, R. J., 18, 151–161, 174, 390, 420, 616 Larson, C., 41 Larue-Achagiotis, C., 93 Laruelle, M., 121 Lasko, N. B., 369 Lason, W., 100 Lassegard, M., 515 Latane, B., 588, 602 Latham, G. P., 300 Latimer, A., 475–484 Latimer, A. E., 478, 482 Lauer, J., 225 Laurenceau, J.-P., 385–394 Lauriola, M., 417 Lauver, D., 477 Lavenex, P., 313 Lawrence, A. D., 313, 472 Lawrence, D. H., 595 Lawrence, J. W., 387–388 Lawton, M. P., 602 Laycock, J. F., 177 Lazarus, R., 7 Lazarus, R. S., 282, 293, 346–348, 351, 353, 356, 358–359, 368, 401, 409, 434 Le, A. N., 182 Leary, M. R., 204, 297, 392, 506, 510–511, 517, 575, 601–609 LeBlanc, M., 174 Lecci, L., 580 LeDoux, J., 7, 133, 152, 291, 294, 298, 313, 369 LeDoux, J. E., 17–30, 43, 55, 314, 348, 369, 438, 463 Lee, A., 136 Lee, A. Y., 421, 478, 560, 562–564, 566 Lee-Chai, A., 296 Lee, F., 91 Lee, G. P., 313 Lee, K., 155 Leeper, R. W., 347 Lee, S., 132 Lees, J. L., 543 Lee, Y. T., 563 Legault, L., 92 Leggett, E. L., 224–225, 565 Legrand, L. N., 192 Le, H., 291, 559 Lehman, D., 336 Lehman, D. R., 507, 557–559, 561, 563 Lehrman, D. S., 73 Leibold, J. M., 298 Leibowitz, S. F., 90, 94, 99 Leith, K. P., 360 Leitten, C. L., 434 Le Magnen, J., 93 Lemery-Chalfant, K., 187–199 Lemery, K. S., 188, 192 Le Moal, M., 81, 99, 101 Le Moine, C., 100 Lemon, C., 133

RT6019X_C038.indd 644

Author Index

Lenard, L., 92, 102 Lenzenweger, M. F., 380 Lenz, P., 182 Leon, M., 130–133 Leppmann, P. K., 421 Lerman, C., 477 Lerner, J. S., 354, 403 Lerner, M. J., 440 Lesch, K. P., 195 Lesnock, J., 91 Lester, L. S., 346 Leung, C., 557, 559 Levenson, R. W., 351 Levine, G. M., 237 Levine, L. J., 401 Levine, S., 42–43, 129, 134 Levine, T., 618 Levin, I. P., 417 Levin, S., 573, 580 Levinson, R. A., 618 Levis, D. J., 21 Levita, L., 29 Levitt, A., 615–629 Lev, S., 157 Levy, B. R., 299 Levy, F., 132, 136–138, 192 Levy, J., 544–545 Lewicki, P., 346 Lewin, K., 3–4, 7, 10, 204, 217–219, 223, 228, 293–295, 346, 490, 493, 543, 547, 585–586 Lewis, M., 400, 402 Li, A. B., 134 Liang, C., 560 Liang, K. C., 25 Liberles, S. D., 129 Liberman, A., 352 Liberman, A. M., 221 Liberman, N., 235, 238, 241, 298, 300, 423, 563 Libero, D. Z., 374 Liberzon, I., 369 Lichtenstein, S., 324 Lichtman, R., 588 Lichtman, R. R., 515 Lickel, B., 443–444 Lieberman, D., 251–270, 275, 281 Lieberman, J. A., 121 Lieberman, M. D., 156, 207 Liedtke, W., 350 Li, H., 58 Limke, A., 523, 526 Lindberg, J., 176 Lindburg, D. G., 169, 172, 174, 182 Lindsey, S., 291 Lindsley, D., 344 Linford, N., 113 Linkowski, P., 197 Lin, M., 471 Li, N. P., 276–279, 282 Linsenmeier, J. A., 282 Linster, C., 130 Linville, P. W., 477, 524, 529, 537, 545, 547

Lin, Y.-G., 205 Lipp, O. V., 58 Lishman, W. A., 156 Litaudon, P., 129 Little, B. R., 417, 419 Littlejohn, R. P., 178 Litwin, G. H., 221, 572, 578 Liu, D., 44 Liu, T. J., 290 Livingston, R. W., 579–580 Li, Y., 91 Locke, E. A., 300 Locke, V., 448 Lockwood, P., 561, 588, 590–591, 594–596 Loddo, P., 80 Loehlin, J. C., 374 Loewenstein, G., 301, 350 Lofberg, L., 137 Logan, G. D., 292 Loh, H. H., 98 Long, K. A., 99 Lonigan, C. J., 472 Lonstein, J. S., 136–137 Lopes da Silva, F. H., 137 López, P., 176 Lord, C. G., 606 Lord, K. A., 590 Lorenz, K., 73 LoSchiavo, F. M., 596 Losco, J., 493 Louie, J. Y., 564 Lovibond, P. F., 27 Lowell, E., 10 Lowell, E. L., 217, 544 Low, M. J., 174 Luca, M. A., 92 Lucas, R. E., 155, 160, 416, 419–420 Luce, C. L., 277, 280 Lucki, I., 96 Luczynska, A., 130 Luebbert, J. F., 403 Luebke, C., 135–136 Lueck, L., 406 Luhtanen, R., 559 Lukon, J. L., 471 Lundqvist, D., 317, 537 Luu, P., 235, 472 Lykken, D., 153 Lynch, G., 129–130 Lynch, K. G., 91 Lyons, D., 6 Lyons, D. M., 42–44 Lyons-Ruth, D., 40

M MacDonald, G., 608 MacDonald, K., 6, 544 MacGregor, J. I., 112 Machin, G., 190 Maciejewska, B., 130 MacKay, D. M., 386

4/16/2008 5:52:27 PM

Author Index

Mackie, D. M., 354 Mackiewicz, K. L., 313 Mackintosh, N. J., 52 MacLean, P. D., 308, 311 MacLeaod, C., 211 MacLeod, C., 157, 211, 467 Macrae, C. N., 110, 403, 454, 578 Madsen, K. B., 344 Maehr, M. L., 224, 227 Maestripieri, D., 373 Magai, C., 354 Maggi, A., 113 Maglinao, C. D., 134 Magnusson, D., 228 Mahone, C. H., 572, 578 Maier, G. W., 222, 419 Maier, S., 6 Mainen, Z. F., 129 Main, K. J., 573 Majewska, M. D., 112 Majidishad, P., 23 Major, B., 360, 442–443, 508, 591, 595, 604 Major, B. N., 442 Malanos, A. B., 155 Maldonado, R., 98 Malenka, R. C., 81 Malinow, R., 19 Malloy, P., 406 Malone, R. P., 403 Maloney, R. E. Jr., 91 Malphurs, J. E., 40 Mandel, N., 562 Mandler, G., 53, 217 Mandler, J. M., 53 Maner, J. K., 281–282, 607–610 Mangan, G., 20 Manis, M., 591–592 Mann, J., 292 Mann, P. E., 136, 138 Mann, T., 475, 478, 482 Mann, T. L., 423 Manstead, A. S. R., 401 Mapes, R., 575, 588 Mapes, R. R., 210, 374, 392, 418, 499, 514–515, 601, 619 Marcel, A. J., 547 March, J. G., 328 Maren, S., 20, 23–25 Margraf, J., 452 Mark, G. P., 92–95, 97–99, 102, 312 Markman, A. B., 241, 292 Markman, K., 590 Markou, A., 98 Markowitsch, H. J., 21, 25, 314 Markowitz, H., 498 Markowitz, T. M., 171, 175, 180–181 Markus, H., 386, 523 Markus, H. R., 422, 507, 557, 559, 566 Marlowe, D., 575 Marr, D., 254 Marshall, A. L., 478 Marshall, H. R., 4 Marshall, J. R., 38

RT6019X_C038.indd 645

645

Marshall, P. J., 43 Marshall, T. C., 561 Marshall, T. R., 39 Marsh, H. W., 514 Marsh, K. L., 293 Martel, F. L., 43 Martin, C., 133 Martin, C. D., 477 Martindale, C., 236, 241 Martín, J., 176 Martin, L., 289–291 Martin, L. L., 237, 244, 346, 542 Martin, M., 156 Martin, N., 190, 193 Martino, S. C., 477 Martin, R., 515, 587–590 Marts, S. A., 112 Marx, C. E., 121 Mascagni, F., 23 Masedo, A. I., 454 Mashek, D. J., 62 Masicampo, E. J., 505–517 Maslow, A., 5, 352 Maslow, A. H., 206, 602 Mason, G. A., 138 Mason, J. W., 20 Mason, W. A., 313 Massar, K., 278 Masterson, F. A., 52 Masuda, T., 559 Matecka, D., 92 Mather, J., 6 Mather, J. A., 167, 174, 178–179 Mather, M., 314 Mathews, A., 157, 211, 374, 452, 467, 472 Matias, R., 40 Matlin, M. W., 466 Matsubara, N., 175 Matsumoto, H., 557 Matthews, A., 607 Matthews, G., 157, 378–379, 461, 543 Mattson, B. J., 136 Matzner, W. T., 208 Maxwell, J. S., 313 May, D., 500 Mayer, A. D., 137 Mayer, J. D., 154 Maynard, S. J., 264 McAdams, D. P., 206, 617 McAllister, D. E., 21 McAllister, W. R., 21 McArdle, J. J., 190 McArthur, C., 221 McBride, T., 59 McBride, W. J., 81, 97 McCann, J., 132 McCarthy, D., 477 McCarthy, M. M., 113, 138 McCaul, K. D., 477 McClearn, G. E., 190 McClelland, D., 10 McClelland, D. C., 205, 217, 220–222, 227–228, 536–538, 544

McClelland, J., 331 McClintock, M. K., 308 McClure, S. M., 99 McConahay, J., 292 McConahay, J. B., 299 McConnell, A. R., 298, 451 McCormack, S., 90 McCormick, C. M., 113 McCrae, R. R., 152–153, 160 McDonald, A., 23 McDonald, A. J., 23 McDonald, H. E., 237 McDonald, R. J., 129 McDonel, E. C., 290 McEwen, B. B., 138 McEwen, B. S., 44, 112 McFall, B. A., 41 McFarland, N. R., 83, 90 McFarlin, D. B., 440, 512 McGaugh, J. L., 133–134, 282, 314 McGeer, E. G., 92 McGeer, P. L., 92 McGhee, D. E., 290 McGraw, A. P., 315 McGregor, H. A., 220, 226–227, 235, 499, 544 McGue, M., 192–193 McGuffin, P., 190, 193 McGuiness, D., 543 McGuire, S., 191 McGuire, W. J., 289 McKeachie, W. J., 205 McKenna, C., 208 McLean, J. H., 132–133 McLeod, M., 112 McMahon, P. D., 523–524, 528 McMahon, S. R., 454 McManis, M. H., 39, 41 McMillan, P. J., 113 McMullen, M., 590 McMullen, N. M., 590 McNally, R. J., 450 McNamara, J. M., 181 McNaughton, N., 352, 354, 378, 462, 547 Meade, J. R., 117 Meaney, M. J., 42, 44 Means, A. R., 112–113 Meddle, S. L., 138 Mednick, S. A., 236, 241 Meehl, P., 151 Mega, M. S., 406 Mehrabian, A., 53, 205, 353 Mehta, P. H., 161 Meijer, Z., 564 Meile, M. J., 93 Meiniger, C., 545, 547 Meir, J., 452 Melcangi, R. C., 111 Mellers, B. A., 315 Mellon, S. H., 121 Mellott, D. S., 293 Melton, R. J., 237 Mendelson, M., 37

4/16/2008 5:52:27 PM

646

Mendes, W. B., 432, 434, 438, 441–444 Mendoza-Denton, R., 579–580 Menzel, P., 324 Merchenthaler, I., 136 Merckelbach, H., 451 Merrifield, P. R., 241 Mertesacker, B., 40 Mertz, E., 236 Mesquita, B., 352 Messaoudi, B., 129, 133 Messner, C., 292 Mestas, M., 229 Metcalfe, J., 471 Mettke-Hofmann, C., 167, 173–174, 178–179, 182 Meyer, B., 390 Meyer, D. E., 292 Meyer, E. M., 113 Meyerowitz, B. E., 476–477 Miao, F., 564 Micco, D. J., 311 Michaelis, B., 207, 500 Miczek, K. A., 82, 112 Middeldorp, C. M., 193 Mifsud, J. C., 97 Migliaccio, A., 113 Mikulincer, M., 207, 236–237, 403 Milberg, S., 608 Milholland, J., 205 Millar, J., 91 Millar, K., 477 Millar, M., 477 Miller, G., 368, 371–373, 375, 378 Miller, G. A., 38, 490 Miller, J. S., 132 Miller, L. C., 223 Miller, L. M., 450 Miller, N., 4, 7, 10, 400 Miller, N. E., 10, 21, 94, 204–205, 239, 309, 317, 385, 490–491, 493 Miller, P. A., 406 Miller, P. J., 560 Miller, R., 76 Miller, S., 607 Millstein, R. A., 177 Milne, A. B., 110, 454, 578 Milner, A. D., 244, 542 Milner, P., 69, 94 Milroy, R., 452 Mineka, S., 283, 371 Mingote, S. M., 28, 92 Minor, B. G., 137 Miranda, J., 452 Mirenowicz, J., 28 Mischel, W., 332, 471, 508, 511 Mistschenka, M. N., 354 Miura, Y., 79 Miyake, A., 240 Moberg, G., 6 Mock, T., 37 Moeller, G. H., 221 Moeller, J. R., 279 Moerk, K. C., 40 Moffat, S. D., 138

RT6019X_C038.indd 646

Author Index

Moffitt, T. E., 196 Mogenson, G. J., 26–27, 90 Mogg, K., 374, 424 Mohn, A. R., 83 Mohr, S., 313, 406 Moise, N., 92 Moita, M. A., 19 Molden, D. C., 423, 494 Moles, A., 134 Molina, A., 55 Molina, J. C., 132 Mollaghan, D. M., 176 Moller, A., 226 Moller, A. C., 226 Moltschaniwskyj, N. A., 168, 170, 174, 176 Monroe, Y. L., 138 Montague, P. R., 99 Monteil, J. M., 597 Monteith, M. J., 574, 579–580 Monti, P. M., 453 Moore, C. C., 353 Moore, S., 594 Moors, A., 291 Moos, R. H., 204 Morgan, C. D., 205, 220 Morgan, C. T., 28 Morgan, H. J., 347 Morgan, M. J., 604 Moriceau, S., 129, 131–135 Mori, K., 129 Morledge, P., 130 Mormède, P., 169, 174, 176, 179 Morokoff, P. J., 620 Morrell, J. I., 136, 138 Morris, M. W., 561 Morrison, A. P., 454–455 Morrison, D. M., 620 Morrison, H. W., 222 Morrison, S. F., 23 Morris, P. L., 36 Morris, W. L., 454 Morrone-Strupinksy, J. V., 207, 393 Morrow, A. L., 121 Morrow, G. D., 608 Morsella, E., 297 Morse, S., 590, 594–595 Mortensen, C., 281 Morton, B. E., 244 Morton, G. J., 94 Morys, J., 130 Moseley, M. E., 42 Moskal, J., 67–84 Moskal, J. R., 76 Moskowitz, A., 121 Moskowitz, G. B., 235 Mota-Ortiz, S. R., 136 Moulder, B., 58 Moulton, R. W., 221 Mouly, A. M., 129 Mowad, L., 478 Mowrer, O., 5, 7, 213, 400, 564 Mowrer, O. H., 21, 293, 400, 490–492 Moyer, K. E., 402

Mücke, D., 299 Mueller, A., 281 Mueller, C., 235 Mugridge, C., 436 Mullen, B., 336 Muller, J., 23 Mullin, L. I., 373 Munafo, M. R., 197 Muramoto, Y., 558 Muris, P., 451, 472 Murphy, D. D., 113 Murphy, D. L., 176 Murphy, F. C., 313 Murphy, J. M., 81, 97 Murphy, R., 223 Murphy, S., 7 Murphy, S. T., 290 Murray, H., 4, 219, 344, 347 Murray, H. A., 205, 219–220, 228–229 Murray, H. H., 205 Murray, H. M., 220 Murray, K. T., 471 Murray, L., 40 Murray, R., 190 Murray, S. L., 608 Murray, T., 223 Murry, E., 403 Muschamp, J. W., 114 Musch, J., 290, 293 Mussweiler, T., 590–592, 597 Mutschler, N. H., 82 Myers, E., 39 Myers, J. M., 192 Myers, K. M., 20, 133 Myers, R. E., 476 Myin-Germeys, I., 121

N Nadder, T. S., 193 Nadel, L., 538, 546 Nader, K., 23, 25 Nagai, Y., 129 Nagamine, M., 197 Nagpal, M., 537 Nahemov, L., 602 Nair, H. P., 130 Najmi, S., 447–456 Nakahara, D., 83 Nakamura, M., 28, 81 Nakamura, S., 133 Nakanishi, S., 129 Naliboff, B. D., 207 Narang, N., 100 Nasr, F., 133 Naumann, E., 37–38, 408 Navon, D., 240 Nawrocki, T., 40 Nayani, T. H., 455 Neale, M. C., 189–190, 192 Nealey-Moore, J. B., 204 Necowitz, L. B., 153 Needham, L., 99

4/16/2008 5:52:27 PM

Author Index

Neel, J., 258 Neel, J. V., 258 Neely, J. H., 236, 242, 292 Neill, D. B., 80, 96 Nelson, E., 139, 207 Nelson, E. E., 134 Nelson, R., 110, 113 Nelson, T. E., 591 Nelson, T. F., 592 Nepps, P., 203 Neri, G., 91 Nestler, E. J., 77, 81, 83, 101 Nettle, D., 181 Neuberg, S. L., 211, 279, 282, 606 Neumann, I., 138 Neumann, I. D., 138 Neumann, R., 241, 243, 540 Newman, J. P., 464, 467 Newman, L., 347 Newman, L. S., 448 Newsom, J. T., 223 Nezlek, J., 604 Nezlek, J. B., 155 Nicastle, L. D., 277, 282 Nicholls, J., 224 Nicholls, J. G., 224–225 Nichols, K. E., 43, 471 Nichols, N., 347 Nickerson, R. S., 242 Nicolaidis, S., 93 Nicola, S. M., 20, 91 Niedenthal, P. M., 290, 292, 522 Nielsen, M., 137 Nieman, L. K., 110 Niemi, P., 465 Nieuweboer, S., 284 Nigg, J. T., 193 Niiya, Y., 531 Nimmo-Smith, I., 313 Nisbett, R. E., 565 Nitschke, J. B., 35, 38, 239, 313 Nizhnikov, M. E., 134 Nocjar, C., 81–82 Nock, M. K., 453–454 Nomoto, H., 121 Noorthorn, E. O., 455 Norasakkunkit, V., 557 Nord, E., 324 Norem, J. K., 522 Norenzayan, A., 284, 558, 565 Norgren, R., 92 Norman, C. C., 208, 393 Norman, W. T., 152 Norris, C. J., 313 Norris, K., 436 Nosanchuk, T. A., 595 Nosek, B. A., 291–293, 298 Novick, N. J., 590 Novick, O., 195 Nowak, R., 134, 136 Nowicki, G. P., 236 Nowlis, S., 283 Numan, M., 135–138 Numan, M. J., 136

RT6019X_C038.indd 647

647

Nummenmaa, L., 465 Nurius, P., 386 Nuss, C. K., 609 Nussdorfer, G. G., 91 Nuttin, J., 227 N-Wihlbäck, A. C., 112 Nyberg, S. E., 368, 371 Nygren, T. E., 469 Nyman, M., 471

O Oades, R. D., 80 Oatley, K., 353, 424 O’Brien, L., 574 Obrist, P., 434, 438 Ochsner, K. N., 352 O’Connell, G. B., 573 O’Connor, C., 53, 352, 401 O’Connor, D. B., 478 O’Connor, J. J., 91 O’Connor, R. C., 478 Oettingen, G., 297, 422 Ogilvie, D, M., 386 Öhman, A., 6, 134, 223, 283, 290, 294, 298 317, 424, 537, 542 Oishi, S., 416, 420–422, 559, 561, 564 Okotoghaide, T., 134 Okubo, Y., 121 Okutani, F., 138 Olbrich, E., 541 Oldfield, M., 455 Olds, J., 69, 74, 78, 94 Olmstead, M. C., 27, 81 Olsen, J. A., 324 Olson-Cerny, C., 204 Olson, J. M., 241 Olson, M. A., 291, 298, 327 Olweus, D., 402 O’Malley, B. W., 112 O’Malley, P. M., 510 Ongur, D., 463 Oppenheimer, S., 313 Orbell, S., 483–484, 621 Orecki, Z. A., 110 Orians, G., 6 Orians, G. H., 604 Oriña, M. M., 392 Orr, S. P., 369 Orsillo, S. M., 456 Ortony, A., 53, 353, 389, 401 Osgood, C., 53 Osgood, C. E., 7, 289–290, 293, 307 Osher, Y., 195 Oshita, M. H., 132 Osincup, D. P., 99 Ostafin, B. D., 453 Ostow, M., 81 Ostrom, T., 592 Oswald, D. L., 479 Otta, E., 284 Otto, T., 129 Ouellette, R., 608

Overmier, J. B., 27 Ozaki, Y., 561 Özelsel, A., 240–241 Ozer, D. J. 228

P Paez, X., 97 Pagani, J. H., 130 Page, A. C., 448, 454 Pagliarini, L., 244 Pagnoni, G., 99 Pahl, S., 336 Paillard, J., 543 Pakstis, A. J., 195 Palfai, T. P., 154, 453 Palmerino, C. C., 93 Palmieri, P. A., 38, 239 Palmiter, R. D., 138 Palm, R. I., 559 Palyo, S. A., 450 Palys, T. S., 417, 419 Panesar, S., 139 Pang, J. S., 223 Panksepp, J., 26, 28–29, 67–84, 134, 139, 207, 276, 353, 369–370, 373, 393, 400, 424, 462, 541 Papadopoulos, V., 111 Papini, M. R., 20 Pappas, B., 55 Paradise, A. W., 530 Parcet, M. A., 211 Pardo, J. V., 313 Parducci, A., 337 Pare, D., 23 Park, B., 293 Park, D., 120 Parker, G. A., 257, 259, 264 Parker, J. G., 604 Parker, K. J., 44 Parkinson, B., 401 Parkinson, J. A., 19, 27–29, 314 Parkinson, J. N., 27 Park, J. H., 276, 281 Park, L. E., 511 Parrott, W. G., 424 Partch, J. J., 278 Partridge, L., 280 Pascoe, J. P., 23 Paskewitz, J., 591 Patashnick, M., 225 Patrick, C. J., 193 Patterson, C., 176 Paulhus, D., 516 Pauli-Pott, U., 40 Paul, M., 136 Paul, S. M., 112 Paulus, M. P., 174 Paunonen, S. V., 155 Pavlides, C., 79 Pavlov, I., 4, 6 Pavlov, I. P., 20, 59, 204 Pawlak, A. P., 282

4/16/2008 5:52:28 PM

648

Payne, B. K. 292, 298 Paz, D., 237 Peake, P. K., 471 Pearson, P. R., 159 Pecina, S., 137, 312–313 Pedersen, C. A., 135, 138 Pedersen, P. E., 131–132, 138 Pelham, B. W., 440, 514, 524, 530–531 Pennartz, C. M., 137 Pennebaker, J. W., 559 Pennington, B. F., 193 Pennington, G. I., 483 Pennington, G. L., 563 Penton-Voak, I. S., 110 Peoples, L. L., 91 Peplau, L., 392 Peplau, L. A., 210, 440, 604, 618 Pereira, M., 137 Perez-Alvarez, M., 455 Perk, C. G., 76 Perrin, N. A., 179 Perry, B. D., 121 Perry, M., 403, 409 Perugini, M., 483 Pervin, L. A., 490 Petersen, C. A., 371 Peterson, C., 399–410 Peterson, C. K., 404, 408–409 Peterson, G., 138 Peterson, R., 282 Petralia, S. M., 113, 116 Petrov, E. S., 131, 134 Petrovich, G. D., 20, 26–28, 132 Pettigrew, T., 581 Pettigrew, T. F., 336 Petty, R. E., 294, 352, 479, 619 Peyk, P., 318 Pezze, M. A., 29 Pfaff, D. W., 110, 112–113, 138, 192 Phan, K. L., 369–370 Phelps, E. A., 313–314, 369 Phillips, A. G., 70 Phillips, B. M., 472 Phillips, D. I., 110 Phillips, M. L., 90 Phillips, P. E., 92 Pickens, J., 39–40 Pickering, A. D., 157, 161 Pickett, C. L., 609 Pickles, A., 190 Picton, T. W., 463 Pierce, G. R., 243 Pierce, R. C., 80 Pieri, M., 111 Piers, W. D., 136 Pietromonaco, P. R., 392 Pietrzak, J., 579 Pilkenton-Taylor, C., 463, 468 Pillig, A. R., 284 Pilon, D. A., 221 Pinel, E. C., 580 Pinsker, H., 203 Pinto, J., 543 Pinto, J. L., 324

RT6019X_C038.indd 648

Author Index

Pintrich, P. R., 227 Pinulas, A., 471 Pitkanen, A., 23, 61 Pitman, R. K., 369 Pitts, G. S., 293 Pizarro, D. A., 477 Pizarro, J., 477 Pizzagalli, D. A., 313 Plant, E. A., 335, 571–582 Pleban, R., 516 Plomin, R., 161, 189–191 Pluchino, N., 111 Plutchik, R., 282, 344, 347, 353, 368, 377, 402 Poehlmann, K. M., 354 Poindron, P., 136–137 Polan, H. J., 131 Pollard, J. C., 168, 171, 174, 178–179 Polo, V., 176 Pomerantz, J. R., 240 Popper, K., 228 Porsolt, R. D., 96 Porter, R., 309 Porter, R. H., 136 Porter, S., 376 Posner, M. I., 188, 192, 292, 461, 463–465 Posthuma, D., 193 Postma, A., 407 Pothos, E., 92, 97–99 Pothos, E. N., 312 Pouliot, W. A., 113 Poulos, A. M., 133 Poulsen, C., 472 Powell, M., 7 Powell, M. C., 290, 526, 608 Powers, A. M., 616 Powers, W. T., 386 Prange, A. J., 138 Pratkanis, A. R., 294, 298 Pratto, F., 290, 317 Pratt, W. E., 90, 97 Prescott, C. A., 192 Prescott, T. J., 80, 331 Pressman, E. K., 41 Presson, C. C., 294 Preston, L. K., 618–619 Pribram, K. H., 490, 543 Price, E., 6 Price, E. O., 175 Price, J. G., 263 Price, J. L., 61, 130, 463 Price, M., 257 Price, T. R., 36 Priel, B., 195 Priester, J., 7 Priester, J. R., 241, 619 Prins, B., 282 Prinstein, M. J., 453 Prins, Y. R. A., 336 Privitera, L., 174 Prizmic, Z., 153 Prokopenko, V., 282 Pronin, E., 477 Protopopescu, X., 110

Pryor, J. B., 577 Przewlocka, B., 100 Przybeck, T. R., 159 Purdie, V., 579 Purdon, C. L., 450–451 Purdy, J. E., 175 Purdy, R. H., 118 Pursnani, N. K., 118 Purvis, K., 114 Putman, P., 403 Putnam, P., 374 Pyszczynski, T., 448, 505, 512, 549

Q Quay, H. C., 378–379, 471 Quetel, C., 113 Quigley, K. S., 439 Quina, K., 620 Quinn, D., 443 Quinn, J. L., 173–174, 181 Quirk, G. J., 20, 23–24

R Rachman, S., 275 Rachman, S. J., 449–450, 454 Rada, P., 89–102 Rada, P, V., 92–99, 102, 312 Radesäter, T., 174 Radhakishun, F. S., 92 Radhakrishnan, P., 422 Radke-Yarrow, M., 40 Radloff, R., 587 Rafaeli-Mor, E., 529 Raichle, M. E., 463–464 Raineki, C., 132 Rakow, T., 483 Ralph, R. J., 177 Ramsey, D. S., 402 Ramsey, S., 298 Ramus, S. J., 20 Randall, C. K., 134 Ranganath, C., 35 Rangel, S., 133 Rao, K., 36 Raphael, B., 36 Rassin, E., 448, 451 Rauch, S., 90 Ravel, N., 133 Rawsthorne, L. J., 225 Ray, A. J. Jr., 182 Ray, J., 168, 170, 174, 179 Raymond, P., 7, 577 Reading, P., 26 Read, J., 121 Read, S., 324 Read, S. J., 532 Rèale, D., 168, 170, 174, 176, 178–179 Rebec, G. V., 74, 80 Reddy, D. S., 112 Redfield, J., 203

4/16/2008 5:52:28 PM

Author Index

Redgrave, P., 80 Redish, A. D., 90 Reeb, B. C., 35–44 Reed, M., 461–472 Reed, M. A., 211, 235, 239–240, 243, 461–464, 466–468, 472 Rees, S. L., 139 Reeve, J., 344 Reeves, B., 53 Reeves, F. B., 235 Regan, D., 589 Reider, S. L., 523 Reik, W., 198 Reilly-Harrington, N. A., 380 Reilly, S., 20 Reisberg, D., 235 Reis, D. J., 19, 23 Reisenzein, R., 356 Reis, H., 7, 392 Reis, H. T., 155, 160, 204, 210–211, 392, 444, 492, 578, 602, 604, 606, 621, 625 Reiss, D., 191 Reitman, W., 222 Renaud, J. M., 451 Renshaw, K., 558 Repa, C., 23 Repa, J. C., 23 Repa, K., 198 Reppucci, N. D., 224 Rescorla, R. A., 20, 26–27 Reynolds, J. N. J., 76 Reynolds, M., 450, 453 Reynolds, S. M., 313, 315 Reznik, I., 346 Rhodes, M. E., 109–121 Ribot, T., 449 Ricciardi, J. N., 450 Ricciuti, H. N., 221 Rice, A. G., 93 Rice, K. C., 92 Richard, F. D., 606 Richards, C., 360 Richards, J. M., 354, 590 Richardson, J., 324 Richardson, K. D., 515 Richardson, R., 130 Richerson, P., 257 Richeson, J., 579–580 Richeson, J. A., 573, 580–581 Rickels, M., 96 Ridgeway, V., 607 Ridley, M., 368, 371–372 Riemann, R., 195 Rietveld, M. J. H., 193 Rinck, M., 452 Rioch, D. M., 20 Riordan, C. A., 336 Risch, N. J., 43 Ris, M. D., 236 Risold, P. Y., 136 Rivera, L. M., 392 Rivers, S. E., 477 Robbins, A., 113 Robbins, T. W., 19, 26–29, 72, 77, 90, 314

RT6019X_C038.indd 649

649

Robel, P., 111 Roberts, B. W., 192 Robertson, T., 282 Roberts, W. W., 83, 94 Robin, D., 543 Robinson, B. M., 318 Robinson, D. L., 80 Robinson, G. E., 176 Robinson, G. F., 236 Robinson, M. D., 424 Robinson, R. G., 36, 404, 407 Robinson, S. R., 131 Robinson, T. E., 29, 74–75, 77, 79, 81–82, 91–92, 96, 312 Robins, R. W., 283, 350, 532 Roby, T. B., 205, 221 Roca, C. A., 110, 112 Rochat, P., 543 Rochford, J., 137 Rockstroh, B., 318 Rodrigues, S. M., 19, 24 Roediger, H. L., 242, 291 Roemer, L., 451–452, 456 Roesch, M. R., 129 Roese, N. J., 483, 563 Rofe, Y., 602 Rogan, M. T., 23 Rogers, C., 5 Rogers, L. J., 41 Rohsenow, D, J., 453 Roitman, M. F., 92 Roldan, E., 55 Rolls, E., 79 Rolls, E. T., 90, 400 Romanides, A., 30 Romanski, L. M., 23 Romeo, R. D., 44 Romero-Canyas, R., 500 Romme, M. A. J., 455 Romney, A. K., 353 Roney, C., 239 Roney, C. J. R., 418, 490 Roney, J. R., 373 Ronsheim, P. M., 136 Root, J. C., 313 Roper, D., 451 Roscoe, J., 155 Rose, J. S., 294, 620 Rosellini, R., 120 Rosellini, R. A., 120 Roseman, I. J., 343–361, 389, 401 Rosenberg, M., 289, 514 Rosenberg, S. E., 561 Rosenblatt, J. S., 128, 131, 135–137 Rosenblum, K., 132 Rosenblum, L. A., 43 Rosenfeld, J. P., 35 Rosenfeld, P., 134 Rosen, J. B., 134 Rosenkranz, J. A., 71 Rosen, S., 509 Rose, R., 559 Roskos-Ewoldsen, D. R., 294, 298 Rossetti, Z. L., 96

Rossi, J., III, 79 Rossi, R. R., 70 Ross, M., 559, 561 Ross, R. S., 133 Rotenberg, V. S., 545–547 Rothbart, M. K., 188, 190, 461, 463–464, 468, 470–472 Rothermund, K., 466, 545, 547 Rothman, A. J., 417, 475–484 Rothman, R. B., 92 Roth, T. L., 131–134 Roth, W. T., 452 Rottenberg, D. A., 279 Rotter, J., 4 Rouby, A., 607 Rousselle, J. G., 438 Rovine, M. J., 392 Rowa, K., 451 Roy, M., 605 Royzman, E. B., 334, 336 Rozin, P., 9, 334, 336, 353 Roznowski, M., 153 Rubin, B. S., 138 Rubin, K. H., 35, 39–40 Rubin, M., 477 Rubinow, D. R., 110 Rubin, Z., 440 Rude, S. S., 452 Rudman, L., 299 Rudman, L. A., 293 Rudnick, J. R., 607 Rudy, J. W., 129–133 Rueda, M. R., 188 Rumelhart, D., 331 Rumpel, S., 19, 25 Rundus, D., 242 Rupprecht, R., 111, 113 Rusbult, C. E., 605–606, 608, 618 Rusch, C. D., 353 Rush, A. J., 452 Rusiniak, K. W., 93 Russ, D., 455 Russell, J. A., 53, 205, 314–315, 352–354, 387, 400 Russell, L. B., 324 Russo, R., 467 Rusting, C. L., 153–154, 157 Ruter, K., 592 Rutten, A. L., 182 Rutter, M., 190, 193, 196 Ryan, R. M., 155, 217, 222–223, 225, 300, 387, 392, 416–417, 421, 537, 545, 548–549 Ryff, C. D., 416, 523–524

S Sabatinelli, D., 62, 313 Sachek, J., 193 Sachser, N., 135 Sachs, P., 589 Sackeim, H., 36 Sackeim, H. A., 507

4/16/2008 5:52:28 PM

650

Sadalla, E. K., 277 Sadler, P., 561 Saetre, P., 170, 179 Sage, J. R., 129 Sahakian, B. J., 26 Sakaguchi, A., 7, 19 Sakaguchi, T., 133 Sakurai, T., 70 Salamone, J. D., 28–29, 75, 80, 92, 96 Salas, D. M., 452 Salkovskis, P. M., 450, 453–455 Salloway, S., 406 Salmon, C., 280 Salomon, K., 442 Salovey, P., 154, 475–484 Salvatore, J., 581 Sampson, L. D., 20 Sanbonmatsu, D., 7 Sanbonmatsu, D. M., 290, 526 Sandel, T., 560 Sander, K., 132 Sanders, D., 110 Sanders, M. J., 129 Sanderson, C. A., 206, 421 Sano, H., 129 Sansone, C., 225 Sapolsky, R. M., 538, 546 Sara, S. J., 130 Sarason, B. R., 243 Sarason, I. G., 243 Sarason, S. B., 217 Sarinopoulos, I., 313 Sarnoff, I., 290 Saron, C., 35, 37 Saron, C. D., 35, 158, 369 Sarter, M., 407 Sarter, M. F., 21, 25 Sato, S., 114 Satpute, A. B., 156 Saudino, K. J., 191 Savander, V., 23 Sawyer-Glover, A., 42 Scalzo, F. M., 130 Scammell, T. E., 90 Schaal, B., 136, 235 Schachner, D. A., 618 Schachter, S., 602 Schacter, D. L., 283, 314 Schaefer, H. S., 313 Schafe, G. E., 19, 23–24 Schaffer, A. R., 392 Schaffer, C. E., 37 Schaller, M., 275–276, 281, 284, 608 Schanberg, S., 40 Schatzberg, A. F., 42–44 Scheffer, D., 544 Schefft, B. K., 236 Scheier, M., 5, 417, 419, 521 Scheier, M. F., 156, 158, 212, 238, 301, 345, 349–351, 360, 386–390, 392, 417–420, 490, 492, 512, 536, 564, 572, 575, 608, 619 Schell, A. M., 58, 547–548 Scherer, K., 290

RT6019X_C038.indd 650

Author Index

Scherer, K. R., 345–347, 350–351, 354, 357, 359, 408 Scher, S. J., 619 Schiff, B. B., 73 Schimel, J., 512 Schimmack, U., 421–422 Schlaepfer, T. E., 208 Schlenker, B. R., 603, 607–608 Schlesinger, M. J., 299 Schlinger, B. A., 111 Schlosberg, J., 53 Schmajuk, H. A., 466 Schmajuk, N. A., 537–538, 546 Schmidt, C. K., 190 Schmidt, G. W., 515 Schmidt, H., 451 Schmidt, L. A., 35, 40 Schmidt, N. L., 190, 201 Schmidt, P. J., 110 Schmidt, T., 174 Schmidt, W. J., 81 Schmitt, D. P., 256, 625 Schmitt, M., 291, 559 Schmitz, C., 110 Schmitz, S., 193 Schmukle, S. C., 299 Schnall, S., 291 Schneider, D. J., 448, 454 Schneiderman, N., 20 Schneider, T. R., 476–477 Schneider, W., 292, 309 Schneirla, T., 6, 9, 52, 166, 370 Schneirla, T. C., 39, 128, 131, 204, 385 Schoenbaum, G., 20, 129, 133 Scholer, A. A., 489–501 Schonberg, M. A., 471 Schonfeld, I. S., 153 Schooler, J. W., 245 Schooler, T. Y., 291 Schore, A. N., 547–548 Schork, N. J., 194 Schorr, A., 357 Schreiber, J. E., 197 Schreindorfer, L. S., 511 Schroeder, H. A., 177 Schulteis, G., 98 Schultheiss, O. C., 220–223, 228, 388, 419 Schultz, L., 132 Schultz, W., 71–72, 75–76, 77, 78–80, 92, 99, 469 Schumacher, M., 111 Schunk, D. H., 350 Schupp, H. T., 57 Schutter, D. J. L. G., 407 Schvaneveldt, R. W., 292 Schwaber, J. S., 20 Schwarting, R. K., 42–43 Schwartz, D. H., 92 Schwartz, G. E., 35 Schwartz-Giblin, S., 113 Schwartz, J., 53, 352, 401 Schwartz, J. E., 121 Schwartz, J. L. K., 290 Schwartz, J. M., 96

Schwartz, M. W., 94 Schwartz, R. D., 112 Schwartz, R. M., 532 Schwarz, N., 292, 592 Schwinghammer, S. A., 592, 595 Schwob, J. E., 130 Sclafani, A., 93, 129, 132 Scott, D. R., 604 Scott, S., 377 Scott-Sheldon, L. A. J., 293 Scott, T. R., 93–94 Scourfield, J., 193 Seamans, J. K., 43 Sears, D. O., 292, 559 Sears, P., 585 Sears, P. S., 217 Sears, R., 400 Sears, R. R., 10 Sedikides, C., 506, 508–509, 512, 532, 542, 558 Seemanova, E., 258 Seery, M., 434, 436, 440–442, 444 Seery, M. D., 441, 443 Segal, M., 113 Segal, Z. V., 452, 456 Segerstrom, S. C., 211 Seibt, B., 238 Seifert, G. W., 6 Seifert, J., 38, 408 Sekaquaptewa, D., 292 Self, D. W., 83 Self, E., 406 Seliga, A., 121 Seliga, A. M., 120–121 Seligman, M. E., 96 Seligman, M. E. P., 20, 203, 337, 541, 563 Sell, A., 251–270 Selye, H., 112 Semin, G. R., 481 Senchak, M., 392 Senulis, J., 36 Senulis, J. A., 35, 158, 369 Seppala, E., 564 Sermat, V., 352 Setlow, B., 20 Sevelinges, Y., 129, 133 Shackman, A. J., 313, 408 Shaffer, D. R., 332 Shaffer, L. M., 298 Shagrass, C., 36 Shaham, Y., 82 Shah, J., 238–239, 296, 360, 423, 482, 494–495, 540, 564, 575 Shah, J. Y., 235, 296–297 Shaklee, A. B., 170, 174, 178 Shallice, T., 463 Sham, P., 193, 199 Shao, L., 160 Shapiro, C. M., 616 Shapiro, L. E., 138 Sharp, A. J., 198 Shaver, P., 53, 352, 354, 392, 401, 408, 578, 621 Shaver, P. R., 207, 347–348, 618

4/16/2008 5:52:28 PM

Author Index

Shaw, B. F., 452 Shaw, D. S., 471 Shaw, P., 198 Shayit, M., 134 Shean, G. D., 155 Sheehan, T., 136 Sheehan, T. P., 136 Sheeran, P., 484, 621 Sheldon. K. M., 155, 222, 389, 417–418, 420–421, 494, 499, 535, 560, 562 Sheldon, M. S., 615–629 Shelton, J. N., 579, 581 Shelton, N. J., 573, 579–581 Shelton, R. C., 58 Shelton, S. E., 41 Shen, F. H., 98 Shenstone, W., 399 Shepherd, G. M., 129 Shepher, J., 281 Shepperd, J. A., 529 Sheridan, J., 58 Sheridan, J. F., 308 Sherif, C. W., 602 Sherif, M., 602 Sherman, D., 475 Sherman, D. K., 423, 478, 482 Sherman, D. S., 423 Sherman, S. J., 290, 294–297 Sherrington, C. S., 308, 309 Sherry, D. F., 283 Sherwood, R. J., 313 Shide, D. J., 134 Shiekh, M., 112 Shiffrin, R. M., 292, 309 Shiner, R. L., 192 Shin, L. M., 369 Shionoya, K., 129, 132 Shiota, M. N., 273–285 Shipherd, J. C., 449 Shipley, M. T., 60, 129, 133, 462 Shipley, T. E., 205 Shippenberg, T., 76 Shippenberg, T. S., 101 Shizgal, P., 7, 83 Shoda, Y., 471 Sholiton, R., 53 Shook, N. J., 245, 329, 333–334 Shopsin, B., 403 Showers, C., 514 Showers, C. J., 521–533, 537, 545, 547 Shrauger, J. S., 561 Shrira, I., 244 Shughrue, P. J., 113, 136 Shulman, T. E., 155 Shweder, R. A., 557 Sidanius, J., 573 Siddle, D. A., 58 Sidman, M., 21 Sidtis, J. J., 279 Siegel, H. I., 135 Siegel, J. E., 324 Siegle, G. J., 157 Sigall, H., 292 Sigelman, J., 37, 313, 405–407

RT6019X_C038.indd 651

651

Sigelman, J. D., 402 Sigurdsson, T., 24 Sih, A., 181 Silberg, J. L., 193 Silk, J. B., 204 Simeonova, D. I., 377 Simerly, R. B., 136 Simmons, D. A., 137 Simon, E. J., 95 Simon, L., 448 Simonson, I., 561 Simpkins, J. W., 113 Simpson, J. A., 278, 283, 392 Sinclair, R., 477 Singer, C. A., 113 Singh, M., 113 Sinn D. L., 168, 170, 174, 176–179 Siviy, S., 139 Skalski, G. T., 182 Skib, B. A., 513 Skinner, B. F., 4, 536 Skinner, C. S., 478–479 Skinner, E. A., 617 Skinner, M. J., 620 Skirzewski, M., 96 Skowronski, J. J., 336 Slamecka, N. J., 242 Slovic, P., 324 Sluyter, F., 197 Small, S. L., 313 Smarandescu, L. O., 592 Smári, J., 451 Smith, A. M., 130 Smith, C. A., 347, 351, 358 Smith, C. P., 223 Smith, D. M., 279 Smith, E. A., 253 Smith, E. R., 293, 354, 591 Smith, G. P., 92 Smith, H. E., 113 Smith, H. G., 137 Smith, J., 28, 516, 596 Smith, J. E., 235 Smith, J. L., 581 Smith, K. S., 137, 312, 317 Smith, M., 516 Smith, M. B., 290, 294, 298 Smith, N. K., 315, 352, 359 Smith, N. W., 493 Smith, P. K., 300, 370 Smith, R. G., 113 Smith, S. E., 93, 208 Smith, S. M., 241 Smith, T. W., 204, 373, 607 Smith, W., 589 Smith, Y., 23, 28 Smits, D. J. M., 403 Smits, K., 130 Smoller, J. W., 197 Smotherman, W. P., 131–132 Snibbe, A. C., 559 Snidman, N. C., 39 Snyder, C. R., 373, 515, 517 Snyder, C. R. R., 292

Snyder, D., 404 Snyder, J., 351 Snyder, M., 223, 575 Snyder, M. L., 513 Sobotka, S., 36 Sokolov, E., 6 Sokolov, E. N., 59, 61 Solberg, E. C., 424 Solomon, B., 392 Solomon, R. C., 352, 368 Solomon, R. L., 21, 27, 327 Solomon, S., 448, 505, 512 Solorz, A., 7 Sommer, K. L., 223, 608, 610 Sorrentino, J., 134 Sorrentino, R. M., 235, 344 Sotres-Bayon, F., 19, 23, 43 Spanagel, R., 101 Spangler, R., 100 Spangler, W. D., 221–222 Spear, L. P., 130 Spear, N. E., 130–132, 134 Spellman, B. A., 242 Spence, E. L., 58 Spencer, S., 443 Spencer, S. J., 235, 293 Spicer, C. V., 579–580 Spiegel, S., 423, 479, 494–495, 562, 566 Spielberger, C. D., 408 Spinath, F. M., 195 Spindel, M. S., 360 Spindler, J., 92 Spinoza, B., 353 Spirito, A., 453 Spoont, M. R., 386 Spors, H., 129 Sprecher, S., 618 Springer, S. P., 545, 547 Squire, L. R., 291 Srull, T. K., 296 Stack E. C., 136–137 Stackenwalt, G., 133 Stafford, T., 331 Stalnaker, T. A., 129 Stam, H., 407 Stang, D. J., 466 Stanley, B. G., 91 Stanton, M. E., 130, 134–135 Stapel, D., 588, 590 Stapel, D. A., 588, 590–592, 596–597 Stark, E., 475 Starr, L. B., 36 Staubli, U., 129 Staubli, U. V., 23 Stayman, D. M., 282 Stearns, S. C., 280 Steele, C., 443, 604 Steele C. M., 443, 580–581 Steenhuis, I., 479 Steiger, S., 174 Steinberg, J., 529 Steiner, J. E., 39, 311 Steiner, M., 110, 139 Steininger, T. L., 100

4/16/2008 5:52:29 PM

652

Stein, N. L., 401 Stein-Seroussi, A., 532 Stellar, E., 94 Steller, B., 235 Stenslie, C. E., 237 Stephan, C. W., 578 Stephan, W. G., 578 Stern, E., 293 Stern, J. M., 137 Stevens, A., 371 Stevenson-Hinde, J., 6 Stevenson, H. W., 559, 565 Stevenson, J., 192 Stevenson, R. J., 128–129, 132 Stewart, B., 292 Stewart, J., 82–83 Stewart, W. B., 129 Stieb, S., 174 Stigler, J. W., 559, 565 Stillwell, A. M., 603, 606–607 Stillwell-Barnes, R., 6 Stinus, L., 98, 100 Stipek, D., 348 Stomati, M., 111 Stone, A. A., 121 Stone, D. J., 113 Stone-Elander, S., 62 Stone, G. O., 277, 282 Stone, L. D., 352 Stoner, P., 237 Strachman A., 211–212 Strack, F., 241, 243, 346, 540, 577, 590–591 Strauman, T. J., 500–501 Strecher, V. J., 478–479 Street, G. P., 448 Strenta, A., 443 Strobel, A., 195 Stroebe, W., 336–337 Stroessner, S. J., 490, 498 Strong, C., 62 Strong, G., 377 Strongman, K. T., 354 Stroop, J. R., 448 Strosahl, K., 456 Strother, S. C., 279 Strotmann, J., 129 Strube, M. J., 605 Stuber, G. D., 92 Stucke, T. S., 609 Stultz, C. H., 452 Stuss, D. T., 463 Stutz, R. M., 70 Suchecki, D., 134–135 Suci, G., 7, 53 Suci, G. J., 289, 307 Sugimori, S., 559 Sugiyama, L. S., 260 Suh, E., 420 Suh, E. J., 138 Suh, E. M., 160, 421 Sukikara, M. H., 136 Sullivan, H. S., 4 Sullivan, H. W., 417 Sullivan, M. W., 400, 402

RT6019X_C038.indd 652

Author Index

Sullivan, R. M., 41–43, 127–139 Suls, J., 515, 585–597 Sumida, K., 118 Summerfield, A. B., 350 Summy-Long, J., 138 Sun, C., 440 Sundie, J. M., 277–278, 282 Sundlass, K., 44 Sundstrom-Poromaa, I., 112 Suomi, S., 6 Supple, W. F., 23 Sutherland, R. J., 129 Sutton, R. S., 327 Sutton, S. K., 9, 37–38, 58, 158, 238, 390, 404, 420, 492, 512 Suzuki, T., 559 Svare, B., 120 Svare, B. B., 120 Svartberg, K., 168, 171, 173–174, 178, 180–181 Svensson, K., 137 Svrakic, D. M., 159 Swaab, D. F., 138 Swann, J. M., 137 Swann, W., 509 Swann, W. B., 440, 532, 559, 625 Jr., 506, 524, 530, 559 Swanson, H. H., 138 Swanson, J., 195 Swanson, J. M., 192, 195 Swanson, L. W., 132, 136 Swartz, T. S., 346–347 Sweatt, R. A., 452 Swets, J. A., 238, 325, 497 Swim, J. K., 299 Swinkels, A., 154 Syme, S. L., 207 Symons, D., 256 Szekely, M., 92 Sznycer, D., 251–270

T Tafarodi, R. W., 559 Takagi, K., 563 Takahahsi, L. K., 134 Takahashi, L. K., 134, 138 Takahashi, S., 138 Takahashi, S. N., 402 Takahashi, Y. K., 129 Takata, T., 559 Takemoto, T., 563 Talley, A. E., 615–629 Tambor, E. S., 506, 608 Tambosso, L., 136 Tamir M., 415–425 Tanaka, A., 227 Tanaka, M., 120 Tanda, G., 80, 92, 98 Tang, A., 42 Tang, A. C., 42, 44 Tanksley, S. D., 194 Tannenbaum, P., 7, 53

Tannenbaum, P. H., 289, 307 Tanner, W. P., 238 Tanner, W. P. Jr., 497 Tapper, I., 174 Tarrier, N., 454 Tartakovsky, M., 573 Tassinary, L. G., 308 Taylor Bianco, A., 238 Taylor, C. J., 452 Taylor, D., 130 Taylor, E., 449–450 Taylor, J., 282 Taylor, J. L., 96–97 Taylor, J. R., 26 Taylor, K. M., 94, 97 Taylor, N., 35 Taylor, S., 588 Taylor, S. E., 207–208, 212, 277, 334, 352–353, 423, 508–509, 515, 531, 538, 560, 588, 596 Taylor, S. F., 369 Teasdale, J. D., 456 Teevan, R., 221 Teevan, R. C., 220, 346 Teitelbaum, P., 90, 94 Tellegen, A., 37, 53, 153, 204, 352, 379, 389–390, 399, 404, 538 Temrin, H., 174 Tennov, D., 352 Terdal, S. K., 506, 608 Ter Schure, E., 401 Tesch, F., 597 Tesser, A., 289–291, 346, 505, 508–509, 512, 516–517, 532, 596 Testa, M., 442, 591, 595 Thayer, J. F., 37, 453 Thayer, R. E., 379, 537–538, 543 Thibault, J. W., 605–606 Thibaut, J. W., 280 Thibodeau, R., 35 Thiel, C. M., 42–43 Thierry, A., 42–43 Thiriet, N., 132 Thoennes, N., 204 Thoma, R., 198 Thomas, A., 376 Thomas, G. J., 177 Thomas, P., 176 Thomas, S., 327 Thomas, S. A., 138 Thompson, J. E., 602 Thompson, R. A., 188 Thorkildsen, T., 225 Thorman, S., 174 Thorndike, E., 4 Thornhill, R., 282, 604 Thornton, D., 594, 597 Thrash, T. M., 7–8, 63, 160, 166, 188, 192, 217–229, 326, 379, 390, 424, 440, 462, 470, 478, 490, 492, 522, 528 Thurstone, L. L., 7, 290, 293, 315 Tice, D. M., 352, 505–517, 606–609, 624, 629

4/16/2008 5:52:29 PM

Author Index

Tierney, R., 42 Tillmann, H. C., 112 Timberlake, W., 60 Tinbergen, J. M., 166 Tindall, D. J., 113 Tjaden, P., 204 Toates, F., 71 Todd, P. M., 369 Toguchi, Y., 506, 558 Tolin, D. F., 448, 450–451 Tolman, E., 4, 9 Tolman, E. C., 352 Tomaka, J., 370, 432, 434–436, 438, 440, 514, 538 Tomarken, A. J., 9, 35, 37–39, 58, 158, 237, 404–405 Tomkins, S. S., 346, 350–353 Tooby, J., 5, 251–270, 275, 277, 282, 284, 348, 368–369, 604–605 Topolski, T. D., 192 Toran-Allerand, C. D., 113 Toru, M., 121 Toufexis, D. J., 127–139 Touretzky, D. S., 90 Touzani, K., 93, 129, 132 Tov, W., 421 Towles-Schwen, T., 335, 573 Tracy, J. L., 283, 350 Tranel, D., 313–315, 544 Trash, T. M., 432 Trawalter, S., 579 Tremblay, L., 92, 469 Trevarthen, C., 544–545 Triandis, H. C., 421 Trinder, H., 450 Trio, M., 448 Trivers, R., 256–257, 259, 264 Troetschel, R., 296 Tronel, S., 130 Tronick, E. Z., 40 Trope, Y., 235, 298, 300, 509, 563 Tropp, L., 581 Tropp, L. R., 580 Trost, M. R., 223, 277 Trout, S. J., 91 Trowill, J. A., 74 Troy, A. B., 393 Tsai, J. L., 352, 422, 564–565 Tucker, D. M., 235–239, 241, 243–245, 472 Tuiten, A., 407 Tulving, E., 291 Turchan, J., 100 Turkewitz, G., 128 Turkheimer, E., 189 Turkington, D., 455 Turner, A. K., 257, 259 Turner, R. J., 390 Turner, S. M., 376 Turner, T. J., 353 Turpie, C. A., 579 Turvey, C., 154 Tversky, A., 238, 328, 332, 352, 466, 469, 476, 498 Twenge, J. M., 608–610

RT6019X_C038.indd 653

653

Tye, M., 254–255 Tykocinski, O., 235, 386, 495, 564 Tyler, S. K., 235, 403 Tzschentke, T. M., 81

U Ubel, P., 324 Uchida, Y., 559, 564 Uchino, B. N., 203–204 Umansky, R., 195 Umberson, D., 204, 207 Underwood, B. J., 390 Underwood, M. K., 347 Ungerstedt, U., 75, 97 Unterwald, E. M., 100 Updegraff, J., 475 Updegraff, J. A., 212, 423, 478 Upshaw, H., 592 Urbanksi, T., 42 Urdan, T., 229 Uriarte, N., 137 Urry, H. L., 39, 420 Ursin, H., 55 Utsurikawa, N., 171 Uzunova, V., 121 Uzunov, D. P., 121

V Vaccarino, F., 136 Vaidya, J., 389, 399, 538 Vaillant, G. E., 223 Vaitl, D., 58 Valencia, J. F., 481 Valenstein, E. S., 74–75, 94 Vallacher, R. R., 298, 300, 483, 490 Valtin, H., 177 Van Anders, S. M., 373 Van Assema, P., 479 Van Beijsterveldt, C. E., 193 Vance, S. L., 579 Vandell, D. L., 156 Van den Berg, A. E., 541 Van den Berghe, P. L., 281 Vandenheede, M., 402 Vandenhoff, P., 6 Van den Hout, M., 407 Van der Kolk, B., 455 Van der Pligt, J., 352 Vanderschuren, L. J., 81–83 Vanderwolf, C. H., 60 Van der Woude, T. P., 138 Van der Wulp, N., 540 Van der Zee, K., 592 Van de Wal, N., 138 Van Dijk, W. W., 352 Van Furth, W. R., 353 Vangelesti, A. L., 607 Van Honk, J., 403, 407 Van Hulle, C. A., 190 Van Knippenberg, A., 292, 545

Van Laar, C., 573 Van Lange, P. A. M., 618 Van Lawick-Goodall, J., 53 Van Leengoed, E., 138 Van Leeuwen, F. W., 138 Vanman, E. J., 58 Van Noordwijk, A. J., 166, 182 Van Oers, K., 166, 168, 171, 174, 177–179 Van Os, J., 121 Van Ree, J. M., 92, 130, 353 Van Reekum, C., 347 Van Ryen, P. C., 138 Van Uum, J. F., 130 Van Vulpen, E. H., 130 Van Yperen, N. W., 228, 588 Vargas, P., 292 Varlinskaya, E. I., 131, 134 Vasey, M. W., 472 Vasquez, K. A., 571 Vasquez-Suson, K. A., 578 Vasudevan, N., 113 Vaughn, K., 313 Vaughn-Scott, K., 406 Vázquez, C., 451 Veldhuis, J. D., 110 Vendlinski, M. K., 196 Verbeek, M., 6 Verhoeven, G., 113 Vernon, M. L., 207 Veroff, J., 205 Versace, F., 62 Vershure, B., 277 Verstynen, T., 42 Vertes, R. P., 79 Verwer, R. W., 130 Vescio, T. K., 452, 573 Vevea, J. L., 558 Vick, S. B., 440, 443 Vidaver, R. M., 112 Villacorta, M., 531 Visser, E. K., 173, 181–182 Vivian, J. A., 82 Vohs, K., 500, 509 Vohs, K. D., 301, 317, 334, 352, 466, 507, 619 Volkow, N. D., 81, 84, 100 Von Clausewitz, K., 52 Vongher, J. M., 118 Von Hippel, W., 278, 292 Vorauer, J. D., 573, 579 Vrana, S., 6 Vrana, S. R., 58 Vrba, E., 542 Vredenburg, D. S., 336 Vrugt, A., 515 Vuga, M., 37, 39

W Wachowiak, M., 129 Wade, C., 113 Wadhwa, P. D., 197 Wager, T., 369 Wahlsten, D., 195

4/16/2008 5:52:29 PM

654

Wakabayashi, K. T., 20 Wakefield, J. C., 376 Waldman, I. D., 192–193 Waldron, M. C., 189 Walf, A. A., 110, 113, 117–119, 121 Walker, C., 138 Walker, C. D., 137, 139 Walker, C. H., 138 Walker, D. L., 20, 133 Walker, M. S., 159 Wallace, J. F., 464, 467 Wallace, K. J., 134 Wallbott, H. G., 354 Wallin, E., 137 Wallstrom, J., 134 Walsh, B. T., 102 Walster, E., 280 Walster, G. W., 280, 335, 625 Walter, J., 198 Wamsley, J. K., 100 Wang, G. J., 81 Wang, Q., 560 Wang, S., 560 Wang, W. C., 197 Wang, Z., 282, 394 Wan, K.-C, 559 Warburton, W. A., 610 Ward, A. J. W., 176 Ward, C. H., 37 Ward, J., 6 Ward, J. C., 156 Ward, S. J., 29 Warner, P., 110 Wasel, W., 235 Wason, P., 605 Waterhouse, B. D., 463 Waterman, A. S., 416, 421 Waters, P., 514 Watkins, M. J., 242 Watkins, S. S., 98 Watson, D., 37, 153, 198, 204, 352, 376, 379, 389–390, 399, 404, 409, 464, 538 Watson, S., 6 Watson, S. J., 194 Watters, J. J., 113 Wawrzycki, J., 110 Way, E. L., 98 Wearing, A., 155 Weber, E. U., 562 Weber, M., 282 Weber, S. M., 28 Webster, J. R., 178 Wechsler, C. E., 453 Wedell, D. H., 592 Wegener, D. T., 352, 479 Wegner, D. M., 298, 300, 447–456, 483, 490 Wehling, M., 112 Weinberger, J., 222, 538 Weinberger, N. M., 23 Weinberg, I., 546 Weinberg, J. B., 94 Weiner, B., 217, 224, 347 Weinstein, H., 560 Weinstein, M. C., 324

RT6019X_C038.indd 654

Author Index

Weinstein, N. D., 336, 483 Weinstein, S., 439 Weinstein, T., 175 Weisbuch, M., 436, 440, 443 Weisbuch-Remington, M., 441 Weiss, M., 541 Wellborn, J. G., 617 Weller, A., 134 Wellman, C. L., 177 Wells, A., 455 Weltman, G., 235 Wendelken, C., 207 Wentura, D., 293 Wenzlaff, R. M., 448–449, 451–452, 455–456 Werth, L., 241, 245 Westerink, B. H., 92 West, M. O., 282 West, S. G., 196 Whalen, P. J., 23 Wheatman, S. R., 530 Wheeler, L., 515, 585–597, 604 Wheeler, R. E., 9, 35, 37, 404 Wheeler, R. W., 35, 37, 158 Whishaw, I. Q., 79 Whitaker, D. J., 530 White, B. J., 602 Whitehouse, W. G., 380 White, K., 559, 561 White, L., 448 White, L. A., 618 White, N. M., 115 White, R. W., 290 Whitesell, N. R., 514 White, T. L., 38, 158–159, 378, 390, 393, 403–404, 478, 500, 616 Wickless, C., 360 Wicklund, R. A., 295 Wiedenmayer, C. P., 134, 135 Wiens, S., 223 Wiepkema, P., 6 Wiese, D., 389, 399, 538 Wiest, C., 346 Wightman, R. M., 80, 92 Wik, G., 62 Wilbarger, J. L., 291 Wilcoxon, H., 283 Wilder, D. A., 602 Wilensky, A. E., 23 Wiley, A. R., 560 Willcutt, E. G., 193 Willhite, D. C., 129 William, J. M. G., 157, 211, 456 Williams, A., 336 Williams, C. J., 293–294 Williams, C. L., 131 Williams, D. C., 257, 259 Williams, G., 256 Williams, G. C., 257, 259 Williams, G. V., 121 Williams, K. D., 207, 608–610 Williamson, D. A., 607 Williamson, P. A., 235–237, 243–245 Williams, P. A., 235–237, 243–245

Williams, R., 374 Williams, V. S. L., 514 Willis-Owen, S. A., 195 Will, M. J., 93, 100 Willoughby, P. J., 19 Wills, T. A., 442, 508, 588, 597 Wilson, A. E., 559, 561 Wilson, D., 6 Wilson, D. A., 127–139 Wilson, D. K., 477 Wilson, E., 456 Wilson, E. O., 370, 373 Wilson, K. G., 456 Wilson, M., 256, 267–268, 278, 280 Wilson, R., 241 Wilson, R. I., 129 Wilson, T. D., 291, 299, 336 Wiltgen, B. J., 129 Winkel, R. E., 608 Winkielman, P., 238, 291 Winson, J., 79 Winston, A., 203 Winston, J. S., 128, 314 Winter, D. G., 544 Winterhalder, B., 253 Winters, R., 390 Wintink, A. J., 82 Wise, P. M., 113 Wise, R., 81 Wise, R. A., 71–72, 74–75, 81–82, 91–92, 96, 99–100, 312 Wisniecki, A., 80 Witkin, H. A., 537, 542 Witte, K., 483 Wittenbrink, B., 289, 293 Wittling, W., 547–548 Witzki, A. H., 240 Wlaschin, J., 475 Wlaschin, J. T., 475–484 Wolf, A. P., 281 Wolfe, C. T., 336, 512, 530–531 Wolff, M., 129 Wolinsky, T. D., 94 Wolterink, G., 130, 353 Wong, P. S., 313 Wong, R., 132 Woo, C. C., 132 Wood, G., 59 Wood, J. V., 513, 515, 517, 588, 596–597, 619 Wood, P. L., 76 Woodside, B., 139 Woodward Hopf, F., 91 Woodward, S. A., 39 Worth, K. A., 417 Wortman, C., 336 Wortman, C. B., 402 Wotman, S. R., 603 Wray, R. J., 478 Wu, C., 332 Wu, D., 113 Wundt, W., 4, 352 Wurf, E., 523 Wu, S., 347 Wüst, S., 197

4/16/2008 5:52:29 PM

Author Index

Wyer, R. S., 296 Wyer, R. S. Jr., 561 Wynne, L. C., 21, 327 Wywell, C. L., 81

X Xun, W. Q. E., 561

Y Yadin, E., 83 Yamagami, M., 564 Yamaguchi, M., 129 Yamaguchi, S., 558 Yamamoto, T., 90 Yamauchi, H., 227 Yang, C. R., 43, 90 Yang, R., 110 Yang, R. J., 177 Yang, X., 129 Yeaman, B., 131 Yeomans, J. J., 95 Yeomans, J. S., 58 Yeo, R. A., 198 Yiend, J., 451, 472 Yim, C. Y., 26, 90 Yokoi, M., 129

RT6019X_C038.indd 655

655

Yoshida, K., 90 Yoshikawa, T., 121 Young, L. J., 138, 282, 394 Young, P., 7 Young, P. T., 293, 402 Young, R. K., 9 Young, S. E., 193 Youngstrom, E., 367–381 Youngstrom, E. A., 354, 373 Yuan, Q., 132 Yu, G. Z., 138 Yun, I. A., 20 Yurak, T. J., 336

Z Zador, A., 19 Zahavi, A., 371 Zahm, D. S., 313 Zahn, I., 229 Zahn-Waxler, C., 40 Zajonc, R. B., 6–7, 289–290, 318, 327, 335, 442 Zak, P. J., 208 Zald, D. H., 313 Zanakos, S., 449–450, 452, 454 Zanna, M. P., 289, 293, 332 Zaw-Mon, C., 134 Zechmeister, E. B., 368, 371

Zeelenberg, M., 352, 401 Zeifman, D., 278 Zeigler-Hill, V., 522–523, 525–529 Zeiss, A. M., 508 Zeki, S., 208 Zelenski, J. M., 152–154, 157–160, 390, 477 Zerbst, J., 596 Zhang, M., 100 Zhang, S., 596 Zhao, Z., 312 Zhou, Y., 113 Zhu, D. C., 313 Zhuikov, A. Y., 172, 182 Ziegler, H. L., 604 Ziemba, R. E., 181 Zierk, K. L., 606 Zigmond, M. J., 94 Zinner, L., 408 Zogmaister, C., 293 Zona, D. M., 159 Zou, B., 42 Zou, X., 498 Zubek, J. M., 360 Zuckerman, M., 157, 159–160, 326, 380, 394, 508 Zuluaga, M. J., 137 Zunz, M., 6 Zusho, A., 227 Zuwerink, J. R., 574 Zwiller, J., 132

4/16/2008 5:52:30 PM

RT6019X_C038.indd 656

4/16/2008 5:52:30 PM

Subject Index A Abient needs, 219 Acetylcholine (ACh), release in NAc, 92, 94–95 Achievement goal tradition, 223 Dweck’s achievement approach, 224 Elliot’s trichotomous and 2 × 2 achievement goal frameworks hierarchical model and mastery avoidance, 226 types of achievement goals, 225 Nicholls’s achievement approach, 224–225 Achievement motivation hierarchical model of, 218, 226–227 PSE measure of individual differences in, 221, 229 theories of, 586 Achievement need (motive) tradition, 229 David MCCAlelland and colleagues, 220–222 approach-avoidance distinction, 220 conflation and coding systems for HS and FF, 221 PSE approach and nAch, 221 Henry Murray and colleagues, 219–220 defining need, 219 TAT methodology, 220 implicit and explicit achievement motives, 222–223 Heckhausen’s coding system, 223 Achievement-related behavior, 387 Active avoidance and approach, 386 Acute stress disorder (ASD), 450 ADHD, see Approach tendencies in childhood; Attention-deficit/ hyperactivity disorder Adient needs, 219 Affect action consequences of, 388–389 issues in conceptualizing of, 390 approach-related negative affect, 390–391 avoidance-related positive affect, 391–392 Affective dispositions, 152 Affect-related loop, in behavior, 387 Aggressive behavior, 55 Agreeableness, 160 Alcohol abuse, 453 Alliance of reflexes, 309 Allopregnanolone, 113 anxiety for, 112 formation, 111 nontraditional endocrine substrates, 111 AMPA receptor, 25 Amygdala

composition, 23 and control lesions, 314 frontal cortex, development, 130 in memory, 129 mild stimulation, 60 neural activity in, 62 olfactory bulb connection, 128 psychophysiological response mediation, 54 right prefrontal cortex modulation, 43 subcortical circuit, 55 ventral striatum connection, 27 Androgen replacement therapy, 94 secretion, in males, 110 and sexual behavior, 114–116 Anger; see also Emotions causes of, 400–402 cognitive appraisal approaches, 401–402 reinforcement approaches, 400–401 as emotion, 400 motivational components of, 402–404 asymmetrical frontal cortical activity, 404–408 subjective and behavioral evidence, 402–404 studies, 36, 543 insult treatment, 37 subjective feelings associated with, 408–409 Anger, recalibrational emotion negotiation over WTR values, 265–266 anger program orchestrating aggression and cooperation, 266–269 approach motivations in anger, 269 raising others’ WTRS toward you, 263–265 Anglo-American behavioristic tradition, 73 Animals, sex studies on, 174 Anterior piriform cortex, 128 Antigoal and approach, 386 Anxiety, 35, 53, 192–193, 195, 213, 239 effect on individual, 607 P4 and allopregnanolone, 112 and self-esteem, 506–507, 510 Appetite-aversion distinction, 9–10 Appetitive motivation, 386 Appetitive motivational circuit, 51, 462 Approach and avoidance motivation affects linked to, 389 in animals, motivation examination benefits accelerated life history, 177–178 greater experimental control, 175–176 greater opportunities for observation, 177

greater opportunities to measure physiological parameters, 176–177 application in motivated information processing, 563–564 challenge and threat as, 432–433 clinical disorders to dysregulation, relationship, 379 cross-cultural variation in, 565–566 cultural differences impact of, 563, 566 decisions influence attitude formation and change, 323 desirability of goals, activity theory perspective, 421 cultural differences, 421–422 distinction between, 562, 588 emotional consequences of, 564 evolutionary perspective, for motivation domain-specificity, 275–279 functionality, 274–275 functional trade-offs, 279–280 implications of, 283–284 research adopting, 280–283 feasibility of goals, telic theory perspective, 422–424 findings from animal studies, 178–182 age and experience influences approach, 180 genetic basis, 179 physiology influences approach, 179–180 fundamental asymmetry in behaviors, 327–328 goals, well-being activity theory perspective, 417–419 impacts, 419–420 individual differences in, 420–421 and meaning in life, 419–420 telic theory perspective, 419 hierarchies, multiple perspectives, 499–500 influence in interracial interactions, 571 interracial interactions, group members, 572 link with temporal construal theory, 563 motivation personality dimensions, 167–168, 178–179 in animal, 166 motives dyadic analyses of, 621–622 synergistic (couple level) effects of, 624–627 personality dimensions, disciplines, 174–175 reaction time studies of, 464 approach-related processing, 466–467

657

RT6019X_C039.indd 657

4/9/2008 6:44:57 AM

658

avoidance-related processing, 467–468 designing paradigm and trial, 464–466 processing relative value, 468–470 regulatory focus theory and, 492–493 relationship, 392 specific functions, 393–394 velocity and distinct contributions of, 392–393 research on antecedents of, 169–171 consequences of motivation, 172–173 role in comparison selection, 588 sensitivities, 389–390 social motivation, early examinations, 204 affiliation and intimacy motivation, 205–206 strategic and tactical levels of, 496 empirical evidence, 496–499 when regulating behavior in interracial interactions, 574 Approach-avoidance comparison model, 590, 592–594 Approach behaviors, 386 Approach motivation, 10, 38, 52, 166 androgens and, 120–121 behavioral paradigms, 26 behavior of rejected people, 609 brain mechanism relation with, 27 conditioned approach, Pavlovian, 26 in contemporary literature, 3 DA-ACH theory, 101 definition, 3, 8–9 dopamine and acetylcholine in, feeding and satiety, 92 elementary personality functioning, 542–544 and estrogens, 116–118 fundamental role, 5–8 history, 4–5 individual exclusion, 610 infant, olfactory modulation in infant rats, 130–131 intensity based behavior, in pups, 131 olfactory assessment, benefits, 128 personality functioning and, 544–545 progestins and, 118–119 Schneirla’s view, 128 striatal networks for, 90 vertical interactions, 545–547 Approach-oriented behavior gene association with, 195 situations in which rewards exceed costs, 606 toward developing social relationships, 603 Approach tendencies in childhood, 193 Approach-withdrawal concept, 9, 38 frontal EEG asymmetry, 36–37 left frontal cortex activation, 36 Arc expression, in nucleus, 20 Armamentarium, 52

RT6019X_C039.indd 658

Subject Index

Aspiration tradition level goal discrepancy, 218 outcomes, possibility of, 219 resultant valence theory, 218 Asymmetric War of Attrition, 256, 259, 264 Asymmetry effect, learning of, 330–331 Attention, 211 motivated and personality development approachful and avoidant children, 470–471 attentional control, 471–472 motivational influences on, 462–463 Attentional bias, 244, 465–468, 470 Attentional tuning theory, 237–239 approach and avoidance motor actions, 241–243 rudimentary promotion and prevention foci, 239–241 virtual regulatory foci, 242–245 Attention-deficit/hyperactivity disorder, 379 Attitude acquisition, 324 coexistence of dual attitudes, 514 and expectancies, 394 formation, 323 functionality, 441 learning, 328–330 negative, 573, 580 socially transmitted, 332–333 towards child rearing, 560 colorectal cancer screening, 483 goal, 298 sex, 618 vs. evaluation, 290 Automatic attitudes, 290–291, 293 Aversive motivation, 386 Avoidance achievement motivation and hierarchical model, 226–229 Avoidance affiliation (Aff), 205 Avoidance motivation, 10, 18, 20, 52, 159; see also Approach and avoidance androgens and, 120–121 association, 535 behavioral paradigms of, 20 brain mechanisms relation with, 22–23 classical fear conditioning, 20–21 consequences of approach and, 180 behavioral experimentation, 181–182 learning and migration and movement, 182 predation risk and production of offspring, 180–181 stress and physical health, 180–181 in contemporary literature, 3 DA-ACH theory, 101 definition, 3, 8–9, 547 elementary personality functioning, 542–544 and estrogens, 116–118 factors effecting cultural variation in, 561 fundamental role, 5–8 higher personality functioning, 544–545 history, 4–5

infant, olfactory modulation, 130–132 olfactory assessment, benefits, 128 and progestins, 118–119 Schneirla’s view, 128 sensitivity to symmetry, 604 striatal networks for, 90 trait-anxious individual, 521 vertical interactions, 545–547 Avoidance of closeness, 207 Avoidance-related behavior and gene– environment interaction, 161 AWA, see Asymmetric War of Attrition

B Basal cortisol levels, genetic analysis of, 197 BAS/BIS questionnaire, 500 Basolateral nucleus, 55 Beck depression inventory (BDI), 37 Bed nucleus of stria terminalis, 69 Behavior complex, motor output, 90 defensive, 60 and ethology, 73–74 hippocampal dependent, 130 and hormones, relationship between, 109 self-worth implication, 516 sexual, components, 113 Behavioral activation, 157 Behavioral activation system (BAS), 38, 378, 386, 616 Behavioral approach system (BAS), 157, 210–211, 491, 512 activation of, 521 Behavioral discrepancies, 387 Behavioral dispositions, 316 Behavioral inhibition system (BIS), 38, 157, 159, 210, 378, 491, 512, 616 Behavioral predisposition, 7 Behavior-genetic analysis endophenotypes, 196–197 gene-environment interaction, 195–196 genetic complexities associated with, 198 linkage and association studies, 193–194 allele-sharing methods, 194 genome scans, complication and QTLs, 194 twin method, 188 ADHD and conduct problems, 193 affect regulation analysis, 190–192 anxiety, 192–193 heritability and environmental variance, 189–190 longitudinal genetic model, 192 univariate twin model, 191 Behavior reinforcement system, 94 Big Five taxonomy, 152 Bio-informational theory, 55–56 Biopsychosocial model (BPSM), of challenge and threat, 432–433 general components of, 437 nature and limitations, 437–438 research supporting

4/9/2008 6:44:58 AM

Subject Index

interindividual process, 442–443 intraindividual process, 440–442 resource and demand evaluations, 438–439 task engagement and energization, 438 Brain dopamine (DA) system, 67–68, 79 discovery, in mammalian, 75 psychobehavioral evolutionary function, 83 wanting-type process, 79 fluoxetine effects on, 96 function of, 18 lateralization, 41 mechanism behavior study, tools for lesions and genetic manipulation, 19 neural activity, 19–20 motivational circuits in, 53 neural circuits in, 51 picture processing and, 61–62 primordial emotional system of, 71 psychostimulant addiction, 81 self-stimulation in, 70 posterior hypothalamus, 94 release of DA, 94 stimulus value computation, 18 Brain reward system, 68 British empiricist, on hedonism, 9 BST, see Bed nucleus of stria terminalis Bulimic patient, 102 Buss and perry aggression questionnaire, 37

C αCaMKII, for short term memory, 25 Cardinal principle, of evaluative bivalence, 316 Causal theory of traits, 152 Central nervous system, glial cells in, 111 Cerebral asymmetry, in animals early experience and development, 41 postnatal stimulation, early, 42–43 Cheater detection, 605 Cheerfulness-related emotions, 238 Children’s Behavior Questionnaire (CBQ), 190 Cholinergic receptor, 96 Classical fear conditioning, 20–21 conditioned stimulus (CS) presentation in, 28 lateral nucleus participation, 23 cellular hypothesis of, 24 molecular mechanisms of, 24 in synaptic plasticity, 23 Cognitive activation, 236 Cognitive behavior, 5 Cognitive dissonance, theory of, 588 Cognitive mechanisms, motives, 592 Cognitive psychology, 290–291 Committed relationships, resistance/ dissolution of, 605 Comparison information, selection of, 588

RT6019X_C039.indd 659

659

Compartmentalization, 523–525 for college students, 529 negative, people with, 528 positive, people with, 527 Competence, attainment of, 217 Complex behavior, 385 Computational architecture of sibling detection in humans, see Sibling detection in humans, computational architecture of Conceptual attention, 236 Conditioned potentiation of feeding model, 26–27 Conflicting goal, 424–425 Conscientiousness, 160 Contingencies of self-worth (CSW), 531 Corpus callosum, 69 Corrugator muscle activity, 57 Cortical motor neurons, 316 Corticosterone (CORT), 133 for pups modulation, 134 Corticotropin releasing hormone (CRH), 197 Cortisol production, in social evaluation, 204 Costs and benefits, in decision making, 324–325 CPF, see Conditioned potentiation of feeding CRH gene, 197 Cross-cultural research, in approachavoidance motivation, 562 cultural variation, mechanisms of, 565–566 emotional experience, 564–565 motivated information processing, 563–564 temporal construal theory, 563 Cross-cultural self-enhancement, 558 Cultural differences effect on East Asians and Westerners, 562 impact on approach-avoidance motivation, 563, 566 mechanisms associated with approachavoidance motivation in, 565–566 in temporal construals, 563 Cultural variation, in psychological processes, 566 Cultures and self-regulation, 559

D DA, see Dopamine DA-ACH theory hypothalamic control, 101–102 Decision making of Chinese and Americans, 562 correct and incorrect, 325 costs and benefits relation, 324–325 decision-outcome combinations, 326 false-negative avoidance decisions, 326 for interracial interactions, 572, 579 uncertainty, and risk, 325–326 Defense motivational circuit and system, 51–52

Dejection-related emotions, 238 Depression, 35, 451–452 DA role, 96 effect on individual, 607 maternal, 40 Desire, 81–82 Diagnosticity motive, 509 Differential importance (DI) model, individuals with, 530 Dihydroprogesterone (DHP), 113 Discrepancy-enlarging and reducing feedback system, 512 Discrete emotions, 353 positive vs. negative affect and arousal, 353–354 Discrimination performance, 325 Disliked task, 238 Dispositional mood, 37 Dizygotic (DZ) twins, 190, 198 Domain-specificity, 278 Dopamine, 67, 312 based seeking system, 68–69, 79 behavior activation, 97 in brain mammalian, 75 psychobehavioral evolutionary, 83 tranmission, 80 hypothesis, 91 incentive salience promotion, 79 lateral-hypothalamic/MFB, illumination, 77 learning facility, 71, 79 microdialysis study, 89, 92 in NAc, 92–93 nigrostriatal pathway, 92 participation of, 71 psychobehavioral resources recruitment, 79 role in mania, 96 sensory-motor arousability, 78–79 single-cell recording of, 72 stimulation of, 75 theory, pandemic of, reward signal and prediction, 78–79 theta rhythm intensity, 79 Dopamine-depleting lesion, 27 Dopamine receptor D4 (DRD4), 195 Dorsal anterior cingulated cortex (dACC), 156 Downward comparison theory, 588 DRD4 gene, 161 Drive theory, 21 Dyadic cooperation cheater detection avoidance motivated function in, 605 individual’s ability to benefit from, 605

E Easterbrook hypothesis, arousal on conceptual selection, 236 Egalitarianism, 292, 299 Electrical stimulation of the brain (ESB), 69

4/9/2008 6:44:58 AM

660

Electroencephalographic asymmetrical frontal brain activity, 405–408 asymmetry, frontal (see Frontal EEG asymmetry) baseline and individual differences, 404 and responses to emotion-eliciting stimuli, 404–405 in emotional situations, 405 Electrolytic lesion, 19, 25 Emotional and motivational reactions, factors influencing, 566 Emotional states, from cultural variation, 565 Emotional system and brain affective pictures, response to, 56–58 biological model of, 61 and cognition, 55–56 electroencephalographic expression, 35 intensity of, 61 learning promotion, 72 network, probability of, 56 neural definition, 70 neuroanatomical model of, 54 preservative, 52 priming of, 58–59 processing of, 53–54 unpleasant reactions in humans, 52 withdrawal system, 36 Emotion-related memories, 314 Emotion response syndromes, 354–356 Emotions, 344–347 alternative determinants, 350 anger as, 400 approach vs. avoidance motivation as determinant, 359 determinants of behavior, 348–350 as evolved capacity, 368 families, 356–358 functionalist perspective on, 368–369 rapid response, 369–370 reproductive fitness and sexual selection, 371–373 runaway software, 374–376 social and interpersonal functions, 373–374 specialization and rapid appraisal, 369 function of, 348 incorporation in theories of behavior, 350–351 joy-and-sadness vs. relief-and-distress, 359–361 negative, 464 related dysfunction, 376 emotion and psychopathology, models of, 376 mutation, 377 sneaky value added, 377–378 as transaction, 376–377 research on, 609 types of, 352–353 Encephalization process, 90 Endocrine glands, 110–111

RT6019X_C039.indd 660

Subject Index

Endophenotype concept, 196–197 Energization, 8, 18, 226, 344 approach-avoidance motivation of, 432 integration and evaluation theory, 433 physiological modulation of, 439 task engagement and, 438 Enkephalin mRNA, in rats, 100 ERαexpression, in hypothalamus, 117 Erotophilia and erotophobia, 618 ERPs, see Event-related potentials Erythropoietin, 255 Escape from fear (EFF), 18 advantage, 21 expression, 21 instrumental learning representation, 22 motive circuit, 28–29 tone processing in, 29 Estrogen expression, genes, 113 Ethology and behaviorism, confrontation, 73–74 Evaluations affect and, 290–291 automatic vs. implicit, 291–292 motivation nature of, 300–301 vs. attitude, 290 Evaluative processes, functional neuroarchitecture, 307–308 evaluative space model and, 315–316 nervous system, levels of organization in hierarchical and heterarchical organizations, 310 neural heterarchies, 309–310 neural hierarchies, 308–309 Evaluative space model, 316–318; see also Evaluative processes, functional neuroarchitecture Evaluative substrates re-representation and organization of, 310 higher neural levels, 311–315 intermediate levels, 311 lower levels and pre-motivational functions, 310–311 Event-related potentials, 57 Evolutionary avoidance systems, 604 Evolutionary psychology, 252 Excitation transfer, calculation, 154 Excitotoxic lesion, 19, 27 Expectancy system, 68, 71, 78, 83 Exploratory behavior, 174 Exteroceptive reflex, 52 Extrapair sex, motive effects on, 622 Extraversion, 151–152, 464 theories relating extraversion to positive affect, 155–156 Eysenck Personality Questionnaire (EPQ), 159

F False-negative avoidance, 330 Fearlessness factor, 180 Fear of failure (FF), 220, 222, 227–228

Feeling, 18 Female partner-approval motives, interactions, 627 Festinger’s theory, 588 Fibromyalgia, 388 Field-independence concept, 537 Fight/Flight System (FFS), 378 Food-cup behavior, in rats, 27 Frontal cerebral activation, 36 Frontal EEG asymmetry, 35 activation, differences in, 36 developmental origins of, 38–41 maternal depression, 40–41 moderate stability in, 37, 39 psychopathology and, 38 as trait measure, 40 Functional magnetic resonance imaging (fMRI), 18, 207 Functional stigma avoidance, 604 Fundamental goals, 276

G GABA A-receptor agonist, 19 blocking of androgen, 120 GABAergic inhibition, 42 Gain-loss framing in BeanFest, 332 Gene-behavior relationships, 176 Generalization asymmetry, attitudes, 333–334 Generalized anxiety disorder (GAD), 452–453 Genetic heterogeneity, 193–195, 198 Genetic manipulations brain site-specific molecules, 19 knock-out mices, 176 Genetic relatedness, 257 Gestalt Completion Task (GCT), 242 Glial cells, in nervous system, 111 Glucocorticoid receptors (GRs), 42 Goal-related interpretation biases, 212 Goal-related progress, 387 Goals, alternative dynamics of, 228 Good mothering, 41 G-protein coupled receptors, 129 Gray’s theory of personality, 157 Guilty individual, 607

H Habituation bias, 236 Hallucinations, 454–455 Health behaviors message framing and, 476, 478–479 prevention-and promotion-oriented, 482–484 promoting, health messages framed, 423 real-life, 495 Health communications, 476 Heart rate (HR), 433 Heart-rate variability (HRV), 453 Hedonism concept, 4 ancient Greeks on, 9

4/9/2008 6:44:59 AM

Subject Index

Hierarchical collectivistic cultural environments, 558 High arousal positive (HAP) emotional states, 564 High-neuroticism, 153 Hope of success (HS), 221 Hormones and behaviour, relationship between, 109 Hostile and hospitable stimuli, 307 Human sexual behavior, 616 Hypothalamic pituitary adrenal (HPA), 43, 110, 433 Hypoxia, 255

I Immediate early gene (IEG) expression, 20 Implicit association test, 292–293; see also Automatic attitudes Implicit motives, 222 Incompetence, avoidance of, 217 Informal social communication theory, 587 Innocuously sociable behavior, 603 Insomnia, 452–453 Insult treatment, for anger, 37 Integration, 523–525 negative and positive self-structure, people, 527–528 Interdependence theory, 605–606 Internal and external motivation to respond without prejudice, 574–575 Internal (personal) motivation to respond without prejudice scale (IMS), 574 Internal regulatory variables human kin detection system model and, 261 and motivation, 253–256 theories of adaptive function, role of, 256–257 Interneuron, 91 Interpersonal relationships incentives in, 207–208 threats in, 206–207 Interpretation-comparison model, 590 Interracial interactions approach and avoidance motivations, implications, 572, 578 approach or avoidance concerns in, 579 in contemporary society, 571 egalitarianism in, 577 minority perspective within, 579 and self-regulatory challenges, 572 self-reported goals and strategies for, 575–577 White people, 574, 581 Introverts, 153 Intuitive behavior control (IBC), 536 Investment model theory, 605 In vivo microdialysis, 91–92

RT6019X_C039.indd 661

661

J Junk mail theory, 508; see also Self-deception

K Knee-jerk reflex, 90, 308

L Labile infantile approach, 133–134 Lateral nucleus (LA) EFF learning and, 25–26 role in classical fear conditioning, 23–24 Law of effect, 4 Left visual field (LVF), 244 Level of aspiration (LOA), 218, 585 connections between social comparison and, 587–588 factors contributing to, 586 Liked task, 238 Locus coeruleus, for pups learning, 133 Loneliness, 204 Long-term memory (LTM), 19 MAPK for, 25 Low arousal positive (LAP) emotional states, 564 Low-neuroticism persons, 153

M Male enhancement motives, interactions, 628 Mania, DA role, 96 Marital satisfaction, 212 Mastery-performance goals, 228 Maternal depression, 40 Medial forebrain bundle (MFB), 69 neurons in, 74 self-stimulation of, 70, 72 Medial prefrontal cortex (mPFC), 41 Memory, 211–212 Mental disorder, 447, 449, 455 Mesocortical dopamine system, 69 function, 71 ultrasonic vocalizations, 82 Mesolimbic dopamine system, 69, 82 Mesopontine reticular nuclei (MPR), 69 Message framing, 476, 478–479, 482, 484; see also Health behaviors Microdialysis dopamine for, 89 in vivo, 91 Miller’s approach-avoidance conflict, 317 Mitochondrial benzodiazepine receptors (MBRs), 111 Mitogen activated protein (MAP), 112 Mitral cell, 129 Monosynaptic stretch reflex, 308

Monozygotic (MZ) twins, 189, 198 Morphological measurements, physiological parameters, 176–177 Motivated information processing, 563–564 Motivation, 344–347; see also Approach and avoidance affiliation, 205–206 appetitive/aversive, 352 avoidance, 20 definition, 18 fundamental role, 5–8 DA involvement, 96 determinants of behavior, 348–350 functions of, 348 internal regulatory variables and, 253–254 conscious and nonconscious access to, 255–256 felt experience and, 254–255 intimacy, 206 nature, 509 nucleus accumbens for, 90 reward-maximizing vs. punishmentminimizing, 359–361 and self-esteem, 512 sexual, 113, 617 social-exclusion, effect, 507 strategy for, 52–53 study, 8, 17 for survival, 51 temperament framework for, 462 types of, 351–353 Motivational activation, 54–55 Motivational dispositions, 157 Motivational styles, development of, 560 Motivation and attention, link between, 236 Motive and goal interactions, 228 Motive-charged achievement goals, 227 Motive congruence, 222 Motive effects, gender specificity of, 629 Motives, alternative manifestations of, 228 Motive state, 28 Motor-control goals, 386 mRNA transcription, 112 Muscarinic receptor, 96 Muscimol, 19 Muscle action potentials, 316 Mutations, 257–258

N NAcc, see Nucleus accumbens Naloxone, in rats, 100 National Violence Against Women Survey, 204 Need for achievement (nAch), 219, 228 Need for affiliation (nAff), 205 Need for infavoidance (nInf), 220 Negative affect (NA), 152, 210 Negative attitudes of ethnic minority group members, 580 impact on interracial anxiety, 573 Negative-mood-inducing stimuli, 154

4/9/2008 6:45:00 AM

662

Negative needs, 219 Neophobia, 174 Neuraxis, 308 Neuroanatomical model, 54 Neurological measurements, 177 Neurological receptors, variations in, 179 Neurons, in lateral nucleus, 23 Neuropeptides, in social attachment system, 207–208 Neuroticism, 151–152, 464 cognitive theories of, 157 to negative affect, theories relating, 156–157 serotonin transporter gene 5-HT, activation, 161 Nicotinic receptor, 96 NMDA receptors, 24 Nonsuicidal selfinjury (NSSI), 453–454 Norepinephrine (NE), 55, 70, 75, 91, 102, 129, 138, 463 Nucleus accumbens, 26, 90, 312–313 acetylcholine in, 92, 95 animals, microdialysis probe, 93 cholinergic drugs in, 97 dopamine release in, 28–29, 91–92, 94 fluoxetine delivery, 96 microdialysis for, 89 Nucleus accumbens septi (NAS), 69 Nucleus tractus solitarius (NTS), 93

O Obsessivecompulsive disorder (OCD), 450–451, 454 Olfactory assessment, benefits, 128 Olfactory bulb limbic structures, 128 locus coeruleus (LC), 129 NE release, 133 odor learning, 132 olfactory receptors and, 129–130 pups maturity, 132 Olfactory cortex, limbic structures, 128 Orexin, 70

P Pain, 4 PANAS, see Positive and negative affect scale Parasitic avoidance mechanisms, 604 Paraventricular nucleus, 29, 94 Pavlovian conditioned approach, 26 People preferences, measurement, 292 evaluative priming paradigm, 292–293 explicit measures of prejudice, 292 implicit association test, 293 11-point scale, 292 unintended and nonconscious evaluative responses, 292 Performance prediction, 590 Periaqueductal gray (PAG), 29, 462 project, 60

RT6019X_C039.indd 662

Subject Index

Peripheral nervous system, glial cells in, 111 Personality constructs, integration of, 159–161 development, 470 individual, 536 temperament framework for, 462–464 Phi coefficient, for compartmentalization, 524 Physiological energization and evaluation theory biological component, 433 psychological component and integration, 434 validational studies, 434–436 Picture-story exercise, 220–221 Piriform cortex, in adult odor learning, 132 Pituitary adrenal cortical (PAC) axis, 433 Pleasure, 4 Politeness, 160 Polyandry and Polygyny, 284 Positive affect (PA), 152, 210 Positive and negative affectivity, 152–155 Positive and negative affect scale, 37–38 Positive emotional stimuli, 312 Positive mood inductions, 154 Positive needs, 219 Posterior piriform cortex, 128 Posttraumatic stress disorder, 449–450 Prejudice explicit measures of, 292 implications for, 334–336 Pre-motivational functions, 310 Preservative emotion, 52 Priming emotion, 58–59 Primordial emotional system, 71 Principle components analysis (PCA), calves’ scores, 179 Private body consciousness, 223 Promotion vs. prevention focus, 332 Propylene glycol vehicle, 118 Protozoa, approach and avoidance exhibition by, 6 Proxy model predictions, 589 PSE, see Picture-story exercise PSI theory, personality levels affect (personality functioning), 538 negative and positive, 539–540 approach and avoidance motivation role, 541 automatic and intuitive, 542 complex cognition, 539 elementary cognition, 536–537 incentive motivation, 543 individual temperament, 537–538 integration, 539 personal goals, 541 motive, individual, 538–539 progression vs. regression, 538 Psychiatric epidemiology, 199 Psychobehavioral tendency, of animals, 73 Psychogenic needs, 219 Psychological processes, cultural variation in, 566 Psychopathology

approach and avoidance emotional models of, 378–380 in approach and avoidance sensitivities, 389 and frontal EEG asymmetry, 38 suppression and, 448–449 PTSD, see Posttraumatic stress disorder PVN, see Paraventricular nucleus

Q Quality Adjusted Life Years (QALYs), 324 Quantitative trait loci (QTLs), 194

R Reappraisal repair strategy, 155 Reciprocal innervation, 308–309 Redundancy bias, 236 Reflexive response, 4 Regulatory fit theory, 566 Regulatory focus approach and avoidance levels in, 492–493 attentional tuning theory and, 239, 241–243 and emotional arousa, 244 maze manipulation of, 240, 244 promotion and prevention, 326 self-guide strength measurement, 495 system–strategy distinction in, 493–496 Regulatory focus theory (RFT), 238, 479, 492, 494, 496–497, 499 Reinforcement sensitivity theory (RST), 157 Relationship-relevant motives, 205 Relationships incentives in, 207–208 threats in, 206–207 Remote associates task (RAT), 440 Retrieval-induced forgetting, 242 Reward-directed behavior, 161 Risk acceptance and aversion, antecedents of, 326–327 Risk aversion, 328 Risk-taking behavior, 174 Roman high avoidance (RHA), 176 Roman low avoidance (RLA), 176 Romantic relationships, 606 Rosenberg self-esteem scale (RSES), 514 Rusbult’s investment model, 606

S SAD, see Social anxiety disorder SAM, see Sympathetic neural and adrenal medullary Seeking system, 67, 77 aid to animals, 68 dopamine based, 69, 79 framework, 68–69 instinctual action, 71

4/9/2008 6:45:00 AM

Subject Index

MFB self-stimulation, for animals, 73 primordial emotional system, 71 Selective breeding of population, 175–176 Self-attributed motives, 222 Self-complexity individuals, components, 529–530 Self-deception Calvinist approach, 507 information manipulation, 508 Self-defeating mental control technique, 456 Self-determination, 222 Self-enhancement definition of, 558 responses in Western and East Asian people, 559 Self-esteem, 207, 440 and anxiety, 510 BIRGing and social comparison strategy, 516 California citizens, 510 compartmentalized individuals, 526 and emotional response system, 608 functions, 506–507 individuals with high, 511, 513, 517, 608 with low, 511–515 individuals instability, 530–531 and self-deception, 508 trait differences in, 511–513 Self-evaluation maintenance (SEM) theory, 508–509, 516 Self-evaluations and happiness, 336–337 Self-handicapping benefits, 513 effect on success, 513 Self-inflicted mortality, 204 Self-injurious thoughts and behaviors (SITB), 453–454 Self-monitoring, 223 Self-regulation function, 608 Self-schema, 222 Self-stimulation reward, phases, 74 Self-verification, individuals, 532 Self-verification motive, 509 Serotonin-1A receptor, 97 Sex approach motives for, 618 avoidance motives for, 619–620 negative emotional responses to, 619 Sexual behaviors androgens and, 114–116 classes of motivations for, 617 components, 113 factor analytic work, 617 of females, 114 intrapersonal motives and social motives, 617 limitations of studying individuals, 620–621 motives underlie, 616–618 partner’s approach and avoidance motives for sex, 622–624 Sexual functioning, 625 Sexually transmitted infections, 616

RT6019X_C039.indd 663

663

Sexual motivations, 618 Sexual permissiveness, 620 Sexual value index, 260 Sherrington’s alliance of reflexes, 309 Short-term memory (STM), 19 Sibling detection in humans, computational architecture of degree of relatedness and altruism, 258–260 and inbreeding depression, 257–258 kinship index computation altruistic motivation system, 261 sexual motivation system, 260–261 triangulation, 261–262 Signal detection theory (SDT), 325 Simple ego type life (SELF), 77 Single nucleotide polymorphisms (SNPs), 194 Snowy Pictures Test (SPT), 240, 242 Social anxiety disorder, 603–604, 608 Social comparison connections with LOA, 587–588 development of conceptual models for, 590 reconceptualization of, 586 Social comparison theory, 515, 587 Social contact, 155 Social evolution, genetic relatedness in, 257 Social information, 211–212 Social interactions comparison and facilitation, 442 individual unfit for, 604 Social-interpersonal goals, 388 Social isolation, 204 Socially transmitted attitudes, 332–333 Social motives and goals approach and avoidance model of, 208–210 processes mediating, 210 ambiguous social information, interpretation of, 212 attention, 211 memory, 211–212 progress on goals, evaluation of, 212–213 social information, weight of, 212 Social reference standards, role of, 586 Social relationship development, 602 direct forms of, 603–605 in relationship partners, 605–606 Sociometer theory, 506, 510–511, 517; see also Self-esteem Sovereign masters, 4, 293 Spinal reflex circuits, 308 Startle reflex inhibition, 59 interneuron, 91 menstrual cycle, 110 potential, 58, 60 Stereotype threat, 443 Steroid hormones, 109 cholesterol from, 110 HPA axis modulation, 110

mechanisms of, 112–113 placenta in pregnancy, 111 secretion, 111 sex differences, 110 in vertebrates, 110 Stigma consciousness in black people, 581 function of, 604 and socio-economic status, 442 Stigmatization, function of, 604 STIs, see Sexually transmitted infections Stretch reflexes, 309 Striatum, in memory system, 90 Suppression alcohol use, abuse and, 453 and depression, 451–452 and dreams, 455–456 in generalized anxiety disorder, 452–453 and insomnia, 452–453 mental disorder and, 455 and obsessive compulsive disorder, 450–451 and posttraumatic stress disorder, 449–450 and psychopathology, 449 and psychosis, 454–455 and self-injurious thoughts and behaviors, 453–454 of unwanted thoughts, 448–449 Sympathetic neural and adrenal medullary, 433 Synthetic obsessions, 449 Syphilis, 113

T Tactics, for motivation, 52–53 Taste hedonics, 311 Tastes, 290 Taste-sensory cortex, 90 Terror management theory (TMT), 506–507, 510, 517; see also Self-esteem Thematic Apperception Test (TAT), 205–206, 220 Theories of achievement, 566 Threat inclusion, 606 Tiwi society, in evolutionary perspective implications, 284 Total systemic peripheral vascular resistance (TPR), 433 Trait-anxious individual, 521 Trait dispositions, 151 True happiness, 416 Tufted cell, 129 Two-factor theory, 21

U Ultrasonic vocalizations (USVs), 81–82 Uncommitted sex, 618 United States, self-esteem movement in, 510

4/9/2008 6:45:00 AM

664

Unwanted thoughts, suppression of, 448–449 characteristics of, 448 cognitive load and asymmetric priming, 449 hyperaccessibility, 448

Subject Index

Violence in relationships, 207 Virtue, 416 Viscerogenic needs, 219

W V Value extremity, 331–332 Velocity and affective potency, 387–389 Ventral tegmental area (VTA), 29, 68, 92 based DA circuits, 79

RT6019X_C039.indd 664

Wanting concept, 75 Wanting-type process, in brain, 79 Welfare trade-off ratio (WTR), 254, 259–260, 264–269 Well-being

approach and avoidance goals in, 417 life satisfaction, contributor to, 416 motivation, central to activity and telic theories, 416–417 Wisconsin Twin Project (WTP), 190

Z Zygomatic muscle activity, 57

4/9/2008 6:45:00 AM

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Motivation: A Biobehavioural Approach

Handbook of Motivation and Cognition Across Cultures

Handbook of Motivation at School (Educational Psychology Handbook)

Psychology of Learning and Motivation

Handbook of Motivation and Change: A Practical Guide for Clinicians

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