Handbook of Youth Prevention Science
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Handbook of Youth Prevention Science
The Handbook of Youth Prevention Science describes current research and practice in mental health preventive interventions for youth. Traditional prevention research focused on preventing specific disorders, e.g., substance abuse, conduct disorders, or criminality. This produced “silos” of isolated knowledge about the prevention of individual disorders without acknowledging the overlapping goals, strategies, and impacts of prevention programs. This handbook reflects current research and practice by organizing prevention science around comprehensive systems that reach across all disorders and all institutions within a community. Throughout the book preventive interventions are seen as complementary components of effective mental health programs, not as replacements for therapeutic interventions. Key Features: Comprehensive—This handbook is the first to bring together and integrate the important work that is currently being conducted on comprehensive youth prevention programs that cut across all mental health disorders and practice disciplines. Evidence-Based—The focus throughout is on the science of prevention and how that science informs the theory, practice, and methodology related to preventive interventions with youth. Issue-Oriented—Contemporary debates about the research-to-practice gap in prevention science are carefully examined, including issues of practice fidelity, program dissemination, taking programs to scale, and infrastructures needed for effective prevention practices. Definition of Mental Health—Outcomes of youth prevention programs are broadly described as the promotion of psychological wellness in addition to the prevention of youth maladjustment. Expertise—The lead editor (Beth Doll) is well known for her research on school-based prevention, particularly for interventions that enhance the school learning environment. She chaired the National Association of School Psychologists’ (NASP) Presidential Taskforce on Prevention. This book is suitable for researchers, instructors, and graduate students in the child and adolescent mental health professions: school psychology, school counseling, special education, school social work, child clinical psychology, and the libraries serving them. It is also suitable for graduate course work in these fields. Dr. Beth Doll is a Professor and Director of the School Psychology program at the University of Nebraska–Lincoln. Dr. William (Bill) Pfohl is a Professor of Psychology at Western Kentucky University in Bowling Green, Kentucky. Dr. Jina Yoon is Associate Professor and Co-Director of the School and Community Psychology program at Wayne State University in Detroit, Michigan.
Handbook of Youth Prevention Science
Edited by Beth Doll William Pfohl Jina Yoon
First published 2010 by Routledge 270 Madison Ave, New York, NY 10016 Simultaneously published in the UK by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN Routledge is an imprint of the Taylor & Francis Group, an informa business This edition published in the Taylor & Francis e-Library, 2010. To purchase your own copy of this or any of Taylor & Francis or Routledge’s collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk. © 2010 Taylor and Francis All rights reserved. No part of this book may be reprinted or reproduced or utilized in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing 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 Handbook of youth prevention science/Beth Doll, William Pfohl, Jina Yoon, editors. p. cm. Includes bibliographical references and index. 1. School mental health services. 2. School children— Mental health services. 3. Problem children—Education. 4. Child psychology. 5. Educational counseling. I. Doll, Beth, 1952– II. Pfohl, William. III. Yoon, Jina. LB3430.H37 2010 371.7'13—dc22 2009035360 ISBN 0-203-86641-X Master e-book ISBN
ISBN 10: 0–8058–6331–1 (hbk) ISBN 10: 0–8058–6332–X (pbk) ISBN 10: 0–203–86641–X (ebk) ISBN 13: 978–0–8058–6331–4 (hbk) ISBN 13: 978–0–8058–6332–1 (pbk) ISBN 13: 978–0–203–86641–2 (ebk)
This handbook is dedicated to Jean A. Baker, who would have been one of our co-editors if she had not died in January 2008. She was a wise and caring colleague, and was so very young to die.
Contents
Figures and Tables 1 The Current Status of Youth Prevention Science
x 1
BETH DOLL, UNIVERSITY OF NEBRASKA–LINCOLN JINA YOON, WAYNE STATE UNIVERSITY
2 Placing Prevention into the Context of School Improvement
19
HOWARD S. ADELMAN AND LINDA TAYLOR, UNIVERSITY OF CALIFORNIA, LOS ANGELES
3 School Mental Health: Prevention at All Levels
45
KEVIN DWYER, AMERICAN INSTITUTES FOR RESEARCH ERIKA VAN BUREN, DISTRICT OF COLUMBIA DEPARTMENT OF MENTAL HEALTH
4 Screening for Mental Health and Wellness: Current School-Based Practices and Emerging Possibilities
70
ERIN DOWDY, MICHAEL FURLONG, KATIE EKLUND, ELINA SAEKI, AND KRISTIN RITCHEY, UNIVERSITY OF CALIFORNIA, SANTA BARBARA
5 Implementing Universal Screening Systems Within an RtI-PBS Context
96
HILL M. WALKER AND HERBERT H. SEVERSON, OREGON RESEARCH INSTITUTE AND THE UNIVERSITY OF OREGON GALE NAQUIN AND CYNTHIA D’ATRIO, UNIVERSITY OF NEW ORLEANS EDWARD G. FEIL, OREGON RESEARCH INSTITUTE LEANNE HAWKEN AND CHRISTIAN SABEY, UNIVERSITY OF UTAH
6 Building Conditions for Learning and Healthy Adolescent Development: A Strategic Approach
121
DAVID OSHER AND KIMBERLY KENDZIORA, AMERICAN INSTITUTES FOR RESEARCH
7 Assessment for Integrated Screening and Prevention Using the Resiliency Scales for Children and Adolescents
141
SANDRA PRINCE-EMBURY, THE RESILIENCY INSTITUTE OF ALLENHURST, LLC
8 Social Support: How to Assess and Include It in Research on Prevention and Youth Outcomes MICHELLE K. DEMARAY, CHRISTINE K. MALECKI, LYNDSAY N. JENKINS, AND CHRISTY M. CUNNINGHAM, NORTHERN ILLINOIS UNIVERSITY
163
viii Contents 9 Peer Support as a Means of Improving School Safety and Reducing Bullying and Violence
177
HELEN COWIE, UNIVERSITY OF SURREY PETER K. SMITH, GOLDSMITHS, UNIVERSITY OF LONDON
10 The Developmental Implications of Classroom Social Relationships and Strategies for Improving Them
194
JAN N. HUGHES AND LISA K. BARROIS, TEXAS A&M UNIVERSITY
11 Factors Influencing Teacher Interventions in Bullying Situations: Implications for Research and Practice
218
JODI BURRUS NEWMAN, KARIN S. FREY, AND DIANE CARLSON JONES, UNIVERSITY OF WASHINGTON
12 Development, Evaluation, and Diffusion of a National Anti-Bullying Program, KiVa
238
CHRISTINA SALMIVALLI AND ANTTI KÄRNÄ, DEPARTMENT OF PSYCHOLOGY, UNIVERSITY OF TURKU ELISA POSKIPARTA, CENTRE FOR LEARNING RESEARCH, UNIVERSITY OF TURKU
13 Promoting the Well-Being of School Communities: A Systemic Approach
253
CHRYSE HATZICHRISTOU, KONSTANTINA LYKITSAKOU, AIKATERINI LAMPROPOULOU, AND PANAYIOTA DIMITROPOULOU, UNIVERSITY OF ATHENS, GREECE
14 Promoting Student Resilience: Strong Kids Social and Emotional Learning Curricula
273
OANH K. TRAN, CALIFORNIA STATE UNIVERSITY, EAST BAY KENNETH W. MERRELL, UNIVERSITY OF OREGON
15 Stimulating Positive Social Interaction: What Can We Learn from TIGER (Kanjertraining)?
286
LILIAN VLIEK, INSTITUTE OF KANJERTRAINING, ALMERE, THE NETHERLANDS BRAM OROBIO DE CASTRO, UTRECHT UNIVERSITY, UTRECHT, THE NETHERLANDS
16 A Hybrid Framework for Intervention Development: Social Justice for Bullying in Low-Resource Schools
307
SAMUEL Y. SONG, SEATTLE UNIVERSITY WAKAKO SOGO, UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL
17 Check & Connect: Enhancing School Completion Through Student Engagement
327
SANDRA L. CHRISTENSON, UNIVERSITY OF MINNESOTA AMY L. RESCHLY, UNIVERSITY OF GEORGIA
18 Prevention and Early Intervention for Preschool Children at Risk for Learning and Behavior Problems MARIBETH GETTINGER, CARRIE BALL, LAURA MULFORD, AND ALICIA HOFFMAN, UNIVERSITY OF WISCONSIN–MADISON
349
Contents ix 19 Partnering to Achieve School Success: A Collaborative Care Model of Early Intervention for Attention and Behavior Problems in Urban Contexts
375
THOMAS J. POWER, HEATHER JONES LAVIN, JENNIFER A. MAUTONE, AND NATHAN J. BLUM, THE CHILDREN’S HOSPITAL OF PHILADELPHIA, UNIVERSITY OF PENNSYLVANIA SCHOOL OF MEDICINE
20 Dissemination of Evidence-Based Programs in the Schools: The Coping Power Program
393
JOHN E. LOCHMAN, NICOLE R. POWELL, CAROLINE L. BOXMEYER, AND RACHEL BADEN, UNIVERSITY OF ALABAMA
21 Prevention, Early Childhood Intervention, and Implementation Science
413
SAMUEL L. ODOM, UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL MARCI HANSON, SAN FRANCISCO STATE UNIVERSITY JOAN LIEBER, UNIVERSITY OF MARYLAND KAREN DIAMOND, PURDUE UNIVERSITY SUSAN PALMER, UNIVERSITY OF KANSAS GRETCHEN BUTERA, INDIANA UNIVERSITY EVA HORN, UNIVERSITY OF KANSAS
22 Taking Effective Prevention to Scale
433
BRIAN K. BUMBARGER, DANIEL F. PERKINS, AND MARK T. GREENBERG, PENN STATE UNIVERSITY
23 Youth Policy and Politics in the United States: Toward an Increased Focus on Prevention
445
SIOBHAN M. COONEY, THOMAS R. KRATOCHWILL, AND STEPHEN A. SMALL, UNIVERSITY OF WISCONSIN–MADISON
Editors Contributors Index
461 462 469
Figures and Tables
List of Figures 2.1
2.2 2.3 2.4 2.5 4.1 5.1 5.2 5.3 5.4 6.1 6.2 6.3 6.4 6.5 7.1 7.2 7.3 7.4 7.5 11.1 12.1 13.1 14.1 15.1
From Primary Prevention to Treatment of Serious Problems: A Continuum of Community-School Programs to Address Barriers to Learning and Enhance Healthy Development A Continuum of Interconnected Systems for Meeting the Needs of All Students Toward a Comprehensive System for Addressing Barriers to Learning: Moving from a Two- to a Three-Component Framework for School An Enabling Component to Address Barriers, Re-engage Students in Classroom Instruction, and Enhance Healthy Development at a School Site Intervention Content Arenas Overview of Subjective Well-Being Sample Student Risk Screening Scale (SRSS) Screening Form for an Entire Class SWIS Office Discipline Referral Form SSPD/ESP Multiple Gating Procedure Preventing Violent and Destructive Behavior in Schools “Student Connection Survey” (aka Conditions for Learning Survey) Score Report to Schools Mean Conditions for Learning Scores for Middle Grades and High School Correlation Between PSAE Subscales and Conditions for Learning Scales (Grade 11) Correlation Between Conditions for Learning and GPA Scores (High School) Conditions for Learning Scores by On Track Status (Grade 9 Students) Resiliency Profiles for Bobby, Linda and Joe Resiliency Profiles for Clinical and Non-Clinical Adolescent Groups Emotional Reactivity Subscale Profiles Sense of Mastery Subscale Profiles Sense of Relatedness Subscale Profiles Relationships Affecting Teacher Interventions in Bullying Situations A Scene from the KiVa Computer Game (“I Can” Component), Version for Grade Levels 4–6 A Synthetic Approach to School Community Well-Being Prevention of Mental Illness Through Continuum of Supports Positive Social Interaction
22 23 26 27 28 84 100 103 105 108 125 130 130 131 132 150 151 155 156 158 220 241 256 275 300
Figures and Tables xi 15.2 15.3 15.4 15.5 15.6 15.7 15.8 15.9 15.10 15.11 15.12 15.13 15.14 16.1 16.2 18.1 18.2 18.3 19.1 21.1
Self-Esteem Aggressive Behavior Depressive Thoughts Perceived Social Acceptance Relationship with the Teacher Emotional Well-Being Positive Social Interaction Self-Esteem Aggressive Behavior Depressive Thoughts Perceived Social Acceptance by Classmates Relationship with the Teacher Emotional Well-Being Hybrid Intervention Manual Development Protective Peer Ecology Framework in Schools EMERGE Multi-Tier Intervention Hierarchy EMERGE and Control Children’s Performance on Emergent Literacy Measures FACET Steps and Outcomes Effective Intervention for a Child with ADHD Typically Involves a Partnership Involving the Family, School, and Primary Care Practice Elements of the Implementation Process
300 300 300 301 301 301 301 302 302 302 302 303 303 312 317 361 363 368 378 418
List of Tables 2.1 3.1 4.1
4.2 4.3 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8
Outline Aid for Analyzing Key Facets of School-Oriented Prevention Efforts Percentage of Schools Providing Various Mental Health Services by School Level, 2002–2003 Percentage of Students by Grade Level and Survey Cohort Year Who Felt So Sad or Hopeless Almost Every Day for Two or More Weeks in a Row That They Stopped Doing Some Usual Activities During the 12 Months Before the Survey from Youth Risk Behavior Surveillance Survey 1999–2007 Content and Psychometric Properties of Omnibus Youth Mental Health Screening Instruments Mental Health Screening Implementation Considerations Number and Percentage of Students in the Chicago School District and in the Surveyed Sample by Student Demographics Middle Grades: Correlations Among Conditions for Learning Constructs High School: Correlations Among Conditions for Learning Constructs School Level Correlations Between Conditions for Learning Constructs and the Logarithm of Enrollment Correlations Between School Safety, School Suspensions, and the Number of Suspended Students Correlations Between School Safety and Neighborhood Crime Correlations Between Challenge (and other Conditions for Learning Constructs) and Dropout School Level Correlation Between Conditions for Learning Constructs and the Average Class Size in High School
20 51
73 77 88 128 128 129 132 133 134 134 135
xii Figures and Tables 6.9 7.1 7.2 7.3 8.1 8.2 10.1 10.2 12.1 12.2 12.3 13.1 13.2
13.3 13.4 13.5 13.6 15.1 17.1 17.2 17.3 17.4 19.1 19.2 23.1
Correlations Between Graduation Rates and Conditions for Learning Constructs T-Score Ranges for the Vulnerability Index and Cumulative Percentages by Age Band RSCA Screening Model 1: Individual Level Screening Model II for Aggregate Classroom Level Six Commonly Used Measures of Social Support in Youth Reliability and Validity Evidence for the Six Most Commonly Used Social Support Scales in Youth Study Characteristics Evaluation of Studies The Core Components (Universal and Indicated Actions) of the KiVa Anti-Bullying Program The Study Sample in the Two Phases of Program Evaluation Diffusion of KiVa: Strategies to Promote the Dissemination, Adoption, Implementation, and Maintenance of the Program Frequencies of Children’s Pre–Post Responses to Indicative Open Questions of the Thematic Units “Communication Skills” and “Self Concept” Pre–Post Comparisons of Students’ Responses to an Open Question of the Unit “Identification, Expression and Management of Emotions” for the Experimental and Control Group, for Migrant and Native Students (Athens Sample), and for Students with Low and High Peer Acceptance (Cypriot Sample) Pre–Post Comparisons for Items of the Thematic Unit “Diversity and Culture” Comparison of Social Skills of Students After One and Two Years of Participation in the Program Pre–Post Comparisons of Teachers’ Evaluation of Sense of Community Pre–Post Comparisons of Teachers’ Evaluation of Competence Descriptive Statistics for Outcome Measures of Training and Control Group Core Elements of Check & Connect Model of Student Engagement Alterable Variables Associated with School Dropout Guidelines for Establishing Criteria for Intensive Interventions Illustrative Examples of Student Connect Intensive Interventions Components of PASS Family Involvement in Each Component of PASS Strategies for Bringing a Preventative Focus to Youth Policy
135 151 152 154 171 172 200 202 242 244 246 264
265 265 266 266 267 299 330 336 338 339 382 385 451
1
The Current Status of Youth Prevention Science Beth Doll, University of Nebraska–Lincoln Jina Yoon, Wayne State University
Youth prevention science is the empirically rigorous examination of practices that prevent psychosocial disturbances or promote psychological wellness in children and adolescents. These include careful examinations of the outcomes of policies and preventive interventions; and developmental investigations of the correlates, moderators, and mediators of youth disturbance or competence that provide the conceptual and theoretical underpinnings for preventive interventions. In its earliest incarnation, the prevention of psychosocial maladjustment in youth was termed the “mental hygiene” movement, drawing parallels between practices to strengthen psychological wellness in youth and community practices that promote physical health by cleaning the water and containing community waste and sewage (Hosman, Jane-Liopis, & Saxena, 2005). However, many prominent preventionists maintain that the science of youth prevention did not truly emerge until 1986 when the National Mental Health Association (NMHA) published its Commission Report recommending that youth prevention efforts be strengthened (Commission on the Prevention of Mental/Emotional Disabilities, 1987). Albee (1996) believes that the origins began at least 10 years earlier. His own commitment to prevention science began when he worked with the 1960 Joint Commission on Mental Illness and Health, tasked with evaluating the United States’ mental health needs and resources and making recommendations for a national mental health program. He became convinced that, “No amount of research on treatment, even if resulting in success, can reduce incidence (rate of new cases)” (Albee, 2005, p. 313). He dates the birth of modern prevention science to the 1960s and 1970s when ambitious social programs were implemented to counteract the effects of poverty, prejudice, and other socially toxic stressors in the United States. A classic example of such social programs is the early intervention with preschool children that began in the United States during the 1960s (Gettinger, Ball, Mulford, & Hoffman, this volume; Odom, Butera, Horn, Palmer, Diamond, & Lieber, this volume). By 1977, during Jimmy Carter’s presidency, education and social engineering were identified in a report of the President’s Commission on Mental Health as important strategies to prevent social disturbances and promote psychological wellness. This socioecological perspective on youth prevention science was shared by the NMHA’s commission when it specifically recommended comprehensive, multi-agency community programs to ensure that all babies were healthy and wanted, prevent adolescent pregnancy, integrate promotion of psychosocial competence into school programs, and help children and adults cope effectively with adversity (Commission on the Prevention of Mental/Emotional Disabilities, 1987).
2 Beth Doll and Jina Yoon
Definitions of Prevention Science Discussions of youth prevention research are inevitably complicated by inconsistent use of terms caused, in part, by the imperfect fit of borrowed medical terms to the sociopsychological phenomenon of youth prevention (U.S. Department of Health and Human Services, 1999). For example, primary prevention, secondary prevention, and tertiary prevention are classic terms attributed to the Commission on Chronic Illness (1957). Primary prevention refers to the prevention of diseases before they develop, secondary prevention refers to prevention of diseases’ worsening or recurrence, and tertiary prevention describes reductions in the functional impact of diseases subsequent to their development. These terms were widely adopted by mental health professionals to describe youth prevention programs, such as the Primary Mental Health Project (Cowan, 1994). Still, prevention researchers and practitioners were troubled by the terms’ implicit assumption that a disease was being prevented. Critics of the terms detailed multiple respects in which medical models were a poor fit for social, emotional, and educational prevention efforts. Four principal arguments were emphasized in these debates: First, a focus on preventing diseases implies that health is the absence of disease. Critics of medical models argued, instead, that authentic definitions of social and psychological health must describe the characteristics of wellness and competence in addition to diagnostic criteria of pathology. Some researchers used the term “primary prevention” as an umbrella term to describe health promotion as well as disease prevention, but others did not follow suit, arguing that the terms had been contaminated by their emphasis on disease. Second, a focus on preventing disease suggests that the purpose of services is to cure or eliminate disorders so that the youth can proceed through life “disease-free.” Critics of medical models endorse an alternative purpose of strengthening youths’ functional competence to meet the demands of their daily lives regardless of whether pathological symptoms of disorders are reduced or eliminated (Albee 1996; Biglan, 2004). Others broaden the purpose of youth prevention to include influencing “problems” that impair youths’ capacities to succeed in their daily lives and not just preventing “mental disorders” as defined within the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision, American Psychiatric Association, 2000). Third, a focus on preventing disease requires that the presence or absence of a disorder be reliably identified. Diagnostic reliability, difficult enough within physical medicine, is often elusive within psychological disorders (Kaplan, 2000). Diagnostic criteria included in the DSM frequently require subjective judgments about the strength of a symptom from imprecise descriptions of the person or members of their family. Moreover, diagnoses do not always lead to effective treatment; they are not always correct; and they are not essential when problems are the result of risky behaviors or environmental risk rather than mental disorders. Fourth, researchers concur that investigations describing the correlates, occurrence, or non-occurrence of a disorder are not sufficient to support a mature prevention science. Instead, effective prevention strategies require understanding the causes and mechanisms underlying negative life outcomes so that it is possible to alter or shift these mechanisms and increase the likelihood of positive outcomes (U.S. Department of Health and Human Services, 1999). In the face of these and other criticisms, the Institute of Medicine convened a Committee on the Prevention of Mental Disorders and charged them with the task of reviewing the status of mental health prevention research (Mrazek & Haggerty, 1994). That committee’s report recommended that the term “prevention” be reserved for services provided before a mental
The Current Status of Youth Prevention Science 3 disorder is present, and proposed the alternative terms of universal, selective, and indicated prevention which they had adopted with some modification from the earlier work of Gordon (1983). Within their spectrum of mental health services, universal prevention described preventive interventions provided to everyone in a community or group; selective prevention described services provided to those members of a group who were at higher-than-average risk for a mental disorder; and indicated prevention described services provided to group members at high risk for a mental disorder and who already evidenced some symptoms of a disorder, although without meeting the disorder’s full diagnostic criteria. (In current terminology, some researchers also use the word “targeted” instead of “indicated.”) Although the committee intended to provide a common language across prevention researchers and practitioners, its recommendations were widely criticized because the definitions continued to presuppose medical models of prevention and failed to acknowledge the importance of wellness promotion (Albee, 2004; Kaplan, 2000; Weissberg, Kumpfer, & Seligman, 2003). The American Psychological Association’s Task Force on Prevention endorsed a broader definition that incorporated both. Alternatively, Weisz, Sandler, Durlak, and Anton (2005) attempted to reconcile the wellness promotion and disease prevention models of mental health prevention by proposing a mental health intervention framework that included wellness promotion, universal prevention, selective prevention, indicated prevention, and therapeutic intervention. At the same time as these definitional debates have raged within youth prevention science, schools have been rapidly moving to adopt a population-based model of prevention actualized into a three-tier approach in which the first tier is universal services, the second tier includes selective services to youth who evidence early signs of emotional or behavioral problems, and the third tier includes indicated services for students with significant emotional and behavioral problems (Dwyer & Van Buren, this volume; Osher et al., this volume; Walker et al., this volume). These tiers of intervention are frequently framed within a Response-toIntervention model in which youth are identified for progressively more intense services based on data showing that their response to less intensive interventions was inadequate (Cooney, Kratochwill, & Small, this volume). Because these data can be used to describe either negative markers of maladjustment or positive indicators of student competence, educational threetier approaches can be framed as preventing disabilities or promoting developmental competence. The three-tier approaches are represented within the U.S. Individuals with Disabilities Education Act as strategies to prevent educational disturbances and interrupt premature identification of students for special education services. These definitional debates are not esoteric but are grounded in the very real dilemma that funding mechanisms outside of education are often wedded to the medical models of youth prevention, at least in the United States, despite the consensus among youth prevention scientists that prevention practices and research must emphasize socioenvironmental perspectives (Albee, 2004). The emphasis on promoting competence and diminishing the impact of environmental adversity is strikingly different from National Institute of Mental Health’s commitment to a program of well-controlled research designed to systematically examine the impact of preventive interventions on the emergence of psychopathology (Mrazek & Haggerty, 1994). NIMH funding explicitly excludes programs to promote psychosocial wellness and focuses instead on biological models of causation and particularly on neurobiological causes of specific mental disorders. Moreover, priorities in mental health funding in the United States continue to emphasize programs to treat psychopathology over prevention programs (Cooney et al., this volume). At the same time, social-environmental frameworks are highly compatible with public education’s mission to promote the success of all youth. One likely outcome is the emergence of at least two competing frameworks for youth prevention
4 Beth Doll and Jina Yoon science—one operating within population-based agencies such as public schools and another dominant within health service agencies. Dwyer and Van Buren (this volume) make a more optimistic prediction—that with time, researchers will come to understand that the two perspectives (environmental supports for wellness and biological contributions to psychopathology) are not truly competing.
Conceptual Foundations for Youth Prevention Since 1980, developmental research has shed light on the complex phenomenon of child and adolescent mental health and their developmental competence (Bumbarger, Perkins, & Greenberg, this volume). In particular, cumulative knowledge from developmental psychopathology and epidemiology research has contributed to the conceptual foundations for youth prevention science. In the United States, epidemiological research in developmental psychopathology has significantly altered estimates of the prevalence of mental disorders in youth. Whereas pre-1980 estimates of childhood mental illness suggested that between 5% and 7% of school-aged children met the criteria for one or more mental disorders described by the Diagnostic and Statistical Manual of Mental Disorders (4th Edition; American Psychiatric Association, 1996), epidemiological studies funded by the National Institute of Mental Health consistently identified between 18% and 22% of their community samples as meeting the criteria for psychopathology (Doll, 1996; U.S. Department of Health and Human Services, 1999). The functional impact of these mental disorders on children’s developmental success has not been fully described by researchers, but the relevance of psychological health and wellness to subsequent adult success is amply documented. The striking prevalence of psychopathology among youth is particularly alarming, given that early signs of maladjustment often proceed to later difficulties in educational, social, and occupational roles during adolescence and adulthood. Results of these epidemiological studies emphasized the importance of very early intervention to promote psychological wellness and prevent long-term disturbances. When prevention research identifies the early warning signs that place children at a higher risk of failure, early preventive interventions can be more effective and less costly than therapeutic interventions provided once children meet diagnostic criteria for a disorder. Moreover, epidemiological evidence for incidence, prevalence, and severity of youth problem behaviors provides important direction so that communities can “systematically prioritize child and adolescent problems in terms of their cost and the likely benefits of preventing each of them” (Biglan, Mrazek, Carnine, & Flay, 2003, p. 433). As such, epidemiological research strategies are critical in evaluating the effectiveness of prevention efforts and ensuring that prevention approaches are guided by evidence. As a second contribution, the field of developmental psychopathology has documented a number of individual characteristics and contextual variables that are responsible for the different forms and severity of developmental maladjustment (Mash & Dozois, 2003). One important finding from this research is that socioecological features of children’s lives are as important as individual child characteristics in predicting children’s healthy development or the incidence and severity of psychopathology (Coie et al., 1993; Doll & Lyon, 1998; Werner, 2006). For example, children’s exposure to poverty, family violence, parental psychopathology, or community violence significantly increases their chances of developing a debilitating mental illness, while their access to caring adults, high-quality parenting, and effective community support services can protect some children from psychopathology. These findings further suggest that evidence-based social and mental health services should emphasize the creation of strong and effective caretaking systems (i.e., family, school, and community) as
The Current Status of Youth Prevention Science 5 much as the remediation of individual characteristics. Moreover, coordinated prevention efforts across families, schools, and communities are likely to be more effective than isolated, stand-alone programs (Greenberg et al., 2003; Kumpfer, Alvarado, Tait, & Turner, 2002; Wandersman & Florin, 2003). A third important perspective of developmental psychopathology is the recognition of ongoing reciprocal influence of multiple factors in explaining youth outcomes. Such concepts as heterotypic continuity, multi-finality, and equi-finality highlight the multi-factorial, longitudinal nature of developmental maladjustment that is further complicated by mediating and moderating influences. As we learn more about the risk and protective factors associated with certain forms of psychopathology, community prevention strategies and approaches are likely to become more specific and tailored. Although it is challenging to capture all the possible pathways in each disorder and it is not all that clear at this point what factors determine the developmental courses, the delineation of a coherent developmental pathway describes possible trajectories of early signs or symptoms and suggests strategies for prevention as well as for intervention. For example, it is well documented that a small number of children with Oppositional Defiant Disorder (ODD) in middle childhood will develop Conduct Disorder (CD) in later childhood or adolescence (Lahey, Loeber, Quay, Frick, & Grimm, 1992; Loeber & Farrington, 2000). Given that a majority of CD youth show ODD characteristics prior to onset of CD, prevention efforts could include specific goals of targeting variables that stop the progression from ODD to CD. Preventive interventions have the potential to interrupt youths’ trajectories into social or emotional disturbance, ameliorating risks and redirecting them along pathways into social health and psychological wellness.
Youth Prevention Programs and Practices As research accumulates documenting the importance of addressing maladjustment among youth, and describing the characteristics of community practices that are likely to promote psychological health and wellness, demands have grown for effective prevention strategies and programs for youth that incorporate: (1) ongoing assessment of the prevalence and incidence of youth difficulties; (2) development of strong and supportive relationships within family, school, and community contexts and with coordinated efforts across these different contexts; (3) multi-year efforts with special attention to developmental issues and changes; and (4) emphasis on enhancing social and emotional competence as well as fighting to reduce risk factors. This framework for youth prevention is well reflected in numerous successful prevention programs (e.g., Conduct Problems Prevention Research Group, 1999; Cook, Murphy, & Hunt, 2000; Greenberg & Kusche, 1998; Nation et al., 2003; Solomon, Battistich, Watson, Schaps, & Lewis, 2000). Other characteristics of effective prevention programs were identified in Nation et al.’s (2003) synthesis of the prevention research to date: effective programs are comprehensive, use a variety of teaching methods, are grounded in strong theoretical frameworks, are implemented at developmentally appropriate times in children’s lives, are compatible with the community norms and culture, and are delivered by appropriately trained practitioners. In this volume, 10 different prevention programs are directly described by researchers, spanning universal, selective and indicated strategies and exemplifying key features of supportive relationships, competence promotion, and ongoing assessment and evaluation Supportive Relationships in Youth Ecologies. Interpersonal relationships lie at the heart of youth prevention efforts. These relational networks are complex and reciprocal, including teachers, families, peers, and other critical community members (Demaray et al., this
6 Beth Doll and Jina Yoon volume; Hughes & Barrois, this volume). Youth prevention interventions invariably incorporate strategies to strengthen these relationships and increase emotional social support in order to improve the psychological well-being of youth and limit the impact that stress and adversity have on their competence. One notable finding of social relationships research is that very early relationships of young children are especially important for personal adjustment and well-being in adolescence and adulthood (Bumbarger et al., this volume). The research review by Demaray et al. (this volume) aligns the goals of social support with anticipated outcomes of youth prevention interventions while that provided by Hughes and Barrois (this volume) relates the social contexts of classrooms to the multiple risk and protective factors underlying students’ school success. Interventions described in this volume include social relationship components that strengthen teachers’ supportive actions to interrupt bullying incidents (Newman et al., this volume); foster strong and authentic relationships between mentors and students at risk of not completing school (Christenson & Reschly, this volume); and strengthen peer social relationships by stimulating children’s values about and responsibility for peer interactions (Vliek & Orobio de Castro, this volume). Cowie and Smith (this volume) describe strategies that prompt peers to offer emotional and social support to classmates in distress with the potential to create cooperative communities that benefit students offering support as well as those receiving support. Other chapters use similar terms to describe cooperative communities including “peer ecology” (Song & Sogo, this volume), “classroom climate” (Hughes & Barrois, this volume), “classroom social context” (Salmivalli et al., this volume), or “community well-being” (Hatzichristou, Lykitsakou, Lampropoulou, & Dimitropoulou, this volume). In educational settings, Demaray et al. (this volume) suggest that this ecology makes unique contributions to students’ school success over and above that made by students’ individual engagement in school. As illustration, the classwide component of the Coping Power program, in which all children in a class were taught social cognitive and emotional regulation skills, enhanced the impact of the individual Coping Power program provided to highly aggressive students in those classrooms (Lochman, Powell, Boxmeyer, & Badr, this volume). Bullying Prevention Programs. Several preventive interventions described in this volume address bullying, a particularly destructive form of peer aggression in which a stronger child repeatedly harasses a weaker child. Bullying has the potential to disrupt peer relations and youth social competence. Because schools are sites with many opportunities for minimally supervised interactions among peers, they are frequently sites where peer bullying occurs. A common goal of these interventions is to boost the results of school bullying prevention programs which Salmivalli, Kärnä, and Poskiparta (this volume) describe “as more modest than was hoped for.” Newman et al. (this volume) describe peer bullying within the context of teachers’ relationships with students, explaining factors that influence teacher decisions to intervene to stop bullying. Their explanation serves as a rationale for Phase 2 of the Steps to Respect bullying prevention program. Three chapters in this volume (Salmivalli et al., Cowie & Smith, and Song & Sogo) call for onlooker interventions to shift the ways that children respond when peers are being bullied. Salmivalli et al. describe the innovative use of game technology to reinforce students’ knowledge, skills, and motivation to confront and challenge bullying when it occurs in their presence. Cowie and Smith predicate their intervention on strategies to prompt classmates to provide social support, while Song and Sogo comment on the pragmatic benefits of peer ecology interventions in that large numbers of students are a ready resource of any school-based program. Family Connections. Many comprehensive preventive interventions include components that train parents or other primary caretakers in particular skills or maintain heightened
The Current Status of Youth Prevention Science 7 communication between families and the prevention program. Families are the primary caretakers in natural youth environments and their participation in prevention efforts is the most obvious way to integrate wellness-promoting strategies into the everyday lives of youth. For example, a parent component of the Coping Power program (Lochman et al., this volume) prepares parents to reinforce skills that their aggressive children are learning in the child component. The Netherlands’ TIGER program includes parallel parent training groups when offered within counseling centers, and parent evenings when provided through local schools (Vliek & Orobio de Castro, this volume). The Partnering to Achieve School Success (PASS) program (Power, Lavin, Mautone, & Blum, this volume) forges strong partnerships between pediatric care settings and parents of children with attention problems, and incorporates additional optional family interventions or family–school consultation depending on the family’s need and interest. Mentors in the Check and Connect program (Christenson & Reschly, this volume) are in regular contact with families of students at risk of not completing school, and work to strengthen the compatibility of schools and families. The KiVa program includes a parents’ guide (Salmivalli et al., this volume) while the early literacy intervention described by Gettinger et al. (this volume) includes a family literacy center in which parents are provided with materials and coaching in literacy-promoting practices. Competence Promotion. The importance of building skills and promoting competence has been well supported by prevention scientists (Bumbarger et al., this volume; Catalano, Berglund, Ryan, Lonczak, & Hawkins 2004; Collaborative for Academic, Social and Emotional Learning, 2003; Weissberg et al., 2003). Inevitably, proposed prevention programs are grounded in comprehensive conceptual frameworks that translate developmental theory and research into practices to promote competence. One of the most prominent frameworks for competence promotion is Social Emotional Learning and Tran and Merrell (this volume) describe a comprehensive school-based program in which teachers provide social emotional instruction to their students. As other examples: Gettinger et al. (this volume) provide a comprehensive description of the theory underlying competence promotion in early childhood; Prince-Embury’s (this volume) conceptual framework for youth resilience describes research identifying individual characteristics that were present in youth who were successful despite adversity; Song and Sogo (this volume) explain the powerful potential outcome of preparing school-aged children to protect each other from peer aggression; Hatzichristou et al. (this volume) describe a school-wide intervention to promote psychological wellness and the wellbeing of the school community; and Vliek and Orobio de Castro (this volume) explain the theory underlying the use of personal responsibility and values to promote prosocial behavior in the Netherlands. Assessment and Program Evaluation. Assessment and early identification of youth who could benefit from prevention programs is essential to the success of universal and selective programs and to planning goals and priorities for prevention programs (Demaray et al., this volume). The availability of increasing numbers of technically sound and highly innovative universal screening assessment strategies is an exciting development within youth prevention science, and makes it possible to collect risk and success data from large numbers of youth without sacrificing accuracy and reliability. Both Walker et al. (this volume) and Dowdy et al. (this volume) provide comprehensive descriptions of the characteristics necessary for universal screening measures. In addition, Dowdy et al. (this volume) describe three universal screening measures that are technically adequate to identify children and adolescents who qualify or nearly qualify as having one or more mental disorder, along with strategies for planning and implementing universal screening in a community’s schools. One of these three measures, Systematic Screening for Behavior Disorders, is described in more detail by Walker
8 Beth Doll and Jina Yoon et al. (this volume) along with the key role that it played in the Jefferson Parish Public School System’s use of universal screening and a three-tiered prevention model to reduce behavioral disorders among its students. Alternatively, Prince-Embury (this volume) explains how definitions of technical adequacy might be operationalized in statistical analyses, and how the strength-based Resiliency Scales for Children and Adolescents meet these criteria for universal screening strategies. Osher and Kendziora (this volume) blur the boundaries between assessment and intervention when they use the AIR Survey of the Social and Emotional Conditions for Learning to prompt ongoing assessment and monitoring, which in turn engages school staff in continuous improvement and early intervention. Youth Prevention and Schools. Schools are inevitably the sites where much youth prevention occurs (Adelman & Taylor, this volume; Dwyer & Van Buren, this volume; Lochman et al., this volume; Power et al., this volume; Tran & Merrell, this volume). Of all community agencies, schools have the daily contact with children and adolescents that makes it cost-effective to provide broad prevention programs across the youth population of a community. Multiple schools in contingent communities often share common concerns and risks for youth, and can pool their resources to plan and provide prevention programs. Moreover, school sites have the potential to improve access to preventive interventions by vulnerable youth, such as those who are impoverished or from under-represented groups, by eliminating barriers such as the stigma associated with services in unfamiliar places, transportation to and from intervention sites, and scheduling around family work responsibilities. Given a shared mission to promote youth wellness, resources of schools and nearby community agencies could potentially be braided together so that schools’ and communities’ goals can be accomplished efficiently. It is not surprising, then, that many of the prevention programs and practices in this volume describe preventive interventions that occur in schools. Sadly, the infrastructure for school-based prevention programs remains inadequate. The number of school-based prevention programs is very small relative to the need, and those that do exist often focus narrowly on a single problem (Adelman & Taylor, this volume). In particular, the vast majority of universal prevention programs implemented in schools focus narrowly on the prevention of drug, tobacco, or alcohol use (Foster et al., 2005). Perhaps more critical, a clear focus on youth psychological wellness and prevention of psychopathology is not an acknowledged part of many schools’ mission (Dwyer & Van Buren, this volume; Walker et al., this volume). For example, despite the increasing availability of population-based assessments that are conceptually sophistically and technically sound, schools and other youth-serving agencies have limited familiarity with universal assessment procedures and are not yet making good use of the innovations (Walker et al., this volume). Instead, they are more accustomed to traditional referral-based identification of students for services that frequently delay identification of troubled students until it is too late to use the most costeffective preventive interventions (Walker et al., this volume). In most schools, youth prevention programs are marginalized within the larger educational efforts to improve schools (Adelman & Taylor, this volume) and school-community partnerships are hampered by historic divisions that separate education from other community agencies (Dwyer & Van Buren, this volume). While schools are providing more population-based youth prevention programs than other community agencies, these efforts have been characterized by many researchers as too little and too late (Dwyer & Van Buren, this volume; Walker et al., this volume). Youth with a significant need for preventive intervention are often not identified or they are identified at an age when interventions are less likely to be effective and more likely to be costly.
The Current Status of Youth Prevention Science 9
Methodological Issues in Youth Prevention Science Researchers and practitioners in youth prevention science have spent the past two decades discussing, refining, and strengthening standards for high-quality research to show which prevention practices improve outcomes for youth, with which populations, under which conditions, and at what cost. These research standards build upon those specified in the late 1990s for all psychosocial interventions (Chambless et al., 1996; Hayes, Barlow, & NelsonGray, 1999; Lonigan, Elbert, & Bennett-Johnson, 1998; U.S. Department of Health and Human Services, 1999). Evidence-based psychotherapeutic interventions are those that have been examined in at least two well-designed group studies or a series of well-conducted singlesubject studies; conducted by unrelated research teams; in which participants were randomly assigned to treatment and control groups; with results demonstrating that improvements in symptoms occur, are not due to chance, are due to the intervention of interest, represent an improvement over no treatment at all, and are at least as strong as those produced by existing interventions. Still, the fit between these generic standards and the unique circumstances posed by youth prevention research is not altogether satisfactory. In evaluations of preventive interventions, the data of interest will frequently be the absence rather than presence of symptoms of disorders or disturbances. This is because interventions to prevent psychosocial disturbances are applied before symptoms are evident or when signs of a disorder first emerge but do not yet meet diagnostic criteria. The measure of the intervention’s success may be the continued absence of problems rather than the remission of problems that were already in evidence. Documenting the continued absence of problems often requires data describing populationbased prevalence or incidence rates. These data require population-based assessments that are epidemiological in design and the designs, tools, and procedures for these assessments are unfamiliar to many agencies or professionals. In many cases, the outcomes of interest for a preventive intervention are displaced by decades or generations in time (Cooney et al., this volume). For example, Kellam, Rebok, Ialongo, & Mayer (1994) showed that enhanced behavior management by first-grade teachers could result in significantly fewer conduct problems six years later. Newman et al. (this volume) report that many outcomes of the Steps to Respect program were not apparent until the program had been in place for 18 months. Longitudinal designs struggle mightily with participant attrition (Hughes & Barrois, this volume). Distal outcomes are particularly difficult to track in communities characterized by high mobility because shifts in residence and dispersal of a population can complicate the task of identifying or tracking youth who were recipients of a school or community intervention many years earlier (Wandersman & Florin, 2003). On the face of it, it ought to be possible to describe the success of prevention programs using existing community indices of health, employment, social, or educational success that are routinely collected across decades. For example, Walker and colleagues (this volume) note that archival school records accrue naturally over time and are unobtrusive ways to track student success. They describe existing strategies for mining these records systematically and objectively. In practice, however, existing agency data is often insufficient for the task. The limitation of existing community records is exemplified by the United States’ 50-year attempt to track high school graduation and dropout rates (Barclay & Doll, 2001). Even with strengthened requirements for state reporting of graduation rates following the No Child Left Behind Act of 2001, there are at least three prominent ways that states compute these rates: longitudinal descriptions of the number of students from a ninth-grade cohort who graduate four years later, the percentage of school leavers who leave with a diploma, or the number of
10 Beth Doll and Jina Yoon graduates from a cohort of students who initially entered school (Swanson, 2003). All three strategies are careful to not penalize schools for students who simply transfer from one district to another. However, the mobility of residence combined with imprecise district records can make it impossible to determine which students were high school dropouts and which students transferred to and completed high school in another community. Some students transfer their files but never show up in the new school, while other students never request a file transfer but still enroll in a new school. Some students transfer to a new high school but subsequently leave without graduating. In some instances, students who left school without graduating returned later to complete their degree. In an attempt to provide a more accurate index, some policymakers have suggested that communities simply track the number of residents with high school diplomas but this, too, has proved to be an imperfect indicator of a local school district’s success in graduating its students. The frequency of earned diplomas is easily distorted by the in-migration of large numbers of residents with limited education, as is the case in many destinations of immigrants into the US. Moreover, functional indicators such as high school graduation are often related to community risk factors such as poverty, unemployment, or access to community support services, and population trends in these risk behaviors can be shifting even while prevention programs are being implemented—such that the impact of a prevention program could be masked by increased adversity within the community or could be inflated by decreased adversity (Pentz, 2004). Prevention researchers also chafe at the emphasis on disorders and dysfunction that dominates traditional psychotherapeutic intervention research (Adelman & Taylor, this volume). The mere absence of a deficit is not necessarily the best early indicator of youths’ future competence; instead the most useful assessment data may be indices of the social, emotional, and behavioral health of youth. For example, “lowering the high school dropout rate” is an inadequate definition of a prevention program’s goal since simply leaving school with a diploma does not necessarily place graduates on a trajectory towards life success and adult competence. A more appropriate goal is “raising rates of successful school completion” in which school completers leave school with a diploma and adequate preparation for productive home, work, and community lives (Christenson & Reschly, this volume). Unfortunately, protocols for tracking positive indicators of psychosocial wellness are less fully developed than those assessing pathology and disturbance. Still, Dowdy et al. (this volume) review very recent research to demonstrate that including positive measures of life satisfaction or school connectedness in addition to negative measures of problems or pathological symptoms heightens the sensitivity and predictive power of universal screening strategies. Ultimately, the purpose of youth prevention research is to alter community programs and practices so that these predispose youth to be successful and competent adults (Bumbarger et al., this volume). This is a much broader purpose than remediating a disorder, and it requires that programs not only have meaningful and significant impact on youth in well-controlled research studies (program efficacy); but also have a significant and important youth impact when implemented within actual communities (program effectiveness); be sustained over time (program sustainability); be broadly adopted in diverse communities beyond those in which the program was first developed (program scalability); and be integrated within the permanent policies, practices, and resources of the community (systemic program supports; Kellam & Langevin, 2003). In deference to these unique demands of high-quality prevention research, the Society for Prevention Research (Flay et al., 2005) has developed five standards for evidence of prevention programs’ efficacy, four additional standards for demonstrating programs’ effectiveness, and three additional standards to demonstrate that the program is ready for broad dissemination:
The Current Status of Youth Prevention Science 11 Under these Standards, an efficacious intervention will have been tested in at least two rigorous trials that (1) involved defined samples from defined populations; (2) used psychometrically sound measures and data collection procedures; (3) analyzed their data with rigorous statistical approaches; (4) showed consistent positive effects (without serious iatrogenic effects); and (5) reported at least one significant long term followup. An effective intervention under these Standards will not only meet all standards for efficacious interventions, but also will have (1) manuals, appropriate training, and technical support available to allow third parties to adopt and implement the intervention; (2) been evaluated under real-world conditions in studies that included sound measurement of the level of implementation and engagement of the target audience (in both the intervention and control conditions); (3) indicated the practical importance of the intervention outcome effects; and (4) clearly demonstrated to whom intervention findings can be generalized. An intervention recognized as ready for broad dissemination under these Standards will not only meet all standards for efficacious and effective interventions, but will also provide (1) evidence of the ability to “go to scale”; (2) clear cost information; and (3) monitoring and evaluation tools so that adopting agencies can monitor or evaluate how well the intervention works in their settings. (p. 151). Several researchers append additional phases to this program of youth prevention research: examinations of programs’ sustainability once they have been shown to be effective in actual practice settings, and empirical investigations of the infrastructure necessary for prevention programs that have been taken to scale (Adelman & Taylor, this volume; Bumbarger et al., this volume; Kellam & Langevin, 2003). Hughes and Barrois (this volume) apply the five efficacy standards to eight universal preventive interventions that had the common goal of increasing positive social interactions in a school classroom, and report that only two programs met all of the standards for efficacy. Three of the eight had at least one well-controlled study of the program efficacy, a mighty accomplishment given that the studies’ participants were typically randomized at the school or classroom level and the studies thus required a large number of participants. Four of the eight had demonstrated that program effects persisted at least six months after the intervention had been completed. Many of the chapters in this volume illustrate the kinds of logistical barriers that prevent researchers from satisfying the Flay et al. standards in program efficacy studies. For example, Vliek and Orobio de Castro (this volume) used a delayed treatment design with random assignment to evaluate the TIGER program but their sample of 28 classrooms left their study underpowered to detect some program effects and there were practical and ethical limits on how long treatment could be delayed in their control classrooms. Hughes and Barrois’ review illustrates that youth prevention science has just begun to provide the kinds of evidence that communities need to identify promising practices that could be applied with good results in real-world settings. Another discouraging reality is that the translation of efficacious programs into communityadopted practices has been elusive. Too many prevention programs that have been demonstrated to work in carefully controlled research studies (evidence of intervention efficacy) are not adopted for actual use by communities, schools, or mental health centers (no evidence of intervention effectiveness). Just as important, in those instances where efficacious programs are adopted by communities, they are rarely implemented with integrity and their results are less dramatic than was suggested by the earlier research studies. For example, programs delivered in community settings may differ in the amount of intervention, the quality of program delivery, the degree to which key components were actually implemented, or the level of participation by
12 Beth Doll and Jina Yoon the children and adolescents or their families (Lochman et al., this volume; Odom et al., this volume). As Song and Sogo (this volume) point out, this is particularly pronounced for underresourced communities such as urban centers or remote rural communities. Actual providers of preventive interventions are not always trained mental health providers, but instead may be classroom teachers, daycare workers, or others. Even though these practitioners are trained to provide the program, they may not implement the program as planned. When manualized preventive interventions are implemented as part of large scale up investigations, it can be extremely difficult to ensure that the interventions are uniformly implemented in sites that are widely dispersed (Gettinger et al., this volume). Moreover, the fidelity of program implementation can shift over time (poorer implementation later in the program rather than earlier). There are many reasons why this might be the case. It may be difficult to provide sufficient dosage of community interventions to show effects (Wandersman & Florin, 2003). Interventions provided through communities require maintaining a community collaboration—which is difficult to do. Frequently, resources diminish once soft money disappears and the program is not sustained. As a result, youth preventive interventions are frequently marginalized and deference is given to school improvement goals that emphasize academic achievement (Adelman & Taylor, this volume). Weisz et al. (2005) conclude that most children and adolescents have very limited access to effective prevention programs because of the continuing divide between research and practice, and the gaps in the evidence base. Furious debates continue about whether this gap between efficacy and effectiveness describes a failure of communities to devote the resources necessary for high-quality youth prevention programs, or a failure of researchers to develop programs that are sufficiently pragmatic and adequate for the complexity of community conditions. Some researchers have identified limitations in community agencies that contribute to their inability to replicate prevention programs with fidelity (Elliott & Mihalic, 2004). These include inadequacies in the site’s capacity or preparation for the program (Bumbarger et al., this volume); difficulties training agency staff to deliver the program, particularly when training is provided under conditions of high staff absenteeism or turnover; inadequate technical assistance for the agency including instances in which technical assistance was not included in the agency budget for the program or was not able to respond quickly enough to problems that arose; and misjudgments of the program dosage necessary to produce the hoped-for effects among the community’s youth. Similar limitations have been described to explain why school-based prevention programs lack integrity and are unsuccessful in some communities (Botvin, 2004): Schools may lack sufficient in-school training and support to carry out the program; or they may be struggling with multiple instances of limited resources such as overcrowded classrooms or budgets that are inadequate for basic program materials. Teachers in the school may have multiple competing pressures including poor student discipline, low teacher morale and burnout, or an overpowering emphasis on basic academic instruction. Nation et al. (2003) point out that practitioners and sites often do not have the resources to implement research-based programs. While some community prevention efforts can begin on a smaller scale and then be broadened over time, it is difficult to implement many prevention programs “piecemeal” because preventive interventions depend on universal screening strategies to select the right youth for intervention, while screening strategies require that there be an appropriate intervention program to serve youth once they have been identified. Consequently, Biglan and his colleagues (2003) call for research on the influence of financial consequences on the practices of schools and other organizations as a necessary first step towards the widespread adoption of prevention practices.
The Current Status of Youth Prevention Science 13 An alternative perspective is that manualized interventions may not be suitable for use in all communities and populations. Castro, Barrera, and Martinez (2004) suggest that problems with intervention fidelity may actually be necessary adaptations that make manualized interventions culturally appropriate for diverse communities. Youth prevention programs developed within a research agenda may not be immediately applicable in communities that differ in their members’ language, ethnicity, socioeconomic status, or cultural values and beliefs. Other researchers agree, and clarify that youth prevention programs can only be strictly replicated in communities where the program is culturally and linguistically compatible with the population, where needs assessment data demonstrates that the program is needed, and where program participants were involved in the decisions about how and why the program is being implemented (Ringwalt, Vincus, Ennett, Johnson, & Rohrback, 2004). A key focus of current prevention science is how to adapt manualized interventions so that these appropriately accommodate diverse community cultures and needs. For example, Power et al. (this volume) describe implementation of an indicated preventive intervention for low-income children with attention problems that has been modularized: decisions about which program modules to provide are made within effective family-practitioner teams, so that these accommodate the unique needs of each family. The description by Lochman et al. (this volume) of the Coping Power program provides a cogent example of “fidelity with flexibility” in which emphasis is placed on the key factors that contribute to the quality of the Coping Power program’s reliable delivery while other aspects of the program may be supplemented or altered to match characteristics of the children or their parents. Christenson and Reschly (this volume) explain how the Check and Connect program is individualized to particular schools and students. Several researchers have suggested that manualized preventive interventions need to include procedures for communities to adapt the program to their unique demands: identifying the “tailoring variables” that moderate the effect of the intervention, describing strategies for assessing the tailoring variables, and providing decision rules for systematically modifying the intervention based upon the results of the assessments (Collins, Murphy, & Bierman, 2004). Contemporary prevention researchers also stress the importance of building practitioners’ capacities for implementing prevention programs in actual settings (Bumbarger et al., this volume; Gettinger et al., this volume; Kaftarian et al., 2004; Lochman et al, this volume; Odom et al., this volume). A common finding is that intervention training provided at the beginning of a program is ineffective unless it is supplemented with ongoing consultation between practitioners and intervention experts. As one example of this kind of research, Salmivalli et al. (this volume) describe an “exceptionally large” array of supports provided to schools implementing the KiVa program for the prevention of school bullying including user-friendly and attractive materials, training programs incorporating key persons chosen by the schools, virtual training provided over a program website, tools to monitor the program impact, and a biannual KiVa conference days to disseminate research and provide for sharing experiences. Newman et al. (this volume) report the key importance of a “coaching” component for teachers who implement the Steps to Respect program. In the EMERGE preschool literacy program, teacher training is augmented by literacy coaches who regularly review program monitoring data with students and help them plan literacy instruction that is responsive to the data. Tran and Merrell (this volume) pose an alternative strategy by designing a low-cost, time-limited schoolwide program to promote student resilience that is carefully matched to the instructional competencies of classroom teachers. In their chapter, they describe procedural strategies that strengthen program fidelity and note that a longer, high-intensity program might produce stronger gains but is less likely to be adopted.
14 Beth Doll and Jina Yoon Methods for prevention science have evolved over time and researchers now use more sophisticated designs and measures. Large numbers of preventive interventions have demonstrated early promise of efficacy. Still, these results continue to be preliminary as very few programs have conducted long-term follow-ups of program impact, described independent replications of program impacts, reported studies with sample sizes large enough for adequate statistical power, or provided sufficient information describing size of program effect.
Implementation Science The dynamic tension between fidelity and adaptation is one of the important themes in current prevention research and may only be resolved through innovative research methodologies that rigorously examine the effectiveness of prevention programs in practice, as well as the conditions under which they are most likely to be effective, and the factors that affect community agencies’ willingness to use evidence-based practices (Biglan et al., 2003; Kaftarian et al., 2004). Odom et al. (this volume) and Bumbarger et al. (this volume) refer to this as “implementation science” and mark it as a priority for the next wave of research on youth prevention. Specifically, emerging studies of youth prevention science need to examine the relation that exists between the degree of program implementation and youth outcomes, describe key features that must be present for a program to be effective and identify the factors that affect program fidelity. A necessary and particularly challenging component of implementation research is technically sound assessment of the degree to which a program has been implemented. Commonly used methods to describe degree of implementation include observation, self-report, interview, and archival records (Odom et al., this volume). Direct measures such as observations may be more intrusive but less vulnerable to bias than practitioners’ self-report or interviews, but the observations’ intrusiveness can alter the implementation fidelity and limit the generalizability of results to programs implemented outside of research settings. Thus, multiple measures are often collected to describe program implementation, with different methods balanced against their impact on practice, and relations examined between the proportion of the program that was implemented and its impact on participants. It is increasingly apparent that implementation studies must also provide a thorough examination of all participant perspectives including those of the children themselves if they are to adequately represent the acceptability and potential impact of a prevention program (Cowie & Smith, this volume). At least initially, this is likely to require mixed-method designs to incorporate qualitative as well as quantitative data to detect program implementation factors and to fully describe program outcomes. Pentz (2004) has suggested that studies of communities’ implementation of preventive interventions will routinely have three comparison groups: participants in programs delivered by trained interventionists and implemented with fidelity, participants in programs delivered by interventionists who were trained but did not implement the program accurately, and participants in programs delivered by interventionists who were not trained. To some extent, characteristics of the interventions themselves may be critical determinants of their implementation. The Diffusion of Intervention Theory (Dusenbury & Hansen, 2004) suggests that interventions are more amenable to diffusion when they fit with existing community values and needs, are relatively simple to use, have clear advantages over other programs, have been tried and evaluated locally, and have a positive reputation. An underemphasized aspect of implementation is youth policy or the degree to which the empirical findings of youth prevention science are reflected in local, state, and national policies for practice and funding. As Cooney et al. (this volume) explain, high-quality research
The Current Status of Youth Prevention Science 15 is only one factor responsible for communities’ course of action. In particular, the timeline of prevention research, its reliance on peer-refereed science, its preference for scholarly discourse, and its focus on long-term outcomes place it at cross-purposes with public decisionmakers’ preference for immediacy, short-term and localized benefits, and simply-stated recommendations. They describe a set of practical steps for researchers to prompt policymakers to attend to and implement prevention science so as to garner greater influence over youth prevention practices. Barring systemic implementation research, Adelman and Taylor (this volume) argue that the demands for communities to use only evidence-based prevention programs are premature. Instead, they suggest that such demands prematurely push practices developed in highly controlled laboratory situations into widespread practice based on unwarranted assumptions about their effectiveness. Moreover, they point out that the expectation that communities should select programs from approved “lists” perpetuates fragmented services that address one problem at a time. For schools, in particular, the degree to which teachers apply a program’s prevention principles in their daily interactions with students may be just as important as the degree to which a manualized curriculum is delivered to students (Hughes & Barrois, this volume). While implementation research is ongoing, a viable alternative to evidencebased programs in the interim will be the incorporation of local program evaluation into community program implementations (Adelman & Taylor, this volume).
Summary As the chapters in this volume illustrate, this is a moment of uncommon importance in youth prevention science. Innovative youth prevention practices are being drawn out of the previous decades’ robust empirical descriptions of developmental pathways into human competence and pathology. Promise is evident in the proliferation of efficacious prevention programs that emphasize high-quality social relationships, family connections, competence promotion, universal screening, and convenient (often school-located) sites. These prevention programs are being carefully examined in concert with rigorous standards for intervention research, and subsequently are being transported into community policy and practice. Tension continues to be reflected in debates to reconcile wellness promotion and disease prevention models; over the central role played by socioecological relative to psychobiological determinants of mental health; to define the standards that should be used to conduct high-quality prevention research; over the ways to balance rigor with community impact; and over the necessary balance of intervention fidelity with community demands for relevant and culturally appropriate practice. Still, consensus is evident in recognition that the phenomena of risk, resilience, and prevention are complex and multi-faceted; that an important gap exists between rigorous prevention research and community prevention practices; and that it is the impact of prevention programs as implemented in communities that matters most. New emphases are being placed on the strategies to translate prevention science into thoughtful and effective prevention policies. At present, the translation of prevention science into evidence-based prevention practice is both frustrating and compelling and holds tempting opportunities to make long-lasting impressions on the mental health and well-being of youth.
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16 Beth Doll and Jina Yoon Albee, G. W. (2004). Prevention of mental disorders. In W. E. Pickren, Jr., & S. F. Schneider (Eds.), Psychology and the National Institute of Mental Health: A historical analysis of science, practice, and policy (pp. 295–315). Washington, DC: American Psychological Association. Albee, G. W. (2005). Prevention of mental disorders. In W. E. Pickren & S. F. Schneider (Eds.), Psychology and the National Institute of Mental Health: A historical analysis of science, practice, and policy. Washington, DC: American Psychological Association. American Psychiatric Association. (2000). The diagnostic and statistical manual of mental disorders— fourth edition, text revised. Washington DC: Author. Barclay, J. R., & Doll, B. (2001). Early prospective studies of the high school drop out. School Psychology Quarterly, 16, 357–369. Biglan, A. (2004). Contextualism and the development of effective prevention practices. Prevention Science, 5, 15–21. Biglan, A., Mrazek, P. J., Carnine, D., & Flay, B. R. (2003). The integration of research and practice in the prevention of youth problem behaviors. American Psychologist, 58, 433–440. Botvin, G. J. (2004). Advancing prevention science and practice: Challenges, critical issues, and future directions. Prevention Science, 5, 69–72. Castro, F. G., Barrera, M., & Martinez, C. R. (2004). The cultural adaptation of prevention interventions: Resolving tensions between fidelity and fit. Prevention Science, 5, 41–45. Catalano, R. F., Berglund, M. L., Ryan, J. A. M., Lonczak, H. S., & Hawkins, J. D. (2004). Positive youth development in the United States: Research findings on evaluations of positive youth development programs. Annals of the American Academy of Political and Social Science. Special Issue: Positive Development: Realizing the Potential of Youth, 591, 98–124. Chambless, D. L., Sanderson, W. C., Shoham, V., Johnson, S. B., Pope, K. S., Critis-Cristoph, P., Baker, M., Johnson, B., Woody, S. R., Sue, S., Beutler, L., Williams, D. A., & McCurry, S. (1996). An update on empirically validated therapies. Clinical Psychologist, 49, 5–14. Coie, J. D., Watt, N. F., West, S. G., Hawkins, J. D., Asarnow, J. R., Markan, H. J., Ramey, S. L., Shure, M., & Long, B. (1993). The science of prevention: A conceptual framework and some directions for a national research program. American Psychologist, 48, 1013–1022. Collaborative for Academic, Social and Emotional Learning. (2003). Safe and sound: An educational leader’s guide to evidence-based social and emotional learning programs. Retrieved March 13, 2008, from http://www.casel.org/pub/safeandsound.php Collins, L. M., Murphy, S. A., & Bierman, K. L. (2004). A conceptual framework for adaptive preventive interventions. Prevention Science, 5, 185–196. Commission on Chronic Illness. (1957). Chronic illness in the United States (Vol. 1). Cambridge, MA: Harvard University Press. Commission on the Prevention of Mental/Emotional Disabilities. (1987). The Commission on the Prevention of Mental/Emotional Disabilities. Journal of Primary Prevention, 7, 175–241. Conduct Problems Prevention Research Group. (1999). Initial impact of the Fast Track prevention trial for conduct problems: II. Classroom effects. Journal of Consulting and Clinical Psychology, 67, 648–657. Cook, T. D., Murphy, R. F., & Hunt, H. D. (2000). Comer’s School Development Program in Chicago: A theory-based evaluation. American Educational Research Journal, 37, 535–597. Cowen, E. (1994). The enhancement of competence: Challenges and opportunities. American Journal of Community Psychology, 22, 149–179. Doll, B. (1996). Prevalence of psychiatric disorders in children and youth: An agenda for advocacy by school psychology. School Psychology Quarterly, 11, 20–46. Doll, B., & Lyon, M. (1998.) Risk and resilience: Implications for the practice of school psychology. School Psychology Review, 27, 348–363. Dusenbury, L., & Hansen, W. B. (2004). Pursuing the course from research to practice. Prevention Science, 5, 55–59. Elliott, D. S., & Mihalic, S. (2004). Issues in disseminating and replicating effective prevention programs. Prevention Science, 5, 47–53.
The Current Status of Youth Prevention Science 17 Flay, B. R., Biglan, A., Boruch, R. F., Castro, F. G., Gottfredson, D., Kellam, S., Moscicki, E. K., Schinke, S., Valentine, J. C., & Ji, P. (2005). Standards of evidence: Criteria for efficacy, effectiveness, and dissemination. Prevention Science, 6, 151–175. Foster, S., Rollefson, M., Doksum, T., Noonan, D., Robinson, G., & Teich, J. (2005). School mental health services in the United States 2002–2003. DHHS Pub. No. (SMA) 05-4068. Rockville, MD: Center for Mental Health Services, Substance Abuse and Mental Health Services Administration. Gordon, R. S. (1983). An operational classification of disease prevention. Public Health Reports, 98, 107–109. Greenberg, M. T., & Kusché, C. A. (1998). Blueprints for violence prevention: The PATHS Project (Vol. 10). Boulder, CO: Institute of Behavioral Science, Regents of The University of Colorado. Greenberg, M. T., Weissberg, R. P., O’Brien, M. U., Zins, J. E., Fredericks, L., Resnik, H., & Elias, M. J. (2003). Enhancing school-based prevention and youth development through coordinated social, emotional, and academic learning. American Psychologist, 58, 466–474. Hayes, S. C., Barlow, D. H., & Nelson-Gray, R. O. (1999). The scientist practitioners: Research and accountability in the age of managed care (2nd ed.). Boston: Allyn & Bacon. Hosman, C., Jane-Liopis, E., & Saxena, S. (Eds). (2005) Prevention of mental disorders: Effective interventions and policy options. Oxford: Oxford University Press. Kaftarian S., Robinson, E., Compton, W., Davis Watts, B., & Volkow, N. (2004). Blending prevention research and practice in schools: Critical issues and suggestions. Prevention Science, 5, 1–3. Kaplan, R. M. (2000). Two pathways to prevention. American Psychologist, 55, 382–396. Kellam, S. G., & Langevin, D. J. (2003). A framework for understanding “evidence” in prevention research and programs. Prevention Science, 4, 137–153. Kellam, S. G., Rebok, G. W., Ialongo, N., & Mayer, L. S. (1994). The course and malleability of aggressive behavior from early first grade into middle school: Results of a developmental epidemiologicallybased prevention trial. Journal of Child Psychology & Psychiatry & Allied Disciplines, 35, 259–281. Kumpfer, K. L., Alvarado, R., Tait, C., & Turner, C. (2002). Effectiveness of school-based family and children’s skills training for substance abuse prevention among 6–8 year old rural children. Psychology of Addictive Behaviors, 16, 565–571. Lahey, B. B., Loeber, R., Quay, H. C., Frick, P. J., & Grimm, S. (1992). Oppositional defiant and conduct disorders: Issues to be resolved for DSM-IV. Journal of the American Academy of Child and Adolescent Psychiatry, 31, 539–546. Loeber, R., & Farrington, D. P. (2000). Young children who commit crime: Epidemiology, developmental origins, risk factors, early interventions, and policy implications. Development and Psychopathology, 12, 737–762. Lonigan, C. J., Elbert, J. C., & Bennett-Johnson, S. (1998) Empirically supported psychosocial interventions for children: An overview. Journal of Clinical Child Psychology, 27, 138–145. Mash, E. J., & Dozois, D. J. A. (2003). Child psychopathology: A developmental-systems perspective. In E. J. Mash, & R. A. Barkley (Eds.), Child psychopathology (2nd ed.). (pp. 3–71). New York, NY: Guilford Press. Mrazek, P. J., & Haggerty, R. J. (Eds). (1994). Reducing risks for mental disorders: Frontiers for preventive intervention research. Washington, DC: National Academy Press. Nation, M., Crusto, C., Wandersman, A., Kumpfer, K. L., Seybolt, D., Morrissey-Kane, E., & Davino, K. (2003). What works in prevention: Principles of effective prevention programs. American Psychologist, 58, 449–456. Pentz, M. A. (2004). Form follows function: Designs for prevention effectiveness and diffusion research. Prevention Science, 5, 23–29. Ringwalt, C. L., Vincus, A., Ennett, S., Johnson, R., & Rohrbach, L. A. (2004). Reasons for teachers’ adaptation of substance use prevention curricula in schools with non-white student populations. Prevention Science, 5, 61–67. Solomon, D., Battistich, V, Watson, M., Schaps, E., & Lewis, C. (2000). A six-district study of educational change: Direct and mediated effects of the Child Development Project. Social Psychology of Education, 4, 3–51.
18 Beth Doll and Jina Yoon Swanson, C. B. (2003). NCLB implementation report: State approaches for calculating high school graduation rates. Washington, DC: The Urban Institute. U.S. Department of Health and Human Services. (1999). Mental health: A report of the Surgeon General. Rockville, MD: U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, National Institutes of Health, National Institute of Mental Health, 1999. Wandersman, A., & Florin, P. (2003). Community interventions and effective prevention. American Psychologist, 58, 441–448. Weissberg, R. P., Kumpfer, K. L., & Seligman, M. E. P. (2003). Prevention that works for children and youth: An introduction. American Psychologist, 58, 425–432. Weisz, J. R., Sandler, I. N., Durlak, J. A., & Anton, B. S. (2005). Promoting and protecting youth mental health through evidence-based prevention and treatment. American Psychologist, 60, 628–648. Werner, E. E. (2006). What can we learn about resilience from large-scale longitudinal studies? In S. Goldstein & R. B. Brooks (Eds.), Handbook of resilience in children (pp. 91–105). New York, NY: Springer.
2
Placing Prevention into the Context of School Improvement Howard S. Adelman and Linda Taylor University of California, Los Angeles
Few argue against efforts to prevent educational, psychosocial, physical, and mental health problems, or against the desirability of doing so on a large scale. Arguments arise, however, about costs, effectiveness, and the role of schools (among other major systems). Beyond specific and narrowly defined public health concerns, prevention is not a high priority in public policy and practice. Beyond immunizations, prevention initiatives for children and adolescents have focused mainly on reducing specific risk-taking behaviors (Center for Mental Health in Schools, 2007a). This has led to an overemphasis on observed problems and on approaching them as separate entities and to de-emphasizing analyses and pursuit of common underlying causes. It also has contributed to the tendency to downplay the promotion of wellness as an invaluable end in and of itself (e.g., Cowen, 1997). Prevention programs in schools are relatively few in number and usually are funded as discrete projects, often with “soft” money (e.g., see the lists described in CASEL, 2003; Center for Mental Health in Schools, 2005a; Cochrane Library, 2007; Cowen, Hightower, Pedro-Carroll, Work, Wyman, & Haffey, 1996; Durlak, 1995; Durlak & Wells, 1997; Greenberg, Weissberg, O’Brien, Zins, Fredericks, Resnik et al., 2003; SAMHSA, 2007; Scattergood, Dash, Epstein, & Adler, 1998; Weisz, Sandler, Durlak, & Anton, 2005). Moreover, existing programs are so fragmented that they often produce inappropriate redundancy, and counterproductive competition, and work against the type of systemic collaboration that is essential for establishing interprogram connections on a daily basis and over time. All this increases costs, reduces effectiveness, and perpetuates widespread marginalization of prevention initiatives. What prevails is a vicious cycle of unsatisfactory policy, research, practice, and training. The cycle is likely to continue as long as prevention is viewed narrowly. To move the field forward, the concept of prevention must be framed in a comprehensive context. Moreover, schools and communities must work together in new ways, and the work must be fully integrated into school improvement policy, planning, implementation, and accountability. This chapter places primary prevention along with the promotion of healthy development at one end of a full continuum of interventions, with each level of the continuum conceived as an integrated system. Then, the continuum is placed into the context of school improvement and explored in terms of a comprehensive, multi-faceted component designed to ensure all youngsters have an equal opportunity to succeed at school. Throughout the chapter, implications are discussed with respect to policy, research, practice, and training, including some general ramifications for systemic change.
Prevention in Broad Context Prevention initiatives have many facets. At a school, for example, approaches may be schoolwide with the intent of having an impact on all students; they may be limited to a classroom;
20 Howard S. Adelman and Linda Taylor Table 2.1 Outline Aid for Analyzing Key Facets of School-Oriented Prevention Efforts I. Form of initiative A. policy (federal, state, local) B. practice C. capacity building D. systemic change II. Context for practice A. community-wide B. school-wide C. in classroom as part of regular program D. an “add-on” program in or outside the regular class E. part of “clinical” services III. Stage of prevention A. primary B. secondary (early-after-onset) C. tertiary (ameliorating severe/chronic problems in ways that prevent exacerbating the conditions and that minimize their influence as secondary instigating factors) IV. Focus A. focal point of intervention 1. environment(s) 2. person(s) 3. both B. intended range of impact 1. a broad-band intervention 2. for one or more specific targets C. breadth of approach 1. directed at a categorical problem 2. multi-faceted D. general area of concern 1. addressing barriers to development, learning, and positive functioning 2. promoting healthy development E. domain 1. knowledge 2. skills 3. attitudes F. strategy 1. instruction* 2. behavior modification 3. enhancing expectations and opportunities for positive behavior 4. counseling/therapy
V.
VI.
VII.
VIII.
IX.
5. physical health programs and services 6. social support 7. social services 8. student to student support and socialization 9. school-home-community partnerships 10. enhancing security and policing measures 11. multiple strategies 12. comprehensive, school-wide approaches Level of schooling/student development A. elementary/middle/high school B. specific grade, age, or stage of development Degree of integration with other interventions A. isolated B. coordinated with others C. systematically integrated Stage of intervention development A. formative B. fully developed, but unevaluated C. empirically supported Scope of implementation A. limited project 1. at one site 2. at several sites B. systemic change initiative 1. still at pilot demonstration stage 2. being phased in—at a few sites 3. being phased in—at many sites 4. all sites involved Approach to evaluation A. focused only on accountability demands B. formative program evaluation C. summative program evaluation 1. of efficacy 2. of effectiveness when replicated under natural conditions 3. cost-effectiveness analyses D. designed as evaluation research
* Content Focus of Curricular Approaches When the emphasis is on curriculum to prevent psychosocial problems (violence, substance abuse, delinquency, pregnancy, eating disorders, learning problems, etc.) and/or promote healthy socioemotional development and effective functioning, the content focus may be on: X assets-building (including strengthening academics, developing protective factors, expanding areas of competence and self-discipline)
X socio-emotional development (e.g., understanding self and others, enhancing positive feelings toward self and others, cognitive and interpersonal
Placing Prevention into the Context of School Improvement 21 problem-solving, social skills, emotional “intelligence”) X building character (e.g., values) X physical development (e.g., diet/nutrition, sports/recreation) X fostering abilities (e.g., one or more of the multiple “intelligences,” enrichment)
X fostering hope (e.g., positive expectations for the future; perceptions of selfdetermination) X resistance education X stress reduction X symptom reduction
they may target a specific group and a specific problem. Various strategies may be used to promote healthy development or address factors that interfere with positive functioning. Table 2.1 outlines some key categories that can aid in differentiating among school-oriented prevention efforts. The outline reflects the fact that prevention encompasses not only discrete strategies but also broad, multi-faceted approaches. Policy-oriented discussions increasingly are recognizing the importance of multi-faceted approaches in accounting for social, economic, political, and cultural factors that can interfere with or promote development, learning, and teaching (Adelman & Taylor, 1997, 2006a; Center for Mental Health in Schools, 1997, 2005b; Dryfoos, 1998; Schorr, 1997). Such policies also reflect a basic assumption that many problems are not discrete, and therefore, interventions that address root causes can minimize the trend to develop separate programs for every observed problem. In turn, this is viewed as enabling increased coordination and integration of resources which can increase cost-effectiveness and impact. Major policies and practices for addressing such factors can be grouped into five areas for purposes of analyzing the state of the art and making recommendations. The areas are: (1) measures to abate inequities/restricted opportunities, (2) primary prevention and early age interventions, (3) identification and amelioration of learning, behavior, emotional, and health problems as early as feasible, (4) ongoing amelioration of mild-moderate learning, behavior, emotional, and health problems, and (5) ongoing treatment of and support for chronic/severe/pervasive problems. The range of interventions can be appreciated better along a continuum. As illustrated in Figure 2.1, the continuum ranges from primary prevention (including a focus on wellness or competence enhancement), through approaches for treating problems early-after-onset, and extending on to narrowly focused treatments for severe/chronic problems. In keeping with public education and public health perspectives, the continuum encompasses and expands efforts to enable academic, social, emotional, and physical development and address behavior, learning, and emotional problems at every school.1 Such a continuum provides one template for assessing the degree to which the set of community and school programs serving local geographic or catchment areas is comprehensive, multi-faceted, and integrated. The programs cited in Figure 2.1 are seen as integrally related. Therefore, it seems likely that the impact of each can be exponentially increased through organizing them into an integrated set of systems. These can be conceived as three interconnected levels of intervention: (1) systems to promote healthy development and prevent problems, (2) systems to intervene as early after the onset of a problem as is feasible, and (3) systems of care. As illustrated in Figure 2.2, the assumption is that effectiveness at the upper levels will result in fewer persons requiring intervention at lower levels. Note that the continuum encompasses the concepts of primary, secondary, and tertiary prevention, as well as the Institute of Medicine’s classification of a continuum of care which groups prevention approaches according to target population into a three-tiered categorical schema: universal, selective, and indicated (Mrazek & Haggerty, 1994). By stressing the importance of integrating interventions across a continuum of systems, the
22 Howard S. Adelman and Linda Taylor Examples of focus and types of intervention
Intervention Continuum Primary prevention
(Programs and services aimed at system changes and individual needs) 1.
2.
Public health protection, promotion, and maintenance to foster opportunities, positive development, and wellness • economic enhancement of those living in poverty (e.g., work/welfare programs) • safety (e.g., instruction, regulations, lead abatement programs) • physical and mental health (incl. healthy start initiatives, immunizations, dental care, substance abuse prevention, violence prevention, health/mental health education, sex education and family planning, recreation, social services to access basic living resources, and so forth) Preschool-age support and assistance to enhance health and psychosocial development
• systems’ enhancement through multidisciplinary team work, consultation, and staff
3.
Early-schooling targeted interventions
• orientations, welcoming and transition support into school and community life for
4.
students and their families (especially immigrants) support and guidance to ameliorate school adjustment problems personalized instruction in the primary grades additional support to address specific learning problems parent involvement in problem solving comprehensive and accessible psychosocial and physical and mental health programs (incl. a focus on community and home violence and other problems identified through community needs assessment)
rD is
• • • • •
tri
Early-after-onset intervention
development education and social support for parents of preschoolers quality day care quality early education appropriate screening and amelioration of physical and mental health and psychosocial problems
bu tio n
• • • •
Improvement and augmentation of ongoing regular support
• enhance systems through multidisciplinary team work, consultation, and staff development
• preparation and support for school and life transitions • teaching "basics" of support and remediation to regular teachers (incl. use of available resource personnel, peer and volunteer support)
fo
• parent involvement in problem solving • resource support for parents-in-need (incl. assistance in finding work, legal aid, ESL and citizenship classes, and so forth)
N ot
• comprehensive and accessible psychosocial and physical and mental health • •
5.
interventions (incl. health and physical education, recreation, violence reduction programs, and so forth) Academic guidance and assistance (incl. use of response to intervention) Emergency and crisis prevention and response mechanisms
Other interventions prior to referral for intensive, ongoing targeted treatments
• enhance systems through multidisciplinary team work, consultation, and staff development
• short-term specialized interventions (including resource teacher instruction and
Treatment for severe/chronic problems
6.
family mobilization; programs for suicide prevention, pregnant minors, substance abusers, gang members, and other potential dropouts) Intensive treatments • referral, triage, placement guidance and assistance, case management, and resource coordination • family preservation programs and services • special education and rehabilitation • dropout recovery and follow-up support • services for severe-chronic psychosocial/mental/physical health problems
Adapted from Adelman & Taylor (1993)
Figure 2.1 From Primary Prevention to Treatment of Serious Problems: A Continuum of CommunitySchool Programs to Address Barriers to Learning and Enhance Healthy Development.
Placing Prevention into the Context of School Improvement 23 School resources
Community resources
(facilities, stakeholders, programs, services)
(facilities, stakeholders, programs, services)
Examples: • General health education • Social and emotional learning programs • Recreation programs • Enrichment programs • Support for transitions • Conflict resolution • Home involvement • Drug and alcohol education
• • • • • • •
Drug counseling Pregnancy prevention Violence prevention Gang intervention Dropout prevention Suicide prevention Learning/behavior accommodations and response to intervention • work programs
Examples: • Recreation & Enrichment • Public health & safety programs • Prenatal care • Home visiting programs • Immunizations • Child abuse education • Internships & community service programs • Economic development
Systems for promoting healthy development & preventing problems primary prevention – includes universal interventions (low end need/low cost per individual programs)
Systems of early intervention • Early identification to treat health problems • Monitoring health problems • Short-term counseling • Foster placement/group homes • Family support • Shelter, food, clothing • Job programs
early-after-onser – includes selective & indicated interventions (moderate need, moderate cost per individual)
Systems of care treatment/indicated interventions for servere and chronic problems (High end need/high cost per individual programs)
• Special education for learning disabilities. emotional disturbance, and other health impairments
• • • • • • •
Emergency/crisis treatment Family preservation Long-term therapy Probation/mcarceration Disabilities programs Hospitalization Drug treatment
Systemic collaboration is essential to establish interprogram connections on a daily basis and over time to ensure seamless intervention within each system and among systems of prevention, systems of early intervention, and systems of care. Such collaboration involves horizontal and vertical restructuring of programs and services (a) within jurisdictions, school districts, and community agencies (e.g., among departments, divisions, units, schools, clusters of schools) (b) between jurisdictions, school and community agencies, public and private sectors; among schools; among community agencies ∗ Various venues, concepts, and initiatives permeate this continuum of intervention systems. For example, venues such as day care and preschools, concepts such as social and emotional learning and development, and initiatives such as positive behavior support, response to intervention, and coordinated school health. Also, a considerable variety of staff are involved.
Figure 2.2 A Continuum of Interconnected Systems for Meeting the Needs of All Students.
framework illustrated in Figure 2.2 moves discussion of prevention beyond a focus on discrete interventions. Specifically, it underscores the importance of horizontal and vertical restructuring of programs and services (a) within jurisdictions, school districts, and community agencies (e.g., among departments, divisions, units) and (b) between jurisdictions, school and community agencies, public and private sectors, among clusters of schools, and among community agencies. Finally, note that the continuum includes a system for promoting healthy development and has the intention of incorporating a holistic and developmental emphasis that envelops
24 Howard S. Adelman and Linda Taylor individuals, families, and the contexts in which they live, work, and play. Also implicit is the principle that the least restrictive and nonintrusive forms of intervention required to appropriately address problems and accommodate diversity are to be used. Most schools have some programs and services that fit along the entire continuum. However, the emphasis is mostly on discrete services, and interventions are not coalesced into integrated systems. Moreover, the tendency to focus mostly on the most severe problems has skewed the process so that too little is done to prevent and intervene early after the onset of a problem. As a result, public education has been characterized as a system that “waits for failure.”
Enhancing School Improvement Policy It is one thing to argue for prevention; it is quite another to argue that schools should pursue prevention comprehensively as part of their school improvement agenda. Such an argument must be framed in the context of the mission of schools. That mission, of course, is to educate the young. In pursuing this mission, schools constantly are engaged in planning improvements. The need to do so has been accentuated by current accountability demands stemming from the No Child Left Behind Act. Unfortunately, the narrow focus of prevailing school accountability measures has resulted in school improvement guidance documents that give short shrift to everything but academic instruction and that simplistically address factors that interfere with learning and teaching. For example, under the federal education act, the U.S. Department of Education (2006) has framed non-regulatory guidance for pursuing school improvement at schools that are “underperforming.” They stress that school improvement processes and timetables should be designed to create a sense of urgency about reform and to focus identified schools on quickly and efficiently improving student outcomes. This statement underscores the reality that federal, and most organizational, guidance for school improvement emphasizes seeking the quickest and most direct ways to address specific factors identified as interfering with learning and teaching (Annenberg Institute, 2006; NCREL, no date). As a result, the trend is for school improvement planning to marginalize attention to many interfering factors (Center for Mental Health in Schools, 2005b). This is the case for both internal and external barriers to learning. Fortunately, relatively few youngsters start out with internal dysfunctions or disabilities that lead to learning, behavior, and emotional problems. For many children and adolescents, however, a range of external factors is interfering with schools’ accomplishing their mission. And, as research indicates, the primary causes for most youngsters’ learning, behavior, and emotional problems are extrernal factors (related to neighborhood, family, school, and/or peers). Anyone who works with young people is all too familiar with the litany of barriers to learning, development, and teaching, such as a host of factors confronting recent immigrants and families living in poverty and, for any student, violence, drugs, and frequent school changes (Adelman & Taylor, 2006a; Catalano & Hawkins, 1995). Such barriers are strongly related to the achievement gap and to student (and teacher) dropouts. It is the impact of so many barriers that argues for schools and communities offering much more in the way of prevention programs. For this to happen, however, the agenda for school improvement must be rethought.
School Improvement Policy Marginalizes Prevention and All Other Efforts to Address Barriers Policymakers have indicated concern about the limited efficacy of student supports, such as those created to prevent and ameliorate learning and behavior problems, substance abuse,
Placing Prevention into the Context of School Improvement 25 violence, school dropouts, delinquency, teen pregnancy, and so forth (Adler & Gardner, 1994; Center for Mental Health in Schools, 2007b). In response, some reformers have attributed the unsatisfactory outcomes to the fragmented and isolated way such programs and services operate. Limited efficacy does seem inevitable as long as so many interventions are carried out in a piecemeal fashion and with little follow-through. Therefore, attention has been directed toward reducing the widespread fragmentation through increased coordination and integration of school-based and linked interventions. In particular, “integrated services” policies have been enacted to reduce redundancy, waste, and ineffectiveness resulting from the many piecemeal, categorically funded approaches. Some of the initiatives for integrated interventions have meshed with the emerging movement to expand school and community connections and enhance the infrastructure for youth development (Adelman & Taylor, 2007a; Adler & Gardner, 1994; Blank, Berg, & Melaville, 2006; Burt, 1998; Cahill, 1994, 1998; Catalano, Berglund, Ryan, Lonczak, & Hawkins, 2002; Catalano & Hawkins, 1995; Dryfoos, 1998; Dryfoos & Maguire, 2002; Pittman, 2002; Rothman, 2007; Schorr, 1997). However, by focusing primarily on coordination and integration, policymakers have failed to deal with the overriding issue, namely that the whole enterprise is marginalized in school improvement policy and practice. This reality not only seriously hampers efforts to reduce fragmentation, it keeps schools from effectively addressing factors interfering with learning, development, and teaching and re-engaging students in classroom instruction.
Toward Countering Marginalization: Expanding the Framework for School Improvement For prevention to play a significant role in the lives of children and their families, school improvement policy and practice for addressing interfering factors must undergo a transformation. Because policy for addressing barriers is so marginalized, schools and communities continue to operate with virtually no commitment and no major frameworks to guide them toward comprehensive and multi-faceted approaches for large-scale prevention and amelioration of problems. This is clearly seen in the lack of attention given these matters in school improvement plans and program quality reviews (Center for Mental Health in Schools, 2005b). This is also evident in the token way addressing barriers is dealt with in the preservice and continuing education of administrators, teachers, and others in state departments of education, district offices, and at schools. We suggest that a major breakthrough in the battle against learning, behavior, and emotional problems can be achieved only when school improvement policy, planning, implementation, and accountability fully address factors interfering with learning. This requires more than specific prevention and early intervention programs, more than outreach to link with community resources, more than coordinating school-owned services, more than coordinating school services with community services, and more than creating family resource centers, full service schools, and community schools. None of these constitute a comprehensive, multi-faceted, and cohesive approach. And, the growing consensus is that a comprehensive approach is essential to cope with the complex concerns confronting students, their families, schools, and neighborhoods (e.g., Adelman, 1993; Adelman & Taylor, 1997, 2006a, 2008; Catalano & Hawkins, 1995; Comer, 1997; Dryfoos & Maguire, 2002; Greenwald, Hedges, & Laine, 1996; Schorr, 1997). The frameworks illustrated in Figures 2.1 and 2.2 not only help ensure that prevention is perceived in a broad intervention context, they highlight the type of comprehensive approach
26 Howard S. Adelman and Linda Taylor that schools should include in school improvement planning. However, unless the current policy framework for school improvement is expanded, this is unlikely to happen. From our perspective, a high-level policy emphasis on developing a comprehensive, multifaceted continuum and doing so as an interconnected set of systems is the key not only to unifying fragmented activity, but to using all available resources in the most productive manner. As a fundamental step in this direction, it has been proposed that policymakers move from a two- to a three-component policy framework (see Adelman & Taylor, 1994, 1997, 1998, 2006b; Center for Mental Health in Schools, 1997, 2005b). As highlighted in Figure 2.3, the proposed third component encompasses a policy commitment to comprehensively enable learning by addressing barriers. When policy and practice are viewed through the lens of this third component, it becomes evident how much is missing in current efforts to enable all students to learn and develop. Establishment of this “enabling” component is intended to elevate efforts to prevent and ameliorate problems at a high policy level and integrate the work as a fundamental and essential facet of school improvement. It is important to stress that addressing barriers is not a separate agenda from a school’s instructional mission. A three-component framework is intended to fully integrate the enabling, instructional, and management components with each other (see Figure 2.3). The third component provides both a basis for combating marginalization and a focal point for developing a comprehensive framework for policy and practice. It can also help address fragmentation by providing a focus for weaving together disparate approaches to preventing and ameliorating psychosocial problems and promoting wellness. The usefulness of the concept of an enabling component as a broad unifying force is evidenced by the growing attention it is receiving at state and local education agencies (where it often is called a “Learning Supports Component” or a “Comprehensive System of Student Support”). Some of the venues are highlighted in a report from the Center for Mental Health in Schools (2005c). Current state of affairs
Direct facilitation of learning & development
Instructional/ developmental component Management component
Governance and resource management
Moving toward a comprehensive system
Student & family assistance Besides offering a small amount of school-owned student “support” services, schools outreach to the community to add a few school-based/linked services.
Governance and resource management
Instructional/ developmental component
Addressing barriers to learning
Enabling component∗
Management component
Governance and resource management
∗ The enabling component is designed to enable learning by addressing factors that interfere with learning, development, and teaching and with re-engaging students in classroom instruction. It is established in policy and practice as primary and essential and is developed into a comprehensive approach by weaving together school and community resources. Some venues where this comprehensive approach is adopted refer to the third component as a learning supports component.
Figure 2.3 Toward a Comprehensive System for Addressing Barriers to Learning: Moving from a Twoto a Three-Component Framework for School.
Placing Prevention into the Context of School Improvement 27 Figure 2.4 depicts a comprehensive enabling component as first addressing barriers to learning, development, and teaching and then re-engaging students in classroom instruction. For schools, such a component covers the three-level continuum of intervention systems outlined in Figure 2.2 and organizes all support programs, services, and activities into a well-circumscribed set of content arenas. Figure 2.5 provides an example that organizes interventions into content arenas designed to: •
• •
enhance regular classroom strategies to enable learning (e.g., improving instruction for students who have become disengaged from learning at school and for those with mild-moderate learning and behavior problems; includes a focus on prevention, early intervening, and use of strategies such as Response to Intervention) support transitions (i.e., assisting students and families as they negotiate school and grade changes and many other transitions) increase home and school connections An enabling component to address barriers and re-engage students in classroom instruction∗ Range of learners (categorized in terms of their response to academic instruction at any given point in time)
I=
Motivational ready & able
Not very motivated/ lacking prerequisite knowledge II = & skills/ different learning rates & styles/ minor vulnerabilities
No barriers
Enabling component Barriers to learning, develop., teaching
(1) Addressing interfering factors
Instructional component (a) Classroom teaching + (b) Enrichment activity
Desired outcomes
(2) Re-engaging students in classroom instruction
Avoidant/ very deficient in current III = capabilities/ has a disability/ major health problems ∗In some places, an enabling component is called a learning supports component. Whatever it is called, the component is to be developed as a comprehensive system of learning supports at a school site.
Figure 2.4 An Enabling Component to Address Barriers, Re-engage Students in Classroom Instruction, and Enhance Healthy Development at a School Site.
28 Howard S. Adelman and Linda Taylor
Classroom-based approaches to enable learning Crisis/emergency assistance & prevention
Student & family assistance Infrastructure (e.g., leadership, resource-oriented mechanisms) Community outreach
Support for transitions Home involvement in schooling
Note: An enhanced school climate (culture/sense of community) is an emergent quality resulting from a well-designed and implemented learning supports component. Adapted from adelman, H.S. & Taylor, L. (1994). On understanding intervention in psychology and education. Westport, CT: Praeger.
Figure 2.5 Intervention Content Arenas.
• • •
respond to and, where feasible, prevent crises increase community involvement and support (outreach to develop greater community involvement and support, including enhanced use of volunteers) facilitate student and family access to effective services and special assistance as needed.
Each of these is briefly described in the appendix. Note that the three levels of Figure 2.2 and six arenas of Figure 2.5 can be formed into a matrix that can be used as a tool for mapping how well a school improvement plan encompasses an enabling component. The map provides data for analyzing what is in place and what is missing related to preventing and ameliorating problems (Adelman & Taylor, 2006c). Such analyses provide a basis for planning and setting priorities. Developing a cohesive enabling component in schools with a strong emphasis on preventing problems requires significant systemic changes (Adelman & Taylor, 2007b). The initial emphasis is primarily on weaving together what schools already have (e.g., pupil services, special and compensatory education and other categorical programs). Then, the focus expands to enhance an integrated set of systems and to link school with home and community resources (e.g., formally connecting school programs with assets at home, in the business and faith communities, and neighborhood enrichment, recreation, and service resources). Accomplishing all this not only involves reframing intervention, it requires redesigning organizational and operational infrastructure, and rethinking the roles and functions of personnel at schools and central offices. Various states and localities moving to pursue school improvement in terms of three primary and essential components have adopted other designations for their enabling component. For example, the state education agencies in California and Iowa and various
Placing Prevention into the Context of School Improvement 29 districts across the country have adopted the term Learning Supports. The Hawai’i Department of Education uses the term Comprehensive Student Support System (CSSS). Building on this, proposed legislation in California refers to a Comprehensive Pupil Learning Supports System. The Berkeley (CA) Unified School District calls it a Universal Student Support System. See Center for Mental Health in Schools (2005c) and the Center’s toolkit for rebuilding student and learning supports for examples of these pioneering initiatives: http://smhp.psych.ucla.edu/ pdfdocs/studentsupport/toolkit/aida.pdf.
Rethinking Organizational and Operational Infrastructure The next concern in enhancing how prevention is pursued throughout a school district involves redesigning the organizational and operational infrastructure. Given that prevention is fully integrated into a comprehensive component for addressing barriers to learning and teaching, the focus of the redesign is on the whole component, not on prevention per se. And, given that the component to address barriers must be fully integrated into school improvement, infrastructure changes at all levels of a district are needed that can make this a reality. In designing and rethinking infrastructure, the fundamental principle remains: structure follows function. So the key to a well-designed infrastructure is first to delineate functions (and related tasks and processes) in ways that are consistent with a school’s “big picture” visionary goals. Then, the focus is on establishing an integrated set of operational mechanisms (e.g., personnel and resources) that enable accomplishment of such major functions in a cost-effective and efficient manner. For school districts, the vision of leaving no child behind requires ensuring that all students have an equal opportunity to succeed at school. Consistent with the three components highlighted in Figure 2.3, achieving such a vision requires effectively pursuing three fundamental functions: (1) facilitating learning and development; (2) addressing barriers to learning and teaching in ways that enable learning and development; and (3) governing/managing the district. To accomplish these fundamental functions and related tasks and processes, an interconnected set of organizational and operational mechanisms must be established to guide and carry out the work on a regular basis. Such infrastructure mechanisms enable leaders to steer together and to empower and work productively with staff. The type of work tasks involved include: designing and directing activity, planning and implementing specific organizational and program objectives, allocating and monitoring resources with a clear content and outcome focus, facilitating coordination and integration to ensure cohesive implementation, managing communication and information, providing support for capacity-building and quality improvement, ensuring accountability, and promoting self-renewal.
Current Infrastructure In our research, we have reviewed existing district line-authority hierarchy charts, descriptions of unit organization, and, where available, detailed descriptions of infrastructure mechanisms. A particular focus has been on how districts organize to provide interventions for addressing barriers to learning and teaching. In general, districts tend to organize around: a b
levels of schooling (e.g., elementary, secondary, early education), traditional arenas of activity, discipline affiliations, funding streams, and categorical programs (e.g., curriculum and instruction; assessment; student supports including
30 Howard S. Adelman and Linda Taylor
c
counseling and guidance, attendance, psychological and social services, health; specific types of support personnel such as counselors, psychologists, social workers, nurses; professional development; special education; specific types of compensatory education such as Title I and English language learners; gifted and talented; safe and drug-free schools; athletics, youth development, and after-school programs; homeless education; alternative schools; dropout prevention; adult education), operational concerns (e.g., finances and budget, payroll and business services, facilities, human resources, labor relations, enrollment services, information technology, security, transportation, food, emergency preparedness and response, grants and special programs, legal considerations).
All the school districts we sampled have administrators, managers, and staff who have roles related to the districts’ various efforts to prevent and ameliorate problems. However, the programs, services, and initiatives often are divided among several associate or assistant superintendents, their middle managers (e.g., directors or coordinators for specific programs), and a variety of line staff. The result is that activities related to the function of addressing barriers to learning and teaching are dispersed, often in counterproductive ways, over several divisions or departments. These include units designated “Student Services,” “Teaching and Learning,” “Title I,” “Parent/Community Partnerships,” “Grant and Special Projects,” “Youth Development,” and so forth. Special education may be embedded in a “Student Support” unit, in a “Teaching and Learning” unit, or organized as a separate unit. Regardless of the unit involved, we find that the work being carried out tends to center primarily around allocating and monitoring resources, assuring compliance and accountability, providing some support for school improvement, generating some ongoing staff development, offering a few district-wide programs and services for students, and outreaching to a minimal degree to community agencies. In general, districts tend not to be organized in ways that emphasize moving toward a comprehensive system for addressing barriers. Indeed, the matter is so marginalized that little attention is given to 1
2 3 4
enhancing the policy framework for school improvement in ways that incorporate all efforts to address barriers to learning and teaching under a broad and unifying umbrella concept established as a primary and essential component of a school’s mission, reframing interventions in ways that are consistent with such a broad, unifying concept, rethinking organizational and operational infrastructure at a school, for the feeder pattern of schools, and at the district level, facilitating major systemic change in organizations such as schools and school districts that have well-established institutional cultures.
Redesigning Infrastructure Most districts could benefit from rethinking their organizational and operational infrastructure. And, from the perspective of preventing and ameliorating problems related to learning and teaching, well-designed, compatible, and interconnected infrastructures are essential at schools, for school complexes, and at the district level. Both school and district levels play key roles in weaving together existing school and community resources and developing a full continuum of interventions over time. Moreover, establishing content and resource-oriented infrastructure mechanisms enables programs and
Placing Prevention into the Context of School Improvement 31 services to function in an increasingly cohesive, cost-efficient, and equitable way. Elsewhere we have explored infrastructure redesign at some length (Adelman & Taylor, 2006b, 2007a; Center for Mental Health in Schools, 2005d, 2005e, 2008). Here, we can only highlight a few major points. From the School Outward. Because daily contact with students happens at the school level, a district’s infrastructure should be designed from the school outward. That is, conceptually, the first concern is with delineating an effective infrastructure for a school. The new infrastructure must have leadership and staff mechanisms that support development of a comprehensive and cohesive system for addressing barriers to learning and teaching, and these mechanisms must be fully integrated into school improvement efforts. Schools in the same geographic or catchment area have a number of shared concerns. Thus, it is important to link a family of schools together to enhance equity and maximize use of limited resources by minimizing redundancy and achieving economies of scale. A properly reworked school infrastructure enables development of well-designed mechanisms for connecting a family or complex (e.g., feeder pattern) of schools, as well as establishing collaborations with surrounding community resources. For prototype illustrations of operational and organization infrastructure redesign for schools, feeder patterns, and district offices, see the references cited just above in this section. Finally, central district units need to be rethought in ways that best support the work at the school and complex levels. Specifically, the key role for these central units should be to provide leadership and build capacity for establishing and maintaining an effective infrastructure (a) at every school and (b) for connecting a family of schools in a neighborhood. All this involves reframing the work of personnel and redistributing authority (power). With this in mind, it is essential at all levels to have appropriate incentives, safeguards, and adequate resources and support for all involved in making the required systemic changes. A few specifics will help clarify the nature and scope of such changes. At the School Level. Obviously administrative leadership is key to ending marginalization of efforts to address behavior, learning, and emotional problems. Usually, the principal and whoever else is part of a school leadership team are enmeshed mainly in improving instruction and management/governance. That is, no one on such a team may be focusing on developing a comprehensive and systemic component for preventing and ameliorating problems. One way to change this is to assign the role to someone already on the leadership team and provide the individual with training to carry it out effectively. Alternatively, someone in the school who is involved with student supports (e.g., a pupil services professional, a Title I coordinator, or a special education resource specialist) can be invited to join the leadership team, assigned responsibility and accountability for ensuring the vision for preventing and ameliorating problems is not lost, and provided additional training for the tasks involved. Besides administrative leadership, another key to ending marginalization of efforts to address behavior, learning, and emotional problems is establishment of a mechanism (e.g., a team) that focuses specifically on how resources are used for problem prevention and amelioration. Few schools have resource-oriented mechanisms to ensure appropriate resource use. Such mechanisms contribute to cost-efficacy by ensuring activity is planned, implemented, and evaluated in a coordinated and increasingly integrated manner. Creation of such mechanisms is essential for braiding together existing school and community resources, and encouraging cohesive interventions. Teams established for this purpose have been designated by a variety of names including “Resource Coordinating Team,” “Resource Management Team,” and “Learning Supports Resource Team.” Note that resource-oriented mechanisms do not focus on specific students, but on how a system’s resources are used most effectively
32 Howard S. Adelman and Linda Taylor (Adelman, 1993; Adelman & Taylor, 1998, 2008; Center for Mental Health in Schools, 2005d; Lim & Adelman, 1997; Rosenblum, DiCecco, Taylor, & Adelman, 1995). One of the primary and essential tasks that a school-based, resource-oriented mechanism undertakes is that of mapping and analyzing available school and community resources (e.g., programs, services, personnel, facilities). A comprehensive “gap” assessment is generated as mapped resources are analyzed in the context of unmet needs and desired outcomes. Analyses of what is available, effective, and needed provide a sound basis for formulating priorities, redeploying resources, and developing strategies to link with additional resources at other schools, district sites, and in the community. When a resource-oriented team is established, efforts are made to bring together representatives of all relevant programs and services. This might include, for example, school counselors, psychologists, nurses, social workers, attendance and dropout counselors, health educators, special education staff, after-school program staff, bilingual and Title I program coordinators, safe and drug-free school staff, and union reps. Such a team also should include representatives of any community agency that is significantly involved with a school. Beyond these stakeholders, it is advisable to add the energies and expertise of classroom teachers, noncertificated staff, parents, and older students. Where creation of “another team” is seen as a burden, existing teams, such as student or teacher assistance teams and school crisis teams, have demonstrated the ability to perform resource-oriented tasks. However, in adding the resource-oriented tasks to another team’s work, great care must be taken to structure the agenda so sufficient time is devoted to the additional tasks. For small schools, a large team often is not feasible, but a two-person team can still do a reasonable and responsible job. Properly constituted at the school level, a resource-oriented team provides what often is a missing link for managing and enhancing programs and systems in ways that integrate, strengthen, and stimulate new and improved interventions. It also can provide leadership in guiding school personnel and stakeholders in evolving the school’s vision, priorities, and practices for addressing barriers and re-engaging students. Connecting a Family of Schools. As noted above, schools in the same geographic or catchment area have a number of shared concerns. A multi-site mechanism can connect schools in a feeder pattern with each other and with the district and the community. Such a mechanism helps ensure cohesive and equitable deployment of resources and can reduce costs by minimizing redundancy, enhancing the pooling of resources, and pursuing economies of scale. By assuming leadership and communication roles, it can (a) coordinate and integrate programs serving multiple schools; (b) identify and meet common needs with respect to guidelines and staff development; (c) ensure quality improvement across sites; and (d) create links and collaboration among schools and with community agencies. In this last respect, it can play a potent role in community outreach both to create formal working relationships and to ensure that all participating schools have access to such resources. Formed as a resource council, the mechanism convenes a monthly meeting that includes one or two representatives from resource teams in a family of schools (e.g., a high school and its feeder middle and elementary schools). Natural starting points for councils are sharing assessments of need, resource maps, analyses, and recommendations for reform and restructuring. Specific areas of initial focus usually are local, high-priority concerns, such as addressing violence and developing prevention programs and safe school and neighborhood plans. In efforts to link schools with community resources, multi-school councils are especially attractive to community agencies who often do not have the time or personnel to make independent arrangements with every school. In this respect, representatives from resource
Placing Prevention into the Context of School Improvement 33 councils can be invaluable members of neighborhood planning groups (e.g., “Service Planning Area Councils,” “Local Management Boards”). They bring information about specific schools, clusters of schools, and local neighborhoods and do so in ways that reflect the importance of school-community collaboration. At the District Level. If districts are to effectively support development of a comprehensive system for preventing and ameliorating problems at every school, they need to ensure potent administrative leadership and capacity-building support. And it is crucial that such leadership be established at a high enough level to ensure the administrator is always an active participant at key planning and decision-making (e.g., is a cabinet-level administrative leader such as an associate superintendent). In reworking district infrastructure, this administrator is assigned responsibility and accountability for coalescing all resources related to addressing barriers in ways that enhance the prevention and amelioration of problems. The resources of concern come from the general fund, compensatory education, special education, and other categorical funding streams, and special projects. This encompasses special initiatives, grants, and programs for afterschool, wellness, dropout prevention, attendance, drug abuse prevention, violence prevention, pregnancy prevention, parent/family/health centers, volunteer assistance, and community resource linkages to schools. Relevant personnel encompass student support staff, such as school psychologists, counselors, social workers, and nurses, and the full range of compensatory and special education staff. The appointed administrator will need to establish mechanisms for accomplishing the unit’s work. These should be comparable to content and process mechanisms established for the instructional component. We suggest establishing a cabinet-like structure consisting of leaders for the major content described in Figure 2.5 and the appendix to this chapter. Organizing in this way moves the enterprise away from the marginalization, fragmentation, unnecessary redundancy, and counterproductive competition that has resulted from organizing around traditional programs and/or in terms of specific disciplines. The intent is for personnel to have accountability for advancing a designated arena and working in ways that ensure all arenas are integrated. A formal infrastructure link also is needed to ensure full integration with district school improvement planning and decision-making. This means the leader (and key staff) must be included at relevant school improvement planning and decision-making tables.
Personnel Retraining at All Levels The type of systemic changes described call for new roles and functions (Adelman & Taylor, 1997, 2006b, 2007b). Such changes provide both a challenge and an opportunity for many school professionals to move beyond just coping with the problems manifested by specific students. In doing so, they can ensure that schools play a much greater role in preventing and ameliorating factors that interfere with learning, development, and teaching. With respect to personnel retraining for new roles and functions, there is growing interest in identifying common skills among education support professionals so they can cover an overlapping range of intervention activity and fully integrate education supports into the fabric of daily school improvement efforts. This is consistent with the view that specialist-oriented activity and training should be balanced with a generalist perspective (e.g., Henggeler, 1995). Proposals and pilot programs have focused on cross-disciplinary training and interprofessional education to better equip school professionals to assume expanding roles and functions (Brandon & Meuter, 1995; Lawson, 1998; Lawson & Hooper-Briar, 1994; Research
34 Howard S. Adelman and Linda Taylor and Training Center on Family Support and Children’s Mental Health, 1996; Ysseldyke, Burns, Dawson, Kelley, Morrison, Ortiz, Rosenfield, & Telzrow, 2008). In general, there is growing recognition of underlying commonalities among a variety of student problems and of the role generalist strategies can play in preventing and ameliorating them (Carnegie Council on Adolescent Development, 1995). All this is consistent with fostering less emphasis on intervention ownership and more attention on accomplishing desired outcomes through flexible roles and functions for staff (see Adelman & Taylor, 1994; Lawson & Hooper-Briar, 1994; Lipsky & Gartner, 1992). Recent work also demonstrates the value of redeploying and training a cadre of pupil services personnel as change agents in moving schools toward better approaches for addressing barriers to learning (Adelman, 1993; Adelman & Taylor, 1994; Center for Mental Health in Schools, 2005e 2005f; Lim & Adelman, 1997). Designated as organization facilitators, such professionals are retooled to come to the work with a relevant base of knowledge and skills. The additional training provides them with an understanding of the specific activities and mechanisms required for establishing and maintaining comprehensive, integrated approaches and increases their capacity for dealing with the processes and problems of organizational change.
Prevention and the Evidence-Based Practice and Accountability Dilemmas Do You Have Data to Support Adopting That Approach? Can You Prove It’s Worth Continuing to Do That? In the context of school improvement, these questions dominate efforts to enhance and sustain school-based prevention programs. Although understandable in light of the unfulfilled promise of so many programs and the insatiable demands on limited resources, premature demands for data are producing dilemmas. Prevention researchers and practitioners appreciate the importance of drawing on the science-base and they understand they must be accountable for the outcomes of their practices. At the same time, most have experienced the dilemmas raised by data demands that ignore the complexities associated with developing and evaluating interventions to prevent and ameliorate major problems. We find that few leaders for school improvement argue, in principle, against using the best data available to inform decisions. Many are concerned, however, about the current reliance on an underdeveloped science-base for making program decisions and on narrow-band measures for demonstrating accountability. Analyses have long stressed that school improvement, first and foremost, needs the kind of data that can help advance practice and policy (e.g., General Accounting Office, 1989). The danger is that a limited body of research and an overemphasis on achievement testing to ensure accountability will reify an unsatisfactory status quo.
Concerns and Controversies about the Existing Evidence-Base The movement for evidence-based practices is reshaping public policy in ways that have generated a host of cautions (e.g., Education Week, 2006; Flay, Biglan, Boruch, Castro, Gottfredson, Kellam, Moscicki, Schinke, Valentine, & Ji, 2005; Gorman, 2002, 2003; Government Accountability Office, 2007; Weiss, Murphy-Graham, Petrosino, & Gandhi, 2008). A central concern is that practices developed under highly controlled laboratory conditions are being pushed prematurely into widespread application based on unwarranted assumptions. This concern is especially salient when the evidence-base comes from shortterm studies and has not included samples representing major subgroups with whom the practice will be used.
Placing Prevention into the Context of School Improvement 35 In general, the rush to provide empirical support for interventions that can be implemented in schools has increased the tendency to by-pass discussion of significant methodological problems that limit claims about the science-base for many interventions. This leads to an overstatement of expertise, which in turn contributes to the mystification of the general public and many practitioners. None of this helps improve school-based practices. Indeed, overstating the evidence-base usually leads to a backlash. Such a backlash already has emerged around claims about the science underlying the prevention practices that schools are being asked to adopt (e.g., Gorman, 2003). With all the factors that continue to hamper the progress of prevention science, it is a mistake to do anything that feeds into public concern about the overselling of outcome evidence. Until researchers demonstrate that a prototype is effective under “real-world” conditions, it can only be considered a promising and not a proven practice. Even then it must be determined whether it is a best practice. And, with respect to the designation of best, it is well to remember that best simply denotes that a practice is better than whatever else is currently available. How good it is depends on complex analyses related to costs and benefits. Despite clear limitations, specific interventions increasingly are prescribed officially, and others are proscribed by policymakers and funders. This especially has been the situation surrounding school-based prevention programs (Gorman, 2002). As official lists have been generated, the growing concern is that only those practitioners who choose from these lists will be rewarded. And a trend to select only from what is on the list surely will exacerbate the tendency for schools to adopt discrete programs, rather than develop and evaluate a comprehensive, multi-faceted, and cohesive system for addressing barriers and re-engaging students. This can only perpetuate current fragmentation, inappropriate redundancy, counterproductive competition for sparse resources, and marginalization.
Current Accountability Mandates Also Create a Dilemma Accountability is a tool that can be used to encourage people and organizations to meet appropriate standards, but it also can generate issues and problems. Current demands related to school improvement illustrate the matter. First, we should note that two unfounded presumptions at the core of current school accountability policies are that: (1) any approach in widespread use must be at a relatively evolved stage of development and thus warrants the cost of summative evaluation; and (2) major conceptual and methodological problems associated with evaluating program efficacy and effectiveness are resolved. The reality, of course, is that some school programs must be introduced prior to adequate development with a view to evolving them based on what is learned each day. As evaluation methodologists clearly acknowledge, the most fundamental problems related to summative evaluation have not been solved. This is particularly the case when it comes to large-scale program replication (Adelman & Taylor, 1997, 2007b; Durlak & Wells, 1997; Replication and Program Services, 1993; Sarason, 1990; Weisz, Donenberg, Han & Weiss, 1995). Second, it should be stressed that the prevailing focus in school accountability is on specific evidence of results—usually in terms of readily measured immediate benefits—and on cost containment. This has led to policies pressuring schools and districts to produce quick improvements in achievement test score averages. As we have suggested in this chapter, one major factor that makes that demand unrealistic in many schools is the absence of a comprehensive and multi-faceted component to prevent and ameliorate problems. The irony is that schools cannot devote the time, talent, and other resources necessary for developing such
36 Howard S. Adelman and Linda Taylor a component because their resources are tied up in being accountable for a school improvement policy that is too narrowly conceived. As a result, schools are caught in a major dilemma. Raising academic standards and expectations includes eliminating social promotion, closing the achievement gap, and reducing dropouts. However, to do all this effectively, schools need to develop a comprehensive system of learning supports. Unfortunately, their current approach to school improvement precludes more than a marginal focus on establishing a comprehensive system for preventing and ameliorating problems and re-engaging students in classroom instruction. The dilemma is compounded by the pressure to choose mainly from a list of discrete programs judged to have an adequate evidence-base. There are undeniable benefits from demonstrating that intended outcomes are achieved. However, if one is not careful, accountability biases and pressures can reshape research and practice (Adelman, 1986; Adelman & Taylor, 1994; Burchard & Schaefer, 1992; Cuban, 1990; Tyack & Cuban, 1995). In most organizations, what is measured receives direct attention, and what is not measured is marginalized. Achievement testing for school accountability is a case in point. Policymakers have decided to collect data only on a relatively small set of academic goals (e.g., reading, math). Because school accountability stresses only academic achievement test gains, matters for which accountability data are not gathered, such as learning supports and social and emotional learning, are given short shrift. Indeed, as more and more resources are used to meet data demands, fewer resources are available for improving the way long-standing and complex problems are addressed and healthy development is promoted. Over the past few decades, social, political, and economic forces pressing for the use of evidence-based practices and immediate accountability increasingly have reshaped what transpires in schools. As is evidenced by the ongoing struggle to advance school-based prevention and early intervention programs, the impact on prevention science has been a negative one (e.g., see Albee & Gullotta, 1997; Bond & Compas, 1989; Dryfoos, 1990; Durlak, 1995; Elias, 1997; Schorr, 1988; Slavin, Karweit, & Wasik, 1994; Weissberg, Gullotta, Hamptom, Ryan, & Adams, 1997; Weiss, Murphy-Graham, Petrosino, & Gandhi, 2008).
Addressing the Data Dilemmas As Sararson (2003) warns: “Intervention confronts a host of problems for which current knowledge and research are inadequate, incomplete, and even misleading” (p. 209). Because the current science-base fails to account for the full scope of a school’s obligations to meet the needs of the society and its citizens, he stresses that schools need to adopt a combined moralscientific stance in making decisions about practices. With specific reference to prevention science, a direct way to deal with the data dilemma is to ensure that data collection is pursued within the context of an evaluative research agenda. Although there are many unresolved concerns related to evaluative research, scholarly work has advanced the way such activity is conceived in education and psychology, and thus there are ample methodological guidelines (Adelman, 1986; Adelman & Taylor, 1994; Chen & Rossi, 1992; Hollister & Hill, 1995; Knapp, 1995; Pogrow, 1998; Scriven, 1993; Sechrest & Figueredo, 1993; Weiss, 1995).2 First and foremost the methodology calls for formative evaluation; that is, data gathering and analyses that can help with the developmental facets of a research and development agenda. At the same time, such formative evaluations should and can be designed with a view
Placing Prevention into the Context of School Improvement 37 to summative evaluation of efficacy and effectiveness and with deference to immediate accountability demands and cost-benefit analyses.
Concluding Comments The next decade must mark a turning point in how schools and communities address the problems of children and youth. In particular, if the mandates of the No Child Left Behind Act and the Individuals with Disabilities Education Act 2004 are to be achieved, schools can and need to focus much more on prevention. Currently, however, prevention in schools is not a high priority. For this to change, schoolbased prevention cannot be pursued as a separate agenda. It must be fully integrated into efforts to counter learning, behavior, and emotional problems and promote personal and social growth. And, in turn, these efforts must be fully integrated into school improvement processes. Clearly, there is much work to be done as schools across the country strive to prevent and ameliorate factors causing so many students to be left behind.
Notes Author note: This article was prepared in conjunction with work done by the Center for Mental Health in Schools at UCLA which is partially supported by funds from the U.S. Department of Health and Human Services, Public Health Services, Health Resources and Services Administration, Bureau of Maternal and Child Health, Office of Adolescent Health. 1 There are too many references to cite related to the continuum, but a perspective on the range of work directly relevant to schools can be garnered from the following resources: Adelman & Taylor (2006a, 2006b), Albee & Gullotta (1997), Borders & Drury (1992), Carnegie Council on Adolescent Development (1988), CASEL (2003), Center for Mental Health in Schools (2004, 2005a), Cochrane Library (2007), Dryfoos (1990, 1994, 1998), Durlak (1995), Duttweiler (1995), Gottfredson & Gottfredson (2001), Gottfredson & Wilson (2003); Henggeler (1995), Hoagwood & Erwin (1997), Hoagwood, Olin, Kerker, Kratochwill, Crowe, & Saka, (2007), Jimerson & Furlong (2006), Karoly, Greenwood, Everingham, et al. (1998), Kazdin (1993), Larson (1994), Scattergood, Dash, Epstein, & Adler (1998), Schorr (1988, 1997), Slavin, Karweit, & Wasik (1994), Smink & Schargel (2004), Thomas & Grimes (2008). Also, see the other cited references for relevant resources. 2 For a discussion of the similarities and differences between research and evaluation, see Adelman (1986).
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40 Howard S. Adelman and Linda Taylor Education Week (2006, Feb 15). White House suggest model used in reading to elevate math skills. Retrieved July 1, 2007 from www.edweek.org Elias, M. J. (1997). Reinterpreting dissemination of prevention programs as widespread implementation with effectiveness and fidelity. In R. P. Weissberg, T. P. Gullotta, R. L. Hamptom, B. A. Ryan, & G. R. Adams (Eds.), Establishing preventive services (pp. 253–289). Thousand Oaks, CA: Sage. Flay, B. R., Biglan, A., Boruch, R. F., Castro, F. G., Gottfredson, D., Kellam, S., Moscicki, E. R., Schinke, S., Valentine, J. C., & Ji, P. (2005). Standards of evidence: Criteria for efficacy, effectiveness and dissemination. Prevention Science, 6, 151–175. General Accounting Office. (1989). Prospective evaluation methods: The prospective evaluation synthesis. GAO/PEMD-10.1.10. Washington, DC: Author. Retrieved July 1, 2007 from http://www.gao.gov/ special.pubs/10_1_10.PDF Gorman, D. M. (2002). Defining and operationalizing a research-based prevention: A critique (with case examples) of the US Department of Education’s Safe, Disciplined and Drug-Free Exemplary Programs. Evaluation and Program Planning, 25, 295–302. Gorman, D. M. (2003). Alcohol & drug abuse: The best of practices, the worst of practices: The making of science-based primary prevention programs. Psychiatric Services, 54, 1087–1089. Gottfredson , G. D., & Gottfredson, D. C. (2001). What schools do to prevent problem behavior and promote safe environments. Journal of Educational & Psychological Consultation, 12, 313–344. Gottfredson, D. C. & Wilson, D. B. (2003). Characteristics of effective school-based substance abuse prevention. Prevention Science, 4, 27–38. Government Accountability Office (2007). Reading First: States report improvements in reading instruction, but additional procedures would clarify education’s role in ensuring proper implementation by states. Washington, DC: Author. Retrieved July 1, 2007 from http://www.gao.gov/new.items/ d07161.pdf. Greenberg, M. T., Weissberg, R. P., O’Brien, M. E., Zins, J. E., Fredericks, L., Resnik, H., et al. (2003). Enhancing school-based prevention and youth development through coordinated social, emotional, and academic learning. American Psychologist, 58, 466–474. Greenwald, R., Hedges, L. V., & Laine, R. D. (1996). The effect of school resources on student achievement. Review of Educational Research, 66, 361–396. Henggeler, S. W. (1995). A consensus: Conclusions of the APA Task Force report on innovative models or mental health services for children, adolescents, and their families. Journal of Clinical Child Psychology, 23, 3–6. Hoagwood, K., & Erwin, H. (1997). Effectiveness of school-based mental health services for children: A 10-year research review. Journal of Child and Family Studies, 6, 435–451. Hoagwood, K. E., Olin, S. S., Kerker, B. D, Kratochwill, T. R., Crowe, M., & Saka, N. (2007). Empirically based school interventions targeted at academic and mental health functioning. Journal of Emotional and Behavioral Disorders, 15, 66–92. Hollister, G., & Hill, J. (1995). Problems in the evaluation of community-wide initiatives. A paper prepared for the Roundtable on Comprehensive Community Initiatives. Russell Sage Foundation. Jimerson, S. R., & Furlong, M. J. (Eds.). (2006). Handbook of school violence and school safety: From research to practice. Englewood Cliffs, NJ: Lawrence Erlbaum. Karoly, L. A., Greenwood, P. W., Everingham, S. S., Hoube, J., Kilburn, M. R., Rydell, C. P., Sanders, M., & Chiesa, J. (1998). Investing in our children: What we know and don’t know about the costs and benefits of early childhood interventions. Santa Monica, CA: RAND. Available online at http://www.rand.org/pubs/monograph_reports/MR898/ Kazdin, A. E. (1993). Adolescent mental health: Prevention and treatment programs. American Psychologist, 48, 127–141. Knapp, M. (1995). How shall we study comprehensive, collaborative services for children and families? Educational Researcher, 24, 5–16. Larson, J. (1994). Violence prevention in the schools: A review of selected programs and procedures. School Psychology Review, 23, 151–164. Lawson, H. A. (1998). Academically based community scholarship, consultation as collaborative
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Appendix Content Areas to Address Barriers to Learning (1) Classroom-Based Approaches encompass: •
•
•
• •
Opening the classroom door to bring available supports in (e.g., peer tutors, volunteers, aides trained to work with students-in-need; resource teachers and student support staff work in the classroom as part of the teaching team) Redesigning classroom approaches to enhance teacher capability to prevent and handle problems and reduce need for out-of-class referrals (e.g., personalized instruction; special assistance as necessary; developing small group and independent learning options; reducing negative interactions and over-reliance on social control; expanding the range of curricular and instructional options and choices; systematic use of prereferral interventions) Enhancing and personalizing professional development (e.g., creating a Learning Community for teachers; ensuring opportunities to learn through co-teaching, team teaching, and mentoring; teaching intrinsic motivation concepts and their application to schooling) Curricular enrichment and adjunct programs (e.g., varied enrichment activities that are not tied to reinforcement schedules; visiting scholars from the community) Classroom and school-wide approaches used to create and maintain a caring and supportive climate.
Emphasis at all times is on enhancing feelings of competence, self-determination, and relatedness to others at school and reducing threats to such feelings. (2) Crisis Assistance and Prevention encompasses: • •
Ensuring immediate assistance in emergencies so students can resume learning Providing follow-up care as necessary (e.g., brief and longer-term monitoring)
Placing Prevention into the Context of School Improvement 43 • • •
• •
Forming a school-focused Crisis Team to formulate a response plan and take leadership for developing prevention programs Mobilizing staff, students, and families to anticipate response plans and recovery efforts Creating a caring and safe learning environment (e.g., developing systems to promote healthy development and prevent problems; bullying and harassment abatement programs) Working with neighborhood schools and community to integrate planning for response and prevention Capacity-building to enhance crisis response and prevention (e.g., staff and stakeholder development, enhancing a caring and safe learning environment).
(3) Support for Transitions encompasses: •
• • • •
• •
Welcoming and social support programs for newcomers (e.g., welcoming signs, materials, and initial receptions; peer buddy programs for students, families, staff, volunteers) Daily transition programs (e.g., for before school, breaks, lunch, after school) Articulation programs (e.g., grade to grade—new classrooms, new teachers; elementary to middle school; middle to high school; in and out of special education programs) Summer or intersession programs (e.g., catch-up, recreation, and enrichment programs) School-to-career/higher education (e.g., counseling, pathway, and mentor programs; broad involvement of stakeholders in planning for transitions; students, staff, home, police, faith groups, recreation, business, higher education) Broad involvement of stakeholders in planning for transitions (e.g., students, staff, home, police, faith groups, recreation, business, higher education) Capacity-building to enhance transition programs and activities.
(4) Home Involvement in Schooling encompasses: •
•
• • •
•
Addressing specific support and learning needs of family (e.g., support services for those in the home to assist in addressing basic survival needs and obligations to the children; adult education classes to enhance literacy, job skills, English-as-a-second language, citizenship preparation) Improving mechanisms for communication and connecting school and home (e.g., opportunities at school for family networking and mutual support, learning, recreation, enrichment, and for family members to receive special assistance and to volunteer to help; phone calls and/or emails from teacher and other staff with good news; frequent and balanced conferences—student-led when feasible; outreach to attract hard-to-reach families—including student dropouts) Involving homes in student decision-making (e.g., families prepared for involvement in program planning and problem-solving) Enhancing home support for learning and development (e.g., family literacy; family homework projects; family field trips) Recruiting families to strengthen school and community (e.g., volunteers to welcome and support new families and help in various capacities; families prepared for involvement in school governance) Capacity-building to enhance home involvement.
44 Howard S. Adelman and Linda Taylor (5) Community Outreach for Involvement and Support encompasses: •
•
• • •
Planning and implementing outreach to recruit a wide range of community resources (e.g., public and private agencies; colleges and universities; local residents; artists and cultural institutions, businesses and professional organizations; service, volunteer, and faith-based organizations; community policy and decision-makers) Systems to recruit, screen, prepare, and maintain community resource involvement (e.g., mechanisms to orient and welcome, enhance the volunteer pool, maintain current involvements, enhance a sense of community) Reaching out to students and families who don’t come to school regularly—including truants and dropouts Connecting school and community efforts to promote child and youth development and a sense of community Capacity-building to enhance community involvement and support (e.g., policies and mechanisms to enhance and sustain school-community involvement, staff/stakeholder development on the value of community involvement, “social marketing”).
(6) Student and Family Assistance encompasses: •
•
•
•
•
• •
Providing extra support as soon as a need is recognized and doing so in the least disruptive ways (e.g., prereferral interventions in classrooms; problem-solving conferences with parents; open access to school, district, and community support programs) Timely referral interventions for students and families with problems based on response to extra support (e.g., identification/screening processes, assessment, referrals, and follow-up—school-based, school-linked) Enhancing access to direct interventions for health, mental health, and economic assistance (e.g., school-based, school-linked, and community-based programs and services) Care monitoring, management, information sharing, and follow-up assessment to coordinate individual interventions and check whether referrals and services are adequate and effective Mechanisms for resource coordination and integration to avoid duplication, fill gaps, garner economies of scale, and enhance effectiveness (e.g., braiding resources from school-based and linked interveners, feeder pattern/family of schools, community-based programs; linking with community providers to fill gaps) Enhancing stakeholder awareness of programs and services Capacity-building to enhance student and family assistance systems, programs, and services.
3
School Mental Health Prevention at All Levels Kevin Dwyer, Senior Associate, American Institutes for Research Erika Van Buren, District of Columbia Department of Mental Health Jeremy, an 11-year-old, sixth-grade child at a large urban school district, is falling increasingly behind in reading and math. Jeremy’s behavior is troubling; sometimes he curses at the teacher, or threatens and hits his classmates. His attendance is less than the desired 80%, and he is reported to have no friends among his classmates. Jeremy is regularly suspended but serves “inschool suspension” to keep him in the building. The counselor and school social worker have had frequent contacts with Jeremy’s caregiver and grandmother, and while she is responsive to their recommendations, she is unable to monitor his out-of-home activities. She indicates that Jeremy’s mother has been in and out of drug rehabilitation, and that his father was murdered. Jeremy’s grandmother says that he cries himself to sleep more often than not, and says he “hates school.” Jeremy’s school has provided many interventions. He was referred and found eligible for special education services, and resources were provided for reading and behavior, including a referral to the city mental health clinic where Jeremy was placed on a “priority” waiting list. The school’s team has also provided incidence-driven consultation to the classroom teacher and “as needed” counseling when Jeremy disrupts his class. After several months and a series of interventions, the measured results have been minimal in changing Jeremy’s disruptive behaviors or improving his attendance or academics.
This is not an unusual scenario. Many schools which serve 400 or more predominantly poor children have at least 60 children with equally complex and intensive needs. Researchers also report that many of these schools have more than 20% of children entering each year with multiple risk factors for mental health and behavioral problems. These problems in early grades escalate year-to-year, having a dramatic negative impact on academic learning for these children and their peers (Walker & Sprague, 1999). In an effort to address the growing numbers of students with complex behavioral and academic challenges, schools and their caring staff can become overwhelmed. Moreover, school interventions frequently come too-little, too-late. As a result, most schools and communities fail to adequately address the very complex social-emotional needs of these children.
The “Domino Effect” of Academic and Behavioral Problems Academic and behavioral problems like those experienced by Jeremy often place students on a road that is paved with school adjustment difficulties, gradual disengagement from school life, and inevitable school failure and dropout. Other research has shown that sixth-grade children who are academically deficient in reading or math, or who received poor marks for behavior, had only a 10% chance of graduating with their peers, and a 20% chance of graduating a year late (Balfanz & Herzog, 2006). Research has also revealed that as many as 80% of
46 Kevin Dwyer and Erika Van Buren youth found delinquent and incarcerated have a diagnosable mental health disorder (Cocozza & Skowyra, 2000). Other research suggests that more than half of students with a diagnosable mental illness drop out of high school (U.S. Department of Education, 2006). Jeremy is very likely to become one of these casualties. In many schools, these youth consume a great deal of the school’s resources and attention; they constantly disrupt classroom instruction; consume the time and resources of disciplinarians, specialists and others; and lead frustrated school staff to reluctantly recommend a deadend “alternative” placement. These are the youth who are at risk of delinquency (Shader, 2001). Sadly, belief in the effectiveness of school mental health services suffers collateral damage from this scenario, as well. Since the school “provided mental health services” (i.e., social work involvement, family contact and/or clinic referral) and the child did not improve, school mental health services therefore must not work. Caring staff and well-intended special education and related services interventions are not enough to address the needs of students exhibiting a multitude of problems, who are attempting to cope with overwhelming trauma and loss, possible depression, or post-traumatic stress disorder. Fragmented services, delivered as a patchwork of disconnected interventions, will fail. Programs that provide little care management and lack intensive, individualized academic and behavioral intervention alignment (the combining and simultaneous delivery of academic and behavioral interventions) are all too common. Jeremy is fragile, acting out, and coping with loss, social isolation, and the frustrations associated with academic delays. His multiple needs require an intensive, well-planned and monitored wraparound system of services: services that address behavioral, emotional, academic and social needs with multi-systemic elements and strong care-giver supports to give him— and his equally troubled peers—a fighting chance to succeed. Schools must provide the home for such programs. Moreover, intensive interventions are critical but by no means sufficient. The school climate must be mentally healthy. The climate must sustain and support mental health by building and maintaining peer and adult connections with all students, providing an atmosphere that promotes the prevention of problems, identifying students early who are placed at risk of problems, and supporting the positive behaviors and academic progress of recovering students.
Overview This chapter will build the case in support of school-based prevention, discuss the state of mental health service delivery for children and youth in the United States, describe common childhood mental health challenges, and describe effective school mental health services, with an additional focus on successful prevention and mental health promotion. It will also explore solutions to the dilemma of how our resources are currently utilized, relative to what is needed to maximize student success. The reader will be provided with ideas and remedies to enable school and community mental health providers to partner with others, be progressive leaders in fostering mentally healthy schools, and ensure that children needing services receive effective, coordinated, proven interventions that produce positive results. Moreover, these challenges and solutions will be discussed within the broader policy and cultural context of school communities to shed light on the importance of the family, school and macro system ecologies in promoting positive student well-being at all levels.
School Mental Health: Prevention at All Levels 47
Embracing the True Potential of Schools School mental health services are critical to the academic mission of schools. Both the research literature and practice-based evidence clearly indicate that social-emotional skills and wellbeing are critical to academic learning; that safe and caring schools and classrooms enhance academic success; that reinforcing positive behaviors increases instructional time; and that supported, challenging instruction increases academic learning (see Osher, Dwyer & Jimerson, 2006). It is also no secret that the interaction between positive student development and safe and caring learning environments produces a synergistic effect, in which one enhances the other. Academically successful students are more likely to see their teachers as caring and less likely to have discipline problems and vice versa (Durlak, 1998). Conversely, students whose academic performance and behaviors are identified as problematic are more likely to experience more negative encounters with school staff and punishment within the classroom, producing an aversion to school and increasing their potential for dropout (National Center for Education, Disability and Juvenile Justice, n.d.). Integrating and aligning effective mental health and education services for children is vitally important to ensure academic learning and the development of life-long social-emotional skills. This integration is becoming increasingly self-evident to many stakeholders and has been acknowledged by leading federal, state and local policymakers, professional organizations and agencies (Weist & Paternite, 2006). Schools provide the perfect milieu for improving the availability of quality services through the implementation of broad-based mental health promotion and prevention programming (Mills et al., 2006). The construct of mental health promotion refers broadly to the processes which serve to optimize the positive mental health and well-being of all individuals, regardless of history or risk for mental health problems (Canadian Mental Health Association, 1999; World Health Organization, 2002). Mental health promotion can include efforts to develop policies, procedures and environments that support positive mental health functioning, and initiatives that help individuals and communities to develop the skills and assets necessary to advocate on behalf of their own mental health needs, as well as to foster resilience against adversity that can increase risk for mental health problems. Within the context of schools, this can include curricula which target the development of social and emotional skills, school-wide initiatives to cultivate positive school climate, and the development of school-community partnerships that promote a sense of belonging, civic engagement and responsibility, to name but a few. It is important to mention that mental health promotion is distinct from traditional “mental health treatment” in that the purpose is to maintain positive mental health outcomes for all (i.e., increase sense of efficacy, personal control, determination, and other protective factors), rather than treating symptoms of mental illness. Moreover, central to the mission of such initiatives is a commitment to utilize the natural support networks already existing within families and communities; to use a diverse range of culturally and linguistically responsive strategies that reflect the needs of the populations served; and to incorporate “. . . active citizen involvement in identifying mental health needs, setting priorities, controlling and implementing solutions, and evaluating progress towards goals” (Canadian Mental Health Association, 1999). Mental health prevention refers to the myriad of interventions and strategies designed to decrease the known risk factors for mental health and academic issues, while simultaneously bolstering the protective factors that protect against the impact of said risk. School-based prevention science has consistently documented the utility and effectiveness of the public health
48 Kevin Dwyer and Erika Van Buren model of prevention—a model which includes a “three-tiered” approach for understanding and addressing the diverse levels of need among students and families within the school community. While numerous terms have been used to name these three levels of prevention, this approach typically includes the following dimensions: •
•
•
Universal Prevention. School-based universal prevention embodies mental health promotion in action. These systems, programs and strategies can be implemented with the entire school community to develop the skills and assets that promote healthy social, emotional and academic functioning in students, to protect against psychosocial difficulties, and create learning environments that will promote and sustain positive youth development and functioning (National Center for Education, Disability and Juvenile Justice, n.d.; JJ/SE Shared Agenda, 2007). Early Intervention. School-based early intervention strategies with students who possess specific individual and environmental risk factors for mental health and academic problems, and/or those students for whom universal prevention strategies have not worked and who are exhibiting initial signs of problems. Examples may include providing supports to students who have recently experienced trauma or personal loss, children who have experienced an unusual increase in school absences, or who have received one disciplinary referral rather than five (National Center for Education, Disability and Juvenile Justice, n.d., JJ/SE Shared Agenda, 2007). Early intervention is viewed as a means to intervene at the onset of psychosocial and school adjustment problems as a means of preventing unnecessary special education placement (Foster et al., 2005). Intensive Intervention. This form of intervention is necessary for about 1–3% of the student population (National Center for Education, Disability and Juvenile Justice, n.d., JJ/SE Shared Agenda, 2007). Students experiencing significant emotional and behavioral problems receive a full continuum of mental health and academic services and supports. The wraparound process has been lauded as an effective approach for structuring and delivering these services. This includes the coordination and planning of services across multiple system to address the diverse ecologies of student and family life as well as home, community and school-based case management and service provision and monitoring in the least restrictive placement. Extensive family involvement is central to the implementation of the process (National Center for Education, Disability and Juvenile Justice, n.d.; JJ/SE Shared Agenda, 2007).
In school communities serving students placed at risk by poverty’s adverse effects these percentage distributions are remarkably different, requiring far greater intervention resources. Studies have shown that in communities burdened by poverty, at least 18% of the school student population have severe mental and behavioral problems, needing intensivelevel interventions, and 40% are at risk with moderate behavioral and academic problems, needing planned early interventions, leaving only 42% having the foundation to respond to universal school-wide interventions and instruction (Baker, Kamphaus, Horne & Winsor, 2006). There is a growing body of evidence supporting the use of the public health model for the design and implementation of comprehensive school-based mental health services. Research suggests that adopting the use of universal, early intervention, and intensive interventions can make a difference in the potential for dropout or graduation for a significant percentage of youth (See School Psychology Review, Volume 32 Number 3, 2003: “Emerging models for promoting children’s mental health: Linking systems for prevention and intervention”; Eggert,
School Mental Health: Prevention at All Levels 49 Thompson, Herting, Nicholas, & Dickers, 1994; Felner, Brand, Adan, Mulhall, Flowers, Satrain, & DuBois, 1993; Hahn, Leavitt, & Aaron, 1994; Reyes & Jason, 1991). Implementation of mental health promotion interventions in the form of universal prevention curricula such as Lifeskills Training (Botvin, Eng, & Williams, 1980), Project ACHIEVE (Knoff & Batsche, 1995), and Responding in Peaceful and Positive Ways (RiPP) have resulted in a host of positive student outcomes, including significant reductions in substance use, violent behavior, discipline referrals, suspensions, special education referrals and placement, and grade retention (Botvin, Griffin, & Nichols, 2006; Spoth, Clair, Shin, & Redmond, 2006). Another commonly cited advantage of school mental health, prevention and related services includes their potential to improve access to services for vulnerable and underserved populations by eliminating traditional barriers to mental health services and supports. Such services can reduce the stigma associated with mental health problems and treatment which often preclude help-seeking behaviors, by offering services in students’ natural environments (Mills et al., 2006). School-based services can also improve access by providing unique opportunities to engage parents and families in the process of fostering their children’s positive development and well-being (Mills et al., 2006). One simple example includes increased opportunities for parents and mental health service providers to interact more frequently and informally, and to provide ongoing feedback and input regarding student needs and progress at common interface points within the school (i.e., report card pick-up days, parent-teacher conferences), as opposed to the once-per-week, “50-minute hour” which has typically characterized the structure of treatment within psychology and other mental health disciplines (Weist & Paternite, 2006; Weist, Evans, & Lever, 2003). Both empirical and practice-based evidence tell us what works and what doesn’t when allocating and structuring our schools’ resources to better address the holistic needs of all students. Therefore, it would seem that such potential would be actualized in many if not most school communities. Unfortunately, reality is quite different; school mental health services are frequently marginalized or operate on a distinct and parallel plane to academic instruction (Adelman & Taylor, 1997). Schools have yet to see themselves as agents of social-emotional, behavioral and mental health skill development and well-being. Community, state and federal leaders demand that schools focus on academic standards, and these standards provide the criterion by which schools are compared and ranked for quality. Schools are rarely ranked on “caring” or their ability to help students “learn interpersonal problem-solving” and conflict resolution. Respect for teachers and students’ sense of responsibility for self are expected, required and often rewarded but rarely overtly taught. In order for schools to move from talking about the critical link between academic and social-emotional skills to implementing effective, integrated practices, dramatic changes are required in the behavior of most stakeholders, particularly school staff and leadership. New methods will need to be learned to replace previously learned methods. Rules, regulations, procedures and resource allocations will require review and change. Learning a new behavior (i.e., reinforcing engaged time-on-task) to replace an old behavior (correcting a student for not working) requires a dramatic refocusing by teachers both in how they respond, and in which behaviors they respond to or reinforce (Doll, 2006).
A Status Report on Child and School Mental Health While historically ignored, the importance of children’s mental health and recognition of childhood mental illness have grown considerably over the past half-century. Mental Health:
50 Kevin Dwyer and Erika Van Buren A Report of the Surgeon General (1999) dedicated a full, 97-page chapter to children. It reported study findings that, “21% of U.S. children ages 9 to 17 had a diagnosable mental or addictive disorder associated with at least minimal impairment . . .” (p. 123) and that 11% were found to be significantly functionally impaired and 5% extremely impaired, showing that mental illness is a significant public health problem. Of equal importance to these high percentages is the report’s finding that among all children the most common diagnosable disorders are anxiety and mood disorders (such as depression and bi-polar disorders) and not the behavior disorders that schools most often identify and associate with mental health problems. That same Surgeon General’s report defined mental illness as: . . . the term that refers collectively to all diagnosable mental disorders. Mental disorders are health conditions that are characterized by alterations in thinking, mood or behavior (or some combination thereof) associated with distress and/or impaired functioning . . . Alterations in thinking, mood, or behavior contribute to a host of problems—patient distress, impaired functioning, or heightened risk of death, pain, disability, or loss of freedom. (p. 5) Intensity and duration delineate mental health disorders from what the report calls “mental health conditions,” the latter being either less intense or occurring for a short duration. Conversely, this same report defined mental health as: . . . a state of successful performance of mental function, resulting in productive activities, fulfilling relationships with other people and the ability to adapt to change and cope with adversity. Mental health is indispensable to personal well-being, family and interpersonal relationships, and contribution to community or society . . . mental health is the springboard of thinking and communication skill, learning, emotional growth, resilience, and self-esteem. (p. 4) School mental health has been defined broadly by national collaborative groups as encompassing mental wellness and the prevention, identification and treatment of mental disorders in children, families and staff. In 2001, the Policy Leadership Cadre for Mental Health in Schools defined school mental health to include “. . . considerations of the school’s role related to both positive mental health (e.g., promotion of social and emotional development) and mental health problems (psychosocial concerns and mental disorders) of students, their families and school staff” (Policy Leadership Cadre for Mental Health in Schools, 2001, pp. 5–6). So the question remains: is the field of school mental health living up to its definition and its potential to improve access to and availability of an array of mental health services and supports to students and families in need? The empirical literature suggests that access to mental health services through the schools is far more universal than many would believe. Across all public schools, the access to school mental health services approaches 90%, such that students and families can seek assistance from school providers. However, it is important to note that access to services is by no means synonymous with direct, individualized or appropriately intensive, and sustained interventions. The most extensive study of school mental health services, sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA), included a sample of 83,000 public elementary, middle and high schools. Results of the study showed that 87% of schools reported that all of the students attending their schools were “eligible to receive mental health
School Mental Health: Prevention at All Levels 51 services” (Foster et al., 2005). Schools within the sample reported the use of a significant array of intensive mental health services (see Table 3.1), including: assessment; consultation; individual counseling; therapy, and family supports. Mental health services, categorized as counseling, psychological, social work and family supports services, were also listed as related services for children who were eligible for special education. While some form of universal prevention appeared to be implemented in most schools, the vast majority (78%) of programs noted in the study focused narrowly on the prevention of drug, tobacco and alcohol use. Universal prevention curricula designed to foster social and emotional skill development were implemented in 59% of schools, while early intervention strategies were provided in 63% of schools within in the study. These results have been echoed by other national research on the implementation of comprehensive prevention initiatives (Carlson & Knesting, 2007). In sum, the authors concluded: “it is now well documented that, insofar as children receive any mental health services, schools are the major provider” (Chapter 1, p. 1). The aforementioned figures suggest that schools appear to be making strides in bridging the gap between the need for school mental health services and access to these services. Nevertheless, there remains a significant level of unmet need for many groups of students and their families. Although most mental health services are provided in the schools, fewer than one in 17 children needing such services receive them and those that do, receive far less than needed. Even children receiving “psychological services” as a related service on an Individualized Education Program plan rarely have those services defined in a manner that can ensure they receive an appropriate evaluation for services. Students from diverse ethnic and cultural backgrounds, including those who have recently immigrated to this country, continue to experience disparities in access to school-based services. It is well documented that students of color are placed at disproportionate risk of academic and eventual school failure. The non-graduation rates are particularly abysmal for males from ethnic minority backgrounds where, in some school systems, their non-graduation rates surpass 75%. Ethnic disparities in access and availability are due to a host of risk factors, including the dearth of sufficient school-based resources to provide quality education and mental health services (EDDJP). This disturbing reality is supported by findings from the SAMHSA study which revealed that eligibility for mental health services was supported less in
Table 3.1 Percentage of Schools Providing Various Mental Health Services by School Level, 2002–2003 Mental Health Service
Elementary (%)
Middle (%)
High School (%)
Assessment Behavior Management Consultation Crisis Intervention Referral to Special Programs Individual Counseling/Therapy Case Management Group Counseling/Therapy Family Support Services Substance Abuse Counseling Medication/Medication Management
90 89 87 85 75 74 70 59 34 33
87 86 86 83 79 70 67 56 53 35
86 82 82 81 72 68 61 58 56 33
Source: Foster, S., Rollefson, M., Doksum, T., Noonan, D., Robinson, G., & Teich, J. (2005). School mental health services in the United States 2002–2003. DHHS Pub. No. (SMA) 05–4068. Rockville, MD: Center for Mental Health Services, Substance Abuse and Mental Health Services Administration. Retrieved December 9, 2007, from http://download.ncadi.samhsa.gov/ken/pdf/SMA05-4068/SMA05-4068.pdf
52 Kevin Dwyer and Erika Van Buren schools across the country with high percentages of students of color, such that eligibility for services was more often restricted to students placed in special education (Foster et al., 2005). Access and availability for ethnic and cultural populations can also be undermined by cultural biases and stereotyping that can occur throughout the referral, assessment, diagnosis and intervention processes, and increase the likelihood of familial mistrust, resistance and dropout from treatment (Coutinho & Oswald, 2004; Hosp & Reschly, 2003; 2004; Skiba et al., 2008). Despite mounting support for a continuum of school-based prevention services at all levels, schools also tend to demonstrate a bias in providing services to students with serious and pervasive problems alone, while prevention and early intervention strategies are less commonly utilized (Foster et al., 2005; Weist & Christodulu, 2000). Schools that provide intensive interventions for students with serious emotional problems may yield some positive results in helping those students; nevertheless, it is commonly seen that providing intensive services only for the most serious problems alone will not change a school. It is valid on the face that “solving” the problems of disruptive students will effect change. However, the trap of addressing only the complex problems of youth with the highest levels of need, without addressing the multiple levels of intervention required for mentally healthy safe and supportive schools, is that the school itself may remain a toxic environment, continuing to produce more problems like the “dropout factories” noted previously. Specifically, if classrooms remain unorganized or behaviorally corrosive, new problems will surface for intensive service providers; children can learn to exhibit problem behaviors and schools will remain mentally unhealthy environments. The leadership and staff’s preoccupation with serious problems may reduce readiness for active participation in systemic, school-wide change and restructuring of how resources are allocated. Teachers may see the clinicians as the responsible agents to address mental and behavioral pathologies and staff may see their responsibility as primarily to help identify and refer other problem children and families to those clinicians. Consequently, this can overwhelm already overtaxed school mental health providers, further “siloing” their work and transforming their role into a “one-stop shop” for managing crises and putting out fires within their respective schools (Weist, 1997). Public mental health prevention and early intervention are just beginning to emerge, starting with a greater awareness of the interaction between environment and social-emotional well-being. (See: From Neurons to Neighborhood: The Science of Early Childhood Developments, 2000, Institute of Medicine, Washington DC: National Academy Press.) In summary, both a public awareness of child mental health and an acknowledgement of the prevalence of child mental illness have recently gained national attention as a public health concern. School-based mental health services and supports are beginning to make headway in improving access and availability of services to students and families with varying levels of mental health support needs; upwards of 70–80% of children who receive mental health services appear to be receiving them in the school (Foster et al., 2005). Nevertheless, school-based services still struggle to catch up with the overwhelming proportion of unmet need within their school communities. Particular groups of students and families, including students of color, students without formal diagnoses, and students who are just beginning to exhibit problems, have more limited access, and may ultimately fall through systemic cracks. Some researchers have suggested that the lack of a unified child mental health policy agenda has brought the field to the point where we have accumulated a mound of evidence supporting the need for such services and so we possess the tools and technologies to intervene effectively, yet we are unable to reach the populations most in need of them (see Lourie & Hernandez, 2003). Within the realm of school mental health, our ability to align and integrate educational and
School Mental Health: Prevention at All Levels 53 mental health policies, procedures and goals may be one of the single most critical determinants of our ability to engender the public will that is necessary to facilitate implementation of mental health and full-scale prevention services in schools, and ultimately improve service access to children, youth and families.
The Great Systemic Divide between Education and Mental Health The practitioner reader may ask: “Why doesn’t my school system get it? Why don’t the systems use the child-centered integrated developmental approach endorsed by most educational and mental health experts?” Although schools are the nation’s primary children’s mental health service provider, school leadership, local policymakers and stakeholders continue to perceive this as a role of public health, rather than public education. In fact, it has been asserted that schools are often actively resistant to taking on this critical role in fostering child development and mental health (Adelman & Taylor 2000). The primary mission of public education has traditionally been to ensure literacy in preparing the nation’s citizens and workforce. The fundamental cause of these barriers is rooted in these firmly entrenched traditional beliefs, and the resultant resource constraints, conflicting demands, inadequate knowledge about what works and availability of skilled professionals to implement interventions that target wholestudent development and wellness. As previously stated, traditions and governmental structures have polarized the governing and delivery of education and mental health. Schools are almost always separately managed and funded from general local or state government, which is responsible for health, safety, transportation and other services. Secondly, many community leaders see mental health as a treatment provided by a myriad of private and public clinicians and agencies, clearly separate from education. The education and public mental health governing processes and policies, as well as the necessary resource streams, are remarkably different. Access to free public education from kindergarten through high school is viewed as a right for all regardless of income, whereas access to publicly funded mental health services is limited to complex eligibility requirements. Public education is designed to prepare youth for employment and citizenship whereas public mental health has been designed to treat the most serious ill, economically disadvantaged children and adults. These differing traditional roles and beliefs, as well as the divide between the organizational supports that currently drive these systems, are significant barriers that must be addressed to ensure a full array of school mental health prevention and intervention services. Student services continue to make their mark in improving education and the mental wellness of children and youth. Nevertheless, at the same time, student services professions are marginalized in addressing both children’s mental health and, some would say, the academic achievement of children (Adelman & Taylor, 1997). Some education leaders continue to see student services as a branch of special education, made up of eligibility assessors or IEP managers. National data suggests that this perception is reflected in the allocation of resources (including use of time) and such progressive ideals and roles are rare. Public mental health prevention and early intervention are just beginning to emerge, starting with a greater awareness of the interaction between environment and social-emotional well-being, or “neurons to neighborhoods” (National Research Council & Institute of Medicine, 2000). In addition, elected officials from governors to local mayors and councils have begun to see the need to align, expand and integrate services in policy and others have initiated efforts to successfully address these barriers. Public policy also supports the inclusion of mental health and education. The nation’s principals’ and superintendents’ associations
54 Kevin Dwyer and Erika Van Buren acknowledge the need for mentally healthy development and recognize its connection to academic achievement. Yet the funders, families and practitioners in the local districts fail to see schools as responsible for teaching those required social and mental health skills or for providing mental health interventions. The skills are often perceived as the responsibility of the home, and agents of morality and treatment the responsibility of clinical agencies. The percentage of schools that teach social skills, which the Collaborative for Academic, Social, and Emotional Learning (CASEL) has defined (Greenberg et al., 2003) to include a focus on building a caring school climate, positive discipline and the provision of an array of mental health supports, has slowly grown, but has not yet been recognized or adopted as a nationally funded priority. Weist and Paternite (2006) suggest that local and state-level autonomy in decision-making around mental health policy and practice have created significant variability in the types and quality of services offered, which has consequently contributed to inactivity in mobilizing reform within child-serving systems, including schools. The rate of progress in moving this agenda forward may likely depend on national and state leadership coordination and recognition of this priority. Likewise, recognition may well be dependent upon the ability of prevention researchers to bridge the divide between research and practice by proving the effectiveness of such preventive instruction and mental health service integration in schools, and disseminating this knowledge more effectively and efficiently to major stakeholder groups. Historical and Current Developments in School Mental Health Services: Translating Policies into Practice Although it is not possible to definitively conclude that the dramatic increase in numbers of school social workers and school psychologists since 1975 has been the result of federal special education and related services laws and regulations, it is hard to ignore that Public Law 94-142 and its regulations had a causal influence on this positive outcome. This law mandated that every school system create access to individuals who deliver eligibility assessment services and other related services to children to determine eligibility for special education. Numerous university programs were established with the law’s federal training grants (Ysseldyke, 1984). In addition, within the realm of school psychology, the first Blueprint for Training and Practice (Ysseldyke, 1984) was funded by special education funds. Progressive research has demonstrated that such practices funded under special education and related laws have led to significant advances in school mental health practice, including grants to train curriculum-based measurement and assessment, the precursor of “Response to Intervention,” instructional methods, classroom behavioral management and preventive school-wide discipline practices, cultural competence, functional behavioral assessment, alternative schools, problem-solving and coordinated services (Knoff & Batsche, 1995). School mental health services for all students followed much later, enhanced by legislative initiatives outside the U.S. Department of Education through the “demonstration” grant processes of SAMHSA and the Child and Maternal Health Administration of the Department of Health and Human Services. Nevertheless, special education law remained the most significant driving force for granting children, families and educators access to schoolprovided direct and indirect mental health services. This was confirmed by the aforementioned document: Mental Health: A Report of the Surgeon General (2000) that indicated that children’s access to mental health services, although severely limited, was through the schools, provided by school’s psychologists, counselors, school nurses and other student service providers.
School Mental Health: Prevention at All Levels 55 Funding of counseling, school social work and psychological services under Medicaid has been another boost to the provision of school mental health services to children and their families. This amendment to Title 19 of the Social Security Act in 1996 made Medicaid the payor of several related services including psychological services for eligible children. Most states allow Medicaid billing for school-provided related services to children who are eligible for that health insurance program. The establishment of the Safe Schools, Healthy Students federal grants and the school mental health technical assistance centers (Adelman et al., 1999) have continued to support the critical roles that schools play in the continuum of mental health services. More recently, the President’s New Freedom Commission on Mental Health explicitly cited the improvement and expansion of comprehensive school mental health programs as a recommendation for effective mental health system reform (Mills et al., 2006). The National Association of School Psychologists and other professional and mental health advocates consistently support legislation and regulations that enable access to effective school mental health services. State certification standards have improved and been adopted by many states that meet the agreed-upon standards for education and mental health. The national certification requirements are well respected and have become the standard for university training programs. Numerous benefits have emerged from building the capacity of schools to support the social and emotional development and needs of children and youth. Many school-wide positive changes, including use of effective behavioral management strategies and school-wide efforts to transition from the use of ineffective suspension and expulsion to positive discipline, are linked to the efforts of student support personnel, including school counselors, psychologists and social workers. And, yes, evidence has begun to accumulate that these services have been critical in supporting best practices in academic instruction (Collaborative for Academic, Social, and Emotional Learning, 2008; Eber, Sugai, Smith, & Scott, 2002; Elias, 2006; Kutash, Duchnowski, & Lynn, 2006; Lewis, Hudson, Richter, & Johnson, 2004). However, it is still unfortunately rare that schools record the provision of recognized “best practice” services and match those to student mental health and academic achievement outcomes. Helping educators to see the interaction between behavior and academic instruction through the use of data-driven problem-solving and decision-making processes has positively changed some schools. While measurement based on curriculum and fidelity to proven instructional practices has been a persistent mantra of student service providers, it has also become clear that measurement of both social-emotional learning and academic achievement go hand-in-hand and inform schools as to what is working to improve learning (Collaborative for Academic, Social, and Emotional Learning, 2008). Measurement has become institutionalized through No Child Left Behind and “Response to Intervention” language in federal special education eligibility procedures. Most likely driven by quality review and accountability mandates at the local, state and/or federal levels, school improvement and problem-solving teams are beginning to identify measurable indicators of school climate and mental health as targets for change (i.e., student attendance rates), to collect and monitor this data to gauge the progress of their initiatives and modify them accordingly. Mental health professionals, particularly school psychologists, have served as practitioner cheerleaders for “best practices,” and as facilitators for collecting data and translating learning, behavioral and mental health research into practice. More than at any time in the past, multiple examples of “best practice” interventions have been identified that can be functionally used in most public schools. We also know what is
56 Kevin Dwyer and Erika Van Buren unproven and what is unlikely to work. For example, school-wide teacher-taught character education can improve behavior and attendance (see the What Works Clearinghouse: http://ies.ed.gov/ncee/wwc/) while imported instruction such as Drug Abuse Resistance Education (DARE) has no measurable effect on reducing student drug use (Ennett, Tobler, Ringwalt, & Flewelling, 1994). Ineffective interventions are less than useless and may actually do harm by increasing cynicism towards school mental health practices and wasting valuable fiscal, human and material resources. Moreover, poorly applied, proven interventions can be equally as harmful. Large and small school districts have been observed using unproven practices (volunteers providing pull-out reading support) or ineffectively mastered proven practices (unmonitored Positive Behavioral Supports). These districts are often both disappointed and puzzled by the lack of desired behavioral and academic outcomes, and consequently teachers and administrators become reluctant to try innovative ideas and lose hope. Yet, carefully planned, resourced and monitored programs and interventions do work. Monitoring both the outputs (what you are doing) and the outcomes (results) of programs and interventions not only provides “proof,” but also informs you of your fidelity to the program (Walcott & Riley-Tillman, 2007). A leader’s commitment to research-based instructional and mental health interventions has proven critical. Time and time again it has been cited in the chronicles of educators, practitioners, and researchers alike that a principal’s visible and proactive commitment to program implementation and evaluation is critical to its success. In one school system where ethnic disparities in reading achievement became evident over several years, a comprehensive research-based reading initiative was started under the direction of the superintendent. Each elementary school was resourced with a master reading specialist/coach and in-service training was provided to all primary grade teachers. Principals were evaluated as instructional leaders in literacy. Technology was provided (DIBELS) so that all children could be frequently monitored in their progress and individualized remedies were prescribed for those falling behind. Progress of ethnic and gender groups, by classroom and school, were all monitored and remedies provided when classroom or school-wide progress lagged. The success of the program was dramatic, in that third-grade reading scores for all students increased, including those of children identified as Hispanic and African American. Measuring Outcomes of School Mental Health Prevention and Intervention Proving that the three-tiered prevention-intervention construct works in schools requires a great deal of planning and management. Too frequently “programs” are initiated without a commitment to measurement of base rate data or the actual measurement of the inputs—the elements of the program itself. It is a difficult process, but there are some tips that many have applied with success, even when the interventions have been started before the pre-intervention measures have been gathered. For example, many have used general school-wide public data from the past three to five years, accounting for any significant changes in staffing, program and population. When looking at individual classrooms or students, some have used trend data over time and the interventions provided. The student is monitored twice a year for several years using individualized self-report, teacher and parent reports and discipline and report card data. The American Institutes for Research is using a model like this as one part of the New York City, United Way’s Safe Schools, Successful Students Initiative in six middle schools in the South Bronx (Osher, Dwyer, & Jackson, 2004). This program uses multiple quantitative and qualitative measures of program implementation and outcomes, including observations and interviews to assess school climate, student and school-reported
School Mental Health: Prevention at All Levels 57 psychosocial functioning, family involvement, and staff satisfaction. To capture baseline school-level functioning, the evaluation conducts comparative analyses with archival indicators of school-level climate and culture that are reported annually through the district as part of their accountability reporting procedures. Where difficulties come into play in the implementation of many three-tiered initiatives is in the lack of measures of the inputs, be they school-wide, targeted or intensive. For example, many schools report they are “using” Second Step (Frey, Hirschstein, & Guzzo, 2000) or Positive Behavioral Interventions and Supports (PBIS) but the quality may not be monitored and quality can vary from a “paper-only” program to one with significant fidelity. The first author of this chapter has had teachers report that they held one faculty meeting on Second Step, and no one was checking as to what they were doing in the classroom with that minimal exposure. He has walked through schools that report they use PBIS without seeing any posted signs reminding students of the positive behavioral expectations. So when the effect size is measured and the quality of the intervention is unknown, what do we know at the end of the day? The inputs have to be measured and ranked on a quality/fidelity scale much as we measure fidelity to the instructional methods for reading. The remedy for this challenge is to designate a well-trained, competent site-based professional to validate training needs, train and evaluate the fidelity of implementation and ensure measures of effects. The school’s principal should also be involved in this instructional leadership responsibility in supervising staff. Both the site-based coach and the principal’s monitoring are recordable inputs. Likert scales can be used to evaluate team functions and processes. In addition to school-wide initiatives, intensive interventions must also be evaluated to monitor progress in reaching treatment goals and to make midcourse corrections where necessary. Again, what are the actual inputs? Are the interventions “deep” enough to address the complexity of student problems? Individual student self-report measures should go beyond symptom scales and look at other risk and protective factors, including the development of social skills, connectedness to school, and academic self-efficacy.
Components of Effective School-Based Mental Health Practices An extensive monograph on school mental health programs involving school psychologists sought to analyze and classify the types of services being provided (Nastasi, Pluymert, Varjas, & Moore, 2002). The programs cited in the report were self-nominated, but were criterionreviewed by a panel for inclusion. Programs were reviewed for their use of a four-level prevention-intervention service model, including (1) prevention, (2) risk-reduction, (3) early intervention, and (4) treatment services. Results of the review suggested that most programs delivered more than one level of service but few delivered all four levels (prevention, riskreduction, early intervention, and treatment). The report identified many common factors across programs. Nearly all programs used a team problem-solving approach in the development and implementation of interventions. In addition, the inclusion of stakeholders beyond the school staff was noted as critical to the design and implementation of these teams. Almost all of the programs staffed more than one school mental health professional, and most included interagency staffing models, including community mental health centers and other child-serving agencies. Most programs documented best practices based on sound theory. Required outcome measures were presented and almost all used multiple measures, including qualitative observations. Fidelity in program implementation was less regularly reported as were formal measures of longitudinal results.
58 Kevin Dwyer and Erika Van Buren The processes and strategies mentioned above are foundational pieces of any schoolwide mental health initiative, but do not magically unfold overnight, or over weeks or months for that matter. Establishing school-wide readiness, fostering organizational and leadership support for the initiative, building mutually beneficial partnerships and changing attitudes about mental health problems and interventions are part of an ongoing developmental process that must be accounted for on the front end of school reform and intervention planning, and that requires multiple strategies to address properly. Viewing effective comprehensive schoolbased prevention through a closer lens elucidates specific “active ingredients” or successful strategies that have consistently emerged from the pool of evidence-based and best practice models of successful and sustainable school-based prevention and intervention. Successful Initiatives Are Facilitated by Site-Based “Coaches/Facilitators/Implementers” Although there is scant research available, school/agency-based coaches or facilitators have been observed to be most effective in making sure that initiatives are implemented with fidelity and that data requirements are followed. We do know that staff training is most effective when trained staff have the opportunity to see skills modeled and have the support of a trusted coach providing immediate feedback regarding their implementation (Garet et al., 2001). The authors of this chapter have observed the coaching model used in several grants, and throughout the process, survey data has shown staff feeling more confident in using new skills when supported by frequent coaching. Some systems have used in-house coaches and others have used an itinerate support model (two to three schools for each coach). Although initially expensive, the in-house model seems the most effective method of ensuring fidelity. Other models such as having the monitoring and support come from existing staff or an administrator may also be effective. Coaches must be highly skilled in the interventions they are training and supporting. They must also have effective interpersonal skills and be proficient in adult learning styles. Teachers and staff must have trust in the coach and be able to access coaching support in a timely manner. Adults, much like older students, are frequently reluctant to ask for help when they need it, particularly if they believe that they are “expected to know” the skill. Therefore, it is critical that coaches regularly monitor and support staff. Many coaches have used grade-level monitoring, focusing on common proficiencies and then focusing on “skills that are more difficult to maintain,” seeking suggestions and support from peers. Coaches also have the potential to serve in the role of cultural liaisons or brokers between the lead and community partners, and the host schools for prevention initiatives. Knowledge of the student and family communities, the complex cultures and competing demands of schools, as well as mastery of intervention model are invaluable in facilitating collaboration, translating diverse interdisciplinary argot, values and norms, and managing the interorganizational dynamics of difference that can emerge when multiple stakeholders come to the table. Successful Initiatives Are Supported by Stakeholders Who Believe They Can Implement the Desired Interventions When asking systems to change, and requiring members to learn new skills and refocus their approaches to tasks, there is a general principle that 80% of the implementers need to “buy into” the desired skills, responsibilities and vision of the program. It is not enough to have coaches and the support of the principal or agency head if the classroom teachers, counselor
School Mental Health: Prevention at All Levels 59 and clinical social workers are not on board in believing that the required changes will enable them to be more successful (and lower their stress). Frequently the first step to “buy-in” is demonstrating that learning the new skill will reduce frustration, including from classroom disruptions that consume energy and precious instructional time. For example, the research staff for Project ACHIEVE (Knoff & Batsche, 1995) observed classes and recorded amounts of lost time caused by disruptions to instruction. When staff saw that engaged instructional time could be increased by giving students training in social skills and reflective thinking, “buy-in” was sustained. Moreover, providing opportunities for systematic decision-making input and needs assessment from staff can be automatically engaging and promote support for the initiative. For example, as part of its preplanning processes, the PBIS model has a prerequisite of written support from at least 80% of staff before intervention planning can move forward. Teacher buy-in can be enhanced by focusing on “learning behaviors” (McDermott, 1999) that have been shown to support academic success. Schaefer (2004) and others have demonstrated that teachers are excellent in identifying keystone behaviors that they can then teach and reinforce. Likewise, teachers recognize that faulty learning behaviors are relatively common in classrooms and therefore conducive to classroom and school-wide interventions. The focus on academic behaviors rather than on “social skills” and discipline may help gain teacher and administrative support for prevention programs. Successful Initiatives Include Measurement of Vital Stakeholder-Identified Outcome One way to increase staff support is to establish agreed-upon measurable outcomes that are meaningful to those front-line workers who interact directly with students. Measuring schoollevel reductions in office referrals may mean little to a teacher who is temporarily relieved of the disruptions by the referred student. Temporary stress reduction is a strong reinforcer. Seeing the cumulative loss to the student, the class and the teacher over time may assist the team in defining a more meaningful outcome for such teachers. Having staff identify outcome measures, using existing school measures (report cards, attendance, formative and summative assessments) as the base, has been demonstrated to increase compliance in data collection. New cumbersome measures are less likely to be supported or used. Measures such as instructional time and individual students’ time-on-task will require both observations and more school resources. Individualized behavioral and academic measures are time-intensive and thus less consistently applied. Overcoming this resistance through direct paraprofessional support or incentives can be critical to securing the necessary data to determine the student’s response to interventions. Questionnaires on school climate and staff (student and parent) satisfaction surveys are usually acceptable measures. Partners, school mental health and clinical providers are most commonly expected to connect their services to measurable outcomes and for students whose IEP contains such services a connection to school progress is required. Successful Initiatives Generate Clearly Identified and Required Interventions and Outputs That Can Be Replicated One of the more serious problems found among school-collected measures are the actual staff and leadership behaviors that are being maintained that produce positive outcomes. Outputs are the things we do that result in the desired outcomes we achieve. Running teacher support teams (TST) that provide little timely and effective ideas, versus teams that respond with immediacy, follow-up, evaluate if needed, and modify supports, are examples of different
60 Kevin Dwyer and Erika Van Buren outputs, although on the surface they may look generically the same (both have regular properly staffed TST meetings). Frequency, intensity and actual descriptions of the interventions are critical. This is more common in academic instruction than in behavioral instruction and management. For instance, manualized cognitive behavioral therapies are effective in documenting evidence of the connection between outputs and outcomes. Individualized Education Programs (IEPs) have been designed to connect interventions to academic and behavioral goals. However, they are too commonly less informative than they could be in helping a new teacher or other staff know clearly what outputs are required to sustain progress. Furthermore, using outputs to inform us as to what elements of prevention programming should be sustained is also very important. Measuring what is required to learn and maintain a school-wide social skills program is critical to its replication in going to scale within a school system. The Collaborative for Academic, Social and Emotional Learning (CASEL) is one organization that has identified criteria for implementing such school-wide programs (Elias, Zins, Graczyk, & Weisberg, 2003). Successful Initiatives Use Structured Team Problem-Solving Processes Structured team problem-solving has been shown to be an effective tool for schools and agencies to ensure meaningful intervention planning and resource allocation that will appropriately address agreed-upon goals and visions (Osher, Dwyer & Jackson, 2004; Dwyer & Osher, 2000). In fact, the three-tiered prevention-intervention construct requires team problemsolving and can be the most critical element in any program’s implementation. However, there are a number of essential factors and cautions when setting out to establish problemsolving teams. Lessons from the field tell us there are a number of clear right and wrong methods for establishing and implementing these processes, which can have clear implications first for staff buy-in and support of the initiative, and ultimately for program success. It is important to note that team problem-solving has been seen by teachers as time consuming and ineffective because the necessary staff support to make the recommendations effective is not available, and suggestions are frequently not backed up by training. When staff members are untrained in team problem-solving, the process becomes mechanical and meaningless, lacking the depth of inquiry and generation of effective, targeted interventions that are monitored for fidelity and measured for results. Without training, “early intervention” strategies generated by teams are almost always shallow and have little effect. The team deteriorates and begins to become a “reactive” and crisis-driven dumping ground, moving students to special or alternative programs. In schools where training in problem-solving is intensive, and where training is evaluated, the results can be significant. Teachers, student support staff and administrators are frequently required to participate on a myriad of school teams. The decision to create problem-solving teams, or to integrate effective problem-solving processes and training into already existing team structures, including school improvement teams and quality review teams, should ideally be informed by a more comprehensive resource-mapping process (Adelman & Taylor, 2006) This process helps to identify and reduce redundant or duplicated efforts and helps with the reallocation and more efficient distribution of time and human resources. Collaboration with other school-based groups and teams can also help to facilitate task completion, reduce fragmentation and foster a sense of shared accountability and support for the implementation of school-wide strategies. The school leadership is critical for shaping the vision and mission of such teams, and providing ongoing guidance and support as needed.
School Mental Health: Prevention at All Levels 61 Successful Initiatives Are Coordinated by School, Community Agency, Non-Governmental Services, Students and their Families Agencies and schools are more successful when they coordinate their family-friendly interventions to ensure that interventions are carried out as designed and supported by all providers. Schools and agencies that blend resources, co-train staff, align services and actively involve families seem to be more effective than services that are merely housed in the same building, implementing parallel or duplicative services. Exemplary mental health programs build in assistance to schools and systems to integrate and coordinate mental health, health, social service and educational programs to maximize efficiency and effectiveness of service delivery. They also provide support for interagency and community programs that safeguard children’s mental health and safety. Successful Initiatives Are Responsive to the Cultural and Linguistic Values, Norms and Preferences of the Students and Families Served Too often we hear of well-supported mental health prevention and intervention programs and strategies that flop because they simply do not translate to the communities in which they are implemented. The selection criteria for prevention and intervention programming and strategies must include a successful track record of use with the cultural and linguistic populations served. Have evidence-based interventions been implemented, and protocols standardized using a meaningful percentage of students and families within the cultural and socioeconomic populations of focus? Are there mechanisms for adapting protocols to incorporate the values, traditions, norms and needs of families? And, just as importantly, are there feedback loops in place to ensure that family members provide ongoing feedback and input throughout the process of implementation? Developing culturally and linguistically responsive mental health services is a developmental process that should be infused in all aspects of program development and implementation (Cross, Bazron, Dennis, & Isaacs, 1989). Successful program models, such as federally funded systems of care communities (Eber, 1998; Stroul, 1996), are based on a set of guiding principles which include a youth-guided, family-driven and culturally and linguistically competent approach to service design and provision. School-based systems of care communities are growing in frequency throughout the country, and have developed innovative strategies for recruiting and retaining representative, community-based staff to work within the cultural frameworks and in the preferred languages of students and families they serve. Such services promote organizational infrastructure development that will support and sustain culturally and linguistically appropriate practice, and prioritize meaningful and respectful collaboration with youth, families and community members in meaningful and respectful ways. For instance, one school-based system of care community has made tremendous progress in outreach and engagement to the Latino community within its cachement area, and specifically with the Latino families and caregivers it serves. Youth and families are represented among their staff and major decision-making bodies. This system of care conducts ongoing dialogues and focus groups with families with the primary goal of engaging them in the development and implementation of service delivery, instilling family empowerment and leadership. Successful Initiatives Measure the Effectiveness of Training and Coaching Most trainings are evaluated immediately after the presentation, using participants’ desired outcomes rather than ongoing surveys of actual use and usefulness. Training research suggests
62 Kevin Dwyer and Erika Van Buren that needs-based training that involves engaged instruction followed by modeling, coaching, observations and evaluation is effective, whereas most didactic training is minimally effective in changing the behavior of the participants. Didactic workshops may be effective in increasing the participants’ awareness of what can be tried or modified to improve instruction or classroom behavior and increase interest in finding out more, but it is not professional development which implies developing, demonstrating and using new and effective skills High-quality professional development is a science that has been evaluated (Garet, Porter, Desimone, Birman, & Suk Yoon, 2001), showing that adequate training time, active participation, the attainment of new knowledge and support of study groups, same-school peer support and mentoring increases skill development and implementation. Successful Initiatives Align Best Practices Across Academic, Social-Emotional, Safety and Other Critical Areas Some schools use math and science vocabulary in their basic reading programs to enhance and reinforce meaning. Some high schools connect literature to history, and math to chemistry. Almost all schools use some standard sequential curriculum to teach reading and the foundations of math and written language. The language of social skills can also be part of the language of reading and writing. Some middle schools have developed creative writing skills using the theme of bullying, writing plays to dramatize the issue. The vocabulary used by staff in the cafeteria to remind students of respect and social responsibility should be the same as the language of the classroom and hallways. The therapist helping a student with impulse control strategies may be most effective using the social skills curriculum’s structure enabling the teacher to naturally reinforce that student’s therapy. Security personnel and hall monitors in a school that use the “Stop-and-Think” program must be trained in that model to ensure they reinforce that approach to behavior. Staff that yell (louder, longer and more frequently) at misbehaving students should be assisted in learning and replacing behavioral language to maximize the positive behavioral support effects. As managers of school-wide social skill promotion, instructional leaders (i.e., principals) should plan for this kind of alignment of academic, social skills, safety and mental health interventions on levels that support applied learning opportunities. Alignment across content areas as well as alignment among service intensities can make the classroom therapeutic and the therapy instructional. Family caregivers have reported that they too can participate in this process when given the tools and support to function as partners in learning. Successful Initiatives Are Planned, and Given the Time and Resources to Demonstrate Results Change takes time. Change, resulting in measurable results, takes even more time than its agents expect. Although this construct is acknowledged by policymakers, leaders and stakeholders, it is rarely concretely noted and accounted for in planning. Patience with “disrespectful, irresponsible children” is rare. Schools want children who are “ready to learn” or change agents who can quickly remedy problems that make teaching difficult. Most teachers are more patient with struggling students trying to phonetically de-code a new word than students struggling with learning appropriate classroom behaviors. Patience is almost always lost when students yell out vulgarities, hit or defy an authority’s command. Classroom control is lost, instruction is disrupted, unwanted feelings of anxiety, anger, even impotence surface and threats may be expressed, too frequently escalating the student’s negative behaviors.
School Mental Health: Prevention at All Levels 63 A structured, highly individualized intervention plan that requires positive comments when appropriate behaviors are observed, predicting outbursts and modifying or acknowledging the warning signs to help stimulate taught/learned replacement behaviors, as well as maintaining firm consistent consequences for serious infractions, will not immediately extinguish the inappropriate behavior, but should reduce its frequency. It takes time to teach new skills and, frequently, more time to extinguish previously learned and reinforced inappropriate behaviors. Likewise, school-wide prevention and mental health promotion plans and interventions will take time to implement and have measurable results. In fact, most school-wide interventions take more than three years to demonstrate significant measurable outcomes. Successful Initiatives Are Cost-Effective, and Use Multiple Funding Sources As noted earlier, public schools and mental health agencies are commonly managed and funded under different governmental systems. Even at the federal level, the funding streams come through different agencies as directed by various laws. Few laws, such as the Safe Schools Healthy Students grants, require interagency controls that can better ensure coordinated resource allocation. The Safe Schools Healthy Students demonstration grants make the school system the grantee but require interagency collaboration and are federally managed by the Departments of Education, Justice and Health and Human Services. Funding at the local level is best managed when it enables the blending and braiding of funds to address the complex barriers to learning, as well as support the prevention of problems. Blending funds requires school system and agencies to pool funds to address a specific agreedupon set of interventions or service. Unlike braided funding there is no tracking of each organization’s dollars. Braiding enables the pool of funds to be followed to specific components of service and is frequently favored over mere blending. Local management boards (such as a Child and Family Collaboration Council) that include representation from schools and agencies, using local, state and federal funds as well as charitable non-governmental organization funds, are becoming more common. The next step at the federal level will be for legislation to give incentives (or mandates) for merging demonstration grants, such as, for example, those that address serious mental illness in children from the Substance Abuse and Mental Health Services Administration with those that support social-emotional education through the U.S. Department of Education’s Leave No Child Behind and Medicaid. Successful Initiatives Are Shown to Quickly Relieve Some Elements of “Crisis” The state-of-the-art model for designing the comprehensive mental health promotion, prevention, early and intensive intervention approach for schools has been to plan for, train and implement the whole model, simultaneously. This construct enables services at different levels of intensity to support each other, to engage all staff in connecting with agreed-upon goals, to ensure interventions are aligned, and to enhance easy inclusion and transitions for youth. Many Safe Schools, Healthy Students federal grant recipients have followed this design, relying on the federal funds to accomplish this multi-year implementation effort. Another approach is to relieve some elements of a crisis. For example, a school that has identified several behaviorally troubling youth who are consuming significant resources and producing a contagion of disruption may find that the first step to change is to address the “fires” by
64 Kevin Dwyer and Erika Van Buren providing wraparound services to the youth and families with the most serious problems. Nevertheless, in this case, the establishment of an effective, school and home-based agencydriven mental health program may be the first step to enable the school to devote its energies to designing the prevention and early intervention components of the model. Regardless, even the intensive intervention component cannot stand alone for long. When youth have their complex social-emotional and behavioral needs addressed, the school’s climate improves best when it mirrors those supports. So the successful treatment reduces the crisis and enables the schools to develop supportive strategies to prevent other youth from following that trajectory. Furthermore, those elements that are shown to promote learning and prevent problems can then be made available to support all youth, including those who have serious, complex problems. Making the determination about where to start may be driven by the level of crisis in which the school finds itself. There is a noted danger in starting with intensive services and that is that those services, like special education, can become a separate entity consuming all the school’s mental health resources. Prevention and effective early intervention services are thus never resourced or implemented. In sum, it is critical that regardless of where one starts, each school establish its plan for a comprehensive prevention, intervention school mental health program and provide assurance that the full program will be implemented. Addressing the crises first can enable the school to begin building a mentally healthy climate and system of prevention and intervention. Successful Initiatives Combine a Spectrum of Comprehensive Prevention, Early and Intensive Interventions and Services Our identification of successful elements of school-based initiatives would not be complete without discussion of the evidence supporting implementation of the full continuum of prevention, early and intensive services, and the successful characteristics of these services. Earlier discussion within this chapter highlighted the general proclivity of US schools to rely on the provision of intensive services, and the negative implications associated with this pattern. The most effective programs appear to provide an excellent universal instructional method. When all students are carefully monitored in their responses to that curriculum and instruction, those who are falling behind are quickly identified and proven remedies are expeditiously applied. For youngsters who do not respond to such interventions, teams examine the “why” and prescribe appropriate intensive interventions, again monitoring results and modifying or maintaining effective interventions that improve the student’s reading. Everything is connected to the general curriculum and instructional measures; in essence, instruction is aligned. The same is necessary for social, emotional development. Behavioral remedies must be connected to the language of the classroom and the reinforcements of teachers, staff and peers. For example, in one school the agency-assigned clinical social worker learned the social skills language used across all the primary grades, and incorporated it into the “language of therapy.” This enabled both the therapist and the parent to shape replacement behaviors that the teacher and staff could naturally support and reinforce.
Conclusion and Summary Children who are mentally healthy, who have proven coping and problem-solving skills, and who have these skills promoted within schools, are far more likely to learn and achieve. Nevertheless, the school mental health promotion and prevention programs which promote
School Mental Health: Prevention at All Levels 65 the development of these important life skills cannot stand alone, nor can intensive intervention services enable children to maximize their learning in schools with corrosive classroom climates. This chapter has summarized the collective knowledge from both research and experience in the field to help practitioners and policymakers put the prevention and intervention pyramid in place. If a school can improve attendance, achievement and graduation rates, decrease suspensions and expulsions, as well as disproportionate special education placements, its initiatives will be seen as winners by most stakeholders. The mental health promotion and prevention-intervention paradigm is believed to be the most efficient and effective model schools can implement to ensure these positive educational outcomes communities seek. Demonstrating a connection between interventions and desired outcomes is the critical issue. What can we conclude about “what works” in schools? We can paint a relatively clear picture using what we know. First, effective programs have been supported by sound theory, including a clear understanding of the research-supported mechanisms for change (Fullen, 1991). We know that interventions that work are well resourced, sustained and celebrated by critical leadership as well as by teachers, students and families. They are connected to the academic mission of schools and their leadership, which provides the cornerstone of “mutual interest” that will sustain principal buy-in and support for the initiative. They are put in place with equal zeal and resources as that of academics. Leadership, policies and procedures related to such programmatic efforts must be system-wide and sustained, independent of personal initiatives or discretionary “soft money.” Programs that succeed are well coordinated, understood by staff, students and community. Like academics, they are evaluated for impact on individuals, classrooms, schools and system-wide. Identified best practices are used with fidelity and the staff is well trained, including such ancillary staff as cafeteria workers, school security personnel, mentors and other community partners. The school principal’s role as instructional leader includes mental health “instruction.” The numbers of student services personnel such as counselors, school psychologists and social workers are commensurate with the needs and such personnel support or provide coaching, consultation, monitoring and individualized services to ensure complete promotion, prevention and intervention services. They work in interdisciplinary and interagency teams that use effective planning and problem-solving techniques to maximize effectiveness and efficiency, always partnering with families. Schools look for incremental success, understanding that persistence of sustained effort and measured outputs will produce results. Although the breadth and depth of our understanding regarding how schools should function continues to grow, the educational system struggles to adopt this vision. Nevertheless, successful state and local initiatives are beginning to emerge which represent a shift from a “two-component policy framework,” which typically includes an agenda for improvements in instruction and school governance, to a three-component framework which addresses barriers to learning and uses language such as “an Enabling Component, a Learning Supports Component, and a Comprehensive Student Support System” (Adelman & Taylor, 2005; this volume). This third element combats marginalization of school mental health services, and supports a commitment to change. Although change is inconvenient, maintaining ineffective educational systems and interventions is more than dangerous to some. Schools can no longer afford to neglect paradigms of teaching and learning that embrace the richness and potential of the “whole child”; a richness that every child possesses, and that need only be cultivated and nurtured within the social worlds in which they live, learn and play. To truly educate is to draw out that richness and to ultimately promote the positive development of mentally healthy children and youth, which will serve to sustain them throughout their education and beyond.
66 Kevin Dwyer and Erika Van Buren
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68 Kevin Dwyer and Erika Van Buren Mills, C., Stephan, S., Moore, S. Weist, M. D., Daly, B. P., & Edwards, M. (2006). The President’s New Freedom Commission: Capitalizing on opportunities to advance school-based mental health services. Clinical Child and Family Psychology Review, 9, 149–161. Nastasi, B. K., Pluymert, K., Varjas, K., & Moore, R. B. (2002). Exemplary mental health programs: School psychologists as mental health service providers. Bethesda, MD: National Association of School Psychologists. National Center for Education, Disability and Juvenile Justice. (n.d.). Prevention and early intervention. Retrieved on December 20, 2007, from http://www.edjj.org/focus/prevention/phcsc.html National Research Council & Institute of Medicine. (2000) From neurons to neighborhoods: The source of early childhood development. Committee On Integrating the Science of Early Childhood Development. Shonkoff, J. P. & Phillips, D. A., Eds. Washington DC: National Academy Press. Osher, D., Dwyer, K., & Jackson, S. (2004) Safe, supportive and successful schools: Step by step. Longmont, CO: Sopris West. Osher, D., Dwyer, K., & Jimerson, S. (2006). Safe, supportive, and effective schools: Promoting school success to reduce school violence. In S. Jimerson & M. Furlong (Eds.), Handbook of school violence and school safety: From research to practice (pp. 51–71). Mahwah, NJ: Lawrence Erlbaum Associates, Inc. Policy Leadership Cadre for Mental Health in Schools (2001). Mental health in schools: Guidelines, models, resources & policy considerations. Los Angeles: Center for Mental Health in Schools at UCLA. http://smhp.psych.ucla.edu/pdfdocs/policymakers/cadreguidelines.pdf Reyes, O., & Jason, L. A. (1991). An evaluation of a high school dropout prevention program. Journal of Community Psychology, 19, 221–230. Schaefer, B. A. (2004) A demographic survey of learning behaviors among American students. School Psychology Review, 33, 4, 481–497 Shader, M. (2001). Risk factors for delinquency: An overview. Washington, DC: Office of Juvenile Justice and Delinquency Prevention. Skiba, R. J., Simmons, A. D., Ritter, S., Gibb, A., Rausch, M. K., Cuadrado, J., & Chung, C. G. (2008). Achieving equity in special education: History, status, and current challenges. Exceptional Children, 74, 264–288. Spoth, R. L., Clair, S., Shin, C., & Redmond, C. ( 2006). Long-term effects of universal preventative interventions on methamphetamine use among adolescents. Archives of Pediatric & Adolescent Medicine, 160, 876–882. Stroul, B. A. (Ed.) (1996). Children’s mental health: Creating systems of care in a changing society. Baltimore, MD: Paul H. Brooks Publishing Company. U.S. Department of Education. (2006). Twenty third annual report to Congress on the implementation of the Individuals with Disabilities Act. Washington, DC. U.S. Department of Health and Human Services. (1999). Mental health: A report of the Surgeon General. Rockville, MD: U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, National Institutes of Health, National Institute of Mental Health. Walcott, C. M., & Riley-Tillman, T. C. (2007). Evidence-based interventions from research to practice. Communiqué, 35(6), 16–20. Walker, H., & Sprague, J. (1999). The path to school failure, delinquency, and violence: Causal factors and some potential solutions. Intervention in School and Clinic, 35, 67–73 Weist, M. D. (1997). Expanded school mental health services: A national movement in progress. In T. Ollendick & R. J. Prinz (Eds.), Advances in clinical child psychology, volume 19 (pp. 319–352). New York: Plenum. Weist, M. D. & Christodulu, K. V. (2000). Expanded school mental health programs: Advancing reform and closing the gap between research and practice. Journal of School Health, 70, 195–200. Weist, M. D., Evans, S. W., & Lever, N. (2003). Advancing mental health practice and research in schools. In M. Weist, S. Evans, N. Lever (Eds.), Handbook of school mental health: Advancing practice and research (pp. 1–8). New York: Kluwer Academic/Plenum Publishers.
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Screening for Mental Health and Wellness Current School-Based Practices and Emerging Possibilities Erin Dowdy, Michael Furlong, Katie Eklund, Elina Saeki, and Kristin Ritchey, University of California, Santa Barbara The 20th century was about treating disease. The 21st century is about prevention —Sir William Castell, Former CEO, GE Healthcare
Research has documented the poor school-related outcomes for children with emotional and behavioral disorders (EBD)(Atkins, Graczyk, Frasier, & Abdul-Adil, 2002, 2003; Franca, Kerr, Reitz, & Lambert, 1990; Rones & Hoagwood, 2000; Wagner Kutash, Duchnowski, & Epstein, 2005). Students with EBD have low overall academic achievement (estimated to be at the 25th percentile in one meta analysis; Reid, Gonzalez, Nordness, Trout, & Epstein, 2004); are suspended or expelled from school at high rates (in secondary school 73% have a history of suspension or expulsion compared to 22% in the general population; Wagner et al., 2005); have high rates of absenteeism (Lane, Carter, Pierson, & Glaeser, 2006); have the highest incidence of contact with the justice system when compared to peers who have either other types of disabilities or no disability; and have low graduation rates (Wagner et al., 2005). As students with EBD transition into adulthood, they are at elevated risk of continued poor psychosocial outcomes (Greenbaum et al., 1996) and many are underemployed or unemployed after high school (Zigmond, 2006). However, the students identified with emotional and behavioral problems comprise less than 1% of the school-age population (Wagner et al., 2005) and, of those identified with EBD, approximately 65% are 12 years old or older (U.S. Department of Education, 2001). This suggests that children are likely under-identified for emotional and behavioral problems and, when they are identified, it is often later in the student’s educational career with missed opportunities for early intervention. The importance of the early identification of youth vulnerable to the complications associated with EBD cannot be overstated. In fact, Goal 4.3 of the President’s New Freedom Commission on Mental Health advocates for the screening of “. . . co-occurring mental and substance use disorders and link with integrated treatment strategies” (Hogan, 2003). Striving to implement Goal 4.3 is important because providing prevention and early identification services are humane—suffering is reduced by early intervention when problems are less complex or symptoms are prevented from developing at all (Desrochers, 2006). Nonetheless, despite what appears to be a logical need for early universal mental health screening, efforts to proactively identify these youth for early intervention services have been poor (Duncan, Forness, & Hartsough, 1995; Walker, Nishioka, Zeller, Severson, & Fell, 2000) and only 2% of schools engage in a systematic universal screening practice for mental health services (Romer & McIntosh, 2005).
Screening for Mental Health and Wellness 71 Fortunately, school mental health providers are trained to use problem-solving strategies to enhance the development of wellness, social, mental health, and life skills of all students, and particularly those with EBD. They often assume leadership roles as part of a school team effort that searches for and provides integrated services for children with mental health challenges (Adelman & Taylor, 2003). They do this while recognizing that positive behavioral and emotional health is associated with academic success (Atkins, Frazier, Adil, & Talbott, 2003; Catalano, Haggerty, Osterle, Fleming, & Hawkins, 2004). Strategies that help children with EBD to cope with immediate mental health symptoms are coupled with a focus on long-term efforts that bolster psychological well-being, which, in turn, result in better school attendance, participation, and school completion (Hazell, 2007). Although it may at first inspection seem to be an easy task to use universal screening procedures to identify students who are experiencing symptoms of mental health problems, these efforts are complicated by social and legal challenges that claim programs such as Teen Screen (see www.teenscreen.org) are funded by pharmaceutical companies with the intent of increasing the use of psychoactive medication with youth (see, for example, PsychSearch [www.psychsearch.net/teenscreen.html] and the Rhoads v. Penn-Harris-Madison School Corporation lawsuit now working its way through the federal courts [www.rutherford. org/articles_db/press_release.asp?article_id=723]). In addition, there is still substantial research to be done to validate the technical adequacy of the instruments and procedures employed in mental health screening procedures. With this as background, this chapter provides a rationale and description of screening and early identification for early intervention, procedural and ethical considerations for screening, an overview of screening instrumentation, and a proposed comprehensive approach integrating positive psychology assessments for mental “health” screening.
Preliminary Considerations Screening and Integrated Student Supports When school mental health providers set out to design and implement comprehensive mental health screening there are a number of core issues to consider. First, screening is not an activity that any individual school psychologist can undertake on his or her own. It needs to be incorporated into an integrated student services program (see Adelman & Taylor, 2006). There is limited benefit to mental health screening if there are no structures in place or disorganized service options available. Second, a number of studies have found that the referral process is complicated by the fact that certain symptoms might be harder to detect than others (Achenbach, McConaughy, & Howell, 1987; Bradshaw et al., 2008). Internalizing and externalizing behaviors are equally important to assess; however, internalizing symptoms might not be as readily apparent to teachers who make many referrals. Reliance on teachers, parents, and other school staff for referrals may overlook students with significant internalizing symptoms. A recent study found that students with externalizing symptoms, such as educational or behavior concerns, receive higher rates of services than children with internalizing symptoms (Bradshaw et al., 2008). This might help explain why boys are over-represented in many special education categories (Oswald, Best, Coutinho, & Nagle, 2003). The detection of both internalizing and externalizing problems, as well as academic difficulties during early elementary school years, is critical for effective prevention of subsequent mental health and educational problems (Bradshaw, Buckley, & Ialongo, 2008) and a systematic
72 Erin Dowdy et al. screening process might reduce some biases in the referral process (Kamphaus & Reynolds, 2007). Establishing Objectives for Screening One of the first issues to consider is to establish the core purpose of the mental health screening. Is the goal to monitor all students (population status) for program planning or to initiate procedures that lead to the identification of specific high-risk students for more intensive follow-up? From a strict clinical perspective, a primary goal of screening is to gather information via referrals/rating scales and youth self-reports to identify specific students who have enough symptoms of emotional problems that they merit additional assessment and possible intervention. This general strategy follows a public health model (Doll & Cummings, 2008; Kleiver & Cash, 2005; Nastasi, 2004; Short, 2003). With respect to screening for mental health needs among children and adolescents, the primary or universal level is what is usually considered to be “screening” for mental illness (Levitt, Saka, Romanelli, & Hoagwood, 2007). It involves the use of strategies in which an entire population (e.g., school, district, classroom) receives needs assessment with follow-up clinical assessments and services. Although the rationale for universal mental health screening to identify specific at-risk students is transparent, it is predicated on searching for symptoms of psychopathology and gathering information that is not anonymous. Given these considerations, it is also possible to decide to conduct screening not to identify specific at-risk youth, but to monitor the mental health needs of a population of students via youth self-reports. In fact, this is done nationally with the Youth Risk Behavior Surveillance Survey (YRBS) that has asked secondary school students about selected mental health experiences related to suicide ideation and sadness/depression. As shown in Table 4.1, data from the YRBS can be used at the national, state, or local school level to monitor mental health indicators for each successive cohort of entering secondary school students. If prevention and intervention efforts are successful, then each successive cohort should report lower rates of mental health symptoms. As these actual data show, a substantial proportion of high school students report at least one significant period of depression-like symptoms in the previous year. Even without knowing the identity of these students, it still provides evidence and a rationale to support the availability of preventive mental health services and a means to assess progress over time. Although this approach does not identify specific students for intervention, it provides information about students’ service needs. This approach requires surveys to be conducted annually with the goal of participation by all students; however, the reader is cautioned that YRBS items do not have the reliability or sensitivity to assess individual differences (see Benner et al., 2002). Even if the core purpose of screening is to identify risk status among students, screening data could be aggregated (with identifying information removed) across classrooms, schools, and districts to provide population-based needs-assessment information. In this way, both needs assessment and individual identification of students could occur.
Implementing a Screening Program Even after addressing core issues, school mental health providers are still faced with a multitude of issues when implementing mental health screening. A school or district that is interested in early identification needs to address the core issue of what to screen for (Stoep et al., 2005) and consider the pragmatics of screening. This section guides readers through a set of issues to consider when implementing a screening program.
Screening for Mental Health and Wellness 73 Table 4.1 Percentage of Students by Grade Level and Survey Cohort Year Who Felt So Sad or Hopeless Almost Every Day for Two or More Weeks in a Row That They Stopped Doing Some Usual Activities During the 12 Months Before the Survey from Youth Risk Behavior Surveillance Survey 1999–2007 Survey Year
Grade 9
Grade 11
Grade 10
Grade 12
1999
27.4
2001
29.4
28.7 (B)
27.2
27.0 (D)
2003
28.0
28.9
29.7
27.4
2005
29.0
28.8
28.9
26.4
2007
28.2
27.1
28.9
29.4
29.3 (C)
Note Survey results from 1999 (Kann et al., 2000; Table 12), 2001 (Grunbaum et al., 2001; Table 12), 2003 (Grunbaum et al., 2003; Table 16), 2005 (Eaton et al., 2006; Table 16), and 2007 (Brener et al., 2007;Table 16) Youth Risk Behavior Surveillance Summaries. Cell A shows the percentage of ninth graders in 1999 who reported being sad and Cell B shows the percentage of students in the same cohort two years later in grade 11 who reported being sad. Cells C and D show the same information for the 1999 cohort of 10th graders who were in the 12th grade when the 2001 YRBS survey was conducted. Efforts to prevent mood symptoms would be reflected in a lower percentage of vertically of ninth graders in each survey year reporting being sad. Successful intervention efforts would be reflected in lower rates (diagonally) as each cohort moves through the school system. This actual YRBS data show that since the tracking of this mental health-related item in 1999, there has been essentially no improvement of students’ experiencing of sadness over an extended period of time. These data also show the limitation of conducting surveillance screenings every two years because it is then possible to assess each ninth-grade cohort only twice while they are in high school.
What to Screen For? With respect to mental health screening Mills et al. (2006) ask, “screening for what?” What mental health problems should be included—depression, suicide, anxiety, or conduct problems? Many screening programs focus their efforts on one mental disorder to the exclusion of others. For example, a screening program that looks solely for symptoms of depression and risk for suicide (e.g., Teen Screen) might miss a student who is having significant difficulties with attention and hyperactivity. However, we do recognize that a school community might take such an approach because of the devastating impacts of teen suicide. Another approach draws upon research that has identified two broad dimensions of mental health problems—internalizing or overcontrolled symptoms and externalizing or undercontrolled symptoms (Reynolds, 1992). An argument can be made that when screening for psychopathology, then a focus could be on identifying internalizing and externalizing symptoms. However, a recent study by Najman and colleagues (2007) reported that a total problems score, such as the one derived from the Child Behavior Checklist (CBCL; Achenbach &
74 Erin Dowdy et al. Edelbrock, 1991) was more predictive of subsequent anxiety and depression problems than the internalizing subscale alone. A related study by Leon and colleagues (1999) lends further evidence to the potential importance of screening for general maladjustment rather than focusing solely on one disorder or a class of disorders and also highlights the need to take comorbidity into account when screening. The authors screened for depression and had the intriguing finding that many clients who were false positives on the screening procedure actually met diagnostic criteria for another mental disorder (Leon et al., 1999). This suggests that overlapping symptomatology might make it more difficult to screen for one particular disorder instead of focusing on screening for general maladjustment and symptomatology. Hence, given the current knowledge, an ideal screener might provide a measure of general maladjustment to be interpreted as a “red flag” for potential emotional and behavioral problems, whether the problems are internalizing or externalizing. The Pragmatics of Screening A substantial research base corroborates that schools often function as the de facto mental health system for many children and adolescents (Burns, Costello, Angold, Tweed, et al., 1995; Rones & Hoagwood, 2000). This is primarily due to accessibility, but also to perceived acceptability—children are more likely to seek help when school-based mental health services are available from adults whom they know and with whom they have been able to develop trust (Slade, 2002). Recent surveys report that the majority of schools offer some level of mental health or social service support, with 20% of all students receiving some type of schoolsupported mental health service (Kutash, Duchnowski, & Lynn, 2006). Sources of Screening Information. If schools are the primary setting for mental health services for children and adolescents, then a key consideration is who gathers screening information. Within the school setting, teachers are often seen as a key source for information about children’s social and emotional functioning. In fact, research has shown that teachers, with a great deal of accuracy, are able to identify children who are at risk of behavioral problems (Taylor et al., 2000). At the preschool, child, and adolescent levels, structured teacher ratings of child behavior have been found to be more reliable than parent ratings and different teachers rate the same child similarly (Reynolds & Kamphaus, 1992). Teachers are particularly adept at assessing problems with attention, a key temperamental variable associated with social and psychopathological outcomes (Molina & Pelham, 2003). Teacher ratings are one part of mental health screening; however, it is often suggested to collect ratings from multiple informants that include parents (when feasible), and students (when old enough to provide valid responses) to provide a comprehensive picture of a youth’s functioning (Kamphaus & Frick, 2002). Even when information from multiple sources is collected, there is often a lack of consistency among raters (Achenbach et al., 1987), suggesting that perhaps raters provide different, yet still valuable, information. However, a screening process that involves multiple informants is likely to be costly and time-consuming. In addition, several studies found that gathering information from a second informant does not significantly increase the amount of explained variance beyond that explained by the first informant (Biederman, Keenan, & Faraone, 1990; Jones et al., 2002; Lochman and the Conduct Problems Prevention Research Group, 1995). In general, there is no current consensus on the number of informants (in a multi-stage screening process) and the type of informants (parent, teacher, child) that should be included in the screening process. In particular, research is needed to evaluate “the value of different informants at various stages of the assessment process” (Johnston & Murray, 2003). In the school context, pragmatics suggests that the
Screening for Mental Health and Wellness 75 ease of obtaining teacher ratings supports their use with younger students and that self-reports be used with secondary school students because of their awareness of their own psychological experiences. Planning for Follow-Up Care. In addition to deciding who provides the screening information, there should be a process to provide follow-up assessment and intervention services for those students who screen positive for emotional or behavioral concerns. Screening without adequate and timely follow-up would be unethical and it is important to ensure that adequate resources are available prior to embarking on a screening program. The capacity to be responsive to student needs as identified through a screening process must be predetermined and should directly influence the program chosen; however, simultaneous work to build capacity for future and ongoing mental health needs should be undertaken. Some schools have successfully answered the question of who will provide follow-up services through the utilization of school-based mental health professionals within school-based mental health centers, while others have relied on linkages with community partners (Nagle & Gagnon, 2008). Initially, follow-up assessments will need to be conducted on all children who screen positively. If screening is to be used at a universal level (screening of all children) then the instrument should minimize the number of false negatives because these children would not have the opportunity to receive further services. However, setting cut scores is a matter of pragmatics because as the number of false negatives is reduced, it conversely increases the number of false positives. To ensure that students do not receive unnecessary services after providing a universal or first-gate assessment, additional assessments will be needed to decrease the number of false positives. A strategy for a second-gate assessment should be predetermined, considering false positives and false negatives, as well. When Should Screening Occur? Even within a universal approach to screening, a key issue is when the screening should occur. The most intensive option would be to collect screening information on every child at multiple time periods during the year. A child would first be screened upon entry into the new school or grade level. If teachers or other significant adults complete screening information, it will be important to ensure that the teachers have adequate time—at least one month—to get to know a student and his or her emotional and behavioral condition. If a child receives a positive screen and additional information leads the assessor to believe that there are no significant concerns, then the screening could be conducted again throughout the year to monitor the student’s symptoms. The child could be screened again prior to completing the school year to ensure that he or she was ready to move on to the next educational phase. An alternative, and perhaps more reasonable, approach would be to conduct screening at critical time periods. Stoep and colleagues (2005), for example, implemented the Developmental Pathways Screening Program (DPSP) in which students are targeted at the critical institutional and developmental transition period from elementary to middle school. The authors indicated that their program identified students at a time when the risk of emotional distress was high, yet possibly below the diagnostic threshold, and with sufficient time to prevent adverse outcomes (Stoep et al., 2005). Other critical time periods such as at entry to school (Spielberger, Haywood, Schuerman, & Richman, 2004) and prior to exit from school have been suggested. Still other programs have gathered information from all second- through fifth-grade students (Catron & Weiss, 1994) and arguments have been made that it might not be useful to gather information on internalizing symptoms of anxiety and depression until adolescence (Najman et al., 2007). Another approach to screening for emotional and behavioral problems would be to screen for these difficulties when other problems arise. For example, a school could implement a
76 Erin Dowdy et al. screening program in which all children that are referred to a student study/success/support team (SST), regardless of the reason for referral, would be screened. This could help make a differential diagnosis if the school-related problem were, in part, due to symptoms of emotional or behavioral distress. Perhaps the referred student is experiencing significant symptoms of inattention or anxiety that could be impacting his or her ability to perform in the reading classroom. However, it should be noted that if a student is already displaying significant signs of emotional or behavioral distress then a screening tool would not be warranted or needed and additional, more comprehensive, information should be obtained. Completing a short, timeefficient screener when a child is referred for a SST meeting, has excessive absences, or has been frequently sent to the office (signifying some problems within the classroom) might provide additional information that the team can use in forming appropriate, individualized interventions. Screening when critical behaviors occur is not as comprehensive as a universal screening approach and can lead to some children not being appropriately identified as needing additional services. However, this systematic process might allow for the identification and treatment of certain children that would not be identified through more traditional means of assessment. In addition, this approach, while confidential, is not anonymous and allows for rapid follow-up. The screening approach chosen should align with the target population and goals of interest (Stoep, 2005). Therefore, knowledge of the context and characteristics of the population to be screened is helpful in implementing an approach that will be most beneficial.
Mental Health Screening Instruments One initial decision that will surely impact other implementation decisions will be to determine which instrument to use. In this section of the chapter, we describe a set of criteria for evaluating instruments followed by a review of several instruments that have strong research support. Screener instruments provide practical benefits (Reise, Waller, & Comrey, 2000; Smith, McCarthy, & Anderson, 2000), but the challenge is to use measures with acceptable psychometric properties that are capable of predicting a wide range of behavioral and emotional outcomes. Glover and Albers (2007) delineated three characteristics of screening instruments that should be evaluated prior to use. First, the screening instrument must be appropriate for the intended use considering developmental and contextual variables and the ability of the instrument to be supportive and complementary of service delivery models. Second, screening instruments must demonstrate technical adequacy including acceptable levels of sensitivity (the proportion of individuals with the disorder who are correctly identified by the instrument as having the disorder; true positives) and specificity (the proportion of individuals without the disorder who are correctly identified as not having the disorder; true negatives). The positive predictive value (proportion of students correctly identified as at risk out of all students identified as at risk on the screener) and the negative predictive value (proportion of students correctly identified as not at risk out of all of the students identified as not at risk on the screener) of an instrument should also be examined. Third, the usability or practicality of the screening instrument should be evaluated. This includes evaluating the instrument on factors such as cost, time to administer and score, requirements for interpretation and data management, and whether it is an efficient use of school resources (Caldarella et al., 2008; Glover & Albers, 2007). The reader will be well served to further investigate how to evaluate screening instruments as they frequently change and the choice of instrument should depend on a variety of factors
Number of Items and Scale Content
11–17 years 3–4 years; 4–10 years; 11–17 years 3–4 years; 4–10 years; 11–17 years
25 for all versions • Hyperactivity-Inattention • Emotional Symptoms • Conduct Problems • Peer Problems • Prosocial Activities • Total Difficulties
Preschool: 3–5 years Child/Adolescent: Grades K–12 Preschool: 3–5 years Child/Adolescent: Grades K–12
Parent
Youth Parent
11 years and older 4–16 years
Pediatric Symptom Checklist (PSC)
Teacher
Grades 3–12
Student
35 35
Preschool: 27 Child/Adolescent: 25
30 for both versions
30
BASC-2 Behavioral and Emotional Screening System (BESS)
Teacher
Youth Parent
Strengths and Difficulties Questionnaire (SDQ)
Instruments/Forms Age Range
Test-retest reliability, 4 months: .77 Internal consistency: .89–.91 Sensitivity: .94 Specificity: .88
Split-half reliability: .90–.96 Test-retest reliability: .80–.91 Inter-rater reliability: .71–.83 Sensitivity: .44–.82 Specificity: .90–.97
Internal consistency: • Total Difficulties (.83) • Peer Problems (.46) • Remaining four subscales (.63–.77) Validity: Parent-reported service contact or special education for their child’s emotional/behavioral problems revealed significant differences (p = .0001) between youth identified by the SDQ compared with youth who were not identified by the SDQ: Sensitivity: .77; Specificity: .85
Reliability & Validity Sensitivity & Specificity
Table 4.2 Content and Psychometric Properties of Omnibus Youth Mental Health Screening Instruments
Jellinek et al. (1999) Murphy et al. (1989) Pagano et al. (2000) Simonian & Tarnowski (2001) Stoppelbeing et al. (2005)
Kamphaus & Reynolds (2007) Kamphaus et al. (2007) DiStefano & Kamphaus (2007)
Bourdon et al. (2005) Goodman (2001) Goodman & Scott (1999) Hysing et al. (2007) Mellor (2004) Shochet et al. (2006)
Research
78 Erin Dowdy et al. including the purpose of screening (for a more comprehensive review see Levitt, Saka, Romanelli, & Hoagwood, 2007). In our view, mental health screeners should be time-efficient, not so comprehensive that they would be better suited for clinical or diagnostic assessment, able to be used universally, sufficiently researched and validated, and capable of identifying an array of potential problems or strengths. With these parameters in mind, we identified the following instruments as potentially useful for school-based mental health screening: Strengths and Difficulties Questionnaire (SDQ); BASC-2 Behavioral and Emotional Screening System (BESS); Pediatric Symptom Checklist (PSC); and the Systematic Screening for Behavior Disorders (SSBD). The following section provides information on each screening instrument and process. See Table 4.2 for additional information. Strengths and Difficulties Questionnaire (SDQ) Overview. The SDQ (Goodman, 1997, 1999, 2001) is a brief, 25-item behavioral screening tool for youth 4–16 years old (more information is available at www.sdqinfo.com) that can be completed in approximately five minutes. The youth self-report, parent, and teacher versions of the SDQ ask about positive and negative attributes of the youth. There are three levels of the parent and teacher versions: 3- and 4-year-olds; 4- to 10-year-olds; and 11- to 17-year-olds. The youth self-report is for 11- to 17-year-olds. The items and subscales are based on the Diagnostic and Statistical Manual of Mental Disorders (4th ed., DSM-IV; American Psychiatric Association, 1994) and were selected using factor analysis procedures (Goodman, 2001). Five subscales cover emotional symptoms, conduct problems, hyperactivity/inattention, peer relationship problems, and prosocial behavior. Each subscale has five items. Respondents rate items using a three-point scale ranging from 0 (not at all) to 2 (very much, all the time). The total difficulties score is generated by summing the items from all of the subscales except the prosocial behavior subscale. The total difficulties score, which ranges from 0 to 40, is then classified as normal, borderline, or abnormal based on the SDQ normative scoring bands. For example, the total difficulties scores on the parent version are: normal (0–13), borderline (14–16), and abnormal (17–40). Psychometric Properties. Normative data were obtained from the parents of 10,367 children between the ages of 4 and 17 participating in the 2001 National Health Interview Survey (Bourdon, Goodman, Rae, Simpson, & Koretz, 2005). Cronbach’s Alpha coefficients are good for the total difficulties (.83), impairment scores (.80), and its four subscales (.63–.77); but poor (.46) for the peer problems subscale. To examine the validity of the SDQ, service contact or use for a mental health reason was used as the criteria. Bourdon et al. (2005) found significant differences (p < .0001) between youth identified by the SDQ with service contact/use compared with youth who were not identified by the SDQ. Goodman and Scott (1999) examined the correlation of scores between the SDQ and the Child Behavior Checklist (CBCL; Achenbach & Edelbrock, 1983), which were completed by the mothers of 132 youth ages 4 to 7. One-half of the sample was recruited from dental clinics, a low psychiatric-risk population. The other half was recruited from child mental health clinics, a high psychiatric-risk population. The results showed that scores from the SDQ and CBCL subscales were highly correlated (.59–.87) and were equally able to discriminate between children recruited from high-risk and low-risk samples, a desirable outcome because the SDQ has more than 100 fewer items than the CBCL. Hysing, Elgen, Gillberg, Lie, and Lundervold (2007) evaluated the sensitivity and specificity of the SDQ in detecting emotional and behavioral problems among children with chronic illness (CI) in Norway. Parents and teachers of 7,007 children attending second to fourth grades
Screening for Mental Health and Wellness 79 (7 to 9 years old) in all public, private, and special schools in Bergen, Norway, completed the SDQ and a question about chronic illness. To calculate sensitivity and specificity, “abnormal” cases were counted as positive and “borderline” and “normal” cases on the SDQ were counted as negative. In the sample of children with CI the sensitivity was 77.3% and the specificity was 85.1%. Mellor (2004) investigated the reliability of younger children’s responses on the self-report version of the SDQ. Of the child participants, 359 were between ages 7 and 11 (younger children) and 558 were ages 11–17 (older children). Their parents and teachers also completed the SDQ. Results found that older children’s self-reports were significantly more consistent with those of their parents compared to those of younger children. Many screening instruments may not include youth self-reports for younger children due to the lower reliability rates for this age group compared to older children. Another possible explanation for these results might be that parents’ accuracy may vary when they report on the behaviors of younger versus older children (Mellor, 2004). BASC-2 Behavioral and Emotional Screening System (BESS) Overview. The Behavioral and Emotional Screening System (BESS) is an instrument used to identify behavioral and emotional strengths and weaknesses in youth ranging from preschool through high school (Kamphaus & Reynolds, 2007). It assesses a wide range of behavioral problems and strengths, such as internalizing and externalizing problems, school problems, and adaptive skills. There are three parallel forms with differing levels as shown in Table 4.2. The number of items ranges from 25 through 30, and each form can be completed in approximately five minutes or less. The majority of the BESS items were taken from the pool of items created during the development of the Behavior Assessment System for Children-2 (BASC-2; Reynolds & Kamphaus, 2004) Teacher Rating Scales (TRS), Parent Rating Scales (PRS), and Self-Report of Personality (SRP). There is one new item for the student form, three new items for the teacher (preschool) form, three new items for the teacher (child/adolescent) form, eight new items for the parent (preschool) form, and four new items for the parent (child/adolescent) form. Respondents are given four rating options—never, sometimes, often, or almost always for each item. The BESS may be scored by hand or with computer software. The report includes raw scores, T-scores and percentiles based on a normative sample that closely matches recent U.S. Census population characteristics. The sum of the items generates a total T-score with high scores reflecting more problems (Kamphaus & Reynolds, 2007). The scoring rubric, or risk level, for behavioral and emotional problems is as follows: (a) 20–60 suggests a “normal” level of risk; (b) 61–70 suggests an “elevated” level of risk; and (c) 71 or higher suggests an “extremely elevated” level of risk. Psychometric Properties. The BESS was developed using a normative sampling group of 12,350 teacher, parent, and student forms, collected from 233 cities in 40 states (Kamphaus & Reynolds, 2007). The split-half reliability estimates range from .90 to .96 across forms and ages. Test-retest reliability estimates are high for all forms and levels, ranging from .80 to .91. Inter-rater reliability estimates range from .71 to .83. The concurrent validity of the BESS was examined by co-administering the items with other social-emotional measures: Achenbach System of Empirically Based Assessment (ASEBA, .71–.77), Conners’ Rating Scales (CRS, .51–.78), Vineland Adaptive Behavior Scales (Vineland, .32–.69), Children’s Depression Inventory (CDI, .51), and the Revised Children’s Manifest Anxiety Scale (RCMAS, .55).
80 Erin Dowdy et al. The risk level classification cut scores were developed to maximize sensitivity and specificity. Results suggest that sensitivity, specificity, PPV and NPV were generally high. The sensitivity and PPV ranged from .30 to .82 and were highest when using the Total Score to predict the Behavioral Symptoms Index. Sensitivity and PPV values were lowest for predicting Internalizing Problems, especially on the parent and teacher forms. However, for the student form, sensitivity and PPV values were higher (.55 and .66, respectively) on Internalizing Problems, suggesting that the Total Score on the student form might be particularly useful for identifying internalizing problems among youth. Pediatric Symptom Checklist (PSC) Overview. The PSC (Jellinek et al., 1999; Little, Murphy, Jellinek, Bishop, & Arnett, 1994) is a screening instrument used to identify cognitive, emotional, and behavioral problems in children (Georgetown University, 2002). There are two versions of the PSC—the parent-completed version (PSC) and the youth self-report version (Y-PSC). The Y-PSC can be administered to youth ages 11 and older. Both versions have 35 items that are rated on a threepoint frequency scale—never, sometimes, or often. The total score is obtained by summing the score for each of the items. For children ages four and five, a total score of 24 or higher on the PSC is used to designate possible psychological impairment. For children ages 6 to 16, a score of 28 or higher indicates possible psychological impairment. The cut score for the Y-PSC is a total score of 30 or higher. Psychometric Properties. Pagano, Cassidy, Little, Murphy, and Jellinek (2000) examined the concurrent validity of the PSC and Y-PSC among 173 third- through eighth-grade students and their parents. When compared with teacher ratings of attention and behavior problems, the Y-PSC demonstrated a sensitivity of 94% and a specificity of 88%. Y-PSC scores and the Children’s Depression Inventory (CDI) scores found that children with positive scores on the Y-PSC were five times more likely to score in the clinical range on the CDI compared to children with negative scores on the Y-PSC. The Y-PSC also correlated significantly with teacher and parent measures of child dysfunction. In another study, Simonian and Tarnowski (2001) examined the correlation of scores between the PSC and the Child Behavior Checklist (CBCL). One hundred eighty-seven mothers of children ages 6 to 12 completed the parent-version of the PSC and the CBCL. The PSC total score was significantly correlated with the CBCL total behavior problem T-score and the externalizing and internalizing T-scores (r = .78, r = .76, and r = .71, respectively). Another validity study examined used a sample of 166 seventh- and eighth-grade students from a suburban, public middle school (Murphy, Jellinek, & Milinsky, 1989). The students completed the Y-PSC and 140 of the 166 students’ parents completed the PSC. The level of agreement between the PSC parent version and Y-PSC was 84%. More than half of the students who screened positive on the Y-PSC also screened positive on the PSC parent version. Results also suggest that students with a positive screen on the PSC parent version were more likely to have failed at least one course than the PSC negative students. The reliability and validity of the PSC was also examined in a population of chronically ill children (Stoppelbein et al., 2005). Parents of 404 children ages 6 to 17 diagnosed with insulindependent diabetes mellitus or sickle cell disease completed the PSC. Internal consistency for the PSC was high (␣ = .89) and test-retest reliability across four months was found to be acceptable (r = .77) for the diabetes sample. The prevalence of psychosocial problems identified by the PSC parent version has been shown to be consistent across different samples (Jellinek et al., 1999). In a nationally representative sample of 21,065 parents of 4- to 15-year-old children, the prevalence of
Screening for Mental Health and Wellness 81 psychosocial dysfunction in school-aged and preschool-aged children (13% and 10%, respectively) was virtually identical to rates of impairment reported in previous studies of smaller sample sizes (12–14% among school-aged children and 7–14% among preschoolaged children). Overall, the PSC meets criteria as a useful screener as it is brief to administer, evaluates a broad range of functioning, and has acceptable sensitivity, specificity, and predictive validity. Systematic Screening for Behavior Disorders (SSBD) Overview. Whereas the SDQ, BESS, and PSC are screening instruments, the SSBD is a general screening process. It identifies students in the primary grades (K–6) who may be at risk for developing externalizing and internalizing behavior disorders (U.S. Department of Education, 1995). The SSBD uses a multiple gating procedure with progressively more precise and specific screening instruments to identify youth who need help. The three stages in the SSBD screening process use teacher nominations, ratings, and observations. First, general education teachers rank order students in their class for both externalizing and internalizing behaviors. Teachers consider all students in their classrooms, nominate 10 students in each category and rank them according to the extent to which they exhibit characteristics of externalizing and internalizing behaviors. The three top-ranked students in each category are included in the stage two screening process. In the second stage, teachers complete the Critical Events Index (33 items) and Combined Frequency Index (11 items for adaptive behaviors; 12 items for maladaptive behaviors) for the three topranked students identified in stage one. Examples of items on the Critical Events Index include being cruel to animals or being physically aggressive with others. The Combined Frequency Index asks about adaptive behaviors such as following rules and also asks about maladaptive behaviors such as “manipulates other children and/or the situation to get his or her way.” During the third stage, students who exceed the normative cut-points on the Critical Events Index and Combined Frequency Index are systematically observed in the school setting. The observational measures used in stage three are academic engaged time, recorded in the classroom, and positive social behavior, recorded on the playground. Academic engaged time is presented as the percentage of observed time during two 20-minute classroom observations. Likewise, the positive social behavior measure is generated through two 20-minute playground observations. The observer records the level, quality, and distribution of the student’s playground behavior during the observations. Positive social behavior is presented as the percentage of intervals in which the target behavior is displayed and the overall rates of positive and negative social behavior. The normative cutoff points for stage three observations are used to determine next steps (e.g., referral to the school’s student study team; possible disability classification). In regards to the time-efficiency of this process, the stage one nomination and ranking of students requires approximately 45 minutes. Stage two, when teachers complete surveys for the top three internalizers and externalizers, also requires approximately 45 minutes. In 1.5 hours or less, the SSBD results in the nomination of six students in each class school-wide who warrant additional evaluation and possible interventions. At stage three, however, the student observations total 80 minutes, which can be quite costly. Psychometric Properties. A national normative sample of 4,500 cases on stage two measures (i.e., Critical Events Index and Combined Frequency Index) was used to develop the psychometric properties of the SSBD (Severson, Walker, Hope-Doolittle, Kratochwill, & Gresham,
82 Erin Dowdy et al. 2007). The inter-rater reliability coefficients for identifying students with externalizing behaviors were between .89 and .94. The inter-rater reliability coefficients for identifying students with internalizing behaviors were between .73 and .88. In addition, the test-retest reliability coefficients were .76 for externalizers and .74 for internalizers. These strong correlations support the SSBD as an objective method for identifying children who may need additional attention. Walker and Severson (1994) found that during a trial testing, 90% of a school’s students were correctly identified as internalizing, externalizing, or neither. Of the remaining 10%, only 1% were identified as having internalizing problems when they actually had externalizing problems, 5% had problems but were not identified (false negatives), and 4% did not have problems but were identified (false positives). This level of accuracy is comparable to other clinical instruments. For example, the Achenbach Teacher’s Report Form (Achenbach & Rescorla, 2001) correctly identified 85% of youth referred for mental health services, with 7% false negatives and 8% false positives. An independent evaluation of the SSBD in middle and junior high school provided further evidence for the reliability and validity of the SSBD ratings (Calderella et al., 2008).
Emerging Trends in Mental Health Screening Although traditional approaches to screening have taken psychopathology, mental illness foci, there is recognition that ultimately the objective is to gather information that promotes mental health. Kazdin (1993), for example, conceptualizes mental health in two broad domains— (a) the absence of dysfunction in psychological, emotional, behavioral, and social spheres; and (b) optimal functioning in psychological and social domains. This raises the question, “Is the absence of psychopathology the ultimate goal?” When considering implementing a screening program, would it be worthwhile to screen for well-being? Is it possible to forego the search for pathology and focus screening resources on measures of thriving and optimal development? This question is potentially important considering research suggesting that preventive interventions should consider the many risk, protective, and other environmental factors that deter negative outcomes for children experiencing mental health symptoms (Tomb & Hunter, 2004). Positive Psychology as a Possible Framework for Mental “Health” Screening “Positive psychology is the scientific study of what goes right in life, from birth to death and all stops in between . . . and that takes seriously those things in life that make life most worth living” (Peterson, 2006, p. 4). The three pillars of positive psychology are the study of positive emotion, the study of positive traits, specifically an individual’s strengths and virtues, and the study of positive institutions and communities (Seligman, 2002). These definitions provide a clear understanding of how determining individual emotions and traits, paired with environmental support, can promote improved individual functioning. Proponents of this approach demonstrate how a focus on positive psychology constructs not only integrates prevention efforts, it also builds upon individual strengths in promoting concepts such as subjective well-being (Diener, Suh, Lucas, & Smith, 1999), resilience (Glantz & Johnson, 1999), developmental assets (Scales & Leffert, 1999), and wellness (Cowen, 1991), which are aspirational developmental outcomes for all youths. Broadening a strengths-based approach to understanding youths’ functioning allows for a comprehensive understanding of psychological well-being. Capitalizing on one’s strengths and fostering positive attributes
Screening for Mental Health and Wellness 83 (e.g., gratitude and optimism) may buffer against negative outcomes and the development of psychological maladies (Masten, 2001; Seligman, 1995). An assessment of youths’ functioning reveals (a) the limits of the current medical model in mental health; (b) a primary focus on positive outcomes; and (c) the belief that building upon these positive outcomes may, in the long run, be the most efficacious way of reducing psychological dysfunction (Cowen & Kilmer, 2002). Strengths-Based Assessment Within the field of psychology, traditional assessment practices have focused primarily on the presence or absence of psychopathology. By determining levels of dysfunction that contribute to disorders such as depression, anxiety, or hyperactivity, individuals are provided a mental illness diagnosis. Clear definitions and measurement of the science of mental illness are provided in the current model and have helped to diminish the incidence of negative sequelae of mental disorders. However, this approach has failed to include an understanding of mental health or mental wellness, and has not incorporated strengths when evaluating an individual’s level of functioning. A different but complementary approach integrates both and shifts the focus slightly to prevent mental disorders by monitoring and supporting thriving and psychological well-being. This model integrates a strengths-based approach to assessment. As current research has discovered that human strengths act as a buffer against mental illness (Keyes & Lopez, 2002), identifying individual assets is a key factor in resiliency. As a result, promising research supports the integration of a dual-factor model, combining traditional assessment measures with strengths-based approaches. This practice provides a complementary perspective on children, assessing both mental wellness and mental illness. A thorough assessment requires the promotion of positive adaptive functioning in addition to the prevention and treatment of dysfunction (Kazdin, 1993). There is increasing support for movement away from deficit-focused service delivery toward more positive, ecological models that capitalize on the strengths of children. Psychologists do not have to pick one approach or the other, but are encouraged to gradually infuse positive psychology into current models of psychopathology and treatment (Lampropoulos, 2001) in order to develop an integrative psychology incorporating both wellness and psychopathological functioning, which more accurately reflects the full range of human functioning (Huebner, 2004; Joseph & Linley, 2006; Seligman & Csikszentmihalyi, 2000). Integrating strength-based assessments and measures of positive functioning into traditional models of assessing for psychopathology promotes a dual-factor model of individual functioning. This provides a potentially beneficial framework when conducting mental health screening in schools. Not only are students screened for at-risk behaviors, but strengths are also identified as potentially mediating factors in the area of mental illness. Although assessments of subjective well-being (SWB) and quality of life (QOL) began with adults, an assessment of these constructs among children and youth has been a recent advancement in the field. The measurement of subjective well-being in adults suggests that its facets and dimensions in youth may be more complex than current research indicates (Keyes, in press). The emphasis on assessment of children is on identifying at least minimal levels of positive subjective well-being and adaptive functioning against which to juxtapose symptom patterns. This research is in its early stages but, even within the field of school psychology, assessing children with emotional disabilities calls for assessments that respect the strengths of the child and their social contexts (Doll & Cummings, 2008).
84 Erin Dowdy et al. Consideration of a Dual-Factor Model of Mental Health Select studies have begun to conceptualize a dual-factor model of assessing not only for mental illness, but also for mental wellness. A study conducted by Suldo and Shaffer (2008), for example, examined a dual-factor model of mental health that pairs assessments of positive indicators of wellness with negative indicators of illness. They compared and evaluated low and high levels of psychopathology in conjunction with low and high levels of subjective wellbeing (SWB, see Figure 4.1). Students were organized into four categories: vulnerable (low on both factors), symptomatic but content (high on both factors), troubled (low SWB and high psychopathology), and complete mental health (high SWB and low psychopathology). This conceptualization argues that positive and negative indicators of mental health are not the opposite ends of the same continuum, but rather that assessment of positive and negative indicators provide separate but complementary perspectives on individual functioning. Only evaluating psychopathology can lead to an over-estimation or under-estimation of a student’s functioning in important areas of life (Suldo & Shaffer, 2008). Utilizing this type of strategy in screening methodologies could provide a more comprehensive picture of individual functioning and potentially reduce false positives and false negatives in the screening process. An ongoing investigation of the relations between positive psychology constructs (e.g., hope, gratitude, and grit) and clinical measures of psychological adjustment problems (e.g., BASC-2, Achenbach scales, etc.) could lead to a well-rounded assessment of individual functioning. Along these lines, one model for integrating positive psychology measures and traditional assessment practices is the integration of assessing quality of life (QOL) with traditional health assessments. Frisch (2006) recommends a model that assesses for symptoms of disorder or disease, combined with overall positive psychology indicators of well-being, quality of life, or life satisfaction. A similar critical component of positive psychology assessment is subjective well-being (SWB). SWB is described as an individual’s affective and cognitive evaluation of his or her life (Diener, 2000). SWB can be measured through an understanding of children’s perceived quality of life (PQOL). PQOL refers to “a person’s subjective evaluation of the degree to which his or her most important needs, goals, and wishes have been fulfilled” (Frisch, 2000, p. 220). In the use of the PQOL, a positive appraisal style (global PQOL) buffers against negative experiences and emotions and behaviors associated with psychopathological characteristics (Huebner, Suldo, Smith, & McKnight, 2004). As such, the PQOL attempts to identify and promote strengths that encourage positive adaptive functioning and simultaneously prevent or Subjective well-being
Positive functioning
Emotional well-being
Psychological well-being
Figure 4.1 Overview of Subjective Well-Being.
Social well-being
Screening for Mental Health and Wellness 85 ameliorate psychopathological conditions. Current research indicates that very high life satisfaction is associated with positive psychosocial functioning (Suldo & Huebner, 2004). A Complementary, Comprehensive Approach to Screening Research on the assessment of life satisfaction with children and adolescents is in the early stages, but the literature provides promising evidence that assessing levels of life satisfaction among children can provide predictive information around mental illness and mental wellness (Huebner, 2004). Specifically, studies have demonstrated that decreasing life satisfaction often precedes the occurrence of psychopathology (Lewinsohn, Redner, & Seeley, 1991); at the same time, life satisfaction measures different constructs than indices of psychopathology (Huebner, 2004). A conjoint factor analysis of Huebner’s Life Satisfaction Scale and the Youth Self Report (short form) of the Child Behavior Checklist (Achenbach & Edlebrock, 1991) found three distinct and independent constructs of internalizing disorders, externalizing disorders, and global life satisfaction (McKnight, Huebner, & Suldo, 2002). As such, it is suggested that screening assessment may be enhanced when employing measures of both domains. Research further indicates that a person can be dissatisfied with his or her life without showing psychopathological symptoms, and conversely that psychopathology could occur with moderate to high life satisfaction (Greenspoon & Saklofski, 2001; Suldo & Shaffer, 2008), showing that the relation between life dissatisfaction and clinical diagnosis is not concordant (Huebner, 2004). This emerging research points to the importance of a well-rounded assessment of an individual’s functioning including measures of mental illness and mental wellness. Well-being is not merely the absence of impairment; rather it refers to the presence of personal and interpersonal strengths that promote optimal functioning (Kazdin, 1993). Even further, recent research has established a robust link between access to external social resources and lower levels of psychopathology and mental health problems in adolescents (Arthur, Hawkins, Pollard, Catalano, & Baglioni, Jr., 2002; Robert, Hoge, Andrews, & Leschied, 2006). Among the social resources that have been singled out as being particularly important is school connectedness (McNeely, Nonnemaker, & Blum, 2002). The importance of this construct for adolescents’ positive mental health was emphasized in a series of studies using the National Longitudinal Study of Adolescent Health, beginning with the influential work by Resnick et al. (1997). In this study, it was found that students who reported higher levels of positive social attachment with their schools also had fewer psychopathology symptoms and engaged in fewer high-risk behaviors such as substance use and aggression. Subsequently, numerous other studies have replicated and extended this association (e.g., Anderman, 2002; Bonny, Britto, Klostermann, Hornung, & Slap, 2000; Klem & Connell, 2004). Most of this research, however, has been cross-sectional and correlational. In a study examining a school-based mental health program in Australia, Shochet, Dadds, Ham, and Montague (2006) administered the Psychological Sense of School Membership Scale (PSSM; Goodenow, 1993) as a measure of school connectedness in tandem with the Strengths and Difficulties Questionnaire (SDQ) and clinical scales of depression and anxiety to a sample of more than 2,000 students ages 12–14. Because the surveys were administered twice over a 12month period, it offers one of the few opportunities to assess the relative predictive power of a traditional symptom-focused screening instrument (SDQ) and a strength-focused instrument (the PSSM). The results of the Shochet et al. (2006) study provide evidence that strength-focused screeners have potential to identify future mental health functioning just as well as symptom-focused screeners. Using hierarchical linear modeling to control for Time 1 mental health symptom
86 Erin Dowdy et al. severity and for possible school-level influences, the authors found some surprising relations. For example, the correlations between PSSM and the Children’s Depression Inventory (–.62) and the SDQ (–.60) were significant and substantial. Even this cross-sectional finding suggested that scores on the PSSM are strongly and negatively associated with reported depression symptoms. Even more importantly, this association remained highly significant for the Time 2 CDI and SDQ scores. In fact, the correlations between the Time 1 PSSM and the Time 2 CDI and SDQ (both –.49) were nearly the same as for the Time 1–Time 2 correlations for the CDI (.53) and SDQ (.52). An intriguing finding was that the Time 1–Time 2 PSSM–CDI correlation (–.49) was larger than the SDQ–CDI correlation (.42). In other words, for this sample of adolescents, the PSSM school connectedness measure predicted mental health symptoms one year later as well as the SDQ. In a similar study using a sample of 10- to 14-year-old students from Texas, Loukas, Suzuki, and Horton (2006) reported smaller but significant one-year correletions between the Add Health School Connectedness Scale and measures of depression (–.29) and conduct problems (–.33). Although the Shochet et al. (2006) study supports efforts to integrate wellness content in mental health screening instruments, additional research is needed to identify which aspects of well-being and protective factors will be the most critical to include. For example, in another longitudinal study, Bond et al. (2007) administered measures of school and social connectedness to students in grade 8 and examined how they predicted mental health adjustment in grade 10. This study replicated the importance of positive school connectedness in grade 8 being associated with lower scores on a depression scale in grade 10. Interestingly, however, they found that the combination of positive school connectedness and positive social connectedness was by far the best predictor of positive mental health status with equally poorer mental health associated with poor school connectedness, social connectedness, or both. These are remarkable findings that merit further research and replication. They inspire creative thinking about the most effective strategies to screen for and monitor the mental health and well-being of youth. Although it can be challenging to motivate schools and communities to screen for depression and other mental health problems, it may be easier to convince them to ask students about well-being-focused constructs such as school connectedness. Not only may this diminish any inappropriate stigma that may be associated with mental health problems, it also focuses on matters that the schools may be better able and motivated to address. When schools screen for mental health symptoms, this might encourage perceptions that the screening primarily leads to mental health referrals and services. If a school inquires about the attachment or connectedness that its students have with the school, the locus of responsibility to respond to students in need gravitates more clearly to the school and its community. For example, Shochet et al. (2006) found that for both males and females differences of just one point on the Time 1 PSSM scale were associated with two fewer points on the Time 2 CDI score. Knowing this outcome, schools could screen for students with low PSSM scores, for example, and implement strategies to increase school connectedness. Such efforts that produce even modest improvement of connectedness could meaningfully decrease depression symptoms one year later. Although this research is in its early stages, it offers an example of how future mental health screening may be enhanced by well-being measures that address factors schools may be better prepared to address. In addition to providing a more comprehensive view of a student’s functioning, collecting information from a strengths-based perspective might be more palatable to the children, teachers, and parents involved in the screening process. For example, consider how parents who are hesitant to provide consent might respond to “screening for mental health problems”
Screening for Mental Health and Wellness 87 as opposed to “screening for happiness, hope, and wellness.” The potential importance of collecting information from a strengths-based perspective, including information on adaptive functioning, might be particularly useful when screening for early identification and early intervention. Can the same goal of early identification for early intervention be accomplished focusing solely on the presence or absence of positive indicators of well-being, utilizing a strength-based approach? This question remains, but surely should be considered.
Discussion and Concluding Comments Although it makes intuitive sense to identify mental health problems so they can be treated early, it is important to consider whether early identification is even possible. School mental health providers need to carefully scrutinize emerging research that informs best practices in mental health screening because previous studies have produced divergent findings about the accuracy of screening procedures. Some studies support the efficacy of school-based mental health screening. Jones and colleagues (2002), for example, used a brief conduct problems screener with 463 children in kindergarten and found that, six years later, they were able to strongly predict which children had EBD problems and were involved in mental health, special education, or juvenile justice services. In a longitudinal study, Kamphaus et al. (2007) used an abbreviated version of the Behavior Assessment System for Children Teacher Rating Scale—Child Version (BASC TRSC; Reynolds & Kamphaus, 1992) with a sample of 206 children. They found that the screener version of the BASC TRS-C (similar to the BESS) was able to predict a substantial range of outcomes one year later including conduct problems, social skills problems, depression, and academic achievement scores. A similar longitudinal study by DiStefano and Kamphaus (2007) found evidence of concurrent and predictive validity for a screener of the preschool version, the BASC TRS-P (Reynolds & Kamphaus, 1992). Specifically, the abbreviated BASC TRS-P was able to predict social readiness for the school environment, disciplinary infractions, academic problems, and counseling referrals in addition to other behavioral and emotional indicators. Further evidence for screening comes from a study conducted by Lane et al. (2007) in which 528 students were placed in low-, moderate-, and high-risk groups based on results of the Student Risk Screening Scale (SRSS; Drummond, 1994). Results indicated that students could be differentiated on behavioral outcomes, such as office discipline referrals and in-school suspensions, with the higher-risk group having more discipline referrals and suspensions. An additional study by Briggs-Gowan and Carter (2008) found that screening with a standardized tool in early childhood (12 to 36 months of age) identified the majority of children who exhibit significant emotional/behavioral problems in elementary school (kindergarten and grade 1) as measured by the Child Behavior Checklist and Teacher Report Form (Achenbach & Rescorla, 2001). In combination, these studies provide evidence that early identification is possible although additional research is warranted. The need for additional research is emphasized by other studies suggesting that schoolbased screening does not have predictive validity. For example, the results of a study investigating the ability of a mental health screener, the Diagnostic Interview Schedule for Children Predictive Scales 8 (DPS-8) to predict mental health diagnoses as identified by the National Institute of Mental Health Diagnostic Interview Schedule for Children-IV (NIMH-DISC-IV) indicated that the screener was unable to accurately predict diagnosis (Roberts, Stuart, & Lam, 2008). Specifically, with a Canadian sample of 153 high school students, the DPS-8 was only able to correctly identify 53.1% of the students with a psychiatric diagnosis. Furthermore,
88 Erin Dowdy et al. Najman and colleagues (2007) screened for risk of later problems with depression and anxiety and they were only able to detect a small proportion of the later cases with significant mental health problems. What may be the case is that youth cope with short-term life challenges that produce significant symptoms, but that over time these symptoms abate and/or the youth are able to cope with them because of internal assets and external social resources. The authors, in fact, challenged the “existing movement encouraging the detection and treatment of those with symptoms of mental illness in early childhood” (Najman et al., 2007, p. 694). We saved this discussion for the end of the chapter because we feel that interest in providing humane care for children mandates that every effort be taken to watch diligently for any signs of emotional distress. Whichever approach to screening discussed in this chapter a school implements, school mental health providers can help to ensure that the latest research evidence is available to modify screening practices so that information is interpreted properly so Table 4.3 Mental Health Screening Implementation Considerations 1. Establish a planning and implementation team
Identify key stakeholders to assist in development and decision-making Staff, community health professional, parents, students c Consider integrating with pre-existing teams (e.g., school safety team) Assign roles for each member of the team c
2. Determine rationale and goals for screening
What is the purpose of the screening? What is the expected outcome? What is the school and community’s comfort level with undertaking this task? What will be done with the information obtained? What services are in place to address concerns? Is the focus on population-based needs assessment and/or screening to identify individual youth? Is the focus on assessing for mental health problems, well-being, or both? In what ways will screening benefit students, staff, school, and/or the community?
3. Identify resources
Identify data, resources, and services currently available at the school and in the community Design screening program to fit current capacity while working to build capacity for future needs Develop budget for screening Evaluate and make determinations about screening instrumentation based on intended use, technical adequacy, and usability Identify additional data, resources, and services that will be needed
4. Work out logistics
Develop a timeline for screening, considering the following: Who will be involved in data collection (teacher, parent, student forms)? c How often and when will screening occur each year? c How will parent consent be obtained if identifying individual students? c What are the pragmatic time and space considerations for actual data collection? c How will students, staff, parents, and community be educated about screening prior to implementation? c
5. Follow-up
How will the data be analyzed and summarized in a way that facilitates open communication? Determine how information will be shared with students, families, staff, and community Link screening outcomes to services and interventions Critically evaluate screening process and monitor effectiveness of services provided
Screening for Mental Health and Wellness 89 as to respect the rights of parents and their children. Recognizing the need for school mental health providers to provide meaningful consultation and leadership for school-based screening, Table 4.3 provides a list of the essential considerations and steps for schools to consider prior to, and while, implementing a screening program for mental health and wellness. While advances in the field of early identification have been made possible through recent improvements in early identification technologies (Levitt et al., 2007), there is not yet a consensus on optimal screening procedures and/or instrumentation to be used. Additional research and development on screening instruments is being sought and longitudinal investigations are currently underway to provide additional reliability and validity evidence for screening instruments such as the BESS (United States Department of Education, Institute for Education Sciences, Grant # R32B060033B, awarded to Kamphaus and DiStefano). Although it is possible that more questions were raised than answered and that empirical validation awaits for some screening procedures, it would be premature to dismiss screening due to preliminary discrepant results and unknown answers. There is enough known now about early identification and early intervention that it is not recommended to wait to take action until systems are further refined. School mental health providers are in a unique position to take a leadership role to start the process of implementing a screening program that is appropriate for use in their schools and communities. Schools can begin to use the data that are already available to them (e.g., results of the periodic Youth Risk Behavior Surveillance Survey) and/or collect additional screening data to begin to monitor the mental health status of their students. These data could begin to inform service delivery and intervention approaches while building the capacity to serve students with unmet mental health needs. Service systems can continue to work together to provide more coordinated systems of care that are responsive to family and child needs. Early intervention and prevention efforts with documented evidence can continue to be implemented to children identified as in need. While there is still much to be done, it is hoped that the concepts and guidelines discussed here will stimulate conversations between school mental health providers, administrators, teachers, and parents about how to best accomplish screening for mental health and wellness. It is also hoped that, following these conversations, action will occur to undertake the vital task of watching for and purposefully responding to the many unmet mental health needs of children and adolescents.
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Implementing Universal Screening Systems Within an RtI-PBS Context Hill M. Walker and Herbert H. Severson, Oregon Research Institute and the University of Oregon Gale Naquin and Cynthia D’Atrio, University of New Orleans Edward G. Feil, Oregon Research Institute Leanne Hawken and Christian Sabey, University of Utah
Professionals in the field of school psychology, child mental health and special education are well aware of the positive impact that early screening, intervention and prevention efforts can have in successfully reducing later, disruptive behavior disorders among at-risk children and youth (Dodge, 2008; Weissberg, 2005). Current efforts by the National Association of School Psychologists to promote preventive interventions for children and youth on a universal basis are fueled by evidence pointing to the critical period of school entry and the need to ensure that every child achieves a good school beginning (NASP Position Statement on Early Childhood Care and Education, 2002). School success can foster school bonding, engagement, and attachment which, in turn, function as powerful protective influences against later destructive outcomes. That is, they have the potential to operate long-term much like a vaccine or inoculation (Embry, 2002). Comprehensive early intervention approaches involving parents, peers and teachers that are directed toward ensuring a successful start to a child’s school career are a proven method for developing these protective influences (Hawkins, Catalano, Kosterman, Abbott, & Hill, 1999). Well-conducted, longitudinal research suggests that much of problem behavior in adolescence has its origins in early childhood (Kazdin, 1987; Loeber & Farrington, 1998; Patterson, Reid, & Dishion, 1992; see also Eddy, Reid, & Curry, 2002). This longitudinal evidence provides empirical support for policies that can positively impact vulnerable children’s later lives (a) by addressing risk factors, and their associated behavioral correlates, early on in the child’s development; and (b) by developing the academic and social readiness skills that contribute to subsequent school success and social effectiveness (Dodge, 2008; Durlak, 1997; Diperna, Volpe, & Elliott, 2002; Gresham, 2004; Hunter, Hoagwood, Evans, Weist, Smith, Paternite, Horner, Osher, Jensen, & the School Mental Health Alliance, 2005). This early developmental period can be viewed as providing a pivotal window in which to intervene for preventing later potential problems, such as violence, substance abuse, educational failure, adolescent delinquency, and adult criminal involvement. Federal and state policies that support collaborative early intervention approaches, mounted within home, school, and community contexts, are perhaps one of the best hopes we have for preventing and remediating destructive behavior patterns before they become chronic and intractable (Zigler, Taussig, & Black, 1992). In a seminal policy piece on addressing youth violence, Dodge (2008) recently argued persuasively for the universal teaching of social skills and social competence as a promising means of accomplishing this important societal goal.
Implementing Universal Screening Systems Within an RtI-PBS Context 97 The RtI framework provides an important context for intervening early on in a child’s schooling career as well as early within a negative developmental trajectory—regardless of age. A primary goal of the three-tiered Response to Intervention (RtI) model is to detect those students as soon as possible who are at risk for learning disabilities, low achievement and possibly later school dropout and to provide an appropriate level of intervention for them based upon continuous progress monitoring (see Batsche, Elliott, Graden, Grimes, Kovaleski, & Prasse, 2005; Shinn, 2007). Although the three-tiered RtI logic seems to apply to the prevention and early remediation of behavioral as well as academic problems, RtI is most commonly mentioned in the context of academic supports and the prevention of learning disabilities (see Glover, Diperna & Vaughn, 2007). Experts in the field of Positive Behavior Support (PBS) have recommended adoption of a similar three-tiered model of positive behavior support to prevent and intervene with the full range of problem behavior typically seen in school settings (Frey, Lingo, & Nelson, in press; Sugai & Horner, 2002; Walker et al., 1996). With the advent of pressures to prevent destructive student outcomes through early intervention programs and supports, there has been a corresponding call for universal screening systems to detect at-risk students early in their school careers and to interrupt the trajectories on which so many find themselves (see Albers, Glover, & Kratochwill, 2007). In addition, a number of school-based professionals, who are working within 3-tier PBS systems and school contexts, have expressed interest in accessing such universal screening systems, for instance, in order to facilitate their efforts at targeting students, within tier 1, who will likely require tier 2 and 3 intervention approaches later on, based upon progress monitoring outcomes. The multi-gating Systematic Screening for Behavior Disorders procedure (Walker & Severson, 1990) has been a recent focus of much of this interest. Despite having been available for over a decade and longer, there have been relatively few demonstrations of how universal screening systems can be used effectively within such RtI-PBS contexts. The purpose of this chapter is twofold: (1) to describe ways in which the SSBD and similar universal screening systems can be effectively utilized within an RtI-PBS school context; and (2) to present a large-scale, case study application of the SSBD that illustrates its use within a court-mandated, child find initiative in a New Orleans regional school district (i.e., the Jefferson Parish Public Schools). The following topics are addressed herein: (a) current status of practices regarding universal screening for behavior problems in schools; (b) sample exemplars of approaches to universal screening for behavior problems in schools; (c) key features of the SSBD universal screening system; (d) recent applications of the SSBD in research contexts; (e) the utility of universal screening systems within RtI-PBS type contexts; and (f) illustration of a multi-year, case study application of the SSBD within a court-mandated initiative to improve services and supports for students experiencing emotional or behavioral disorders (EBD). The chapter concludes with some observations about needed directions for future research, practice and policy on universal screening and prevention.
Current Status of Practices Regarding Universal Screening for Behavior Problems in Schools It can be argued that school-based methods of identifying students with mental health needs are currently failing. In any given year, only about 1% of the public school population is identified, referred and actually certified as emotionally or behaviorally disordered (EBD) (Kauffman & Landrum, 2008). Yet estimates of the numbers of children and youth experiencing significant mental health problems in need of attention range upwards of 20% of the K–12, school population (see Burns & Hoagwood, 2002; Levitt, Saka, Romanelli, & Hoagwood,
98 Hill M. Walker et al. 2007). There is scant evidence that either of these percentages has shown appreciable movement in the past decade (Walker, Nishioka, Zeller, Severson, & Feil, 2000; Walker, Severson, & Seeley, in press). From the available evidence regarding current practices, it appears that the relative absence of school-based, proactive identification procedures and persistent inconsistencies in decision-making are key contributors to the low rates at which EBD students are identified and served. Further, the tepid investments in early detection initiatives by educational gatekeepers to date have often led to a reduced capacity to mount effective prevention efforts. As a result, children with EBD are identified much too late in their school careers at which point intervention efforts are likely to be less successful and also come at increasing cost. The primary outcome of these practices is very often “too little, too late” (Albers, Glover, & Kratochwill, 2007). Kauffman (1999; 2005) has insightfully examined barriers to the mounting of universal screening systems for detecting behaviorally at-risk students in school settings. Obstacles he has identified include: (1) the stigma of being identified as behaviorally at-risk and labeled EBD in order to qualify for services; (2) cost savings in order to avoid the expense of referral and certification as EBD; (3) the possibility of lawsuits by parties dissatisfied with available or provided services; and (4) the often nettlesome burdens of complying with IDEA bureaucratic requirements associated with certification as EBD. Another likely restraint on the early detection of EBD students concerns the reluctance of many teachers to refer behaviorally at-risk students as such referral may be interpreted as an indication of weak classroom management skills. Research on teacher referral practices indicates that teachers are the primary gatekeepers of both academic and behavioral referrals and while they are prone to make academic referrals early, they tend to delay behavioral referrals well into the upper elementary and the middle school grades (see Walker, Nishioka, et al., 2000). In addition, general education teachers typically under refer externalizing students and rarely refer internalizing students (Lloyd, Kauffman, Landrum, & Roe, 1991; Walker et al., 2000). These trends and practices coalesce to validate Kauffman’s claim that we actually “prevent prevention rather efficiently” (Kauffman, 1999).
Sample Exemplars of Approaches to Universal Screening for Behavior Problems in Schools Although Albers et al. (2007) note that additional research is needed on the feasibility, efficacy, cost, and consumer acceptance of universal screening approaches, a substantial amount of research and development work has been invested in universal screening approaches since the mid-1990s. In our view, a strong level of innovation is apparent in these efforts and the field of education greatly underutilizes the potential benefits of many of these advances. Some examples of these universal screening methods are briefly described below. These methods are based upon a diverse array of information sources including teacher informants, archival school records, and in vivo behavioral observations. Teachers’ Use of Nominations and Likert Rating Scales Teacher appraisal of student behavior, based on Likert rating scales, have been a relatively popular approach in the evaluation of students referred for social, emotional, and behavioral problems (see Merrell, 1999, 2001). Such Likert scales typically ask the rater to assess students’ behavior along three-, five-, or seven-point dimensions of problem frequency or severity.
Implementing Universal Screening Systems Within an RtI-PBS Context 99 Hundreds of such scales are in use and evaluations of many of them can be accessed through the Buros Mental Measurements Yearbook (Geisinger, Spies, Carlson, & Plake, 2007), which annually reviews newly developed scales. The Child Behavior Checklist (Achenbach, 1991) has become the rating scale gold standard for measuring child and youth psychopathology and is, by far, the most widely used instrument for this purpose. Merrell (1999) has contributed a comprehensive analysis of assessment instruments for use in social, emotional, and behavioral domains. In addition to their relatively unsystematic use, critics of teacher rating instruments point to their global and relatively crude assessment properties (e.g., “How many fidgets are there in pretty much?”). Others argue that the sensitivity of teacher ratings pales in comparison to more direct measures such as in vivo behavioral observations. In spite of these criticisms, teacher ratings continue to be a widely used and important source of information in child screening, identification, and evaluation processes. Teacher ratings have the advantage of defining and pinpointing the behavioral content of a student’s perceived adjustment problems, are based upon many hours of teachers making social comparisons among students, and can be standardized so as to enable valid comparisons as referenced to normative age and gender scores. Merrell (2001) has pointed out that Likert behavioral ratings have a number of additional advantages. For example, they (a) are relatively inexpensive; (b) provide essential information on low-frequency behavioral events of potential importance; (c) are relatively objective and reliable, especially when compared to interview and projective assessment methods; (d) can assess individuals who are unable to contribute self-reports; (e) take into account the many observations and judgments of child behavior made by social agents within natural settings over the long term; and (f) reflect the judgments of expert social informants who are familiar with the student’s behavioral characteristics (i.e., parents, teachers, peers). In school-based practice, general education teachers are typically asked to nominate behaviorally at-risk students (often in the absence of specific criteria for nomination) and then to follow up with Likert ratings for each nominated student on a scale such as the Achenbach Behavior Checklist or the Social Skills Rating System (Gresham & Elliott, 1990). If a student’s profile is within the clinical range on the Likert scale being used, he or she is then considered for further evaluation, possible certification and/or services and supports. Drummond (1993) has developed an intriguing matrix system, based on Likert teacher ratings, that is designed to screen entire classrooms of students for their risk status in relation to antisocial behavior patterns. In this universal screening approach, every student in the teacher’s classroom is rated on a set of seven indicators of antisocial behavior. Drummond’s Student Risk Screening Scale (SRSS) is a cost-efficient and popular procedure for quickly screening entire classrooms. A matrix format is used that has seven behavioral descriptors across the top of the rating form and students’ names down the left side (see Figure 5.1). The classroom teacher assigns every student a Likert rating, ranging from 0 = never to 3 = frequently, for each of these seven items of the SSRS: (1) stealing; (2) lying, cheating, sneaking; (3) behavior problems; (4) peer rejection; (5) low academic achievement; (6) negative attitude; and (7) aggressive behavior. Teachers compare each student against all other students in the classroom as they rate each item. The SRSS is a brief, research-based, easily understood, reliable, valid, and cost-efficient instrument. The SRSS was recently investigated in a study of 674 high school students by Lane, Kalberg, Parks, and Carter (2008) and found to have acceptable psychometric characteristics. The major advantages of the SRSS are that (a) all students are systematically screened and evaluated; (b) it accomplishes universal screening; and (c) normative social comparisons are facilitated by requiring the teacher to evaluate all students on each item at the same time rather
100 Hill M. Walker et al. Sample student risk screening scale (SRSS) Screening form for an entire class Items Names
Stealing
Lying, cheating, sneaking
Behavior problems
Peer rejection
Low academic achievement
Negative attitude
Aggressive behavior
Susan
0
0
1
1
1
0
0
3
Low
Jamie
3
0
1
2
0
1
1
8
Moderate
Fred
1
1
3
3
2
3
3
16
High
Totals
Levels of Risk: High risk = 9–21; Moderate risk = 4–8; Low risk = 0–3 Scale: 0 = Never to 3 = Frequently
Figure 5.1 Sample Student Risk Screening Scale (SRSS) Screening Form for an Entire Class.
than rating individual students on a series of items on a case-by-case basis. The SRSS thus affords every student an equal chance to be evaluated in relation to the seven SRSS items. A matrix system of this type is also ideally suited for the classwide assessment and pre-post evaluation of instruction for all students in a series of social skills. A more complete description of the SRSS and its potential applications is provided in Walker, Colvin, and Ramsey (1995) and Sprague and Walker (in press). Critical Behavioral Events Critical behavioral events refer to episodes having great intensity, salience and social impact; they include but are not limited to assault, fire -setting, self-injury, exposing oneself, stealing, cheating, bullying, and so on (Todis, Severson, & Walker, 1990). Research by Walker and his colleagues on mainstreaming and social integration shows that such behavioral events (1) are unacceptable to teachers in the extreme; (2) are likely to prompt teacher efforts to have the student displaying them permanently removed from the classroom; and (3) differentiate atrisk students in terms of the severity of their behavioral adjustment problems (Walker, 1986). These critical behavioral events have been characterized as “behavioral earthquakes” because of their disruptive influence on classroom ecology. The importance of critical events is derived from their severity and their potential destructiveness to the individual and other social agents. The impact of critical events is not dependent upon their frequency of occurrence but rather determined by the fact that they occur at all. These are very rare occurrences in the behavioral repertoires of typically developing children and youth but are not all that infrequent in the lives of some behaviorally at-risk individuals. Gresham, MacMillan, and Bocian (1996) conducted a study of the Critical Events Index (CEI) in their use of the SSBD screening procedure within a larger study of the social-affective status of at-risk students. The CEI was used to identify three groups of students from an elementary-aged student sample based upon the groups’ total number of critical events: (a) highrisk (n = 30), (b) moderate-risk (n = 55), and (c) low-risk (n = 30). These groups were then contrasted on a series of cognitive/achievement, social competence, externalizing behavior, and school history variables as derived from searches of archival school records of individual students. Multivariate and univariate analysis procedures showed that the three at-risk groups were differentiated primarily on social competence and externalizing behavioral measures.
Implementing Universal Screening Systems Within an RtI-PBS Context 101 However, a series of cross-validated, stepwise discriminant function analyses, contrasting the high- and low-risk groups only, and using combinations of social competence, externalizing, internalizing, and school history variables, correctly identified over 85% of the high-risk group and 78% of the low-risk group. Gresham et al. (1996) recommend inclusion of critical events measures within multi-method assessments of at-risk, behavioral status and they view these events as “vital signs” indicative of childhood psychopathology. Blechman and Hile (in press) make the following observations regarding critical events: (1) Student involvement in critical events provides a bias-free screen for the detection of at-risk students in the general or universal student population; and (2) Systematic documentation of all critical events provides the most effective and least expensive method of screening for at-risk students. They note further that reliance upon readily available information from archival student records within screening efforts reduces costs, increases feasibility, and avoids extraordinarily adverse consequences to students. Blechman and Hile (in press) define critical events in their work as including school and criminal offenses, threats of violence or suicide, suicide attempts, and caregiver requests for assistance with behavior management. They argue that these events offer a useful and inexpensive predictor of future and more serious critical events. The work of these authors reflects an increasing trend toward using critical behavioral events in screening practices, as either rated by knowledgeable informants or culled from existing archival records. Archival School Records If the early preschool detection of behavior problems is not possible, school records can provide an additional valuable source of screening information as students move through the primary and intermediate grades. Archival school records that accumulate as a natural part of the schooling process provide a rich and inexpensive information source regarding a range of school adjustment problems and also provide a record of the manner in which schools try to cope with such problems. Because these records build naturally as an ordinary part of the schooling process, they are relatively unobtrusive and far less reactive than typically recorded assessments (e.g., teacher ratings, in vivo behavioral observations, sociometric measures). Our experience shows that they become more complete as students progress through the intermediate grades and into middle school settings. Walker and his colleagues developed the School Archival Records Search (SARS) procedure (see Walker, Block-Pedego, Todis, & Severson, 1991) to accomplish the coding, analysis, and aggregation of archival school records. SARS provides for the systematic coding of 11 archival variables, which can then be analyzed individually or aggregated into domain scores that provide profiles of student status in three areas of school adjustment: disruption, needs assistance, and low achievement. The individual SARS variables that are coded comprise the following: number of different schools attended, days absent, low achievement, grades retained, academic/behavioral referrals, current Individualized Educational Program (IEP), nonregular classroom placement, Title I, referrals out of school, negative narrative comments, and school discipline referrals. In the context of schooling, archival school records are the closest proxy we have for police contacts and juvenile records that are used in evaluating delinquency prevention programs and in validating measures that purport to predict later delinquent acts. Disciplinary referrals of students to the front office, as reflected in archival school records,
102 Hill M. Walker et al. have emerged as a very useful measure for assessing overall school climate and for identifying student groups and individuals who are in need of behavioral supports and intervention (see Irvin, Tobin, Sprague, Sugai, & Vincent, 2004; Tobin & Sugai, 1999; Walker, Stieber, Ramsey, & O’Neill, 1993). Sugai, Horner, and their colleagues have conducted extensive research on this topic in the past five years. Sugai et al. (2000) reported normative data profiles on disciplinary referrals involving a sample of 11 elementary schools and nine middle/junior high schools. These elementary schools averaged 0.5 disciplinary referrals per student per school year. At the middle/junior high school level, however, students being referred to the principal’s office due to disciplinary infractions was a very common occurrence. In the Sugai et al. study, the elementary schools averaged 566 students enrolled and 283 disciplinary referrals within a school year; in contrast, the middle/junior high schools averaged 635 students and 1,535 disciplinary referrals within a school year. These authors also analyzed some of the patterns that existed within this pool of disciplinary referrals. Based on their analysis, they argue that such patterns can guide the direction and focus of intervention approaches for addressing chronic behavior problems within the school setting (i.e., targeting the whole school, small groups, and/or individual students). For example, at the elementary level, Sugai. Sprague, Horner, & Walker (2000) found that the top 5% of students with the most discipline referrals also accounted for 59% of total disciplinary referrals within the school; at the middle/junior high level, the top 5% accounted for 40% of all discipline referrals. These figures closely parallel outcomes for juvenile crime where 6 to 8% of juveniles typically account for 60 to 65% of all delinquent acts (Loeber & Farrington, 1998). According to Sugai et al., elementary-aged students with five or more disciplinary referrals within a school year are considered to be behaviorally at risk; those with 10 or more such referrals are considered to be chronic discipline problems who may be severely at risk for both inschool and out-of-school destructive outcomes. Recording and utilizing disciplinary referrals to identify at-risk students and to guide intervention applications requires the computerization of school records. Horner and his associates have developed the School Wide Information System (SWIS) procedure, which is a web-based computer application for entering, organizing, and reporting office discipline referrals found within schools (May, Ard, Todd, Horner, Glasgow, & Sugai, 2001). SWIS computerizes discipline referrals and is a valuable tool for use by teachers and school administrators in collecting and analyzing discipline-related information. Perhaps the advantage of the SWIS procedure is that it systematizes and standardizes the process of documenting, recording and reporting on disciplinary referrals. Figure 5.2 illustrates the SWIS Office Referral Form, which is completed for each disciplinary referral made by a teacher to the school office. This referral form documents each disciplinary episode for which a front office referral is initiated by the teacher. The SWIS referral form describes the location, specific problem behavior, and possible motivation for the behavior, the resulting administrative decision, and other persons who were involved in the incident. Parents are asked to sign and date the referral form to indicate that they have knowledge of the incident, the referral, and its disposition. SWIS is an important advance in the computerization of archival school records that allows individual schools to profile themselves in relation to disciplinary practices and their resulting effects. It can be used also as a measure of certain aspects of school reform efforts, as a measure of the school’s climate, as a pre-post measure of schoolwide interventions, and as a vehicle for guiding and targeting allocation of intervention resources to small groups and individuals. It is also recommended as a schoolwide, behavioral screening device to identify those students who are experiencing serious to chronic school adjustment problems.
Implementing Universal Screening Systems Within an RtI-PBS Context 103
SWISTM OFFICE DISCIPLINE REFERRAL FORM Grade Level
Referring Staff
Student(s)
Time
Date
Location Classroom
Cafeteria
Bus loading zone
Playground
Bathroom/restroom
Parking lot
Commons/common area
Gym
On bus
Hallway/breezeway
Library
Special event/assembly/field trip
Other
Problem Behaviors (check the most intrusive) MINOR
MAJOR
Skip class/truancy
Vandalism
Inappropriate lang.
Abusive lang./inapprop. lang.
Forgery/theft
Property damage
Physical contact
Fighting/physical aggression
Dress code
Bomb threat
Defiance/disrespect/ non-compliance
Defiance/disrespect/insubordination/non-compliant
Lying/cheating violation
Arson
Tobacco
Weapons
Disruption
Harassment/ tease/taunt
Alcohol/drugs
Other
Property misuse
Disruption
Other
Tardy
Combustibles
Possible Motivation Obtain peer attention
Avoid tasks/activities
Don’t know
Obtain adult attention
Avoid peer(s)
Other
Obtain items/ activities
Avoid adult(s)
Others Involved None
Peers
Staff
Teacher
Substitute
Unknown
Other
Administrative Decision Time in office
Detention
Saturday School
In-school suspension
Loss of privilege
Parent contact
Individualized instruction
Out-of-school suspension
Conference with student
Other
Comments: Follow up comments:
Figure 5.2 SWIS Office Discipline Referral Form.
Behavioral Observations Behavioral observations recorded in natural settings (e.g., homes, classrooms, playgrounds, hallways) remain the preferred assessment method of most behavior analysts for assessing the behavior problems of students. In typical school usage, the teacher referral process requires that a school psychologist, or other related-services professional, directly observe the target student in a setting or context in which the problem behavior occurs (i.e., the referral setting). A wide range of coding systems and recording procedures are used for this purpose. However, the vast majority of them do not have adequate technical data or information to support their use(s). In addition, most of these codes lack local, state, or national norms that are appropriate for making social comparisons among students (see Leff & Lakin, 2005, for a recent review). It should be noted that behavioral observations are rarely used for universal screening purposes due to their labor-intensity and high cost. Much more typically they are used in
104 Hill M. Walker et al. conjunction with teacher nominations and ratings to develop a more complete picture of the target student, to verify teacher impressions or ratings of the student, and to document the nature, estimated frequency, and topography of the behavior problems cited in a referral. Teacher referrals are often based upon discrete behavioral events of high intensity or salience (e.g., insubordination, teacher defiance) that may be missed within the narrow window of time and occasions sampling that most such observations involve. Naturalistic behavioral observations are also vulnerable to observer bias and expectancy effects that can be induced by the observer’s prior knowledge of the case. Further, direct observations are timeconsuming and labor-intensive in that they usually require considerable planning and careful monitoring if they are conducted effectively (see Merrell, 2001). In spite of these downsides, naturalistic behavioral observations remain popular among school professionals and they do have an important role to play in the screening-identification process if they are incorporated into a comprehensive assessment process that involves other, less expensive measures (e.g., teacher nominations, rankings, ratings, archival records searches, etc.). We do not recommend their use in isolation; but rather that they constitute an important component of a multi-agent, multi-method, and multi-setting assessment approach to the screening-identification process (Merrell, 1999). All of the approaches described above have some degree of applicability to universal screening within an RtI-PBS context—some more than others. Behavioral observations and Likert teacher ratings have the most relevance in progress monitoring and decision-making regarding moving a student into more intensive levels of intervention and remediation. Archival school records, critical behavioral events and office disciplinary referrals, because of their low frequency and high salience, are much less sensitive and are more useful for initially identifying those students who are less likely to respond to a universal intervention. Some guidelines and recommendations for the use of universal screening procedures within RtI-PBS type contexts are discussed in the sections that follow.
Key Features of the SSBD Universal Screening System Walker and Severson (1990) developed the Systematic Screening for Behavior Disorders (SSBD) screening procedure for use with elementary-age children (K–6 grades) based upon a conceptual model, and corresponding empirical findings, documenting that children’s problem behavioral characteristics could be divided reliably into “externalizing” (e.g., aggressive, hyperactive, noncompliant, antisocial, etc.) and “internalizing” dimensions (e.g., shy, phobic, depressed, anxious, isolated from peers, etc.) (see Achenbach, 1991; Ross, 1980). The SSBD was patterned after screening models developed and validated by Greenwood, Walker, Todd, and Hops (1979) for the preschool screening of children at risk for social withdrawal and by Loeber, Dishion, and Patterson (1984) for the screening of adolescents at risk for later delinquency. The SSBD is a proactive, universal screening procedure that provides each student with an equal chance to be screened and identified for either externalizing or internalizing behavior disorders. The SSBD procedure consists of three interconnected screening stages or gates where movement through each gate is required for consideration at the next gate. Most students are screened out in the initial SSBD gates (i.e., gates 1 or 2) because they do not meet the behavioral criteria necessary to proceed to the next phase of screening. Walker and Severson began their first trial testing of the SSBD in the mid-1980s and conducted extensive research, supported by a series of federal grants, on this screening system prior to its publication in 1990 (Walker, Severson, Stiller, Williams, Haring, Shinn, & Todis, 1988; Walker, Severson, Todis, Block-Pedego, Williams, Haring, & Barckley, 1990).
Implementing Universal Screening Systems Within an RtI-PBS Context 105 Figure 5.3 illustrates the three screening gates of the SSBD. In gate 1, teachers are asked to think about all students in their class and to nominate those students whose characteristic behavior patterns most closely match either the externalizing or internalizing behavioral definitions provided for them. The three highest-ranked externalizing students and the three highest-ranked internalizers then move to screening gate 2 where their behavior is more specifically rated by the teacher on a 33-item Critical Events Index (CEI) and on an Adaptive (11 items) as well as a Maladaptive (12 items) Likert rating scale that requires estimates of frequency of occurrence. Students who exceed national, normative cutoff scores on these measures move on to an optional screening gate 3 where they are observed in classroom and playground settings. Using a direct observation procedure, a school professional (school psychologist, counselor, or behavioral specialist) observes and codes each target child’s behavior for two 20-minute sessions in the regular classroom. A stopwatch measure of Academic Engaged Time (AET) is used for this purpose. The Peer Social Behavior (PSB) code is used to record the level, quality, and distribution of the target student’s peer-related, social behavior at recess during two 20minute, observation sessions. Multiple-gating assessment procedure for identification Pool of regular classroom preschoolers
STAGE I:
Teacher ranking on internalizing & externalizing behavioral dimentions 3 Highest ranked children on externalizing & internalizing behaviral criteria Pass gate 1
STAGE II:
Teacher ranting on critical events checklist (CEI) & combined frequency index (CFI) Exceed normative criteria on CEI or CFI Pass gate 2
STAGE III:
Direct observations & parent questionnarire direct observation in freeplay & structured activities & parent rating Exceed normative criteria
Classroom interventions
Pass gate 3
Referral to multidisciplinary evalution
Adapted from: Feil, E., Severson, H. and Walker, H. (1994). Eary screening project: Identifying preschool children with adjustment problems. The Oregon Conference Monograph. Vol. 6.
Figure 5.3 SSPD/ESP Multiple Gating Procedure.
106 Hill M. Walker et al. Normative data for the SSBD gate 2 instruments consist of over 4,000 cases representing the four U.S. census zones. The SSBD user’s manual also provides normative observation data for the AET and PSB codes involving over 1,300 cases for each code—also collected across the four census zones. Those students who exceed national, normative cutoff points on the AET and PSB codes are considered to have serious problems and are usually referred for further evaluation to specialized, school-based services. As a rule, an archival records search is conducted at this point to provide further confirmation of results of the screening-identification process and serves as a further source of information for decision-making. The first two screening gates of the SSBD can be completed by the classroom teacher in approximately one to 1½ hours. Completion of the gate 2 screening tasks typically identifies one externalizer in every classroom and one internalizer in every two or three classrooms. The time involved in conducting SSBD screening assessments increases as one moves through the screening stages; however, the number of students who are the targets of those assessments is greatly reduced from gates 1 to 3. It is recommended that universal SSBD screenings be conducted twice a year—once in the fall and once in the spring (e.g., in October and February) to identify students in need of intervention supports and services, to maximize the sensitivity of school staff to initial behavior problems in the fall of the school year, and to detect emerging behavior problems later in the school year. The SSBD has been extensively researched and has excellent psychometrics (see Severson, Walker, Hope-Doolittle, Kratochwill, & Gresham, 2007; Walker & Severson, 1990; Walker, Severson, Nicholson, Kehle, Jenson, & Clark, 1994).
Recent Applications of the SSBD in Research Contexts The SSBD has been used as an initial behavior screen in two multi-site federal initiatives funded by the U.S. Office of Special Education Programs within the past decade. These initiatives are: (1) the National Reading and Behavior Centers Program, and (2) the National Behavior Research Centers Program. Coordination and technical assistance supports were provided for these two initiatives respectively by the University of Wisconsin (Elliott & Kratochwill) and by SRI (Wagner, Woodbridge, & Sumi). In these applications, the SSBD was used primarily as a universal screening instrument to identify appropriate candidates for inclusion in RtI-PBS interventions and, in some cases, as measures of pre-post outcomes. Use of the SSBD in a standardized fashion across the varied implementation-data collection sites comprising these programs of research provided substantial advantages in identifying comparable sample populations and in improving the external generalizability of empirical findings. There have been some recently reported SSBD studies by investigators who are engaged in individual programs of research and development involving student populations that are behaviorally and/or academically at risk. For example, Walker, Cheney, Stage, Blum and Horner (2005) used the SSBD as a primary means of identifying their intervention sample of target students (n=1,540). They concluded that students at risk of school failure are best identified by monitoring school discipline referrals and use of the SSBD screening process. Kathleen Lane and her associates have conducted an extensive series of studies using the SSBD as a primary vehicle of instrumentation with this same at-risk population and found it to be an effective instrument for the identification of students from this population in need of intervention supports and services (see, for example, Lane 2007; Lane, Parks, Kalberg, & Carter, 2008). To date, Lane and her associates have assembled an SSBD data base of approximately 7,000 cases at elementary and middle school levels.
Implementing Universal Screening Systems Within an RtI-PBS Context 107 Caldarella, Young, Richardson, Young, and Young (2008) recently reported an investigation in which they evaluated the SSBD screening procedure for use with middle and junior high school students (n=123). They reported that their study provided evidence for the reliability and validity of SSBD teacher ratings of early adolescent students who are behaviorally at risk. Collectively, these studies are encouraging in that they validate the SSBD’s use as a research instrument in identifying target student populations who share behavioral characteristics across diverse participating sites. They also serve to extend the SSBD’s effective range of application with adolescent student populations and validate its use as a criterion in evaluating other screening instruments (see Lane et al., 2008).
Applications of Universal Screening Systems Within RtI-PBS-Type Contexts In 1996, Walker and his colleagues adapted the U.S. Public Health classification system governing prevention outcomes for use as a scaffold in coordinating the integrated delivery of behavioral interventions within school settings (Walker, Horner, Sugai, Bullis, Sprague, Bricker, & Kaufman, 1996). The goal of this adaptation was to enable the coordination and integration of differing intervention approaches (i.e., primary, secondary, tertiary) and to maximize the resources needed to respond to the needs and problems of the three groups of students found within any school or preschool setting: (1) those who are not at risk and are progressing normally; (2) those who have mild to moderate risk status; and (3) those who are severely at risk. This classification schema allows schools to (1) address all three types of prevention goals and outcomes (primary, secondary, tertiary) in a coordinated fashion across these three groupings of students; (2) deliver positive behavioral supports and services in a cost-effective manner to all who need them; and (3) create and sustain a positive school climate and social ecology that provide a supportive context for teaching and strengthening school expectations governing student conduct (e.g., be safe, be respectful, be responsible). Figure 5.4 illustrates this classification schema along with some of the universal, selected and indicated interventions that are used to achieve respectively primary, secondary and tertiary prevention outcomes. This model of service delivery defines prevention as a goal or outcome of intervention rather than as an approach (Walker, Ramsey, & Gresham, 2004). Differing intervention types are used to achieve specific prevention goals and outcomes. For example, primary interventions are directed toward achieving outcomes in which the goal is to keep problems from emerging. Secondary interventions are used to achieve goals and outcomes where the focus is on reducing or eliminating the emergent problems of already behaviorally at-risk students. Finally, tertiary interventions produce focused outcomes for student populations having severe risk status. This delivery model allows for a more cost-effective use of available, schoolbased resources. The schema or heuristic in Figure 5.4, sometimes referred to as the teaching pyramid, has also been adapted for use in coordinating interventions for very young preschool children by Fox, Dunlap, Hemmeter, Joseph, and Strain (2003). The SSBD screening system parallels and lines up seamlessly with the three-tiered model of increasingly intensive intervention approaches that are built into the RtI model. For instance, as one moves through the sequential SSBD gates, those students who remain in the screening pool (i.e., are not screened out) are more likely to be candidates for secondary and tertiarylevel PBS interventions and supports (Walker, Severson, & Seeley, in press). In particular, those students who have positive profiles on the Critical Events Index at screening gate 2 may be especially at risk and in need of intensive, indicated interventions at the tertiary level. Further, the screening tools and procedures of the three SSBD screening gates also parallel assessment needs at each of the three-tiered levels within the RtI model.
108 Hill M. Walker et al. Preventing violent and destructive behavior in schools: Integrated systems of intervention Assessment
Intervention
Full risk and protective factor assessment Suspension and expulsion data Youth services contacts
Students with chonic/ intense problem behavior (1–7%)
Students at-risk for problem behavior (5–15%)
Students without serious for problem behaviors (80–90%)
Tertiary prevention
• •
Secondary prevention
• •
Primary Universal screening prevention Academic progress
• •
Brief functional assessment School records review Discipline referrals
Specialized individual interventions Individual student servies Wraparound services (family, community) Specialized targeted interventions First step to success Treatment packages ♦ Self management ♦ Scheduling ♦ Academic support
Universal interventions Social skills training High academic expectations • School-wide rules • ATOD education
Figure 5.4 Preventing Violent and Destructive Behavior in Schools.
There are at least five potential applications of a universal screening system like the SSBD within an RtI-PBS context. They include: (1) universal screening to identify candidates who will likely need exposure to secondary and tertiary-level interventions; (2) assessments to monitor progress within PBS tiers and for determining whether the student should move to a different level of intervention and support; (3) as a source of information for designing interventions at both group and individual levels; (4) as a tool for planning staff development training and technical assistance initiatives based on analysis of teacher ratings of behavioral deficits and excesses collected at screening gate 2 for at risk students; and (5) as one index of how well a school-wide intervention is functioning based on the severity of gate 2 SSBD behavioral profiles of teacher-nominated students within a single classroom or a series of classrooms in a school. That is, those students who pass out of screening gate 2 should be fewer in number and have less problematic behavioral profiles, compared to national norms, if a schoolwide behavioral intervention is operating effectively. The case study described below is an example of the SSBD being used within an RtI-PBS context and nicely illustrates this type of SSBD application. Naquin and D’Atrio of the University of New Orleans describe how they integrated the SSBD screening system into a larger assessment battery that provides multiple information sources on the impact of their Pupil Assistance Model in addressing the needs and challenges of behaviorally at-risk students and their teachers.
Illustration of a Multi-Year, Case Study Application of the SSBD Within a Court-Mandated Initiative to Improve Services and Supports for EBD Students The material herein describes an actual application of the SSBD screening procedure within an RtI-PBS context for the purpose of responding to the mandates of a court-ordered child find process. Specifically, this court-ordered initiative was prompted by a continuing failure of
Implementing Universal Screening Systems Within an RtI-PBS Context 109 a Louisiana School District (Jefferson Parish Public Schools) to adequately screen, identify, place and serve students who are at risk for emotional and behavioral disorders (EBD) within general education settings. The SSBD fulfilled a number of purposes in this multi-year process including: (1) serving as a child find-screening process; (2) providing a template for developing staff training regimens for participating schools; and (3) evaluating outcomes. Details of this initiative follow. Description of Jefferson Parish Public Schools The Jefferson Parish Public School System (JPPSS) is a local education agency in the Greater New Orleans Region and forms the largest metropolitan area in Louisiana. According to the U.S. Census Bureau, as of July 1, 2007, the Greater New Orleans population was 704,010. At that time, the population in Jefferson Parish was reported to be 423,520 persons based upon approximately 98% of the population reported by the Census in 2000. In addition to being the largest metropolitan area in Louisiana, JPPSS ranks as the largest school district in the state. JPPSS consists of 88 schools located on the east and west banks of the Mississippi River in Jefferson Parish. Student enrollment during the 2007–2008 school year was 44,019 students enrolled in kindergarten through the 12th grade. JPPSS student enrollment currently is comprised of 33% Caucasian and 67% minority students with 61.9% of the students participating in the free or reduced lunch program. JPPSS is recognized as having the largest limited English-proficient student population in Louisiana with more than 2,500 students eligible for services. These students represent more than 68 countries with 52 spoken languages. There are 36 non-public schools located in Jefferson Parish that serve an additional 18,883 students in the community. Background of the CAP Initiative The Pupil Assistance Model (PAM) team at the University of New Orleans (Naquin & D’Atrio) began working in JPPSS elementary schools in 2000 providing staff development and consultation services. By 2003, the PAM team began to focus consultative services on the implementation of a Response to Intervention (RtI) model. At that time, services were provided in 10 identified “vanguard” schools and assistance focused on the identification of students needing intervention in the areas of reading and mathematics. JPPSS Corrective Action Plan—2005. Implementation of the current PAM-RtI/PBS model in JPPSS was facilitated by the issuance of a Corrective Action Plan (CAP) that resulted from monitoring of the district conducted by the Louisiana Department of Education during 2005. In the Mediated Settlement Agreement, the administrators of the CAP identified nine areas in need of remediation as described below. The first goal stipulated that teachers and administrators in JPPSS be urged to comply with all conditions of the CAP and that parish personnel be educated about provisions of each goal. Second, and central to the core findings of the Settlement Agreement, was that JPPSS “develop, devise, and implement an effective positive behavioral intervention and support program for all students.” The stated intent of implementing such a program would also indirectly increase the access that students with EBD would have to the general education setting. Thus, in response to the requirements of goal 2, JPPSS adopted a Positive Behavior Support model for the entire school district and the associated training initiatives recommended by the Louisiana Department of Education.
110 Hill M. Walker et al. Goal 3 pertained to restructuring of the special education pre-referral process. While Louisiana had established School Building Level Committee (SBLC) teams at every school (as mandated by law), their intended functions as problem-solving bodies were never fully executed. Historically, the SBLC system resulted in a “test and place” process that simply facilitated the placement of students into special education. At the time that the CAP was initiated, a very high percentage of referrals to the existing SBLCs resulted in identification and placement into a special education setting. Research conducted by Algozzine, Ysseldyke, and their colleagues has indicated that approximately 97% of all referrals to SBLCs have resulted in identification and placement into a special education setting (Algozzine, Ysseldyke, & Christenson, 1983; Ysseldyke, Vanderwood & Shriner, 1997). Additionally, and perhaps just as alarming, was the finding that JPPSS had over 2½ times as many students with EBD (12.8%) as the state average (4.5%) (Louisiana Department of Education, 2005). Goal 3 of the CAP also required that the existing SBLC process be redefined and reorganized into a true problem-solving model that used evidence-based interventions. Thus, the SBLC teams in JPPSS were renamed as the Academic and Behavior Intervention Teams (ABITs), with school-level participation being required of at least three regular education teachers, two special education experts (which could include members of the Pupil Appraisal Unit) and a school administrator. The CAP also called for implementation of a three-tiered Response to Intervention (RtI) model of service delivery that operated within the context of general rather than special education. The purpose of this change was to create an effective, cost-efficient and responsive process to manage and oversee the assessment and intervention of student needs on every level within each participating school site. The University of New Orleans PAM team has been most directly involved with JPPSS in addressing this goal. The fourth provision of the CAP as specified in goal 4 pertained to students in JPPSS with emotional or behavioral disorders (EBD). This goal required that alternative methods be developed to handle behavior and discipline concerns of students with EBD and that behavior management methods other than school suspensions and expulsions be used to manage student problem behavior. This goal also focused on how the provisions of student Individual Education Plans (IEPs) were developed and implemented. The five remaining goals pertained to providing services for students identified as having EBD. These goals were included to increase the quality of related services delivered by qualified service providers, to improve overall accountability measures of tracking services for students with EBD, and to enhance the knowledge base of school personnel and those who work directly with these students. Another CAP goal called for the provision of higher-quality and more programmatic transition services to students with EBD. Finally, the CAP obligated JPPSS to review the access that students with EBD had to the general education setting and provide assurances that these students received special education programming in the Least Restrictive Environment (LRE). The initial implementation template of the RtI model proposed by the CAP delayed referral to the school-based problem-solving team until the third tier of the three-tiered intervention process was reached. The PAM team revised this proposed rule to include the oversight of students needing intervention at all levels, not just the third or tertiary-level tier. The involvement of the ABIT problem-solving team in the PAM version of the RtI/PBS model was essential at all tiers of the intervention model so that appropriate interventions could be delivered via a seamless continuum of service delivery. Another key component of the PAM model was the emphasis it placed on the key role of the school-based, problem-solving team (ABIT) within each school. The ABIT is consolidated so
Implementing Universal Screening Systems Within an RtI-PBS Context 111 that communications across departments are enhanced and all students are considered in team decision-making processes. The problem-solving team (ABIT) at each school is comprised of members from the school’s administration, general education staff, pupil appraisal staff, and representatives from other compensatory programs such as Section 504, and special education. At the district level, a Consolidated Team consisted of representatives from essential and compensatory district programs including representatives from general education, special education, Positive Behavior Support, Section 504, Technology, Accountability, Safe and Drug Free Schools and consultants from the University of New Orleans. The purpose of creating a consolidated team on the district level and in each school was to foster development of a true seamless model of service delivery across departments, service areas, and educational entities with the entire school system, and eventually the community. JPPSS is at the time of this writing in the third year of implementing the PAM-RtI/PBS model in its 53 elementary schools and is expanding the model to middle and high schools for the 2008–2009 school year. The universal screening procedures utilized within the PAM model are described below. Using the Systematic Screening for Behavior Disorders (SSBD) to Identify EBD Students 2006–2007 SSBD Screenings. During the 2006–2007 school year, the SSBD was used to screen general education students respectively in grades 1–5 in all 53 elementary schools within JPPSS. Of the students included in the screenings, 49.3% were African American, 33.7% were Caucasian, and 17.0% were distributed across an Other category. For the first year of screening using the SSBD in JPPSS, the PAM team conducted all screenings in the 53 elementary schools. This team was comprised of Master’s and Doctoral-level staff with a primary background or certification as either an Educational Diagnostician or School Psychologist. All screening staff had at least 30 hours of graduate coursework in assessment and diagnostic methods. In January of 2007, training was conducted with the 53 elementary school Academic and Behavior Intervention Teams (ABITs) regarding the utilization and philosophy behind using the SSBD, the administration of the SSBD, and the scoring and interpretation of data. During the second semester of the 2006–2007 year, SSBD screenings were conducted at each school in either a faculty meeting (typically one to 1½ hours) or in grade-level meetings (i.e., during teacher planning periods). To assist the school system, all gate 1 and gate 2 protocols were collected by UNO personnel. SSBD gate 2 protocols were scored and data were entered into a Microsoft Excel spreadsheet for each school. The Excel spreadsheet for each school included a summary page of all SSBD data for the school, and summaries of at-risk students according to name, teacher, grade and Critical Events Index score. Finally, each spreadsheet included a grade-by-grade roster of all students who were either nominated or considered to be behaviorally “at-risk.” Spreadsheets were disseminated to schools by members of the UNO PAM team and results were discussed with school administrators and members of the ABIT. Of the 22,101 students screened in spring, 2007, a total of 3,488 students were nominated by their teachers (approximately 15.8% of all students screened) for further screening using gate 2 SSBD measures. Across the 53 schools, the percentage of students nominated ranged from 3.7% to 34.3%. Of those students nominated, 1,533 students were determined to be at-risk according to the SSBD criteria and cutoff scores. The percentage of at-risk students ranged from 1.3% to 14.6% of the students screened, which was 6.9% of the total student population. Of the 1,533 identified at-risk students, 71.7% were male and 28.3% were female; 66.6% of the
112 Hill M. Walker et al. at-risk students were Externalizers and 33.4% were Internalizers. These statistics are consistent with findings reported by Walker and Severson (1990) for the SSBD standardization data (Walker & Severson, 1990). 2007–2008 SSBD Screenings. In the fall of 2007, JPPSS Pupil Appraisal staff members, comprised of Educational Diagnosticians, School Psychologists, and Social Workers, were trained in the SSBD’s administration, scoring and data interpretation procedures. For the second year of behavioral screening, Pupil Appraisal staff assisted the UNO PAM team in the administration of the SSBD in the 53 participating elementary schools. To enhance the likelihood that administration procedures would be similar across the school district, each member of the Pupil Appraisal team was given a Coach Card (developed by UNO) that outlined the step-bystep administration of the SSBD. During the 2007–2008 school year, SSBD screenings began in mid-October and data for most schools were collected by the end of November. UNO personnel collected gate 1 and gate 2 protocols and data were entered into spreadsheets as they were during the 2006–2007 school year. Spreadsheets for the SSBD data collected during the second year of screening were expanded and refined. Specifically, more descriptive and demographic data were provided on the school summary sheet and two additional pages were added to each file. UNO staff developed an SSBD Item Analysis process that provided a frequency count for each item on the Critical Events Index (CEI) of the SSBD according to gender and grade. Each time one of the 33 CEI items was checked by a teacher it was tallied on the Item Analysis sheet. Each tally was placed into a box that specified the grade of the student and whether the behavior was produced by a male or female student and whether he or she was an Externalizer or Internalizer. This process was followed for all protocols received from each school, regardless of whether the student was simply nominated or at-risk. A similar format was used to analyze scores on the Adaptive and Maladaptive Behavior Scales. The Adaptive Behavior Scale of the SSBD assesses the frequency of behaviors that are considered to be socially desirable and appropriate to the classroom. Each of the 12 items on this scale is assigned a score ranging from 1 to 5, depending on frequency of occurrence. A score of 1 indicates that the student “Never” exhibits the behavior in question and a rating of 5 indicates that the student “Frequently” exhibits the behavior. Students can receive a maximum score of 60 on the Adaptive Behavior Scale, with higher scores indicating that students frequently exhibit socially desirable or appropriate forms of expected classroom behavior. For the Item Analysis procedure, a tally was kept for an item on the Adaptive Behavior Scale that received either a score of 1 or 2, indicating that a student never or seldom exhibited that desired behavior. Tallies were entered into boxes that specified student grade, gender and whether the student was identified as an Externalizer or Internalizer. On the Maladaptive Behavior Scale, students were rated on 11 items according to the frequency with which they exhibited undesirable behaviors. Student ratings range from 1 to 5, with a score of 1 representing “Never,” and 5 representing “Frequently.” Students can receive a maximum score of 55 on the Maladaptive scale, with higher scores indicating that students frequently exhibit inappropriate or socially undesirable behaviors. For the Item Analysis, a tally was developed for an item on the Maladaptive Behavior Scale if a student was assigned a score of 3 or higher. Each tally was entered into boxes that again specified student grade, gender and whether he or she was identified as an Externalizer or Internalizer. As noted, the Item Analysis procedure was developed by the UNO PAM team to assist with the specification of areas of concern identified within each school. Positive Behavior Support teams were able to utilize data from the Item Analysis to more accurately develop school-wide training plans for each participating school. Information from the Item Analyses for the
Implementing Universal Screening Systems Within an RtI-PBS Context 113 Adaptive and Maladaptive Behavior scales was also used to guide social skills training in areas needing more intensive attention. By using the Item Analysis, administrators and members of the ABIT and PBS teams were able to obtain information (per teacher report) about specific behaviors and/or areas in their respective schools as well as subgroups of students needing more focused intervention. The Item Analysis for the CEI provided information about the behaviors most frequently reported by teachers to be seriously problematic (e.g., “Ignores teacher warnings”). Further examination of the Item Analysis also provided information about whether intervention should be directed toward a specific grade (e.g., fourth grade), gender, or at-risk subgroup (e.g., Externalizer or Internalizer). An additional component pertaining to administration of the SSBD in 2007–2008 was the manner in which information from three items on the Critical Events Index was handled. Discussion between UNO personnel and JPPSS administrators led to a determination that items #18, #22 and #24 required mandatory reporting by the school administration and UNO personnel if checked off by a teacher. These items refer to the presence or evidence of a student having suicidal (or death-related) thoughts and the suspicion of a student having been either physically or sexually abused. The district decided that if a protocol was found to have a check by any of the three items, a report was to be made immediately to the school principal. During the 2007–2008 school year, the SSBD was used to screen 16,634 JPPSS students in grades 1–5. Five sixth-grade classes were also included. Of the total number of students screened, 3,521 (approximately 21% of the screened population) were nominated for gate 2 assessments by general education teachers. Of those students nominated, 1,299 were determined to be behaviorally at-risk based on their SSBD gate 2 profiles. Across the 53 schools, the percentage of students nominated ranged from 5.1% to 33.8% and the percentage of students judged to be at-risk in each school ranged from 2.0% to 21.7%. Overall, 7.8% of all students screened were at-risk as compared to 6.9% of all students in the previous school year. The percentages of males and females identified as at-risk were identical to the percentages identified during the first year of screening (i.e., 71.7% males, 28.3% females). The distribution of Externalizers and Internalizers was also quite similar (i.e., 66.6% Externalizers, 33.4% Internalizers). Operating Details of the Pupil Assistance Model (PAM) at Tiers I, II, and III The PAM applies a comprehensive Response to Intervention (RtI) and Positive Behavior Support (PBS) framework with the goal of incorporating research-based assessment tools and evidence-based interventions into a systematic approach that yields positive results for students. PAM is a multi-tiered academic and behavior-focused model in which both assessment and intervention processes increase in intensity and measurement precision at each successive tier. The Pupil Assistance Model includes the following components: • • •
Tier I: General Education—Universal screening, school and/or class-wide interventions Tier II: Standard Protocol—Small group and targeted interventions Tier III: Problem-Solving—Individual and more intensive services
The PAM model is based on the best practices of providing high-quality instruction and interventions carefully matched to student need, monitoring progress frequently to make needed changes in instruction, and applying student response data in making important educational decisions. PAM promotes the use of Curriculum-Based Measurement (CBM) for academic universal screening and frequent progress monitoring. The behavioral component of the
114 Hill M. Walker et al. model incorporates the use of Office Discipline Referral (ODR) data and the Systematic Screening for Behavior Disorders procedure as measures to align student needs with effective behavioral interventions. The integrated PAM model has produced improved academic and behavioral outcomes for JPPSS students. PAM also encourages evaluating school climate by using a measure such as the Safe School Assessment and Resource Bank (SSARB) as an initial assessment when developing a culture of positive behavioral support. Below is a brief description of the PAM process at Tiers I, II, and III. Central to high-fidelity implementation of the PAM model is the establishment of a school-based problem-solving team that functions to oversee and guide assessment and interventions on each level of the tiered model. Tier I: General Education—Universal Screening, School and/or Class-Wide Interventions. In Tier I, all students are screened in reading, math and behavior to determine who has satisfactory competence levels in specific academic areas and demonstrates expected levels of appropriate behavior. This information provides teachers and administrators with the necessary information to select curricula, design instruction, and implement behavior strategies to prevent school failure. After screening in reading and math, assessments are scored, graphed, and the data are analyzed by grade, class and student. If at least 50% of the students in a classroom are not performing at an appropriate level as determined by normative comparisons, then the possibility of inappropriate instruction, ineffective classroom management, or a potential curriculum change is considered. If at least 50% of the students have performed at a level consistent with grade-level norms and expectation, yet some students are still performing within the “at-risk” range, those students are further assessed to determine if poor motivation or a lack of skills or both are factors in their performance problems. If either or both are determined to be contributing factors, these students are referred on to Tier II. In the behavioral area, screening is accomplished by examining Office Discipline Referral (ODR) data and administering the Systematic Screening for Behavior Disorders (SSBD). Office Discipline Referral data are analyzed to identify areas of concern that may impact the entire school, or large numbers of students, such as the time of day of behavioral incidents, location, and type of offense and so forth. If 20% of the student population is “at risk” for a particular offense, or 20% of the students repeatedly get in trouble in a particular setting or time of day, the School-Wide Positive Behavior Support Plan is revised to address these concerns. Next, the SSBD is administered to all students (with the exception of those already identified as receiving special education) during the fall semester. Any target student meeting gate 2 SSBD exit criteria is then considered for referral to Tier II or possibly Tier III interventions and/or assessments. PAM encourages the use of item analyses on the gate 2 rating scales to determine whether school-wide, grade-level or individual classes need a specific intervention focus. Tier II: Standard Protocol—Small Group and Targeted Interventions. Tier II is designed for small groups and individual students who may need more targeted and intensive intervention. Systematic interventions with standard Coach Cards are generally used at this level. Interventions may include differentiated instruction, a different type of program, or targeted behavior strategies such as Check-In/Check-Out (CICO). Additionally, peer tutoring, peer mentoring, psycho-educational groups and/or a parent training component aspect may be added as intervention support in Tier II. For academic interventions, aim lines are set using Curriculum-Based Measurement (CBM) procedures. Data are collected daily and examined after every five to seven data points by calculating the level and rate of student progress. Decisions are made based on the students’
Implementing Universal Screening Systems Within an RtI-PBS Context 115 success or failure to respond to appropriate interventions that have been implemented with solid treatment fidelity. These decisions may include continuing the intervention, modifying the intervention and/or strategy; moving back to Tier I or intensifying the intervention at a Tier III level. Behavior interventions follow similar procedures. Goals are set, behavior is monitored carefully using teacher ratings, observations, work completion, attendance, and/or Office Discipline Referral data. Aggregated data are also examined at least every five to seven data points to determine the students’ success or failure in responding to interventions that have been implemented with treatment fidelity. The decision options are to continue the intervention, change the intervention and/or strategy, return to Tier I or move the student on to Tier III. Tier III: Problem-Solving—Individual and More Intensive Services. An individualized problem-solving approach is generally used at Tier III for the persistent and atypical problems which are not resolved by the more standard and manualized interventions at Tier II. Generally, these procedures are applied with individual students. The design of Tier III interventions is guided by systematic assessment and review of the problem; hypothesis development is intended to target specific academic and/or behavior skill deficits. Examples of academic interventions may include instructing students on a lower grade level or teaching a prerequisite skill set. Typically, students assigned to Tier III due to behavioral issues will have a functional behavior assessment (FBA) completed to assist in the problem-solving process. The FBA helps identify significant, pupil-specific, social, affective, cognitive and/or environmental factors associated with the occurrence and non-occurrence of specific behaviors. On the Tier III level, data are collected daily and examined every five to seven data points to determine the students’ success or failure to respond to the intervention. The resulting decisions may be to continue the intervention, change the intervention and/or strategy, or in rare cases to move a student back to Tier I or Tier II. Students who are not successful at this level may eventually be referred for special education services and may involve tertiary resources such as child mental health and/or other social service agencies. The Pupil Assistance Model application of RtI and PBS, as described herein, can be conceptualized as a continuum of programs and services for students having moderate to severe academic and behavior difficulties. PAM is an RtI/PBS multi-tiered service delivery system critical to meeting NCLB and IDEA regulations. The continuous monitoring of the adequacy of student responses to well-implemented, universal curriculum and positive behavior support procedures is particularly relevant to the PAM approach as a means of determining whether existing instruction and support are sufficient. The overarching goals of the PAM are: (1) to ensure that quality instruction, good teaching practices, differentiated instruction, remedial opportunities and evidence-based, behavior strategies are available and accessible within general education; and (2) that special education is provided for students with disabilities who require more specialized services than can be provided in a general education context. PAM appears to be a promising model for jointly addressing academic and behavior problem domains within an integrated framework. Future research on its outcomes with at-risk student populations, and their sustainability, will help establish the parameters of its efficacy.
Directions for Future Research, Practice and Policy The origins of antisocial behavior patterns appear to be in evidence at an increasingly early age and it is known that these behaviors can be prevented from escalating into more serious and
116 Hill M. Walker et al. intractable problems (Strain & Timm, 2001). Effective practices for this student population in schools should include universal screening procedures to provide early detection, schoolbased interventions, training in parenting skills, and teacher in-service training, all of which have been empirically demonstrated to increase prosocial behavior and reduce aggressive behavior problems (Reid, 1993; Walker, Ramsey, & Gresham, 2004). Prevention begins with early detection and as RtI-PBS approaches continue to be adopted by schools, it is imperative that a standard universal screening component be adopted as a continuing part of their routine procedures. The movement toward using an RtI-PBS approach, as illustrated by the PAM model described above, can address both academic and behavior concerns but it needs to begin with increased awareness of the scope and extent of the problem. Teachers, administrators, policymakers, legislators, staff development specialists, and researchers alike need to become aware of the integral relationships that exist between academic and behavioral performance. Continuing to address them as independent issues can lead to stunted progress for many students and continued frustration for teachers (Dodge, 2008). Along with increased awareness, there needs to be a more robust knowledge base developed to support the potential of the RtIPBS heuristic to positively influence student performance across these domains and using a school-based, team approach (Albers, Glover, & Kratochwill, 2007; Elliott, Huai, & Roach, 2007). This team should include, at a minimum, general and special education teachers, school psychologists, behavior specialists, reading specialists, and administrators. In order for RtI to effectively address behavioral and academic domains, currently available technology needs to be improved and expanded. Specifically, a system for integrating academic and behavior data needs to be developed so that it can be aggregated and accessed for rapid, high-quality decision-making. In this regard, the authors of the SSBD procedure are currently in the process of developing a web-based, electronic version of the instrument that will allow for administration, scoring and profiling of student outcomes. Existing software such as Discipline Tracker or SWIS may be able to be modified to integrate academic data. It will also be important to develop behavioral measures that can be given repeatedly and remain sensitive to change over time similar to the DIBELS measures for reading performance (see Gresham, in press). To do so will require the identification of meaningful behavioral benchmarks and normative criteria for grade levels by gender and developmental stages. We believe the risk factors that result in children coming to school suffering from palpable, environmentally induced damage can be effectively addressed by a coordinated continuum of effective early interventions, including the PAM approach illustrated herein, that address the needs of severely at-risk children from the beginning of their school careers. Compelling longitudinal research by Hawkins et al. (1999) shows that comprehensive early intervention, delivered in the first three grades of school and that involves parents, teachers, peers, and the target child, provides long-term protection against a number of health-risk behaviors at age 18. These risks include delinquent acts, school failure and dropout, teenage pregnancy, heavy drinking, school behavior problems, and having multiple sex partners. We cannot afford to ignore the enormous policy implications of these and similar robust findings. We currently have the knowledge and available expertise to implement these prevention initiatives with good integrity using an RtI-PBS framework. For example, Walker, Seeley, Small, Severson, Graham, Feil, Serna, Golly, and Forness (2009) recently reported results of a four-year, randomized controlled trial that illustrates the combined use of the SSBD screening system with the First Step to Success early intervention program which addresses secondary prevention goals in school and home contexts (Walker, Kavanagh, Stiller, Golly, Severson, & Feil, 1998). Prevention initiatives of this type for at-risk students, mounted early in their
Implementing Universal Screening Systems Within an RtI-PBS Context 117 school careers, appear to be increasingly in evidence within the educational and psychological literatures. However, as yet, we have not demonstrated the will, on a broad-based scale, to (a) assume ownership of the problems that these prevention efforts are designed to address; (b) invest the resources necessary to support their high quality implementation; and (c) provide the long-term supports that will ensure their maintenance and durability. We are hopeful that the next decade will see positive changes in the policies of schools, mental health systems, social services agencies, and legislative bodies that will allow these important goals to be realized.
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Implementing Universal Screening Systems Within an RtI-PBS Context 119 Loeber, R., & Farrington, D. P. (Eds.). (1998). Serious and violent juvenile offenders: Risk factors and successful interventions. Thousand Oaks, CA: Sage Publications. Louisiana Department of Education (2005). State special education data profile—2005. Baton Rouge, LA. Louisiana Department of Education (2008). District composite report—Jefferson Parish. Baton Rouge, LA. May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., & Sugai, G. (2001). School-wide information system. Eugene, OR: University of Oregon, Educational and Community Supports Merrell, K. W. (1999). Behavioral, social, and emotional assessment of children & adolescents. Mahwah, NJ: Lawrence Erlbaum Associates. Merrell, K. W. (2001). Assessment of children’s social skills: Recent developments, best practices, and new directions. Exceptionality, 9(1 & 2), 3–18. NASP Position Statement on Early Childhood Care and Education (2002). http://www.naspoline.org/ about_nasp/pospater_earlychild.aspx. Bethesda, MD: National Association of School Psychologists. Patterson, G. R., Reid, J. B., & Dishion, T. J. (1992). Antisocial boys. Eugene, OR: Castalia. Reid, J. B. (1993). Prevention of conduct disorder before and after school entry: Relating interventions to developmental findings. Development & Psychopathology, 5, 311–319. Ross, A. (1980). Psychological disorders of children: A behavioral approach to theory, research and therapy (2nd ed.). New York: McGraw-Hill. Severson, H., Walker, H. M., Hope-Doolittle, J., Kratochwill, T., & Gresham, F. M. (2007). Proactive, early screening to detect behaviorally at-risk students: Issues, approaches, emerging innovations, and professional practices. Journal of School Psychology, 45(2), 193–224. Shinn, M. (2007). Identifying students at risk, monitoring performance, and determining eligibility within response to intervention: Research on educational need and benefit from academic intervention. School Psychology Review, 36(4), 601–617. Sprague, J. & Walker, H. M. (in press). Building safe and healthy schools to promote school success: Critical issues, current challenges, and promising practices. In M. Shinn & H. Walker (Eds.), Interventions for achievement and behavior problems in a three-tier model including Response to Intervention. Bethesda, MD: National Association of School Psychologists. Strain, P. S., & Timm, M. A. (2001). Remediation and prevention of aggression: An evaluation of the Regional Intervention Program over a quarter century. Behavioral Disorders, 26(4), 297–313. Sugai, G. & Horner, R. (2002). The evolution of discipline practices: School-wide positive behavior supports. Child and Family Therapy, 24(1/2), 23–50. Sugai, G., Sprague, J., Horner, R., & Walker, H. (2000). Preventing school violence: The use of office discipline referrals to assess and monitor school-wide discipline interventions. Journal of Emotional and Behavioral Disorders, 8, 94–101. Tobin, T. & Sugai, G. (1999). Using sixth-grade school records to predict violence, chronic discipline problems, and high school outcomes. Journal of Emotional and Behavioral Disorders, 7, 40–53. Todis, B., Severson, H., & Walker, H. M. (1990). The critical events scale: Behavioral profiles of students with externalizing and internalizing behavior disorders. Behavioral Disorders, 15(2), 75–86. Walker, B., Cheney, D., Stage, S., Blum, C., & Horner, R. (2005). School-wide screening and positive behavior supports: Identifying and supporting students at risk for school failure. Journal of Emotional and Behavioral Disorders, 7, 194–204. Walker, H. M., Block-Pedego, A., Todis, B., & Severson, H. (1991). School archival records search (SARS): User’s guide and technical manual. Longmont, CO: Sopris West. Walker, H. M., Colvin, G., & Ramsey, E. (1995). Antisocial behavior in schools: Strategies and best practices. Pacific Grove, CA: Brooks/Cole. Walker, H. M., Horner, R. H., Sugai, G., Bullis, M., Sprague, J. R., Bricker, D., & Kaufman, M. J. (1996). Integrated approaches to preventing antisocial behavior patterns among school-age children and youth. Journal of Emotional and Behavioral Disorders, 4, 194–209. Walker, H. M., Kavanagh, K., Stiller, B., Golly, A., Severson, S., & Feil, E. (1998). First step to success: An early intervention approach for preventing school antisocial behavior. Journal of Emotional and Behavioral Disorders, 6(2), 66–80.
120 Hill M. Walker et al. Walker, H. M., Nishioka, V. M., Zeller, R., Severson, H. H., & Feil, E. G. (2000). Causal factors and potential solutions for the persistent under-identification of students having emotional or behavioral disorders in the context of schooling. Assessment for Effective Intervention, 26(1), 29–40. Walker, H. M., Ramsey, E., & Gresham, F. M. (2004). Antisocial behavior in school: Evidence-based practices (2nd ed.). Belmont, CA: Wadsworth/Thomson Learning. Walker, H. M., Seeley, J., Small, J., Severson, H., Graham, B., Feil, E., Serna, L., Golly, A., & Forness, S. R. (2009). A randomized controlled trial of the First Step to Success early intervention: Demonstration of program efficacy outcomes in a diverse, urban school district. Journal of Emotional and Behavioral Disorders, 17(4), 197–212. Walker, H. M., & Severson, H. H. (1990). Systematic Screening for Behavior Disorders (SSBD): User’s guide and technical manual. Longmont, CO: Sopris West. Walker, H. M., Severson, H., Nicholson, F., Kehle, T., Jenson, W., & Clark, E. (1994). Replication of the Systematic Screening for Behavior Disorders (SSBD) procedure for the identification of at-risk children. Journal of Emotional and Behavioral Disroders, 2(2), 66–77. Walker, H. M., Severson, H., & Seeley, J. (in press). Universal, school-based screening for the early detection of behavioral problems contributing to later destructive outcomes. In M. Shinn & H. Walker (Eds.), Interventions for achievement and behavior problems in a three-tier model including Response to Intervention. Bethesda, MD: National Association of School Psychologists. Walker, H. M., Severson, H., Stiller, B., Williams, G., Haring, N., Shinn, M., & Todis, B. (1988). Systematic screening of pupils in the elementary age range at risk for behavior disorders: Development and trial testing of a multiple gating model. Remedial and Special Education, 9(3), 8–14. Walker, H. M., Severson, H. H., Todis, B. J., Block-Pedego, A. E., Williams, G. J., Haring, N. G., & Barckley, M. (1990). Systematic screening for behavior disorders (SSBD): Further validation, replication and normative data. Remedial and Special Education, 11(2), 32–46. Walker, H. M., Stieber, S., Ramsey, E., & O’Neill, R. (1993). Fifth grade school adjustment and later arrest rate: A longitudinal study of middle school antisocial boys. Journal of Child and Family Studies, 2(4), 295–315. Weissberg, R. (2005, August). Social and emotional learning for life success. Paper presented at the annual meeting of the American Psychological Association, Washington, DC. Ysseldyke, J., Vanderwood, M., & Shriner, J. (1997). Changes over the past decade in special education referral to placement probability: An incredibly reliable practice. Diagnostique, 23(1), 193–201. Zigler, E., Taussig, C., & Black, K. (1992). Early childhood intervention: A promising preventative for juvenile delinquency. American Psychologist, 47, 997–1006.
6
Building Conditions for Learning and Healthy Adolescent Development A Strategic Approach David Osher and Kimberly Kendziora American Institutes for Research
Schools can play a key role in promotion, prevention, and adolescent development. In schools, students confront major developmental challenges, are judged by important natural raters, interact with prosocial and antisocial peers, and acquire (or fail to acquire) important capacities and credentials that may enable them persevere or thrive. From the perspective of risk and protection, schools may function as a protective factor, creating a safe harbor and sense of safety, offering challenges and a sense of mission, fostering positive relationships with adults and prosocial peers, developing competencies and a sense of efficacy, and providing students with access to social capital, mental health supports and youth-development opportunities. Unfortunately, schools—particularly many serving students of color—may also be stressful places that function as a risk factor, as youth adapt their behaviors to relatively inflexible bureaucratic structures and adult-driven demands within a high-stakes environment (e.g., Eccles & Midgely, 1989). Instead of safe harbors, schools can be treacherous whirlpools, exposing students to physical and emotional violence, boredom, alienation, and academic frustration, negative relationships with adults and peers, teasing, bullying, gangs, public humiliation and failure, segregation with antisocial peers, harsh punishment, and expulsion from the school community and its resources. In this chapter, we outline the role of schools in student development, describe an intervention that has been implemented successfully, describe the intervention’s development, and discuss the implications of the intervention, including research findings that emphasize the importance of improving the social and emotional conditions for learning to prevention initiatives.
Conditions for Learning in Schools Schools can be “lifelines . . . opportunities which potentially lead from pathways associated with deviant or destructive outcomes” (Cairns & Cairns, 1994, p. 6). For schools to play this role they need to protect and hold on to all their students and to help them develop the academic, social, and emotional competencies that they will need to succeed as adults. Longitudinal analyses from the Woodlawn study of 1,000 African American children found that early school performance and school (as well as family) attachment were related to adolescent substance use, delinquency, and school dropout (Ensminger, Kellam, & Rubin, 1983; Ensminger & Slusarcick, 1992) and that strong school (as well as family) bonds were protective for African American children who grew up in poverty in Chicago (Ensminger & Juon, 1998) Successful schools create and maintain what we refer to as effective conditions for learning. Such conditions typically include high-quality pedagogy, well-trained teachers, adequate resources, and effective leadership. Another equally, if not more, important set of conditions
122 David Osher and Kimberly Kendziora is called the social and emotional conditions for learning. Students who feel “connected” to school across these social/emotional indicators are more likely to have improved attitudes towards school, learning, and teachers; heightened academic aspirations, motivation, and achievement; and more positive social attitudes, values, and behavior (Allensworth & Easton, 2007; McNeeley, Nonnemaker, & Blum, 2002; Resnick et al., 1997). Recent research emphasizes the view that learning is optimized only after students’ social, emotional, and physical needs have been successfully met (CASEL, 2003; Learning First Alliance, 2001; Osher, Dwyer, & Jackson, 2004). The social and emotional conditions for learning include a number of factors that are essential for ensuring that students feel safe and supported in school. Specifically, four components define the social and emotional conditions for learning: (a) school safety, (b) challenge, (c) student support, and (d) social and emotional learning. Research and practical experience demonstrate that a high level of school safety and student discipline, that comes as a result of challenging curriculum and instruction and effective supports, reduces administrative burdens and allows teachers to spend more time on the task of raising academic performance (Osher, Dwyer, & Jackson, 2004). School safety refers to an overall school climate in which students feel physically and emotionally safe. There is little to no violence, fighting, bullying, crime, substance abuse, or gang presence. Overall, there is a climate of mutual respect and trust among all members of the school community, and students feel comfortable in taking personal and academic risks. Failure to support academic achievement is related to students’ disengagement from school and increased risk-taking behavior (Blum, Beuhring, & Rinehard, 2000). A safe and supportive learning environment fulfills students’ basic psychological needs for belonging, autonomy, influence, competence, and physical security. As these needs are met, students tend to become increasingly committed to the school community’s norms, rules, and values (Learning First Alliance, 2001). Research also shows that the physical environment can have a profound effect on the ability of students to learn efficiently (National School Boards Association, 1996). An analysis in schools of such areas as bathrooms, cafeterias, hallways, and isolated areas can determine if safety “hot spots” exist. With this information, a school improvement team can change the environment to minimize opportunities for inappropriate behavior (Osher, Dwyer, & Jimerson, 2006). In addition, providing teachers and other staff with opportunities to influence decisions on school safety policy (as well as other student connection indicators) can help to create a more cohesive, well functioning professional community (Smylie, 1994). Finally, students who participate in structured extracurricular activities are less likely to engage in negative and risky behaviors and have better attendance, lower dropout rates, lower rates of drug use, higher academic achievement, and higher aspirations than non-participants (Brown & Theobald, 1998; Mahoney, 2000). A second key component to the social and emotional conditions of learning is challenge. Schools may be safe and orderly, but if they fail to build a supportive, engaging community and press for high academic expectations, students learn little (Learning First Alliance, 2001; Lee & Smith, 1999). Teachers should challenge students in terms of the level of effort they put forth, as well as the academic and behavioral standards to which they are expected to achieve. Ideally, teachers and other school staff provide rigorous academic support to all students, and work to ensure that the curriculum has direct relevance to students’ life goals. In addition, all students should have access to high-level, demanding courses, as well as service learning opportunities, extra-curricular activities, and internships that allow them to explore their post-secondary options. Research has shown that when students feel that teachers and other
Building Conditions for Learning and Healthy Adolescent Development 123 adults challenge them, they are likely to do better in school (Catalano, Berglund, Ryan, Lonczak, & Hawkins, 2004). Examinations of the NELS: 88 survey, which collected data from students in high school, established that students were more likely to perform well on tests when they believed that their teachers cared about them and that this relationship was stronger for students who were judged to be at risk for dropping out of high school (Muller, 2001; Ryan & Patrick, 2001). In the classroom, cooperative learning strategies (e.g., group discussions, presentations, projects) have been shown to promote students’ development of social learning, sense of the classroom as a community, and academic achievement (Johnson & Johnson, 1989; Slavin, 1990). Finally, students who perceived their teachers as warm, caring and supportive had higher classroom participation rates which in turn positively affected their academic achievement (Voelkl, 1995). In addition to appropriately challenging students, an overall sense of student support is a critical condition for learning. When coupled with a consistent emphasis on academic performance, a strong sense of support and school community boosts academic achievement (Lee, Smith, Perry, & Smylie, 1999). There is also evidence that these effects may be most pronounced for students who are considered to be at-risk (Shouse, 1996). Establishing effective student supports involves ensuring that children’s basic needs are met and that the significant adults in their lives work collaboratively to encourage, support, and nurture them. Students work with and receive support from teachers who are able to establish a connection with them, personalize their experience, and engage them in the learning process. For example, examinations of national data have shown that positive student beliefs about how much their teachers support their efforts to succeed in school can reduce the probability of their dropping out by half (Croninger & Lee, 2001). A study of 167 sixth-grade students found that student support was associated with increased grade-point averages, through its effects on students’ interest in class, interest in school, and social responsibility (Wentzel, 1998). Goodenow (1993) found teacher support to be predictive of students’ expectancy of success, which in turn predicted their class effort and resulting grades. Other studies of interventions designed to build relationships between adults and students in school have also shown a positive impact of these programs on school-related attitudes and motives (Battistich, 2001; Sinclair, Christenson, & Thurlow, 2005). Finally, schools that provide sufficient conditions for learning ensure that students learn and exhibit the social and emotional learning they need to succeed. Social and emotional learning is the process of developing the ability to recognize and manage emotions, develop caring and concern for others, make responsible decisions, establish positive relationships, and handle challenging situations effectively. Related skills that can be developed and reinforced in schools include relationship-building, anger management, and responsible decision-making (CASEL, 2003; U.S. Department of Education, 2000). Students with strong social and emotional learning are able to maintain healthy interpersonal relationships with peers and adults, and have access to a multitude of coping strategies to manage stress and difficult situations. Moreover, social and emotional learning is strongly tied to learning and performance at school. Evidence from social and emotional learning programs suggests that social and emotional learning increase students’ capacity to cope with emotional experiences that interfere with learning, to work effectively with other students in the classroom, to face barriers to academic achievement, and to set and strive towards academic goals. Several studies have found that early evidence of prosocial behaviors (e.g., effective problem-solving, effective decision-making, and effective interpersonal relationships) predicts better academic outcomes later on. For example, one study found that good behavioral conduct during late childhood (ages eight to 12) had a direct positive impact on academic success during late
124 David Osher and Kimberly Kendziora adolescence (ages 17–23) (Masten et al., 1995). Another recent study found that higher levels of social and emotional learning in seventh grade significantly predicted higher academic achievement in 10th grade (Fleming et al., 2005). This research strongly suggests that social and emotional learning has an enduring impact on outcomes related to school achievement. Schools can promote social and emotional learning through regular practice and modeling among adults and students in the school, and by placing a high value on conflict resolution, communication, caring, appreciation for diversity, problem-solving, and teamwork. Research on social and emotional programming suggests that maximizing students’ opportunities for participation and choice is essential for fostering student decision-making abilities, selfefficacy, self-expression, personal responsibility and accountability (Greenberg et al., 2003; Zins, Weissberg, Wang, & Walberg, 2004). School interventions that have focused on creating a caring learning environment and providing students with the skills and supports to manage school transitions have proven effective in increasing attendance, GPA and stability of self-concept, and decreasing dropout, emotional and behavioral problems (Felner & Adan, 1988; Reyes & Jason, 1991). Mentoring programs provide the relational context for promoting social and academic competence, and in research have resulted in improvements in school attendance, parental relations, academic performance and peer emotional support, as well as decreases in conduct problems in youth (Catalano et al., 2004). Diverse instructional and classroom management practices, including cooperative group learning, service learning strategies and positive behavioral supports, can have a significant impact on improving student relations, academic gains, prosocial attitudes and behavior, cognitive problem-solving abilities, empathy, sense of civic responsibility and sense of contributing to the community (Billig, 2000; Elias, Zins, Graczyk, & Weissberg, 2003; Johnson, Johnson, & Maruyama, 1983). In addition, social and emotional learning can significantly improve learning in the classroom when they are integrated into different subject matter (CASEL). Involving parents and community members in teaching and reinforcing the development of social and emotional learning appears to be a cornerstone of many effective youth development programs (Zins et al., 2004). Specifically, research suggests that when parents are involved in implementing social and emotional interventions, students benefit more and the effects of participation are more lasting and pervasive (Elias et al., 2003). Building a comprehensive plan for improving student connection across the critical components of safety, challenge, student support, and social and emotional learning takes time and requires input, planning, and commitment from students, teachers, administrators, school counselors, psychologists, parents, and relevant community agencies (CASEL, 2003). There are barriers to addressing the social and emotional conditions for learning in schools, including inadequate resources; lack of information about the importance of social emotional development and how to address it; as well as the enormous pressure on staff, principals, superintendents, and school board members to produce short-term gains on high-stakes tests. We believe the maxim that what gets assessed gets addressed, and unless social and emotional conditions for learning are assessed and acted upon, it is unlikely that schools will become a protective factor for all students. A fully functioning process for addressing these factors includes three parts: (a) an efficient assessment process; (b) transformation of data into actionable information, which connects to key school metrics; and (c) tools to respond to that information in a deliberate manner.
Building Conditions for Learning and Healthy Adolescent Development 125
The Intervention: Surveying the Social and Emotional Conditions for Learning for Performance Management and Continuous Improvement The intervention has five objectives: (a) changing discourse within districts, as school and district staff discuss the conditions for learning; (b) orienting the behavior of principals, school staff, and district personnel to addressing the social and emotional conditions for learning in a strategic manner; (c) monitoring how subgroups of students and schools are doing; (d) providing data for continuous improvement; and (e) creating conditions where schools, districts, and states can learn about the importance of addressing the social and emotional conditions for learning. The intervention has three components. The first is a psychometrically robust survey of the social and emotional conditions for learning, which can be incorporated into school, district, or state score cards. This contains four scales and takes 15–25 minutes to complete. The toolkit, which is linked to the individual school reports, is designed to help school teams use the survey information by presenting the school’s survey results; housing a database of evidence-based programs and strategies for addressing student connection issues; providing advice for how to look at data, implement programs, and take the next steps; and providing a forum for offering comments or quotes about personal experiences with a program or strategy. The programs and strategies identified include universal, selective/targeted, and indicated/intensive programs, which have been demonstrated to work with similar groups of students in similar contexts.
Developing the Intervention An increasing body of research provides the basis for conceptualizing the social and emotional conditions for learning (Osher et al., 2008). In 2003, AIR joined with the Collaborative for
Figure 6.1 “Student Connection Survey” (aka Conditions for Learning Survey) Score Report to Schools.
126 David Osher and Kimberly Kendziora Academic, Social, and Emotional Learning (CASEL) and the Learning First Alliance (LFA) to develop a strategy for overcoming the barriers to creating safe and supportive schools. This led to an invitational conference sponsored by the Fetzer Institute in 2004, which brought together nationally recognized experts in youth development, cognitive psychology, and education. The basic premise was that the approach to standards-based reform, which has been effective in focusing educators on advancing academic achievement—establishing standards, measuring progress toward meeting those standards, and supporting a continuous improvement process for making corrections and aligning resources to meet standards—should be expanded to explicitly address personal, social, and organizational facilitators of learning, and that doing so would, in turn, support greater academic and life success for more students. Our initiative progressed substantially in July 2005 when Chicago Public Schools (CPS) asked AIR to demonstrate that conditions for learning could be assessed and to identify three or four indicators for CPS’ high school scorecards that reflect the conditions for learning in a school, such as school climate or student engagement. The indicators had to be (a) practical to measure, (b) scientifically valid, (c) easy to communicate to diverse audiences, and (d) actionable by school personnel. In August 2005, AIR convened a meeting with many of the same national experts and CPS staff. Again, their paradigms were diverse, and their work focused on a variety of factors (social emotional learning, positive behavioral support, student connection, drug prevention, violence prevention, dropout prevention, engagement, educational intervention, clinical psychology, survey research, and measurement). The group came to a strong, clear consensus on the most important factors that schools should address if they wanted to improve student attendance, achievement, graduation, and post-secondary success, as well as actionable indicators of these factors. The indicators identified as most critical were (a) students are safe, (b) students are challenged, (c) students are supported, and (d) students are socially and emotionally skilled. Each of these indicators has extensive research to support its importance for schools and its link to students’ academic success, graduation, and postsecondary success. Together they constitute what has been conceptualized as the social and emotional conditions for learning (Osher et al., 2008). AIR conducted 22 structured focus groups with students, parents, and teachers to inform the survey with the authentic input of stakeholders. Based on expert consensus, stakeholder input, and a review of existing school climate surveys, the AIR team developed the survey. The initial high school survey was pilot-tested with 1,700 students in 24 high schools to identify psychometrically strong scales. We administered the survey to students in 115 Chicago high schools and attained a response rate (77%; 74,602 valid surveys) approaching the average daily attendance rate of 84%. For the 2006–2007 school year, Chicago asked AIR to include students in grades 6–8 in the survey and to modify some of the items to increase the range of responses on items and to attain greater between-school variance. AIR revised items and tested the new scales in cognitive laboratory interviews with diverse students in grades 6–12. We pilottested the new version in 21 high schools (n = 1,359) and 24 elementary schools (n = 1,685), resulting in a stronger survey instrument. The 2007 operational administration, which was combined in the same form with the Consortium on Chicago School Research’s survey, obtained 60,802 valid surveys from 119 high schools (at a 64% response rate) and 76,187 valid surveys from 484 elementary schools (at an 83% response rate). CPS administered the survey in 2008 on its own. The results of the survey are published annually, and are intended to be used by parents and youth to choose schools. These reports have started to change discourse in the district. For example, they have been used by district staff for planning, and are drawn upon for discussion at regional meetings with principals and at district training events.
Building Conditions for Learning and Healthy Adolescent Development 127
Research on the Survey While the survey can be viewed as an intervention, it also provides data that can be used to understand more about the social and emotional conditions for learning. With support from the Spencer Foundation and collaboration from CPS and the Consortium on Chicago School Research, AIR studied the conditions for learning in Chicago middle and high schools, analyzing data from the 136,989 students who completed the 2007 survey to understand which student and school characteristics are associated with conditions for learning, including achievement. Analytic Strategy We combined data from different sources and years: at the student level the 2007 survey data were combined with district data on each student’s race, gender, English language learner (ELL) status, grade level, cumulative GPA, and achievement scores. Additionally, we obtained a constructed “on track” variable that the Consortium developed and CPS uses to predict timely graduation (the variable indicates whether a student has earned at least five full-year course credits and no more than one semester F in a core course in their first year of high school). At the school level, data were merged from different sources. First, some of the 2007 studentlevel variables were aggregated to the school level, such as achievement test results, to obtain indicators of the context of schoolwide achievement. Second, some data were retrieved from the CPS website, such as high school dropout and graduation rates, enrollment data, suspension, and average class size. Third, 2005 data from Common Core of Data were used to obtain some descriptive characteristics of the schools such as school type. Finally, some neighborhood data were also obtained from the Consortium on Chicago School Research at the University of Chicago. These variables include various measures of crime from the school or students census block (which summarizes information from November 2005 to October 2007), and poverty indicators from the census. Characteristics of the Conditions for Learning Survey Participants Table 6.1 presents demographic characteristics for the CPS students overall, compared to those who completed the survey. Because not every eligible student participated, it is important to understand the ways in which the surveyed sample is different from the district overall. Results indicate that the two groups are very similar on some, but not all, demographic characteristics. Both groups have similar percentage of females; White students; Asian and Hispanic students who are classified as having limited English proficiency (LEP); and students in the Free or Reduced Price Lunch Program. In the surveyed sample, however, African American students are slightly under-represented (47%) compared to the whole population (52%). Also there is a minor tendency for students in the middle grades to be slightly over-represented and for high school students to be somewhat under-represented. In addition, the proportion of grade 9 students “on track” is over-represented in the surveyed sample. While in Chicago this percentage is around 53%, in the surveyed sample it is 66%. This result might be expected in a survey which depended upon students being in school. Still, it is important to consider that the surveyed sample—at least for grade 9—is more representative of “better” or “on track” academic achievement students.
128 David Osher and Kimberly Kendziora Table 6.1 Number and Percentage of Students in the Chicago School District and in the Surveyed Sample by Student Demographics All Middle Grade & High School Students
Surveyed Students
N
%
N
%
Gender
Male Female
100,508 101,611
50% 50%
63,174 68,558
48% 52%
Ethnicity
White African American Native American Asian/Pacific Hispanic
17,946 104,190 308 7,186 72,482
9% 52% 0.2% 4% 36%
13,033 62,007 210 5,563 50,919
10% 47% 0.2% 4% 39%
Grade level
Grade 6 Grade 7 Grade 8 Grade 9 Grade 10 Grade 11 Grade 12
32,371 32,424 30,991 38,639 30,073 24,166 20,675
15% 15% 15% 18% 14% 12% 10%
25,088 25,074 22,883 20,301 16,074 12,633 9,679
19% 19% 17% 15% 12% 10% 7%
LEP status
Not LEP LEP
192,916 9,203
95% 5%
126,514 5,218
96% 4%
Special Ed
No disability With disability
166,880 35,239
83% 17%
112,721 19,011
86% 14%
Lunch status
Not in lunch In lunch
33,837 168,282
17% 83%
20,326 111,406
15% 85%
On track status*
Off track to graduate On track to graduate Total
14,223 16,169 202,339
47% 53%
6,432 12,238 131,732
34% 66%
Source: 2007 Chicago Public School district data * Note: On track information is available only for grade 9 students.
Correlations Among the Conditions for Learning Survey Constructs What is the relationship between the four conditions for learning? Table 6.2 presents the correlations among the Conditions for Learning survey for middle-grade students; Table 6.3 presents results for high school students. As expected, all the scales were positively correlated with each other. In the middle grades, the correlations between School Safety and Challenge and School Safety and Student Support
Table 6.2 Middle Grades: Correlations Among Conditions for Learning Constructs
1 2 3 4
Middle level
1
2
3
4
School Safety Challenge Student Support Social & Emotional Learning
1 0.17 0.25 0.48
1 0.62 0.20
1 0.34
1
Note: All the correlations are statistically significant.
Building Conditions for Learning and Healthy Adolescent Development 129 Table 6.3 High School: Correlations Among Conditions for Learning Constructs
1 2 3 4
High school
1
2
3
4
School Safety Challenge Student Support Social & Emotional Learning
1 0.25 0.26 0.52
1 0.65 0.25
1 0.32
1
Note: All the correlations are statistically significant.
were small, which suggests that these are separate constructs. The correlation between School Safety and Social Emotional Learning was moderate, suggesting that students who felt safer at school tended to rate the social emotional learning of their peers more highly. This makes sense because some of the items on the Safety Scale assess “emotional safety”—the extent to which students are picked on or bullied. Challenge is highly correlated with Student Support (r = .62), which is logical because both scales ask students to rate teacher or school factors such as whether teachers “Think all students can do challenging school work” and whether they “Often connect what I am learning to life outside the classroom.” Challenge was less correlated with Social Emotional Learning (r = .20) which focuses on the behavior of other students. Finally, Student Support had a small correlation with Social Emotional Learning (r = .34). The same pattern of results was observed among high school students, although on average the magnitude of the correlations was slightly higher. Conditions for Learning in Middle Grades vs. High School Are there differences in how middle-grade and high school-grade students experience the conditions for learning? The following figures present the mean values on the scales by different student demographic characteristics. It is important to remember when examining these figures that the ranges of the constructs were to some extent different. Therefore, comparisons are more meaningful when done within the same construct. The results show that middle-grade students tended to provide higher scores on all the Conditions for Learning scales than high school students. All differences were statistically significant. It may be that older students’ perceptions of their surroundings were more critical than those of their younger peers; on the other hand, it may be that the actual conditions for learning were worse in high schools. Perhaps high schools in Chicago were less safe, teachers were less challenging, students received less support, and they were less likely to have socially and emotionally skilled peers compared to middle-grade students. Additional data would need to be collected to explain these effects. Nonetheless, the finding of lower ratings for variables, such as school climate, that are similar to conditions for learning is consistent with a broader body of research and experience that shows that both students and staff report progressively less satisfaction as they advance higher in grade levels (Eccles & Midgley, 1989; Spier, Cai, Kendziora, & Osher, 2007). Correlations Between Achievement and Conditions for Learning What are the relationships between the conditions for learning and academic achievement? In the following figures, we present the correlation coefficients between Prairie State Achievement Examination (PSAE) scores and conditions for learning. The PSAE measures the
130 David Osher and Kimberly Kendziora 340
Mean scale score
320
300
280
260
240 School safety
Challenge
Stud. support
Middle school
Soc. & Emot. skills
High school
Figure 6.2 Mean Conditions for Learning Scores for Middle Grades and High School.
Correlation between PSAE tests & conditions for learning
achievement of grade 11 students relative to the Illinois Learning Standards for Reading, Mathematics, and Science. Each correlation value is illustrated using a bar, where the size of the bar represents the linear strength between the two variables and the vertical axis shows the range of the correlation. Therefore, the taller the bar, the larger the correlation. The School Safety scale showed the highest correlations with the subscales from the PSAE test. All the correlations were statistically significant and suggest the importance of school safety and academic achievement. Although not presented here, results of achievement tests administered to students in grades 8, 9, and 10 showed a similar pattern of results, with safety having the highest correlation with achievement.
Grade 11 Writing
Math
Reading
Science
0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 School safety
Challenge
Student support
Social emotional skills
SCS Constructs
Figure 6.3 Correlation Between PSAE Subscales and Conditions for Learning Scales (Grade 11).
Building Conditions for Learning and Healthy Adolescent Development 131 Exploring Correlations Between GPA and Conditions for Learning Cumulative GPA data from the spring semester of 2007 were obtained to cross with the Conditions for Learning survey responses. In contrast to the pattern of correlations observed between achievement scores and the conditions for learning scales, the students’ GPAs were highly correlated with the Challenge construct. These correlations were above .23 for the four grade levels, whereas the correlations between the School Safety and GPA across the different grades were approximately .18. It may be the case that GPA was more strongly related to Challenge than achievement test scores because Challenge taps the proximal teacher behaviors that are hypothesized to be associated with greater academic success (e.g., “My teachers often assign homework that helps me learn,” “In my classes, we often discuss different interpretations of things we read”). Because grades were a more proximal indicator of teacher ratings of this success than achievement test scores, the higher correlation with GPA may indicate that a student is meeting a teacher’s expectations, whether or not these are aligned with the standards assessed on the achievement tests. Conditions for Learning by On Track Index (Ninth Grade) What are the relationships between the conditions for learning and students being on track to graduate? The Chicago on Track to Graduate index is computed for ninth-grade students to identify students who are at risk of not graduating on time. The index was developed by the Consortium on Chicago School Research, and is thought to be a better indicator of graduation than achievement test scores or student demographic characteristics. Students are “on track to graduate” if they have earned at least five full-year course credits in their freshman year, and received no more than one semester F in a core course. Figure 6.5 shows that “on track” stu-
High school
Correlation scores between GPA & conditions for learning
0.30 0.25 0.20 0.15 0.10 0.05 0.00 School safety
Grade 9
Challenge
Grade 10
Student support Grade 11
Social and emotional skills Grade 12
Figure 6.4 Correlation Between Conditions for Learning and GPA Scores (High School).
132 David Osher and Kimberly Kendziora High school Mean scale score
320 300 280 260 240 School safety
Challenge Off track
Student support On track
Social and emotional skills
Figure 6.5 Conditions for Learning Scores by On Track Status (Grade 9 Students).
dents tended to score higher than “off track” students on the School Safety, Challenge, and Student Support. No differences are observed between the two groups in the Social Emotional Learning scale. Conditions for Learning and School Enrollment Does school size appear to affect the conditions for learning? Enrollment size ranged from 41 to 2,005 students in schools with middle grades and from 67 to 4,248 students in high schools. The distributions of enrollment in both levels were highly positively skewed; schools with more than 2,000 students were not very common. Because of the skewness, simple Pearson correlations are not very meaningful. To approximate the relation between enrollment size and the responses on the Conditions for Learning survey, the enrollment distribution was divided into quintile categories: the lowest 20%, between 20% and 40%; between 40% and 60%; between 60% and 80% and above 80%. Especially in high school, there seemed to be a tendency for Conditions for Learning to be negatively associated with enrollment. These negative relations were more evident for the Challenge, Student Support Scales, and Social Emotional Learning scores. The correlations between the Conditions for Learning constructs and the logarithm of enrollment are shown in Table 6.4. Particularly for students in high school, larger enrollment is associated with worse conditions for learning, especially student ratings of support from teachers. These specific data, which are consistent with data that we analyzed for another city (Lampron, Brown, Osher, & Table 6.4 School Level Correlations Between Conditions for Learning Constructs and the Logarithm of Enrollment
School Safety Challenge Student Support Social & Emotional Learning Note: Values in bold are statistically significant.
Middle School log(enrollment)
High School log(enrollment)
0.01 –0.07 –0.15 0.02
–0.21 –0.35 –0.59 –0.37
Building Conditions for Learning and Healthy Adolescent Development 133 Poirier, 2008), suggest that smaller high schools are perceived by students as being safer, more challenging, much more supportive, and having a more socially and emotionally skilled peer group. Specific Correlations for Conditions for Learning Scales What are the relationships between student perceptions and other data that can be collected at schools? To examine the utility of Conditions for Learning for performance management, we investigated the extent to which student perceptions of the conditions for learning in their school related to objective data available to principals for decision-making. Answering this question involved testing the distributions of variables (and transforming where necessary) and calculating bivariate correlations. Results for each of the scales follow. School Safety, School Disruption, and Neighborhood Crime. Students’ ratings of perceived Safety in their schools should be associated with objective measures of school disruption. Results for correlations with school suspensions and number of suspended students are presented in Table 6.5. Both suspension variables needed to be logarithmically transformed. The high school variable was still somewhat skewed, which likely attenuated the very high correlations presented below. The numbers of school suspensions and suspended students were almost perfectly correlated; both were very strongly associated with School Safety as assessed on the Conditions for Learning survey. Additionally, we examined the relationship between School Safety and neighborhood crime, testing the logic that schools in neighborhoods with more crime would feel less safe to students. Crime in students’ home census blocks was more strongly related to school safety than crime in the school’s own census block (“imported disorder”), supporting the finding by Clark and Lab (2000) that the school’s neighborhood characteristics do not strongly influence in-school crime. However, Wayne, Welsh, Stokes, and Greene (2000) have reported findings that the school’s surrounding neighborhood is more influential for in-school victimization than students’ home neighborhoods. Recent analyses conducted by the lead author using data from Cleveland may help illuminate some of the relationships among student and school environments, the conditions for learning, and school academic achievement. Along with colleagues from Kent State University’s Institute for the Study and Prevention of Violence, we linked conditions for learning with data on neighborhood disadvantage and school performance. Results are described Table 6.5 Correlations Between School Safety, School Suspensions, and the Number of Suspended Students
1 2 3
1 2 3
Middle Level
1
2
3
School Safety ln school suspensions ln N suspended students
1 –0.43 –0.43
1 0.99
1
High School
1
2
3
School Safety ln school suspensions ln N suspended students
1 –0.65 –0.62
1 0.99
1
Note: All correlations are statistically significant.
134 David Osher and Kimberly Kendziora Table 6.6 Correlations Between School Safety and Neighborhood Crime
1 2 3 4
1 2 3 4
Middle Grades
1
2
3
4
School Safety logarithm of crime count in school’s census block ln of per capita crime in school’s own census block Average ln of per capita crime from students’ home census blocks
1 –0.47 –0.61 –0.70
0.65 0.58
1 0.78
1
High School
1
2
3
4
School Safety logarithm of crime count in school’s census block ln of per capita crime in school’s own census block Average ln of per capita crime from students’ home census blocks
1 –0.26 –0.39 –0.45
1 0.56 0.46
1 0.70
1
Note: All correlations are statistically significant.
in Table 6.6. We found that neighborhood disadvantage predicted the School Performance Index (PI) score for elementary and high schools and that school safety explained the neighborhood disadvantage effect: more disadvantaged neighborhoods had less-safe schools, accounting for significant variation in lower academic performance scores. Further, when we controlled for neighborhood disadvantage, attendance and discipline events, we found that student perception of school safety alone predicted the PI score for both K–8 schools and high schools (Osher et al., 2008). Challenge and Dropout. To examine the strength of the relationship between perceptions of high expectations and school variables, we sought to correlate Conditions for Learning scores for Challenge with dropout in the Chicago data. Dropout data were available for high school students. Our hypothesis was that the schools that were perceived as the most challenging and engaging would have the lowest levels of dropout. This is in fact what we found. We log-transformed the dropout variable to improve its distribution, and found that dropout correlated significantly with Challenge, but correlations between dropout and other Conditions for Learning scores (Safety and Social Emotional Learning) were also significant. Results are presented in Table 6.7. Student Support and Class Size. In the previous section on school characteristics, we explored the relationship between Conditions for Learning constructs and school enrollment. We found that Student Support was significantly related to the log-transformation of student enrollment in both middle grades and in high schools (–0.15 for middle grades and –0.59 for high school). This indicates that smaller enrollment is strongly associated with higher perceptions of support, especially in high school. Table 6.7 Correlations Between Challenge (and other Conditions for Learning Constructs) and Dropout High School
ln dropout percent
School Safety Challenge Student Support Social & Emotional Learning
–0.31 –0.33 –0.13 –0.32
Note: Values in bold are statistically significant. Note: Dropout percent data are from 2006.
Building Conditions for Learning and Healthy Adolescent Development 135 Table 6.8 School Level Correlation Between Conditions for Learning Constructs and the Average Class Size in High School Average Class Size HS School Safety Challenge Student Support Social & Emotional Learning
0.15 0.01 –0.24 0.13
Note: Values in bold are statistically significant.
The Student Support construct did not covary with many other educational variables, but it related strongly to proxy measures of personalization (as it should). We had data on average class size for high schools; the only Conditions for Learning construct with which it was significantly associated was Student Support. (See Table 6.8.) Peer Social Emotional Learning and Graduation. For the 2007 Conditions for Learning survey, students rated their peers’ levels of social emotional learning. We hypothesized that students’ collective social emotional learning should be associated with measures of persistence in school, which could be indexed by the graduation rate. Graduation rates for high schools ranged from 21 to 100. Correlations are presented in Table 6.9. As expected, the correlation between social emotional learning and graduation was significant. However, it was not quite as high as the correlation between safety and graduation. Overall, the constructs that compose the Conditions for Learning survey have demonstrated evidence of validity. They are associated with variables that they should be associated with, and are not associated with variables that they should not be.
The Implications of This Work The challenge for schools and communities is to create environments where students are supported in developing the skills and capacities to thrive. This involves interventions in three domains: health; social/emotional/behavioral; and cognitive/academic (Kendziora, Osher, & Schmitt-Carey, 2007). Schools play a key role in this process. For example, a meta-analysis of more than 200 universal school-based studies showed significant improvements in students’ social-emotional learning; attitudes towards self, school, and others; social behaviors; conduct problems; emotional distress; and academic performance. Notably, SEL programming yielded an average gain on achievement test scores of 11 to 17 percentile points (Payton et al., 2008). Schools can develop the social emotional and cognitive capacities that enable students not just to survive but to thrive. Doing this successfully involves leveraging and disseminating Table 6.9 Correlations Between Graduation Rates and Conditions for Learning Constructs High School
Graduation Rate
School Safety Challenge Student Support Social & Emotional Learning
0.41 0.25 –0.03 0.36
Correlations obtained for graduation rates higher than 40 Note: Graduation percent from 2006 dataset. Note: Values in bold are statistically significant.
136 David Osher and Kimberly Kendziora information about the connections between learning and academic performance. For example, in Alaska, where AIR developed a survey to assess the impact of a youth development initiative across 18 school districts, we found that not only were several aspects of school climate and connectedness related to student achievement, but positive change in school climate and connectedness was related to significant gains in student scores on statewide achievement tests. Our findings showed that whether a school started with high or low school climate and connectedness, or high or low achievement scores, changing that school’s climate and connectedness for the better was associated with increases in student performance in reading, writing, and mathematics (Spier et al., 2007). Similarly work we have done in previously troubled schools in the South Bronx suggested that mental health supports, when coupled with family engagement and organizational efficacy, were effective in creating conditions for learning in these schools (Kendziora et al., 2008). The Chicago work does not stand alone. Work on the measurement of conditions for learning, by AIR and others, has extended to additional sites: • •
• •
• •
•
•
•
The survey and school report are likely to be piloted in a large state to help monitor its progress toward educational equity; Two of the four survey scales will be used in 2008 and 2009 in San Diego to help monitor its Gates-funded small high schools (it already collected survey information on challenge and support); A number of large cities are currently exploring use of the AIR survey; New York City has used a similar student survey to monitor how students (among other stakeholders) are experiencing schools, and will use these surveys as part of their principal accountability process; Individuals connected with school mental health have identified the report card strategy as a vehicle for promoting school mental health (Hunter et al., 2005); The state of Illinois and the city of Anchorage, Alaska, have developed social emotional learning standards, and New York State legislation calls for its Departments of Education and Mental Health, create voluntary social emotional learning standards; Say Yes to Education, an organization focused on dramatically increasing high school and college graduation rates for our nation’s inner-city youth, has targeted social emotional and behavioral factors and health, along with cognitive and financial factors as key to realizing its goals; The Association for Supervision and Curriculum Development has initiated a major campaign that focuses on addressing the whole child, which focuses on health, physical and emotional safety, caring adults, engagement, and challenge; and United Voices for Education, an organization of over 42 educational stakeholder organizations, has called for school report cards that focus on the conditions for learning.
In spite of the examples of progress in this area noted above, barriers remain. The first is to demonstrate the importance of social-emotional factors in education. Although more research is accumulating, it will be important to demonstrate dramatically the impact of the social emotional conditions for learning and of addressing these conditions effectively. The second is financial; doing good surveys and providing support for responding to these surveys is not inexpensive. Paradoxically, as long as social emotional factors are marginalized, it will be hard to generate the resources for such surveys. The third barrier is making sure that interventions enter the classroom, affect the learning process, and reach the individual child. This is a struggle in all systems change, including education. Steps are being taken in this direction. For
Building Conditions for Learning and Healthy Adolescent Development 137 example, Say Yes to Education has developed, and is piloting in five Harlem Elementary Schools, a monitoring process, linked to individual growth plans, that look at whether students are off track, on track, or on track to thrive in the domains of health, social-emotional, and cognitive/academic development. Although these barriers exist, the middle school and high school “crises” and the continuing inability to transform educational outcomes for disadvantaged students create a window of opportunity for scaling up an intervention that can contribute significantly to improving attendance, learning, performance, graduation rates, and post-secondary outcomes in multiple cities and states. In conclusion, there are three major recommendations or action steps that should be taken to create emotionally safe and supportive school that promote students’ positive social, emotional, and academic learning: (a) help districts and states develop the capacity to assess and monitor the social and emotional conditions for learning; (b) ensure that stakeholders understand the importance of the social and emotional conditions for learning; and (c) and provide schools and communities with effective tools and strategies to improve the social and emotional conditions for learning.
Notes The research presented in this chapter was funded by a grant from the Spencer Foundation. The development and initial implementation of the school survey was funded by the Children First Fund: Chicago Public Schools Foundation and the American Institutes for Research. We are also grateful for the collaboration and support of our colleagues at the Collaborative for Academic, Social, and Emotional Learning and the Consortium on Chicago School Research. The work of many of our colleagues at AIR—especially Drs. Marjorie Chinen and Allison Gandhi—is reflected in this report. 1 http://research.cps.k12.il.us/cps/accountweb/Reports/download.html 2 In this report, we refer to “middle grade” students rather than “middle school” students because approximately 80% of the students in grades 6, 7, and 8 who completed the survey were in fact enrolled in K–8 elementary schools.
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Assessment for Integrated Screening and Prevention Using the Resiliency Scales for Children and Adolescents Sandra Prince-Embury, The Resiliency Institute of Allenhurst, LLC
Introduction: Need for Universal Mental Health Screening Psychologists who work in schools have identified the need for universal screening for social and emotional disturbances in the schools (Doll & Cummings, 2008). Epidemiological research conducted in the 1980s showed that at least 20% of school-aged youth had a diagnosable psychiatric disorder, and only a fourth of these children were receiving therapeutic services (Doll, 1996; U.S. Department of Health and Human Services, 1999). Others have also identified high rates of unidentified and untreated youth with mental disorders (Katoaka, Zhang, & Wells, 2002; Costello, Mustillo, Erkanli, Keeler, & Angold, 2003). About 20% of children are estimated to have mental disorders with at least mild functional impairment. Due to a significant gap between the need for and availability of mental health services, schools have become, by default, the mental health provider for most school-aged children and adolescents (Hoagwood & Johnson, 2003). The role of schools in monitoring mental health is supported by developmental research of the past three decades which demonstrated that mental health and psychological wellness are not ancillary to school success but are integral to it (Haertel, Walberg, & Weinstein, 1983; Masten et al., 2005). Doll and Cummings (2008) recommend universal screening in the schools that will both identify vulnerable children earlier than would otherwise be the case, and guide the planned development of services to match children’s needs. Universal mental health screening programs have also been suggested by national task forces and mental health commissions (New Freedom Commission on Mental Health, 2003). The consensus is that early identification is desirable in that children who are identified and treated early may avoid the development of psychopathology and associated impairments. Pre-symptom identification is desirable because once psychological symptoms have occurred there is a greater chance that the symptoms have already interfered with the youths’ functioning as well as a greater likelihood that the symptoms might crystallize into a psychological disorder. Early identification is also beneficial because more fully developed psychopathology is more difficult and more costly to treat. A special issue of the Journal of School Psychology highlighted the need for universal screening in the schools as well as the need to inform school personnel about the use and utility of tools for universal screening (Albers, Glover, & Kratochwill, 2007a; 2007b). However, as Levitt, Saka, Romanelli, and Hoagwood (2007) point out, the implementation of universal screening for social and emotional problems is different from universal screening for other conditions in that it is not yet possible to identify asymptomatic youth and offer interventions that would prevent the onset of symptoms. According to these authors, current screening methods rely on youth having some level of symptoms or impairment in functioning in order
142 Sandra Prince-Embury to identify them as being at-risk. In this chapter we present an alternative model of universal screening that is based on resilience and vulnerability as a framework for prevention-focused screening. The Resiliency Scales for Children and Adolescents (RSCA) (Prince-Embury, 2007) are presented as theoretically based and psychometrically sound tools for the identification of vulnerability and resilience in youth who may be asymptomatic but at risk for the development of symptoms. The sections below discuss the constructs underlying the RSCA, its psychometric properties and validity evidence, and sample models for screening and intervention using the RSCA.
Resiliency Framework Traditional approaches to mental health services have not necessarily integrated the processes of screening and prevention. For example, symptom-based screening may not be accompanied by more comprehensive assessment and suggestions for appropriate intervention. Conversely, preventive programs may be selected for targeted risk populations without specific assessment tools to evaluate the pre- and post-intervention conditions of the participants. Consequently, there is a need for a framework that systematically links screening with specific intervention decisions and which provides a method for evaluating the specific impact of these interventions. Resilience theory presents a model for integration of screening, intervention and outcome assessment. It considers strengths as well as vulnerability. Strength-based screening is advantageous because it is associated with less stigma and may provide more information for designing preventive interventions. Resilience in the face of adversity has been studied extensively by developmental psychopathologists for the past 50 years. This body of work has defined resiliency as the ability to weather adversity or to bounce back from a negative experience. Research of resilience suggests that mental disorders and psychological symptoms may be based in part on less personal resiliency or greater vulnerability that the child may have experienced in a variety of ways. See the work of Rutter, Garmezy, Masten and others for more information (Garmezy, 1971; 1985; 1991; Garmezy, Masten, & Tellegren, 1984; Luthar, 1991; Luthar, Cicchetti, & Beckev, 2000; Luthar & Zieglar, 1991, 1992; Masten, 2001; Masten & Coatsworth, 1998; Masten & Curtis, 2000; Masten & Powell, 2003; Masten et al., 2005; Rutter, 1987; 1993). Resilience has been recognized by school psychologists as a concept that is very consistent with overall educational goals and well suited for application in educational settings. The National Association of School Psychologists embraced the theme of “Resilience: Building Strength for Life” for its 2008 Conference in New Orleans. This theme was part of a year-long initiative aimed at integrating resilience concepts into the practice of school psychology and presenting practices to build resiliency within the school setting. Application of resilience constructs in educational environments makes sense for many reasons. The constructs are based on relative strength and vulnerability as opposed to clinical pathology. The constructs relate to academic achievement and positive educational environments as well as avoidance of pathology and dysfunction. The constructs are developmental and normative and may be applied universally to guide system-level practice as well as individually to screen for children and youth who may be at risk. For example, principles of resilience have been applied in describing resilient classrooms (Doll, Zucker, & Brehm, 2004), in coaching parents (Brooks & Goldstein, 2001), and in coaching teachers (Brooks & Goldstein, 2008). What is currently needed is a way to summarize, quantify and standardize resiliency in a way that is reliable and easily understood. The Resiliency Scales for Children and Adolescents (Prince-Embury, 2006; 2007) are based on three theoretical constructs that emerge as cornerstones of developmental resiliency
Assessment for Integrated Screening and Prevention 143 theory—Sense of Mastery, Sense of Relatedness, and Emotional Reactivity—and the relationship of these factors to one another. Together these constructs form a framework for understanding a child’s balance between strength and vulnerability in the potential development of symptoms. These core constructs are represented by three scales collectively comprised of 10 subscales. Sense of Mastery One core mechanism that has been consistently identified in general developmental research and resilience research is the development of a sense of mastery or self-efficacy. White (1959) introduced the construct as a sense of mastery/efficacy in children and youth that provides them with the opportunity to interact with and enjoy cause and effect relationships in the environment. According to White, a sense of competence, mastery, or efficacy is driven by an innate curiosity, which is intrinsically rewarding and is the source of problem-solving skills. Bandura (1977) has studied the importance of self-efficacy in children on various aspects of behavior and achievement. Subsequently, the study of competence was incorporated into the third wave of resilience studies that focused on intervention and in particular the promotion of competence as a strategy for preventing or ameliorating behavioral and emotional problems (Masten & Coatsworth, 1998; Masten, Burt, & Coatsworth, 2006). Consistent with this focus, the Project Competence group (Masten & Obravadic, 2006) examined competence criteria for positive adaptation in their studies of resilience and particularly on competence in age-salient developmental tasks (Masten & Powell, 2003). Several studies conducted as part of the Rochester Child Resilience Project supported the hypothesis that positive efficacy expectation is related to resilience. Positive efficacy expectations in 10- to 12-year-olds predicted better behavioral adaptation and resilience to stress (Cowen, Pryor-Brown, Hightower, & Lotyczewski, 1991). Positive expectations about their future predicted lower anxiety, higher school achievement and better classroom behavior control (Wyman, Cowen, Work, & Kerley, 1993). The RSCA Sense of Mastery scale operationalizes the constructs mentioned above in three subscales; Optimism, Self-Efficacy and Adaptability. The Optimism subscale includes items describing positive attitudes about the world and life in general and about an individual’s life specifically, currently, and in the future. The Self-Efficacy subscale includes items describing belief in one’s own general and/or specific competence and control. The Adaptability subscale includes items describing one’s personal receptivity to feedback, to learning from his or her own mistakes, and willingness to ask others for assistance. Previous research and theory suggests that children and youth who have less of a sense of mastery may be more vulnerable to the development of psychological symptoms. Consistent with this assumption, preventive interventions may target increasing general or specific sense of mastery by increasing children’s problem-solving skills and sense of self-efficacy. The Sense of Mastery scale and subscales may be used to screen for low sense of mastery in youth or to assess whether preventive interventions designed to increase sense of mastery have accomplished this goal. Sense of Relatedness A second body of literature links youths’ relational experience and abilities with resilience against adversity. The implication of this body of literature is that social relatedness provides external buffering in two ways. First, youth may view relationships as providing specific
144 Sandra Prince-Embury supports in specific situations. Second, internal mechanisms reflecting the cumulative experience of previous support may shield youth from negative psychological impact. The RSCA Sense of Relatedness scale operationalizes sense of relatedness in four subscales: perceived access to support, trust, comfort with others and tolerance of difference with others. The importance of relationships and relational ability as mediators of resilience has been supported in research by developmental psychopathologists such as Werner and Smith (1982). Throughout her writing, Werner has stressed the importance of children having relationships with caring adults other than, or in addition to, their parents. Werner and Smith noted that resilient youth sought support from non-parental adults more often than nonresilient youth, especially from teachers, ministers, and neighbors. These supports were influential in fostering resilience. The RSCA Access to Support subscale was designed to assess this construct. The significance of trust has been identified most clearly by Erik Erikson (1963) as the first stage of social emotional development, upon which all social development is built. Erikson defined basic trust as the ability to receive and accept what is given. He believed that basic trust was initially based in infancy with the oral mode of functioning, and then emerged from aggregated experiences with the primary caregiver to establish children’s balance of trust versus mistrust. The RSCA Trust subscale was designed to tap this construct. Early differences in physiologically based temperament have frequently been cited by developmental and personality theorists as influencing the relationships that individuals have with others, which in turn influence development of the capacity to trust. Constructs such as “slow to warm up to others” (Thomas & Chess, 1977) or internality (Eysenck, 1967) have been used to describe discomfort with others. The RSCA Comfort subscale was designed to tap the opposite of these: manifested by meeting people and making friends easily and generally feeling calm in the presence of others. The ability to have one’s own thoughts and express them even though they may differ from the thoughts of others has been conceptualized by Bowen (1978) as one manifestation of “differentiation within a family system.” It may be hypothesized that this ability would be part of the child’s balancing dependency and striving for autonomy and would become increasingly important with age. The Tolerance subscale was designed to tap this construct. Screening that employs the Sense of Relatedness scale of the RSCA might identify youth who feel isolated or disconnected from others. Interventions designed to increase sense of relatedness might be implemented and pre-post comparisons of scores from the Sense of Relatedness scale could evaluate the effectiveness of these interventions. Emotional Reactivity Research in the field of developmental psychopathology has found that children’s development of pathology in the presence of adversity is related in some way to their emotional reactivity and ability to regulate this reactivity. Strong emotional reactivity and the associated difficulty with emotional self-regulation have been associated with behavioral difficulty and vulnerability to pathology. Conversely, the ability to modulate emotional reactivity is a significant factor in fostering resilience (Cicchetti, Ganaban, & Barnett, 1991; Cicchetti & Tucker, 1994). Consistent with these findings, pre-symptom universal screening might consider youths’ personal vulnerability associated with emotional reactivity. Emotional reactivity may be defined as arousability or threshold of tolerance that exists prior to the occurrence of adverse events or circumstances. Rothbart and Derryberry (1981) have defined emotional reactivity as the speed and intensity
Assessment for Integrated Screening and Prevention 145 of a child’s negative emotional response. Emotion regulation is defined as the child’s capacity to modulate emotional responses (Eisenberg, Champion, & Ma, 2004). Emotional regulation is further defined as the intra- and extra-organismic factors by which emotional arousal is redirected, controlled, modulated, and modified so that an individual can function adaptively in emotionally challenging situations (Cicchetti et al., 1991; Thompson, 1990). Siegel (1999) identified aspects of reactivity as intensity, sensitivity, specificity, windows of tolerance, and recovery. The RSCA Emotional Reactivity scale operationalizes emotional reactivity in three subscales: The Sensitivity subscale addresses how easily the individual is aroused; the Recovery subscale assesses how long it takes the individual to recover after arousal; and the Impairment subscale describes the degree to which youths’ functioning is impaired by emotional reactivity. Thus pre-symptom screening using the RSCA Emotional Reactivity scale incorporates identification of high sensitivity to emotional triggers, difficulty recovering when emotionally triggered, and significant impairment of functioning when triggered. Preventive interventions offered in response to high scores on this scale might incorporate relaxation exercises to decrease sensitivity, or instruction in coping skills to speed recovery and minimize impairment. Description of the Resiliency Scales for Children and Adolescents (RSCA) The RSCA is a self-report instrument and describes the experience of the child as reported by the child. It consists of three global scales: Sense of Mastery, Sense of Relatedness, and Emotional Reactivity. T-scores on these three global scales comprise the Resiliency Profile which displays the child’s relative strengths and vulnerabilities. Two composite scores, the Resource Index and the Vulnerability Index, are summary scores that quantify the child’s relative strength and vulnerability. The three global scales are comprised of 10 subscales that can be used to understand the child’s specific strengths and vulnerabilities in more depth. The Sense of Mastery scale is a 20-item self-report questionnaire written at a third-grade reading level. Response options are ordered on a five-point Likert scale: 0 (Never), 1 (Rarely), 2 (Sometimes), 3 (Often), and 4 (Almost Always). The Sense of Mastery scale consists of three conceptually related content areas: optimism about life and one’s own competence; self-efficacy associated with developing problem-solving attitudes and strategies; and adaptability, which is flexibility, being personally receptive to criticism, and learning from one’s mistakes. Internal consistencies for the Sense of Mastery Scale are good with an alpha of .85 for youth ages nine to 11, .89 for youth ages 12–14 and .95 for youth ages 15–18. Test-retest reliability coefficients were .79 for youth ages nine to 14 and .86 for youth ages 15–18 (PrinceEmbury, 2007). The Sense of Relatedness scale is a 24-item self-report questionnaire written at a third-grade reading level. Response options are frequency-based, ordered on a five-point Likert scale: 0 (Never), 1 (Rarely), 2 (Sometimes), 3 (Often), and 4 (Almost Always). Within this scale, a sense of relatedness refers to comfort with others, trust in others, sense of access to support by others when in need, and tolerance of differences with others. Internal consistency was good to excellent for the Sense of Relatedness scale: .89 for children ages nine to 11, .91 for children ages 12–14 and .95 for youth ages 15–18. Test-retest reliability coefficients were good; .84 for youth ages nine to 14 and .86 for youth ages 15–18 (Prince-Embury, 2008). The Emotional Reactivity scale is a 20-item self-report questionnaire written at the thirdgrade reading level. Response options are ordered on a five-point Likert scale: 0 (Never), 1 (Rarely), 2 (Sometimes), 3 (Often), and 4 (Almost Always). Unlike the Sense of Mastery and
146 Sandra Prince-Embury Sense of Relatedness scales, lower scores on the Emotional Reactivity scale are indicative of resilience and high scores are indicative of vulnerability. This scale consists of three related content areas: the Sensitivity subscale assesses the child’s threshold for emotional reaction and the intensity of the reaction, the Recovery subscale describes the length of time required for recovering from emotional upset, and the Impairment subscale describes the degree to which functioning is disrupted while upset. Internal consistency for the Emotional Reactivity scale was excellent with alphas of .90 for youth ages nine to 11, .91 for youth ages 12–14 and .94 for youth ages 15–18. Test-retest reliability coefficient was .88 for youth ages nine to 14 and youth ages 15–18 (Prince-Embury, 2007). Summary Index Scores. Universal screening requires as much simplification of scoring as possible along with the potential to unfold the scores into deeper levels of information as needed. The RSCA Summary Index scores are useful for screening purposes because they combine information into two scores for initial screening, but also may be unfolded to provide more detailed information at the global and subscale levels. The Index scores were developed based on empirical analyses of RSCA scale score profiles, factor analytic studies and validity studies (Prince-Embury, 2006, 2007; Prince-Embury & Courville, 2008a; 2008b). A first index score, the Resource Index, is the standardized average of the Sense of Mastery and Sense of Relatedness scales. This average is an estimate of students’ personal strength or resources, weighting Sense of Mastery and Sense of Relatedness equally. Factor analytic studies indicate that although the three RSCA scales represent three distinct factors, two of these factors are highly related and thus may be considered together for screening purposes (PrinceEmbury & Courville, 2008a). Internal consistency for the Resource Index was excellent with alphas of .93 for youth ages nine to 11, .94 for youth ages 12–14 and .97 for youth ages 15–18. Test-retest reliability coefficient was .90 for youth ages nine to 14 and .77 for youth ages 15–18 (Prince-Embury, 2007). Resilience theory suggests that youth who perceive themselves as having sufficient personal resources will be more resilient and less likely to develop psychopathology than those who experience themselves as having insufficient personal resources. Students with significantly below-average scores on the Resource Index require preventive interventions to increase personal resources. The Vulnerability Index score is the standardized difference between the Emotional Reactivity T-score and the Resource Index score. It quantifies children’s personal vulnerability as the relative discrepancy between their combined self-perceived resources (the Resource Index) and their fragility as described by emotional reactivity (the Emotional Reactivity Scale; Prince-Embury, 2007). Internal consistency for the Vulnerability Index score is excellent with alpha coefficients of .93 for youth ages nine to 11, .94 for youth ages 12–14 and .97 for youth ages 15–18. Test-retest reliability coefficient was .83 for youth ages nine to 14 and .90 for youth ages 15–18. Sensitivity and Specificity using the Vulnerability Index cut score in adolescent sample with a Vulnerability Index cut score of T54 yielded Sensitivity of 81.2% and specificity of 75.5% and a total hit rate of 78% (Prince-Embury, 2008). The Vulnerability Index score is consistent with theories that define vulnerability as the result when internal fragility or external challenge is not balanced by personal resources. Personal vulnerability would be indicated by a high Vulnerability Index score which would indicate that students’ personal resources were significantly below their level of emotional reactivity.
Psychometric Properties and Validity of the RCSA Despite consensus on the need for universal pre-symptom screening that employs a resilience framework, there are few psychometrically sound screening tools. Glover and Albers (2007)
Assessment for Integrated Screening and Prevention 147 provide criteria for universal screening tools, arguing that these should demonstrate appropriateness, usability, and technically adequate norms, reliability, and validity. They suggest that few current screening tools have adequate norms, reliability, or sensitivity and specificity. In their review of currently available assessment tools, Levitt et al. (2006) also conclude that few of the currently available screening instruments demonstrate high levels of both sensitivity and specificity. These authors also call for assessment tools with demonstrated reliability and validity. Adequate reliability is particularly important if follow-up testing is needed. Screening tools require sufficient internal and test-retest reliability for different age groups and in different populations in order to be sensitive to change in pre-post testing for different groups. Lack of internal consistency indicates that the measured characteristic is not clearly defined and may include excessive error variance. Such measures are in turn likely to have poor test-retest reliability. This is important because if measures do not assess a construct consistently in an untreated or control sample over time, they are unlikely to detect the effect of interventions over time in treatment groups. Measures that are sensitive enough to measure change at a group and individual level over time are necessary to determine whether or not preventive interventions are effective. In response to the call for efficacious and effective screening tools the sections below examine evidence of the reliability and validity of the RSCA. Reliability Cicchetti (1994) suggests that coefficient alphas at or above .70 are adequate, at or above .80 are good, and at or above .90 are excellent. Alphas of .90 are thought of as adequate for tracking individual scores over time. Alphas of .80 or more are considered adequate for tracking group scores over time. Using these criteria, reliability evidence was excellent for the RSCA Index Scores, good for the Global Score, and adequate for most subscales. The RSCA index and global scale scores show good or excellent internal consistency across age and gender groups and, as expected, greater internal consistency was evidenced with increased age (Prince-Embury, 2007). For children ages nine to 11, the RSCA Index scores and the Emotional Reactivity Scale score meet the criterion of alpha > .90 for individual-level tracking. The Sense of Mastery and Sense of Relatedness Scale scores meet the criterion of .alpha > .80 for grouplevel tracking. For children ages 12–14, the RSCA Index scores and all three global scores meet the criterion for individual level tracking. Six of the RSCA subscales met criterion for grouplevel tracking. For youth ages 15–18, both Index scores, three global scale scores, and three subscale scores meet the criterion for individual level tracking. All scores meet the criterion for group-level tracking. Hence the RSCA demonstrates good internal consistency, confirming the conceptual and theoretical derivation of the scale, subscales and indices. Test-Retest Reliability. Most RSCA scales have at least adequate test-retest consistency across two weeks for both the child and adolescent sample. Test-retest reliability is good for the Index and global scale scores. As expected, adolescents evidenced more consistency over time than children (Prince-Embury, 2007). Test-retest reliability is important if a score is to be used as pre-post measures of the effectiveness of an intervention. High test-retest reliability indicates that changes in the score are more likely due to change in circumstances and are not due to error variance or chance alone. Low test-retest reliability would make it difficult to use the measure for pre-post testing as one would not know whether change in score was due to error variance or intervention. For children ages nine to 14, only the Resource Index meets the criterion for individual longitudinal tracking while the Vulnerability Index, Emotional Reactivity and Sense of Relatedness scale scores meet the criteria for group-level tracking. For
148 Sandra Prince-Embury youth ages 15–18 the Vulnerability Index may be used for individual-level tracking while all of the global scales and five of the subscale scores may be used for group-level tracking. It should be noted that the test-retest samples described are relatively small and these test-retest coefficients should be replicated in additional larger samples. Validity Evidence Validity evidence of a measurement tool is not provided by any single study or statistic, but rather consists of a body of findings demonstrating that the instrument measures what it says it does and may be used in the way that it is intended. One form of validity evidence is concurrent validity which is demonstrated by high correlations between scores on the instrument and scores on relevant other measures. Concurrent validity for the RSCA as a screening tool would be demonstrated by high correlations between the RSCA and other measures of psychological symptoms and other difficulties. Predictive validity is demonstrated by the ability of a cut score to accurately classify cases into relevant criterion groups. Sensitivity is defined as the ability of a score to accurately predict those individuals who have an identified problem. Specificity is defined as the ability of a score to accurately identify those individuals who do not have the problem of concern. False negatives are those students who are missed or who have the problem but who have not been identified as having the problem. False positives are those individuals who are falsely identified and who do not have the problem in question. “Hit rate” is the term used to describe the overall number of individual’s accurately identified. Evidence of Concurrent Validity. Prince-Embury (2007; 2008) reported strong positive correlations between the Vulnerability Index Score and the Emotional Reactivity score and all Beck Youth Inventory—Second Edition (BYI-II; Beck, Beck, Jolly, & Steer, 2004) scores of Negative Affect and Behavior for a non-clinical group of adolescents. The Vulnerability Index score had significant positive correlations with the BYI–II scores of Negative Affect and Behavior: .65 (Anxiety), .66 (Disruptive Behavior), .75 (Depression), and .77 (Anger). Similarly, high positive correlations between the Emotional Reactivity score and scores on all BYI–II scores of Negative Affect and Behavior: .65 with Anxiety, .67 with Disruptive Behavior, .74 with Depression, and .76 with Anger support the hypothesis that a high degree of emotional reactivity is associated with Negative Affect and Behavior. In addition the Vulnerability Index score and the Emotional Reactivity scores correlate with BYI-II scores across affective domains in adolescents and are not limited to any one affective domain. There are also high negative correlations between the Resource Index score and the BYI–II scores of Negative Affect and Behavior: –.51 with Disruptive Behavior, –.53 with Anxiety, –.61 with Depression, and –.62 with Anger. Similarly, high negative correlations were found between the Sense of Mastery (–.51 to –.61) and the Sense of Relatedness (–.45 to –.57) scales and all BYI–II scores of Negative Affect and Behavior. Evidence of Criterion Group Differences. Prince-Embury (2007) reported significant differences between mean scores of clinical groups and matched control groups for children and adolescents. The non-clinical group scored higher on the Resource Index score, Sense of Mastery, Sense of Relatedness scales and subscales. The clinical sample scored higher on the Vulnerability Index, Emotional Reactivity scale and subscale scores. Effect sizes were large for all differences. Discriminant Function Analysis and Classification. Discriminant function analysis reported elsewhere (Prince-Embury, 2008) examined the relative predictive validity of the RSCA Index and scale scores, demographic variables and the psychological symptoms assessed by the
Assessment for Integrated Screening and Prevention 149 BYI-II (Beck et al., 2004). Variables entered as independent variable included the following: (1) parent level of education, (2) gender, (3) RSCA Scale scores (Sense of Mastery T-score, Sense of Relatedness T and Emotional Reactivity T-scores), Index scores (Vulnerability and Resource) and Beck Youth Inventory II scores for Anxiety, Depression, Anger, and Disruptive Behavior. Groups to be discriminated were coded according to clinical status as 0 (non-clinical) or 1 (clinical). The structure matrix reported by Prince-Embury ( 2008) indicated a high loading for both the Vulnerability Index and the BYI-II Anxiety scores on the final discriminant function. The standardized canonical coefficients indicated that the Vulnerability Index contributed more unique variance to the function than did the BYI-II Anxiety score. The canonical correlation for the function was .599 indicating that this function accounted for 36% of the variance in clinical membership. Seventy-seven percent of the original cases were accurately classified. The classification sensitivity was 73% and specificity was 81%. When the Vulnerability Index was entered alone into the discriminant function sensitivity was 79% and specificity was 78%, while the percentage of original cases accurately classified was 78.6%. Therefore, removing the BYI-II from the discriminant function decreased specificity, but increased sensitivity by 6% or 11 clinical cases. In addition, regression analyses conducted with the Vulnerability Index score removed indicate that the Emotional Reactivity Score accounted for most of the variance of the Vulnerability Index when predicting symptoms. The Resource Index score accounted for 1% to 3% of the variance, suggesting a slight ameliorative effect. In summary, validity evidence was the following. 1
2
Significant and high correlations were found between Negative Affect and Behavior (BYI–II scores) and all of the Resiliency Scales and Index scores. The strongest correlations were between the Resiliency Vulnerability Index and Emotional Reactivity scores and the BYI–II scores. Discriminant Function analysis using gender, parent education level, Resilience Scale and Index scores and BYI–II Negative Affect and Behavior scores to predict membership in the clinical versus non-clinical sample indicated the RSCA Vulnerability Index was the best predictor followed by the BYI–II Anxiety score accurately predicting 73% of cases. Emotional Reactivity accounted for most of the predictive variance of the Vulnerability Index score with the Resource Index score accounting for only 1–3% of the variance.
Linking Screening with Preventive Intervention Personal Resiliency Profiles In the previous sections we have discussed the need for universal screening in the schools, and the challenge posed by the task of screening students in a way that does not focus on psychological symptoms alone. We have also discussed the need for screening tools to have adequate psychometric properties while at the same time being easy to use. The Resiliency Scales for Children and Adolescents (RSCA) was presented for use in screening as an instrument that is based on resilience theory and has good psychometric properties. The Personal Resilience Profile is based on RSCA global scale scores (Sense of Mastery, Sense of Relatedness and Emotional Reactivity) and provides a visual tool for better understanding the multiple aspects of personal resilience. The profile presents three scores standardized using the same T metric that, when viewed together, emphasize relative
150 Sandra Prince-Embury 70 60 50 Bobby
40
Linda 30
Joe
20 10 0 Mastery
Relatedness
Reactivity
Figure 7.1 Resiliency Profiles for Bobby, Linda and Joe.
perceived resources and vulnerabilities of children and adolescents. Figure 7.1 displays individual Resiliency Profiles for three students, Bobby, Linda and Joe. Joe’s profile reveals relative vulnerability associated with an Emotional Reactivity T-score of T60 which is high relative to the standardization sample. However, Joe’s Sense of Relatedness and Sense of Mastery are in the average and above-average range. Linda’s Resilience Profile shows that she, like Joe, has high Emotional Reactivity (T60). Linda’s Sense of Mastery and Sense of Relatedness T-scores are both in the average range, close to T50. Bobby’s profile shows a high Emotional Reactivity score also (T60). Unlike Joe and Linda, however, Bobby’s Sense of Mastery and Sense of Relatedness T-scores are low (T37) and below-average (T42). Comparing these three personal Resiliency Profiles, Bobby appears to be most at risk in that his profile suggests high Emotional Reactivity and below-average perceived personal resources with which to manage his emotional reactivity. Joe and Linda, who indicate the same degree of emotional reactivity, also indicate higher levels of Sense of Mastery and Sense of Relatedness with which to manage their reactivity. This example illustrates that individual Personal Resiliency Profiles may be used to examine the relative strengths and weakness of individuals, in order to identify students who are most at risk and/most in need of preventive intervention. Aggregate Resiliency Profiles. In addition to use of the Personal Resiliency Profile to examine individual profiles, aggregate Resiliency Profiles may be compiled to represent the relative strengths and vulnerabilities of groups of youth that share one or more characteristics in common. Figure 7.2 displays aggregate Resiliency Profiles for six groups of adolescents: non-clinical, Anxiety Disorder, Depression, Conduct Disorder, Bipolar Disorder and a group that had been in therapy previously. The Resiliency Profile of the non-clinical group approximates a straight line around a T-score of 50. The Resiliency Profiles of the four clinical groups vary somewhat but share these characteristics in common: high Emotional Reactivity, low Sense of Mastery and low Sense of Relatedness. These similarities suggest that in spite of differences in disorder, youth with clinical disorders have similar Personal Resiliency Profiles.
Assessment for Integrated Screening and Prevention 151 70 60 50
Non Anxiety Depression Conduct Bipolar Nonspec
40 30 20 10 0 Mastery
Relatedness Reactivity
Figure 7.2 Resiliency Profiles for Clinical and Non-Clinical Adolescent Groups. Resiliency Scales for Children and Adolescents—A Profile of Personal Strengths. Copyright 2006 NCS Pearson, Inc. Reproduced with permission. All rights reserved.
Multi-Tiered Universal Screening Using the RSCA Index Scores The relationships between the three global RSCA scores illustrated in the profiles above may be quantified and expressed in two Index scores. The Resource Index combines the Sense of Mastery and Sense of Relatedness scale scores. The Vulnerability Index score quantifies the difference between the Emotional Reactivity scale score and the Resource Index score. As illustrated in Figure 7.2, this discrepancy is visible across clinical groups. Validity evidence suggests that the Vulnerability Index may be used as a first-line predictor in accurately classifying clinical status (Prince-Embury, 2007). Therefore, Tier 1 screening first uses the Vulnerability Index to identify students who may be at-risk for developing clinical symptoms and other difficulties. Students who have Vulnerability Index T-scores in the above-average or higher ranges are screened for further examination. Table 7.1 shows three Vulnerability Index score ranges, above-average, high and very high, for three age bands. The cut score for screening ultimately depends on how wide a screening net is desired as well as the relative resources available to the school. Table 7.1 shows that a cut score of T55 on the Vulnerability Index score would identify approximately 30% of a normative sample as above-average. A cut score of T60 would identify approximately 16% of the sample as high and a cut score of T65 would identify approximately 9% of the sample as very high. A multi-tiered screening model for identification of individual students at-risk for social and emotional problems is illustrated in Table 7.2. This model begins with the Vulnerability Index score and follows up with the Emotional Reactivity scale score and Resource Index scores taking the steps indicated in Table 7.2. Table 7.1 T-Score Ranges for the Vulnerability Index and Cumulative Percentages by Age Band Range
T-Score Range
9–11
12–14
15–18
Very High High Above Average
>64 60–64 55–59
91+ 84–90 70–83
92+ 83–91 70–82
91+ 87–90 76–86
152 Sandra Prince-Embury Table 7.2 RSCA Screening Model 1: Individual Level 1. First Tier: using the Vulnerability Index score. If the Vulnerability Index score is T55 (above average) or higher, monitor by retesting in three to six months. 2. Second Tier: If the Vulnerability Index score is T60 (high) or higher and if Emotional Reactivity Score is T60 or higher, then students may be identified for preventive intervention addressing management of emotional reactivity. 3. Third Tier: If the Resource Index is T40 or below, examine the Sense of Mastery and Sense of Relatedness scale scores to determine specific areas for preventive intervention. If the Sense of Mastery Score is T40 or below refer for preventive intervention pertaining to Sense of Mastery, self-efficacy, adaptability. If the Sense of Relatedness is T40 or below, refer for preventive intervention pertaining to Sense of Relatedness, social skills, communication skills, etc.
To illustrate how the RSCA Index and scale scores might be used for universal screening, the following example is provided. If the RSCA was administered to a school population of 1,000 at the beginning of the academic year, Tier 1 might identify 300 students as above-average in vulnerability, using a Vulnerability Index score equal to or greater than T55. This group would be monitored by retesting in three months. Of these 300 students, approximately 150 students might have Vulnerability Index scores equal to or greater than T60, identifying them as potentially high in vulnerability and warranting preventive intervention. Of this identified group of 150 students, approximately 135 students would also have Emotional Reactivity T-scores equal to or greater than T60. This group would be identified as potentially high in emotional reactivity and potentially in need of preventive intervention aimed at reducing emotional reactivity. In addition, 110 students would have Resource Index scores equal to or less than T40, suggesting that these students are low in resources and warrant preventive intervention to enhance resources. Approximately 85 of the 150 students would meet these criteria: Vulnerability Index and Emotional Reactivity scores of T60 or above, as well as Resource Index scores of T40 or below. Preventive intervention based on the hypothetical screening for the 1,000 students provided above might include the following: intervention on managing emotional reactivity for 40 students; intervention for enhancing personal resources for 25 students; both interventions for 85 students. Outcome Assessment One advantage of systematic screening and targeted intervention is that outcome assessment can be implemented to determine whether a preventive intervention had a positive impact on the targeted aspect of personal resiliency. The importance of outcomes assessment is underlined by the fact that it is easier to convince policymakers of the importance of implementing preventive interventions that are empirically supported. To the extent that preventive interventions are implemented prior to the appearance of symptoms, positive outcomes often need to be inferred from the observation that symptoms did not occur for a specified period of time during and after the intervention. Screening with the RSCA provides another option for the assessment of impact. For example, interventions designed to assist with lowering emotional reactivity could be evaluated based on their effectiveness in producing lower scores on the RSCA Emotional Reactivity scale. Similarly, interventions designed to increase sense of mastery could be evaluated based on their effectiveness in producing higher scores on the RSCA Sense of Mastery
Assessment for Integrated Screening and Prevention 153 scale while those designed to increase sense of relatedness could be evaluated based on their effectiveness in producing higher scores on the RSCA Sense of Relatedness scales. Using the hypothetical example, the above outcome assessment could proceed as follows. The 300 students identified as above-average on the Vulnerability Index score (> T55) during universal screening would be retested three months later. If the first testing occurred at the end of September, the second testing might occur in the middle of December. During this three months, preventive interventions would be implemented in October and November for the group of 150 students identified with Vulnerability Index and Emotional Reactivity scores equal to or above T60 (the high vulnerability range). In January and February, RSCA scores at first and second testing would be compared for students in the identified group who had not received the intervention as well as for students who had received the intervention. Analysis of preventive screening and intervention would address the following questions: 1
2
Did any significant changes occur over time in the group of students who had scored above-average on the Vulnerability Index but had not participated in any intervention? Significant changes that may have occurred at the aggregate level for the nonintervention group could be examined to determine whether these changes were related to school-wide events or circumstances, or whether these changes reflected changes for a few specific individuals in this group. Students in the non-intervention group whose Vulnerability Index score had increased by five T-score points or entered the high range might be considered for preventive intervention in April or May of the academic year. Did any significant changes occur between pre- and post-intervention testing of the intervention group? For example, did the average Vulnerability Index score for the Intervention group decrease by five or more T-score points? Were these changes consistent with the specific intervention received? For example, did students receiving preventive intervention to manage emotional reactivity manifest lower Emotional Reactivity scale scores post-intervention? Students in the intervention group whose Vulnerability Index scores remained high might be considered for additional intervention.
The importance of psychometrically sound outcome assessment is highlighted by the fact that solid evidence of statistically significant change underlies empirical support for preventive interventions. Empirically supported interventions provide solid argument in favor of funding for widespread implementation of such interventions. Classroom Screening Applications Although applications discussed thus far have focused on identification of individual students who might benefit from preventive intervention, there are other potential benefits of universal screening using an instrument such as the RSCA. For example, Doll et al. (2004) describe the use of the ClassMaps survey for the purpose of selecting classrooms and interventions to enhance classrooms’ resilience. The RSCA scores may be used in a similar way to supplement the ClassMaps approach. Schools that administer the RSCA may aggregate RSCA scores within classrooms rather than focusing on individual scores. In this way classrooms rather than individual students may be identified as high in Vulnerability or Emotional Reactivity, or low in Sense of Mastery or Sense of Relatedness and classroom interventions could be designed accordingly. Use of the RSCA with an aggregated classroom approach as suggested by Doll, Zucker and Brehm in the Resilient Classroom (2004) is described in Table 7.3.
154 Sandra Prince-Embury Table 7.3 Screening Model II for Aggregate Classroom Level a b c d e
At-risk classroom identified by aggregate class scores on RSCA using Vulnerability Index score T60 or higher. At-risk classrooms examined to see if high score are due to presence of individual at-risk outlier score (individual RSCA Vulnerability Index scores T65 or higher). ClassMaps administered to all at-risk classrooms to determine classroom characteristics that need attention. RSCA class Resiliency Profiles and ClassMaps profiles examined for high risk classrooms to determine appropriate interventions. Pre- and post-intervention comparisons made to determine if intervention was successful.
Impact of Unanticipated Events Another application of universal screening that occurs regularly at the beginning and end of the academic year is describing the potential impact of anticipated and unanticipated circumstances. For example, much work has been done to assess the impact of a disaster on children and adolescents after its occurrence. Due to the absence of pre-disaster measurement, impact of the event is a matter of inference. If universal screening data had been collected, it would be possible to compare pre- and post-event status of a school’s students. Resiliency and Academic Achievement Finally, resilience in children and adolescents is related to many aspects of their functioning in an educational setting including academic achievement, school attendance, dropout rate, etc. Universal resilience screening would make it possible to assess variables other than cognitive ability that influence the ability of students to benefit from the education that is provided for them.
Assessment-Based Preventive Interventions Preventive interventions are many and a comprehensive discussion of these interventions is clearly beyond the focus of this paper. This section is intended to provide examples of preventive interventions that are linked with specific RSCA scores and the developmental constructs underlying these scales. RSCA prevention strategies may be based on the personal resiliency profiles of children and individuals, and may be focused on groups or individuals, across age band. Such theoretical consistency allows for more systematic assessment of whether interventions targeted to foster resiliency in a certain way do in fact impact children and adolescents in that way. This moves assessment of efficacy of intervention from a simple “Does it work or doesn’t it?” to the more complex assessment of “How does it work?” It is recognized that personal resiliency, although based on core developmental constructs, is highly complex in nature. For this reason, interventions designed to achieve one type of goal may impact other aspects of youth functioning. It is for this reason that a robust multi-factored assessment tool is needed. According to the RSCA framework provided above, child-focused preventive interventions may be broadly considered as vulnerability-reducing, resource-enhancing or some combination of both. The RSCA research mentioned above (Prince-Embury, 2008) suggests that prevention of psychopathology should first address psychological vulnerability associated with high emotional reactivity. In the clinical experience of the author, efforts at enhancing resources while emotional reactivity is high may be less effective than when emotional reactivity is lower.
Assessment for Integrated Screening and Prevention 155 Interventions to Reduce Personal Vulnerability: Emotional Reactivity
Scaled scores
Youth who have very high Emotional Reactivity scores (T65 or higher) should be referred for further assessment. Such youth are usually found to have very high BYI-II Anger, Depression and/or Anxiety Scaled scores and may benefit from psychoactive medication to reduce their reactivity. For these students, intervention may include referral for medication evaluation as well as training in monitoring and controlling emotional reactivity. Re-administration of the RSCA Emotional Reactivity scale two or three weeks after beginning medication may indicate whether the medication is helping. For youth who have higher-than-average emotional reactivity, but who are not in the highest range (T55–T64), preventive intervention may focus initially on intentional management of emotional reactivity. This preventive strategy might start by helping the youth to identify emotional reactivity as a potential source of vulnerability. Some youth may already be aware of this, but others may need time to fully understand the connection. Awareness may be enhanced by breaking emotional reactivity down into the more discrete and observable components of sensitivity, recovery and impairment. Once these constructs are understood by the youth in terms of his or her own experience, strategies for self-monitoring and eventual self-management are possible. This section discusses some assessment-linked tools for helping children and adolescents to identify and manage emotional reactivity. These tools may be used individually and in groups. The techniques focus on identifying triggers for emotional reactivity and helping youth quantify and communicate the difficulty they have in various types of situations. Figure 7.3 illustrates that clinical groups of adolescents are above-average or high on the three subscales of the Emotional Reactivity Scale. Intervention tools described below address the personal attributes addressed by each subscale separately although the tools may be administered simultaneously. Pre- and post-intervention comparison of each subscale score might help in evaluating the specific impact of prevention strategies designed to address aspects of emotional reactivity. 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0
Non clinical Depression Anxiety Conduct disorder Bipolar disorder Non specific
Sensitivity
Recovery
Impairment
Figure 7.3 Emotional Reactivity Subscale Profiles. Resiliency Scales for Children and Adolescents—A Profile of Personal Strengths. Copyright 2006 NCS Pearson, Inc. Reproduced with permission. All rights reserved.
156 Sandra Prince-Embury Interventions to Enhance Resources
Scaled scores
Interventions targeting Resource Enhancement would be implemented when Resource Index scores are low (T44 or lower). The specific type of intervention implemented would be determined by the Personal Resiliency Profile which distinguishes between Personal Resources associated with Sense of Mastery and Personal Resources associated with Sense of Relatedness. Low Sense of Mastery scale scores might trigger interventions focused on increasing students’ sense of mastery. Interventions Targeting Sense of Mastery. Low Sense of Mastery scale scores (T44 or lower) might trigger interventions focused on increasing students’ sense of mastery. Research, theory and interventions for children have tended to combine the constructs of Optimism and SelfEfficacy (i.e., Seligman’s Optimistic Child, 1995). The Resilience program at the University of Pennsylvania employs cognitive behavioral techniques to overcome depression in children (Reivich, Gilham, Chaplin, & Seligman, 2005). Cognitive behavior treatments for depression are based on the belief that depression is based in part on a triad of hopelessness about the future, oneself and the world in general. Consistent with this assumption, many treatments focus on challenging negative assumptions and encouraging more positive reframing of beliefs. Approaches that are based on increasing self-efficacy may increase opportunities for success, so that youth can be reinforced by the experience of themselves as successful. The RSCA Sense of Mastery scale score makes it possible to assess whether preventive interventions designed to promote optimism and self-efficacy in youth actually do so. Subscales that make up the Sense of Mastery scale make it possible to estimate impact on specific aspects of sense of mastery represented as subscales tapping optimism, self-efficacy and adaptiveness. Figure 7.4 displays aggregate Sense of Mastery subscale profiles for non-clinical and clinical adolescent samples. These profiles suggest that all subscales are low for most of the clinical groups particularly the depressed group. 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0
Non clinical Depression Anxiety Conduct disorder Bipolar disorder Non specific
Optimism
Self-efficacy
Adaptability
Figure 7.4 Sense of Mastery Subscale Profiles. Resiliency Scales for Children and Adolescents—A Profile of Personal Strengths. Copyright 2006 NCS Pearson, Inc. Reproduced with permission. All rights reserved.
Assessment for Integrated Screening and Prevention 157 The following interventions, described in the RSCA manual (Prince-Embury, 2007) are examples of preventive interventions targeting increased Sense of Mastery. Although these interventions might effect change in all three subscales of the Sense of Mastery scale they are specifically targeted to improve sense of self-efficacy. Strength Identification. Adolescents who have experienced more failure than success in their lives may have lost the ability to identify their own strengths. For such youth, it is helpful to provide preventive interventions that help them remember and identify positive experiences associated with hidden, forgotten, buried, or uncultivated strengths. Block and Block (1980) originally coined the term “islands of competence” and Brooks and Goldstein (2001) have recently expanded this concept with numerous clinical examples of identifying islands of competence to enhance resilience in youth. In addition, once areas of strength are identified, preventive intervention may further identify, elaborate, enhance, and generalize these strengths. These interventions can help youth generalize their strengths to other areas where they may not feel as successful. Structured preventive interventions might also help youth identify specific skills and think about how these skills could be employed in other areas. Preventive Interventions Targeting Sense of Relationship Preventive interventions focusing on relatedness frequently emphasize increasing social skills, assuming that low sense of relatedness is related to lack of social skill. The ability to relate to others and to gain strength and resilience from these relationships is a multi-faceted and complex process. Relating to others is particularly important in adolescence as teenagers prepare for adulthood and attempt to be more independent of parents. Those who have worked with adolescents hear reports of feeling lonely, isolated, unpopular, popular but fearful of losing their status with a particular group of peers, or being the victim of bullying behavior by others. These relationship difficulties are frequently reported in relatively simple terms and often reflect the outcome of more complex interpersonal processes. Subscales of the Sense of Relatedness scale suggest aspects of relatedness that might be identified and targeted as outcomes when designing preventive interventions. Figure 7.5 displays Sense of Relatedness subscale scores for adolescent clinical groups as compared with a non-clinical sample. Two of the clinical groups display mean subscale scores in the below-average or low range, the Depression and Conduct Disorder groups. The Relationship scale and subscale scores may be used to track impact of interventions designed to improve sense of relatedness in children and adolescents by comparison of pre- and postintervention scores on these subscales. For example, adolescents who score low in access to support subscale scores frequently have difficulty communicating with their peers and or their parents. Interventions targeting these specific areas might yield changes in this specific subscale score. Perceived Social Support. Developmental theorists have acknowledged the significance of perceived social support for intervention. Research has indicated that an individual’s perception that social support is available and accessible is the most important dimension of social support (see Hogan, Linden, & Najarian, 2002). Thompson, Flood, and Goodvin (2006) suggest that it is sometimes more important to focus on youths’ subjective experience of supportiveness by carefully examining their expectations of support and how these are or are not discrepant from the support that they perceive to be provided by others. Thompson et al. also suggest that troubled youth may be less capable of viewing others as sources of available support because of their emotional turmoil, and youth in difficulty may be less able to mobilize supportive networks when they are needed. These ideas highlight the need to
Scaled scores
158 Sandra Prince-Embury 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0
Non clinical Depression Anxiety Conduct disorder Bipolar disorder Non specific
Trust
Support
Comfort
Tolerence
Figure 7.5 Sense of Relatedness Subscale Profiles. Resiliency Scales for Children and Adolescents—A Profile of Personal Strengths. Copyright 2006 NCS Pearson, Inc. Reproduced with permission. All rights reserved.
explore the supports identified by children and adolescents before a time of crisis, so that they can objectively reflect on the support and think of how they might ask for help in different circumstances.
Summary: Implications for Screening and Intervention Programs In summary, the premise of this chapter asserts that screening in schools should be proactive, detecting personal vulnerability or those who may lack personal resiliency, as opposed to symptom-based which is reactive and pathologizing. A proactive method provides the opportunity to screen and intervene with children before psychological symptoms have occurred. From a classroom management perspective, once symptoms occur they have already had a chance to disrupt the learning of a symptomatic youth as well as others in the classroom environment. From the perspective of family and community relationships, screening based on personal vulnerability is non-stigmatizing and thus may be shared with youth and their parents in useful and non-alienating ways. From a broader child mental health perspective, allowing symptoms to occur runs the risk of allowing these symptoms to crystallize and to further compromise normal development. As we know, symptoms which have crystallized into psychological disorders are more difficult and costly to treat. In addition, screening based on symptoms alone runs the risk of only identifying children with externalizing symptoms or those symptoms that are most visible to others. Thus a symptom-based model of screening may run the risk of allowing youth with internalizing symptoms to slip through the cracks. If, as educators, we propose that the purpose of screening is not just identification but also intervention we should consider the utility of the screening tools that we employ for this
Assessment for Integrated Screening and Prevention 159 purpose. Screening based on personal vulnerability and personal resources bypasses symptoms and is based on etiology of problems. Screening using the RSCA has inherent in it the identification of areas of personal strength (sense of mastery and sense of relatedness) and personal vulnerability (emotional reactivity) which are rooted in developmental theory. In this way, well established principles of development may guide universal and individual levels of preventive intervention. To aid in this process, examples of specific interventions for strengthening sense of mastery and sense of relatedness and minimizing emotional reactivity have been provided in this chapter. Finally, assuming agreement on all of the principles above, the bottom line for school administrators and funding sources is, “Does it work?” For this reason we need screening tools that are simple to administer and score and which have excellent psychometric properties of reliability and validity. This chapter presents the Resiliency Scales for Children and Adolescents as a nationally normed assessment tool with demonstrated reliability and validity. The advantages of psychometric strength are multiple: credibility in obtaining funding, integrity of assessment and the ability to effectively assess relative success of targeted interventions. In closing we are well aware of the daunting nature of translating good ideas into practical application. For this reason we have included in this chapter two examples of screening programs using the RSCA: one based on screening for individual children who are at risk and one based on classroom screening. We have also included an example for using the RSCA to assess outcomes of preventive interventions. These examples are provided as helpful guidelines to be modified to fit the specific needs of individual school systems.
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Social Support How to Assess and Include It in Research on Prevention and Youth Outcomes Michelle K. Demaray, Christine K. Malecki, Lyndsay N. Jenkins, and Christy M. Cunningham, Northern Illinois University
Even for people not well-versed in research, intuitively social support seems essential for a positive, healthy life for people throughout the lifespan. Focusing on childhood and adolescence, it is easy to see how having a loving, caring parent; a supportive, honest, and sharing friend; or an information-sharing, accessible teacher would be building blocks for positive well-being. Researchers seem to agree, and have conducted a great deal of work examining the relationship between social support and many positive outcomes in youth (Demaray & Malecki, 2002; Demaray, Malecki, Davidson, Hodgson, & Rebus, 2005; DuBois, Felner, Brand, Adan, & Evans, 1992; Jackson & Warren, 2000) as well as the negative relationship of social support with distress and problem behaviors (Sheeber, Hops, Davis, & Andrews, 1997; Wills & Cleary, 1996; Windle, 1992; Zimmerman, Ramirez-Valles, Zapert, & Maton, 2000). Thus, social support is a critical variable for prevention research and programming to focus on when developing or evaluating prevention efforts. Many types of interventions can be perceived as increasing social support, even though different terminology may be used. For example, a group intervention with victims of bullying in schools may focus on teaching specific social skills to victims for dealing with future bullying. However, an important outcome of this group may also be increased emotional social support among the group members and the development of supportive networks or bonds. In addition, from the broad definition of social support presented above, providing information, such as concrete skills to deal with bullying, is also a type of informational social support. Social support is often present in many prevention efforts and assessing students’ perceptions of social support is important for understanding the specific mechanisms in the interventions that are making a difference. For example, in the victim group described above, is it the teaching of specific skills to victims for dealing with bullying or is it the building of emotional bonds with fellow victims that may be related to positive outcomes for victims? The focus of prevention programming to prevent youth problems and promote healthy children and youth has increased in recent years (Small & Memmo, 2004). Especially with the 2004 reauthorization of the Individuals with Disabilities Education Act, the use of prevention practices in schools has received increased attention (Glover & DiPerna, 2007). Following a three-tiered model of prevention, the Response to Intervention (RtI) model is actively being applied to school settings. Although there is a renewed interest in prevention, prevention efforts and three-tiered models of prevention have been around for a long time and have strong support (Kratochwill, Volpiansky, Clements, & Ball, 2007). This chapter will not go into depth on the definition and models of prevention which are presented thoroughly in the first chapter (and other chapters) of this book. However, the importance of social support and how it relates to prevention and youth outcomes will be highlighted. Furthermore, assessment methodologies for including social support in prevention research will be detailed,
164 Michelle K. Demaray et al. and a few current prevention studies that have included the construct of social support will be reviewed.
Social Support Based on the work of House (1981), Tardy (1985) developed a comprehensive framework to conceptualize the construct of social support. His model describes five different issues that are theoretically and operationally relevant in defining the multi-dimensional construct of social support: direction, disposition, description/evaluation, content, and network. While Tardy conceded that these five issues are not exhaustive, he did suggest that they encompass the primary elements of social support, and recommended explicit discussions of these issues in each study so that conceptualizations of social support are clear. In addition, recent developers of children’s social support measures have cited Tardy’s work and highlighted the need to consider the usefulness of these five key dimensions (Malecki & Demaray, 2002; Zimet, Dahlem, Zimet, & Farley, 1988).
Tardy’s Model of Social Support Direction. Are you more interested in the social support someone is giving or the social support someone is receiving? The concept of direction focuses on who is giving the social support and who is receiving it. Disposition. What matters most, whether social support is available to you or if you have actually used that social support? A common situation that reflects available support is when a young woman takes her first babysitting job at a neighbor’s house. If her mother is at home, a few doors away, she knows that she can call her mom for advice or help if something were to happen. Knowing that this support is available provides a sense of security in the new, unfamiliar situation. There may be benefits to knowing that support is available even if it is not utilized. Taking available support one step further, is it important to measure the perceptions of available support, which may be different from what support is really available. For example, teachers may be available to students after school and during prep times but if a student is not aware of that, they will perceive less support than is really available to them. It could be argued that it is the perception of the support that truly matters in the lives of youth. An adult may believe a child/student is supported, but if youth do not perceive being supported, that will influence the outcomes related to social support. Description/Evaluation. Students may be asked to describe the social support they perceive or they may be asked to evaluate that support. What is most important, the amount of support a student perceives/receives or how satisfied he or she is with it? Content (Type). The four types of support (emotional, instrumental, informational, and appraisal) that Tardy (1985) compiled from the literature are important to consider when defining and studying social support. Emotional support is what is typically thought of when asked about social support; it is feeling loved, cared for, and a sense of belonging. Instrumental support consists of providing resources to support the youth (e.g., time, money, physical resources). Providing youth with necessary and important information and knowledge is informational support and providing them with feedback about their performance and functioning is appraisal support. Network (Source). The people who are providing (or are available for providing) social support are an important factor to consider. For example, the research is clear that there are
Social Support 165 differences in the support that children and adolescents perceive from parents versus friends, or that they perceive from teachers versus parents. Who, then, are the key players in students’ lives? There are developmental changes in the people that children and adolescents rely on for support over time (Cauce, Felner, Primavera, & Ginter, 1982; Furman & Buhrmester, 1985). Thus, if global social support is examined rather than support from specific sources, we may miss potentially important information. Theoretical Basis of Social Support Cohen and Wills (1985) noted that there is a vast amount of evidence documenting the positive correlation between social support and well-being, but speculated that there were different processes at work. Two primary theoretical orientations drive the majority of the literature on social support: the stress-buffering theory and the main effect theory (Cohen, Gottlieb, & Underwood, 2000). When the positive effects of social support are in response to stress or risk status, the stress-buffering theory is at work (Barrera, 1986; Cohen et al., 2000; Cohen & Wills, 1985). The stress-buffering theory makes sense when studying resilience. For students to be considered “resilient,” by definition they must have conditions in their lives that place them at-risk. Social support may be one protective factor that contributes to their resilience. If a youth’s baseline level of social support is not adequate to provide beneficial effects, maybe because the child has extra stressors in his or her life, focusing on increasing social support via group interventions (i.e., secondary prevention) or individualized interventions (i.e., tertiary prevention) may buffer the child or adolescent from negative outcomes. Alternatively, the main-effect theory advocates that social support has a positive benefit for all children and adolescents regardless of any specific stressors or risk circumstances (Cohen et al., 2000; Cohen & Wills, 1985). The main-effect model suggests that access to social support improves students’ overall psychological well-being and therefore reduces psychological problems (Cohen et al., 2000). Thus, it logically follows that having sufficient levels of social support for all students (i.e., primary prevention) is an important goal for schools and prevention programs. There is evidence for both the stress-buffering and the main effect models depending on the way that support is measured. Measures of social support that assessed available interpersonal resources during times of stress provided evidence for the buffering model. But when the measure of social support measured the degree to which a person was a part of a social network, there was evidence for the main effect model. Generally, both models may be used as tools in explaining the role of social support in the lives of resilient children, but most typically, the stress-buffering model will be most relevant.
Social Support and Youth Outcomes The goal of this section of the chapter is to review selected studies that investigated the relationship of social support to various youth outcomes. Some of these studies found main effect relations for social support—that social support was associated with beneficial outcomes regardless of a specified risk—while the remaining studies investigated the stress-buffering role that social support serves for youth identified as at-risk. These selected studies have examined the impact of social support on outcomes for specific groups of children and adolescents, including those victimized by peers, HIV-positive youth, adolescents experiencing acculturation related to immigration into the United States, and students considered at-risk based on socioeconomic status.
166 Michelle K. Demaray et al. Social Support and Main Effect Role Social support has been found to be positively related to a wide variety of outcomes, thus demonstrating a main effect role. A study by Demaray et al. (2005) investigated a longitudinal relationship between social support and student adjustment in a sample of 82 middle school students. Student adjustment was measured by the Behavior Assessment System for Children, Self Report of Personality (BASC; Reynolds & Kamphaus, 1998), a broad-band measure of student’s emotional well-being. The results showed significant relationships between parent support and clinical maladjustment (a measure of internalizing problems) and emotional symptoms (assesses anxiety, social stress, depression, sense of inadequacy, interpersonal relations, and self-esteem); classmate support was related to emotional symptoms; and school support was related to school maladjustment (a measure of dissatisfaction with school). Social support was measured via the Child and Adolescent Social Support Scale (Malecki, Demaray, & Elliott, 2000), which measures the frequency of social support from five different sources (parents, teachers, classmates, close friend, and school) as well as four different types of social support (emotional, appraisal, instrumental, and informational). The relationship between social support and academic well-being was investigated in a large sample of Latino youth (DeGarmo & Martinez, 2006). This study demonstrated a main effect as well as a stress-buffering role of social support. Academic well-being was assessed by four variables: GPA, frequency of homework completion, students’ evaluations of their own academic performance, and a question about how likely the student was to drop out of school. Via structural equation modeling, they found that social support was significantly related to higher levels of academic well-being. This main effect relationship was found for overall support and for support from parents and the school. The researchers also found that social support from parents buffered the relationship between discrimination and poor academic well-being. This study demonstrates that social support may play a main effect role as in the relationship between social support and academic-well-being and also play a buffering role, as in the relationship between discrimination and academic well-being. A study by Atri, Sharma, and Cottrell (2007) examined the main effect role of social support, along with acculturation and hardiness on mental health, in Asian Indian international students. These researchers found that social support, primarily the belonging aspect of social support, was positively related to mental health. They concluded that belonging support, also referred to as companionship support, is important for the mental health of individuals migrating to different countries; thus experiencing empathy, caring, trust, and reassurance is important for these individuals. Atri et al. (2007) assessed social support via a version of the Interpersonal Support Evaluation List, which is a 12-item scale that assesses the perceived availability of three types of social support: belonging support, appraisal support, and instrumental support. In addition to the main effect role of social support in the health of individuals who have immigrated to a new country, a stress-buffering role may be present and is described in an additional study below. Social Support and the Stress-Buffering Role Davidson and Demaray (2007) examined social support as a moderator in the relationship between peer victimization and internalizing and externalizing distress from bullying. They found that social support buffered the relationship between peer victimization and internalizing distress, but not externalizing distress. Thus, Davidson and Demaray concluded that social support may be serving a protective function against internalizing problems for individuals
Social Support 167 who are victims of bullying. Children and adolescents who are victims of bullying often report many mental health difficulties, including anxiety and depression, poor school adjustment and poor social competence, so these findings are promising. For the study, social support was measured via the Child and Adolescent Social Support Scale (Malecki et al., 2000), which is a comprehensive 60-item measure that measures the frequency of social support from different sources (parents, teachers, classmates, close friend, and school) as well as different types of social support (emotional, appraisal, instrumental, and informational). Another study examined the relationship of social support with the mental health of HIVpositive adolescents and young adults. Research has shown that these individuals are at risk for mental health problems that can impact their quality of life and physical well-being (Lam, Naar-King, & Wright, 2007). This study found that social support buffered against the negative mental health concerns that commonly arise in HIV-positive youth, such as depression and anxiety. The researchers used an abbreviated version of the Social Provision Scale (Cutrona & Russell, 1987), which consisted of 12 items that asked participants about relationships with people in their lives. A recent study examined the stress-buffering relationship of social support on the mental health of adolescents and young adults that had immigrated to a different country. Oppedal, Roysamb, and Sam (2004) in Norway examined the impact of social support in the relationship between acculturation and mental health among junior high students who immigrated to Norway. They found that low support from family or friends along with low ethnic competence (low levels of acculturation) yielded significant negative effects on mental health. Additionally, when individuals experienced discrimination as well as low family and class support, mental health was negatively affected. They determined that there were complex interactions between social support, acculturation status, discrimination, and mental health, but that low levels of social support were consistently linked to mental health difficulties. This study used an unpublished scale of social support that was based on research by Cohen and Wills (1985), Hesbacher, Rickels, Morris, Newman, and Rosenfield (1980), and Ystgaard (1997). The scale measured two types of social support (emotional and instrumental) from four different sources (family, class, friend, and teacher). Another study examining the protective factors of social support was conducted by Malecki and Demaray (2006). Although weak and mixed findings were found for a main effect relationship between social support and academic performance, these researchers found that social support buffered the relationship between low socioeconomic status (SES) and academic performance. Therefore, students who lived in poverty were less likely to have poor academic outcomes if they had higher levels of social support than those students who lived in poverty and had lower levels of social support. In this study social support was assessed via a rating scale, the Child and Adolescent Social Support Scale (CASSS; Malecki, Demaray, & Elliott, 2000) that assessed four types of support (emotional, appraisal, instrumental, and informational) from five sources (parents, teachers, classmates, close friends, and school). The above summarized research is a small sample of the research that focuses on the role of social support in the lives of children and adolescents. The studies clearly indicate that for some outcomes there are beneficial aspects of social support for all individuals (main effect). This is important as one thinks about the role of social support in primary prevention programs. The research also demonstrates that, at times, social support may play more of a buffering role and aid children and adolescents who are at risk. Again, this is important as researchers think about the roles of social support in secondary and tertiary intervention programs. There were also several examples where social support played both a main effect and stress-buffering role; indicating that social support may be important at various levels of prevention. Although
168 Michelle K. Demaray et al. the research reviewed was not necessarily focused on prevention programming, it demonstrates the important relationships that may be present between social support and the wide variety of youth problems practitioners are trying to prevent. In order to assess students’ perceptions of social support in research focused on prevention programs and youth outcomes, the researcher needs to adequately assess the construct. A brief overview of assessment of social support is provided next.
Measurement of Social Support Social support can be measured via four primary orientations. Researchers or clinicians can use measures of one’s network size, measures of social integration, measures of functional support, and/or measures of social status. Network Analysis Using network analysis, participants are asked to provide the number of people that are in their social support network (i.e., Tardy’s sources). Additionally, some network analyses measure the density of a network by measuring how someone’s network members know each other. For example, if there are five people who support an individual, and those five people know each other, that network will be stronger than a network of five people who do not know each other. If they are connected with one another, network members can collaborate and combine efforts in providing support. Network analysis is done simply by asking questions such as “List all of the people in your life that are there for you when you need them.” or “How many people do you have in your life that support you?” For network density, participants can be prompted to draw lines connecting the people who know one another on the list. Often network analysis (if measuring density) can be done graphically (Gottlieb, 2000). Social Integration One can also measure social support via social integration which is measured by the number of different types of social relationships one has in their life. For example, a parent–child relationship, a coach–player relationship, a brother–sister relationship, and a mentor–mentee relationship would make up four distinct types of relationship roles, all supportive. Additionally, researchers interested in social integration as a way of measuring social support would want to know how frequently someone participates in the social activities with which they are involved (Brissette, Cohen, & Seeman, 2000). If a child is in softball and violin, how often do those organizations meet? How many people are involved in those activities? How connected does the child feel to those activities? Does participation in those activities provide the child with support? Social Status Sociometric analysis compiles techniques and methods for determining social networks and the social status of individuals. Several methods to determine this have been established, including a process in which respondents are asked to write names of people in the class whom they like and dislike (Kaya, 2007). Another method, derived from Newcomb and Bukowski (1983), includes nominating each person for both sympathy and antipathy nominations.
Social Support 169 From the scores obtained for either of these methods, a classification for each respondent is derived: popular, rejected, neglected, controversial, and average (Maassen, Akkermans, & Van Der Linden, 1996). These status categories enable researchers to determine other characteristics, which often coincide with these labels. For instance, Kaya (2007) noted that children identified as popular often exhibit higher self-esteem, better academic and social skills, and are less likely to use substances, while children identified as neglected tended to be more aggressive and less compliant. One might surmise that students of popular or average status perceive higher levels of support than students of neglected or controversial status. While such status information can be helpful in determining which students may need further attention, sociometry has been a controversial technique due to its very nature. According to Bell-Dolan and Wessler (1994), despite the usefulness of sociometry, many parents, teachers, ethics review committees, and researchers are concerned about the nominating nature of this method. In the process of obtaining the information, participants may disclose with each other their choices of who they like or dislike in the class. This could yield conflict or distress between the participants if one was chosen over another. While respect and understanding must be given at all times while performing a sociometric survey, the data from a survey this controversial can produce significant information regarding a student’s social and emotional growth. Another form of peer evaluation includes teacher nomination which can avoid possibly negative associations related to peer assessments (Kaya, 2007). Direct Observations Observations can be used to measure the functional aspects of social support. Researchers could observe interactions and code the frequency, quality, type, source, and level of support. This is advantageous in that the researcher is not relying on student perceptions and can view supportive behaviors in the natural environment. However, there are practical reasons why this is not typically feasible (e.g., time-intensive, expensive). Additionally, it may be important to still measure perceptions of support. If one observes a great number of supportive interactions, but the recipient does not perceive those interactions as supportive, that is important information to gather. Functional Support Approaches By far the most common method of measuring social support is through a functional approach using rating scales. Typically rating scales adhere in some form to Tardy’s model (1985) of social support and tap some or all of the dimensions in the model (i.e., source, type, direction, evaluation, etc.). Often rating scales measure only the frequency of one or two types of support. However, influenced by the stress-buffering model of social support, rating scales can have items that ask about support in response to a specific stressor. For example, if researchers are investigating how social support might buffer a student’s response to being bullied, they could use a rating scale that asks about specific supportive behaviors that are available to them regarding being bullied. Some measures also include ratings of negative interactions (Brissette et al., 2000). Although someone may have a supportive relationship in his or her life, it may be important to look at the ratio of positive to negative interactions in that relationship. If the same person who provides someone with a great deal of support is also someone that causes conflict or stress in his or her life, that is important information to consider.
170 Michelle K. Demaray et al. Frequently Used Measures of Social Support with Children and Adolescents A review of the social support literature from 2000 to 2003 (four years; 290 studies reviewed) listed the six most commonly used measures in the child and adolescent research (Malecki, Demaray, & Rueger, 2008). These measures included the Child and Adolescent Social Support Scale (Malecki, Demaray, & Elliott, 2000), the Multidimensional Scale of Perceived Social Support (Zimet, Dahlem, Zimet, & Farley, 1988), the Network of Relationships Inventory (Furman & Buhrmester, 1985), the Social Support Questionnaire (Sarason, Levine, Basham, & Sarason, 1983), the Perceived Social Support Scale (Procidano & Heller, 1983), and the Social Support Scale for Children (Harter, 1985). Table 8.1 provides a summary of the measures of social support that were used most frequently in this four-year time frame. Included are the age range of the validation sample or age of intended population, the number of times it was used in the literature from 2000 to 2003, the number of items and response format of the measure, and the type and source of support measured. Table 8.2 summarizes the reliability and validity evidence provided in their respective validation studies/manuals. Overall, all measures provided evidence of excellent reliability, although some of the subscales on the Network of Relationships Inventory were below the commonly accepted standard of .70 (Nunnally & Bernstein, 1994). Validity standards among the measures varied considerably, but in general, all measures evidenced support for their validity. One measure described in Table 8.1 was created using Tardy’s (1985) model. Specifically, the current authors have further developed the Child and Adolescent Social Support Scale (CASSS) to assess perceived, available social support from parents, teachers, classmates, a close friend, and people in the school. Within each source of support, four types of support are assessed: emotional, informational, appraisal, and instrumental. As noted in Table 8.1, there are 12 items per source (three items representing each type of support). Given that there are five sources tapped, there are a total of 60 items. Students rate each item on frequency and importance. A total frequency score and a total importance score can both be computed. Additionally, a frequency and an importance score can be computed for each source of support (e.g., Parent Frequency and Parent Importance). Therefore, a total of 12 scores are available. Finally, some work has been done suggesting that type scores can be adequately reliable within each source (e.g., Parent Emotional Support, Parent Informational Support, etc.). The benefits of the CASSS are that (1) it was developed specifically with children and adolescents in mind (appropriate for use with third- through 12th-graders); (2) it taps several sources and types of support; (3) it taps evaluation of and frequency of support; and (4) there is strong evidence that the scores produced are reliable and valid. Specifically, all frequency scores on the CASSS have demonstrated internal consistencies in the high .90s consistently across studies where it has been used. Additionally, the results of factor analyses consistently yielded a clear five factor structure representing the five sources of support (Rueger, Malecki, & Demaray, 2010). There are some limitations of the CASSS. Currently, it does not produce a network size score, a measure of network density, or a measure of social integration. However, the overwhelming majority of studies on child and adolescent social support take a functional approach and use a rating scale of the frequency of social support. So, the CASSS is representative in its approach. However, it could be improved by including an optional network density and social integration measure. How Can Social Support Assessment Data Be Utilized? Currently in childhood and adolescent realms, social support is measured primarily as a construct of interest to researchers. The social support measures described in Table 8.1 are used by
Developed for adults
Validated on sample of 5th and 6th graders
Developed for adults
Developed for adults
Validated on a sample of 3rd to 8th graders
Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al., 1988)
Network of Relationships Inventory (NRI; Furman & Buhrmester, 1985)
Social Support Questionnaireb (SSQ; Sarason et al., 1983)
Perceived Social Support Scale (PSSS; Procidano & Heller, 1983)
Social Support Scale for Children (SSSC; Harter, 1985)
36 items using two-part answer strategy
40 items (20 items for Family, 20 items for Friend) using agreement ratings (Yes, No, Do not know)
27 items used to determine network density as well as satisfaction that is based on a 6-point Likert scale
241 items on a Likert-type scale; 29 items for each of 8 relationship figures plus 9 general questions
12 items on a Likert-type scale
120 items; 12 each of Frequency and Importance items on a Likert-type scale for each source
Items and Response Format
Notes a 3 of the 7 studies used an earlier version of the CASSS. b 7 of the 13 studies used the “Short form” of the SSQ, which uses 6 items.
Developed for 3 to 12th graders
Child and Adolescent Social Support Scalea (CASSS; Malecki, Demaray, & Elliott, 2000)
rd
Ages
Scale and Author
Table 8.1 Six Commonly Used Measures of Social Support in Youth
No subscales based on type, but items appear to be emotional and instrumental
No subscales based on type, but items appear to be emotional and informational
No subscales based on type, but items appear to be emotional, instrumental, informational, and appraisal
Social support subscales for Companionship, Instrumental Aid, Intimacy, Nurturance, Affection, Admiration, and Reliable Alliance
No subscales based on type, but items appear to be emotional and instrumental
Possible to score emotional, instrumental, informational, appraisal subscales for each source or across all sources
Subscales Based on Type
Parent, Teacher, Classmate, Friend subscales; Total/Global Support score
Friend, Family subscales
Overall Network Number Score; Family Network Score; Overall Support Satisfaction Score;
Type of support for: Mother, Father, Sibling, Relative, Boy/Girl Friend, Same-Sex Friend, Other-Sex Friend, Extra Person
Family, Friend, Significant Other subscales; Total/Global Support Score
Parent, Teacher, Classmate, Close Friend, School subscales; Total/Global Support Score
Subscales Based on Source
Frequency items: .90 to .96 range for various source subscales and .96 to .98 for global scores Importance items: .88 to .96 range for source
.85 to .91 range for various source subscale and global score
All but two subscales were above .60
Network Score = .97 Satisfaction Score = .94
Friend Support = .88 Family Support = .90
.72 – .88 range for subscales
CASSS
MSPSS
NRI
SSQ
PSSS
SSSC
Not provided in manual
Total Scale .83 (Interval of 1 month)
Network Score .90 Satisfaction Score .83 (Interval of 4 weeks)
Not provided in manual
r’s in the .72 to .85 range for various source subscale and global score (2–3 months)
Global Frequency: .75 to .78 Subscales: .58 to .74 (Frequency) .45 to .65 (Importance) (Interval of 8–10 weeks)
Test-Retest Reliability
SPPC: Global self-worth (.28 to .49 range for various sources)
Langner symptom scores: Friend (–.27); Family (–.29) —Also correlated with measures of psychiatric symptoms, self-statements, and observed interactions
MAACL (Depression) with Satisfaction Score —Men (–.22) and Women (–.43) EPI: Personality (significant for women only) —Extraversion with Network (.35) and Neuroticism with Satisfaction Score (–.37)
Adolescent friends’ descriptions of their relationships are moderately to highly related (r’s = .34 to .63 range)b
HSCL Depression Subscale (r = –.24 for both Family and Friends subscale; –.13 for Significant Other) HSCL Anxiety Subscale (r = –.18 for Family)
SSRS: Social skills (r = .62) SSCS: Self-confidence composite (r = .49) SSSC: Self esteem (r = .56) SSAS: Social Support measure Total Score (r = .55) BASC: Behavior Ratings—Maladjustment (r in the –.20 to –.41 range); Personal Adjustment (r in the .36 to .43 range)
Convergent and Divergent Validitya
Note. Unless otherwise stated, the following reliability and validity evidence were found in the validation study or manual cited in the first column of the table. a The following instruments, cited in the respective validation studies and manuals, were used to test the convergent/discriminant validity of the support measures: Social Skills Rating System (SSRS; Gresham & Elliott, 1990), Student Self-Concept Scale (SSCS; Gresham, Elliott, & Evans-Fernandez, 1993), Social Support Scale for Children (SSSC; Harter, 1985), Social Support Appraisals Scale (SSAS; Dubow & Ullman, 1989), Behavior Assessment Scale for Children Self Report of Personality (BASC; Reynolds & Kamphaus, 1998), Hopkins Symptom Checklist (HSCL; Derogatis, Lipman, Rickels, Uhlenhuth, & Covi, 1974), Multiple Affect Adjective Check List (MAACL; Zuckerman & Lubin, 1965), Eysenck Personality Inventory (EPI; Eysenck & Eysenck, 1968), Langner screening instrument (Langner, 1962), Self Perception Profile for Children (SPPC; Harter, 1985). b Validity evidence was taken from Furman (1996), which was cited in the scoring manual of the NRI.
Internal Consistency
Test Name
Table 8.2 Reliability and Validity Evidence for the Six Most Commonly Used Social Support Scales in Youth
Social Support 173 researchers in the health, development, psychology, social policy, and education fields for a variety of purposes. Social support could be included in schools as they focus on prevention efforts in programming or in research evaluating the outcomes of prevention efforts. This chapter clearly articulates the important dimensions of social support to consider in either programming or research efforts and the methods to conduct reliable and valid assessments of the construct. School psychologists, administrators, social workers, and other school personnel could use a brief measure of social support (a brief functional rating scale, a social network questionnaire, etc.) to determine whether the majority of their students perceive adequate levels of support in their lives. This type of assessment would fit nicely into a Tier 1 assessment approach in a problem-solving or Response to Intervention model. If 80% to 85% of students do not perceive adequate levels of support from teachers, classmates, or people in their school, a largescale prevention/intervention program addressing the relevant source of support could be implemented. Using a brief measure of social support to evaluate the effectiveness of large scale curricular changes or the implementation of a new prevention program in schools could be very useful. Students also could be screened to select students for small-group intervention. Perhaps small groups of same-age peers with low perceived classmate support could be furthered assessed to determine the extent and nature of the problem. For example, a school psychologist may determine that the students who perceive low classmate support have poor social skills or do not know how to seek support from their classmates. This problem could be addressed in a small group intervention. Small group or individual interventions targeting social support also could be evaluated with a brief, reliable measure of support. Of course, if initial interventions are not effective, more in-depth assessment methodologies would be helpful. A network analysis, social integration analysis, and/or direct behavioral observations would be useful tools in determining the availability and quality of the social support in a student’s life. These data would help guide intervention while the brief rating scale methodologies could be used for evaluation of those interventions.
Conclusions With a renewed focus on prevention, researchers and practitioners are attempting to create a wide range of approaches to preventing negative youth outcomes and promoting positive outcomes. Given that social support has a long history of being related to many positive outcomes for youth, it should not be ignored in the prevention research and literature. Although many variables are important to consider, youths’ perceptions of social support should also be included as part of a comprehensive protocol to the assessment of prevention programming and as a potential variable related to positive outcomes for children and youth.
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176 Michelle K. Demaray et al. Zimmerman, M. A., Ramirez-Valles, J., Zapert, K. M., & Maton, K. I. (2000). A longitudinal study of stress-buffering effects for urban African-American male adolescent problem behaviors and mental health. Journal of Community Psychology, 28, 17–33. Zuckerman, M., & Lubin, B. (1965). Manual for the Multiple Affect Adjective Check List. San Diego, CA: Educational and Industrial Testing Service.
9
Peer Support as a Means of Improving School Safety and Reducing Bullying and Violence Helen Cowie, University of Surrey Peter K. Smith, Goldsmiths, University of London
Introduction One could argue that the root cause of the problems endemic in modern society is the abuse of power, particularly by those who are unaware that they are doing it. School, as a microcosm of society, creates a context where children experience power and become familiar with oppression and bullying. The victims of oppression often come to accept that some peers’ privileged position is natural, and form constructions of themselves as “subordinates.” They internalise a sense of low self-esteem and a heavy weight of resentment. The dominant ones can also be damaged emotionally. They cannot risk being too aware of their own feelings or those of others, since they might become unbearably sensitive to the pain of those whom they abuse. In between these two groups lie the bystanders—those who observe the oppression though they do not directly take part. A majority of bystanders usually dislike bullying, and a proportion would like altruistically to help; but they are often unsure of what they should do to intervene, or are too confused or embarrassed to be able to offer practical support (Schulman, 2002). Some ignore the problem, becoming (in the terminology of Salmivalli, Lagerspetz, Björkqvist, Österman, & Kaukiainen, 1996) “outsiders” who ostensibly bear no responsibility for what is happening in their school community. Some assist or reinforce the perpetrators of violence and social exclusion. A few become defenders of the victims; Batson, Ahmad, Lishner, and Tsang (2002) identify the source of this kind of altruistic behaviour as “empathic emotion towards a person in need.” They argue that empathy-based socialisation practices can encourage perspective-taking and enhance prosocial behaviour, leading to more satisfying relationships and a greater tolerance of stigmatized outsider groups. Defenders are usually friends of a victim who help them by intervening on their behalf, comforting them, confronting bullies, or seeking adult help, thus making future attacks less likely (Boulton, Trueman, Chau, Whitehand, & Amatya, 1999). A critical way of extending such protectiveness beyond the immediate friendship group is to create contexts where there is optimism and hope that relationships need not be abusive, violent or exploitative (Seligman, Reivich, Jaycox, & Gillham, 1995). Schools can do this by developing a moral community founded on principles of equality, concern for others and empathy for others’ feelings (Schulman, 2002). Spanish educators call such community spirit convivencia—living and working together in harmony. One method that can play a critical part in this is peer support, an approach originally grounded in counselling. Essentially peer support systems in schools are defined as flexible frameworks within which children and young people are trained to offer emotional and social support to fellow pupils in distress (Cowie & Jennifer, 2008). Although counselling is often
178 Helen Cowie and Peter K. Smith considered to be an intervention for the privileged individual few, its real importance is that “it could point to a new understanding of morality and be the harbinger of a different kind of culture” (Kitwood, 1990, p. 221). Peer support can go beyond the help offered by one person to another, useful though that is; its greater strength lies in its potential to create a cooperative community based on mutual trust, respect, open communication and a willingness to explore past hurts as well as present needs and desires. Peer support is a form of lived morality and encompasses a range of activities and systems within which young people’s potential to be helpful to one another can be fostered through appropriate training in such skills as mentoring, active listening, conflict resolution, befriending and the promotion of children’s rights to work and learn in a safe environment. For examples of peer support training and practice in action, see Cowie and Jennifer (2007) and Cowie and Jennifer (2008). The method of peer support has been quite widely used in Canada and Australia since the 1980s. It has grown in popularity in recent years and is now used in many countries; for example in the UK the existence of such systems is reported in around 50% of both primary and secondary schools (Smith & Samara, 2003), where it is now a widely used intervention to promote emotional health and well-being (Cowie, Boardman, Dawkins, & Jennifer, 2004). Varieties of peer support programs have become more popular internationally in schools as anti-bullying interventions that promote the United Nations Convention on the Rights of the Child (UN, 1991) and have the potential to improve pupil safety, emotional health and wellbeing (Cowie et al., 2004). They often get funding as an intervention to combat school bullying, violence and social exclusion. Studies of such programs have been reported in Australia (Ellis, Marsh, & Craven, 2005; Peterson & Rigby, 1999; Rigby, 1996; Slee, 1997), Canada (Carr, 1994; Cole, 1987; Cunningham et al., 1998; Gougeon, 1989; Pepler, Craig, & Roberts, 1995; Rosenroll, 1989), Finland (Salmivalli, 2001), Italy (Menesini, Codecasa, Benelli, & Cowie, 2003), Japan (Taki, 2005; Toda, 2005), New Zealand (Sullivan, 2000), Spain (Andrès, 2007; Fernandez, Villaoslada, & Funes, 2002) and the USA (Benson & Benson, 1993; Boehm, Chessare, Valko, & Sager, 1991; Lane-Garon & Richardson, 2003; Sanders & Phye, 2004).
Types of Peer Support Programs Primary school schemes generally involve training certain pupils as buddies or befrienders (DfES, 1994, 2000; Smith & Sharp, 1994). They look out for pupils that appear lonely, often in the playground, and offer to play with them or help them (Cartwright, 1996); they also report serious fights and conflicts to adults (Cremin, 2007). There may be a “buddy bench” or “friendship stop” where pupils can go in the playground if they would like peer support (Cowie, Boardman, Dawkins, & Jennifer, 2004). In addition, some primary schools incorporate other activities for peer supporters such as leading structured games activities, supporting learning at a homework club (Demetriades, 1996), and one-to-one work with very young pupils who needed support in learning how to play with others (Cowie & Wallace, 2000). For further examples, see Cowie and Jennifer (2008). Secondary school peer support schemes usually involve peer mentors, who may offer support to pupils with difficulties in a “drop-in” room, do group work with a tutor group, offer one-to-one contact with a pupil in need over a period of time, or run a lunchtime club for younger pupils (Andrès, 2007; Cowie & Wallace, 2000; Smith & Watson, 2004). Peer supporters can also be elected by their peers to deal with interpersonal issues (Andrès, 2007). Some secondary school pupils work as mediators to resolve conflicts through a structured process in which a bystander in the role of neutral third party assists voluntary participants to resolve their dispute (Fernandez, Villaoslada, & Funes, 2002).
Peer Support as a Means of Improving School Safety 179 Peer support schemes have evolved over time and change in line with local needs and pupil perceptions of the effectiveness and acceptability of this type of intervention (Cowie, Naylor, Talamelli, Chauhan, & Smith, 2002). An example of this is the Question and Answer Handout method, developed in Japan, to preserve the anonymity of pupils seeking help (Toda, 2005). With advances in technology, peer support methods now take account of distance-learning types of support, including use of the internet and email support (Cartwright, 2005; Cowie & Hutson, 2005; Hutson & Cowie, 2007). Training in peer support generally involves active listening and the skill to respond genuinely and authentically to the needs and feelings of those seeking help. But peer supporters need to go beyond empathy to a rational problem-solving stance so that the participants can move into some form of resolution or restitution. This is where good communication skills are essential. The peer supporters must show, through their choice of words, the tone of their voice, the rhythm of their speech, and their confidence, that they believe in the real possibility of a solution to the problem. There should also be some form of supervision and debriefing to allow time for peer supporters to process what they do and collectively to address the issues that they encounter.
Key Aspects and Aims of Peer Support Programs Peer support programs have laudable intentions, but do they deliver? How effective are they? We consider three key aspects of peer support to be fundamental, and conceptually useful in distinguishing the main aims, and possible outcomes. We will assess the outcomes of peer support schemes in these three main areas. Various specific outcomes might be looked for in each domain. (1) Selected peers are trained to be peer supporters. An immediate aim here is to give peer supporters certain skills, often including opportunities to learn good communication skills; to share information and to reflect on their achievements in supervision groups; to develop perspective-taking and empathic abilities; and to deal with interpersonal conflicts, social exclusion, violence and bullying in proactive and non-violent ways. Outcomes: are useful skills acquired, and are they used? Do they gain self-esteem and heightened self-awareness? Do peer supporters gain status with peers or are they sometimes made fun of? Is gender an issue? (2) Certain peers will be users of the peer support scheme(s). The aim here—ostensibly the usual immediate aim of such schemes—is that they will be helped in this way, either directly by the peer supporter, or by the peer supporter arranging or encouraging other forms of help to be sought and/or given to them. Outcomes: do users feel they gained from the peer support system? Would they use it again? Did problems of bullying or violence reduce for them, after using a peer support scheme? (3) An ostensible longer-term aim of such schemes, through the training of peer supporters and the help and advice given to users, is to reduce rates of unresolved conflicts and bullying among pupils in the school. In this way, the workings of the peer support scheme(s) in a school might generally raise the profile of the school as a caring and moral institution, and have effects on school climate or ethos. Outcomes: Is the existence of the peer support system known through the school? Do pupils know how to use it? Is it used? Is it seen favourably, by pupils, teachers, by parents and others in the school? Is it thought to have positive effects, either generally on school climate, or more specifically on liking of school and perceived safety in school? Do peer relationships improve? Do general levels of school bullying or violence decline in the school?
180 Helen Cowie and Peter K. Smith In this review, we look at the main sources of evidence regarding these outcomes and conclude with a discussion of what such evidence tells us so far, what further research is called for, and implications for the running of peer support systems in schools.
Research findings Evaluations of peer support schemes are as varied as the different types. Many are impressionistic “in-house” case studies, often carried out by the enthusiastic practitioners who introduced and implemented the intervention. Others have used independent evaluation, but varied in the nature of the data base, from generalised summaries backed up by supportive quotes, through to quantitative surveys of attitudes and outcomes. These studies have, however, rather consistently indicated advantages of peer support. Peer supporters usually report that they benefit from the helping process, that they feel more confident in themselves and that they learn to value other people more. For vulnerable pupils, use of the peer support system can be a critical part of the process of feeling more positive about themselves and dealing with difficulties such as victimisation. Teachers frequently report that the school environment becomes safer and more caring following the introduction of a peer support scheme, and that peer relationships in general improve (Cowie et al., 2002; Cowie & Sharp, 1996; Cremin, 2007; Hurst, 2001; Mental Health Foundation, 2002; Naylor & Cowie, 1999). Some studies have reported some independent evaluation, including quantified findings: Cowie (1998), Naylor and Cowie (1999), Cowie, Naylor, Talamelli, Chauhan, and Smith (2002), Smith and Watson (2004), Cowie and Oztug (2008) and Cowie, Hutson, Oztug, and Myers (2008). A few studies have used a longitudinal pre-post test design to assess effects: Andrès (2007), Cowie and Olafsson (2001), Ellis, Marsh, and Craven (2005), Houlston and Smith (2008), Lane-Garon and Richardson (2003), Menesini, Codecasa, Benelli, and Cowie (2003), Peterson and Rigby (1999) and Salmivalli (2001). We will describe and review the outcomes of these studies under the three main headings given above.
The Outcomes of Peer Support Schemes Those Trained in Peer Support Cowie (1998) conducted interviews to capture the experiences of peer supporters and the members of staff in charge of peer support services with 25 peer supporters and nine teachers in nine UK schools (two primary, seven secondary), where peer support systems had been established for at least one year (range one to four years, mean 2.4 years). She asked about the perceived benefits of the peer support scheme for the peer helpers and for the school as a whole; about any problems that been encountered, and ways in which these might be overcome. She found that all of the interviewees (both teachers and young people) claimed that peer supporters gained personal benefit from taking part in the scheme. The most frequently mentioned benefits were: an increase in self-confidence, a sense of responsibility, and a belief that they were contributing positively to the life of the school community. Sixty percent of the peer supporters reported that these benefits arose directly from the training that they had received. At the same time, the peer helpers reported some degree of derision or hostility from members of the peer group in the form of “adverse comments,” “jealousy at all the attention,” or “doubts about the capacity of the service to offer help.” This played a part in the striking gender difference in the balance of boys and girls at all stages of recruitment, application, training and implementation. Even when boys were recruited, their dropout rate was high,
Peer Support as a Means of Improving School Safety 181 apparently because of “peer pressure from other boys” (secondary school teacher) or “macho values in the school” (peer supporters). In a larger-scale study, Naylor and Cowie (1999) surveyed 2,313 secondary school pupils and 234 teachers about their experiences of and attitudes towards peer support in 51 schools where there was a well-established system of peer support. They questioned peer supporters, groups of service users or potential users, teachers involved in managing the systems and a sample of teachers not involved in running the systems. They found that 78% of peer supporters reported that they had gained useful social and interpersonal skills, such as active listening, from the training and 58% reported that, through the practice of peer support, they had become able to demonstrate that they cared for peers in need and so were able to put into action their altruistic wish to do something about the problem of bullying in their schools. Cowie, Naylor, Talamelli, Chauhan, and Smith (2002), in a follow-up study two years later from 35 of the original 51 schools (413 pupils of whom 204 were former victims and 209 former non-victims), found that peer supporters appreciated the opportunity of addressing a real problem in their school community and being given the skills and structures to tackle it. Peer supporters commented favorably on the usefulness of the communication skills that they learned in the course of training, especially “active listening.” All peer helpers reported that there were personal benefits for them through their involvement in the schemes, highlighting active listening (100%), developing the capacity for empathy towards a person in need (81%), and experiencing a gratifying sense of responsibility (74%), for example in helping to make the school a safer place and in being able to make changes to the systems on the basis of their experience. A frequent comment was that the experience of participating in the peer support scheme had led them to decide on one of the caring professions for a career. Cowie et al. (2002) noticed that peer supporters in their study changed over time. There were transformations in confidence and a growing identity as peer supporters. There were also differences that often related to the extent and degree of help that the peer supporters received from others, including the quality of teacher facilitation, parental approval, the extent and relevance of training and debriefing groups, and feedback from other pupils, whether users or potential users. Some boy peer supporters struggled with the issue of gender identity; others managed to find compatibility between the role of peer supporter and being “manly.” There were also useful links with other systems, such as external training agencies (for example, ChildLine: http://www.childline.org.uk/), national groups (for example, the UK Observatory: www.ukobservatory.com), and higher education (for example, a university-based research project), each of which had potential for wider dissemination of the work of the peer supporters, for example, through presentations at conferences, publication of achievements in newsletters, and opportunities to meet and learn from peer supporters from other schools. Cowie and Olafsson (2000) studied the workings of a peer support scheme in one innerLondon secondary school (population 420), which, unusually for a state school, was single-sex (boys) and which was set in a disadvantaged inner city catchment area. Because of its poor reputation in the neighborhood, parents tended to send their children to other schools if possible, and the school had a large number of empty places and a large intake of boys who had been suspended from other schools because of their disruptive behaviour. The seven peer supporters were interviewed, and the Olweus bullying questionnaire was given before the introduction of a peer support service, and 7.5 months after. They found that, despite the extremely difficult circumstances in which they worked, the seven peer supporters in the school, which had high levels of aggression, expressed belief in and commitment to the peer support principles in which they had been trained. All reported the positive impact on them of being trusted to take some responsibility for the issue of bullying and gave a strong sense that the peer support
182 Helen Cowie and Peter K. Smith intervention had made a difference. At the same time, they all commented that a greater number of peer supporters would be needed to service the 420 boys in the whole school and were resigned to the fact that some victims did not seek out help for fear of reprisals or anxiety about appearing to be weak. Smith and Watson (2004) obtained data from 20 schools in England (10 primary, two middle, eight secondary) that had taken part in ChildLine in Partnership with Schools (CHIPS) training. They interviewed the head teacher and the CHIPS co-ordinator(s), held discussion group meeting(s) with pupils who had been trained in peer support; and collected questionnaires focusing on knowledge of the school’s peer support system and opinions about its effectiveness. Questionnaires were obtained from 455 primary and 379 secondary pupils (including 178 trained as peer supporters), plus 109 primary and 95 secondary staff. They found that, generally, peer mentors felt very enthusiastic about their work. It was appropriate to the training they had received, and they felt that they had developed useful skills as peer mentors. While most were well occupied, some had little to do; this was more likely in some playground or drop-in room schemes. Also, some schemes where peer mentors worked with younger-aged tutor groups ran the risk of the peer mentors being assigned routine or administrative tasks. Houlston and Smith (2008) carried out a one-year longitudinal study in an all-girls secondary school, evaluating the effects of a peer counseling scheme which was implemented as part of a whole-school anti-bullying intervention. Both qualitative and quantitative findings indicated that peer counselors did benefit from their involvement in the school’s peer support project. Students were largely very positive about the training they had received and displayed an awareness that it had led to the acquisition of transferable communication and interpersonal skills. Pre- and post-tests were carried out on the 14 peer supporters, and 14 agematched control pupils. There were no differences from controls in shame acknowledgement and displacement, or social skills, but the peer counselors did show a significant differential increase in social self-esteem. Andrès (2007) carried out a longitudinal study in two secondary schools in Spain: an experimental school with 778 pupils, which had developed a system of peer support to enhance convivencia, and a control school (462 pupils) in the same catchment area. This area had a large influx of families from other cultures and an ongoing concern about rising levels of violence, both in the community and in schools. In the experimental school, pupils in each class elected classmates to act as peer helpers; these pupils were given training to intervene directly to resolve peer conflicts, with a particular brief to intervene in cases of bullying and the abuse of power. The program had positive effects on the social development of those who participated as peer helpers. The girls showed significant gains on measures of empathy, prosocial behaviour, self-efficacy and problem-solving ability; the boys, who started from a lower level on these measures, also made progress but at a slower pace. In summary, there is consistent qualitative evidence that the practice of peer support gives direction to some young people’s altruistic wishes to address injustices such as bullying and deliberate social exclusion in their school community, and that the training enhances their communication and problem-solving skills and their capacity to feel empathy for peers in distress. To date the best quantified findings concern improvements in social self-esteem, self-efficacy and the capacity to resolve interpersonal difficulties. Users of Peer Support Naylor and Cowie (1999), in their survey of secondary school pupils, found that of 65 pupils who were users of the peer support systems, 82% reported that they found them “useful” or
Peer Support as a Means of Improving School Safety 183 “very useful”; 82% said that they found these helpful in giving them the strength to cope with bullying; and 80% said that they would recommend the system to a friend. Only 18% had negative thoughts about the systems—for example, that they were “not helpful” or “off-putting.” The reasons users gave as to why a peer support system was perceived as beneficial were: the service provided someone who listens; users were helped to overcome the problem; and the existence of the peer support system indicated that the school cared about their well-being. In the follow-up study two years later, Cowie et al. (2002) confirmed these findings; overall, 87% of bullied pupils said that the system had been useful or very useful to them, the most frequent reason given being that it helps to talk to a peer. Cowie and Olafsson (2001) interviewed seven users of the peer support service in one secondary school with severe problems; of these, four found peer support helpful and would recommend it to a peer. They valued having a peer to listen to their problems and found it helpful to have the protection of a peer supporter’s presence. But three reported that they did not feel any safer at school and resented the fact that the bullies had not been punished for their actions. Smith and Watson (2004), in their evaluation of the ChildLine peer support schemes in the UK, found that usage of schemes varied between schools, and often depended on the role and “hours” of the peer mentors. Just over half of all pupils (53% primary, 52% secondary) were aware of someone that had made use of the peer support scheme. When asked if they themselves had used the scheme, in primary schools 22% had used it once and 11% more than once; in secondary schools, 9% had used it once and 8% more than once. The pupils that had used the scheme were asked whether they had found the peer support to be helpful. Overall, 44% of primary school users said it helped a lot, 50% said it helped a bit, and 6% that it did not help. In secondary schools, 47% said it helped a lot, 42% said it helped a bit, and 11% said it did not help. There was no gender difference in primary schools, but in secondary schools more boys said it did not help than girls (18% versus 7%). When asked if they would use the peer support scheme again should they have a problem, 75% of primary school users said yes, 22% not sure, and 3% no. In secondary schools, 67% said yes, 22% not sure, and 11% no. There was no significant difference between primary and secondary users, or between boys and girls. Houlston and Smith (2008) found that over 30% of year 7 students in an all-girls secondary school indicated that they had used the peer support service at least once, but only 11% in year 8 (the two years the program was targeted at). In year 7, 33% of pupils said the scheme had helped “a lot,” and 50% “a bit”; 17% said it had not helped. In year 8, no-one said it had helped “a lot,” 75% said “a bit” and 25% said it had not helped. In summary, most users report finding the schemes helpful; in successful schemes this is likely to be a large majority, but it may not always be so in schools with severe problems or a poorly implemented scheme. School Ethos A survey of schools across England by Smith and Samara (2003) asked them to rate how satisfied they were with different anti-bullying interventions on a five-point scale (1, not at all satisfied, to 5, extremely satisfied). Active listening/counselling-based approaches had a rating of 3.9, Befriending a rating of 3.6, and Mediation by peers a rating of 3.5; these indicate moderate satisfaction and are similar ratings to those given to many other interventions (e.g., whole school policy 3.9; support group approach 3.5; training playground supervisors 3.5; see Smith & Samara, 2003, for a full table).
184 Helen Cowie and Peter K. Smith Pupil and teacher reports, often qualitative in nature, also generally indicate satisfaction, but with some exceptions. Cowie et al. (2002) found that teachers reported that a school’s reputation was enhanced in the local community through the presence of a peer support system since it indicated that the school cared for its young people’s well-being. The Mental Health Foundation (2002) developed and evaluated peer support schemes in six secondary schools and one further education college in England. The quantifiable data is limited to responses by staff (n=34) to six items; 61% of staff felt that the peer support systems had reduced incidents of bullying. Grossman and Tierney (1998) had similar positive outcomes in their evaluation of the Big Brothers, Big Sisters peer mentoring program in the US. Naylor and Cowie (1999) found that pupils generally, and teachers, reported that the presence of a peer support system was reassuring; it was perceived as beneficial even by pupils who had never actually used the service. But some adults and pupils were not aware that a peer support program was in place, indicating some serious shortcomings in dissemination of information about the schemes and a failure to provide induction on the topic of peer support to new staff, new pupils and key staff such as lunchtime supervisors. Cowie et al. (2004) observed some difficulties in keeping up the momentum of a peer support program in a school with high levels of racial tension and aggression. In fact, the peer supporters themselves identified poor communication and lack of commitment on the part of staff and pupils as key barriers to success in implementation. Naylor and Cowie (1999) found that peer support systems did not appear to reduce bullying, since its incidence as measured by an anonymous questionnaire was similar to that reported in other surveys at that time (e.g., Whitney & Smith, 1993). Nevertheless, on the basis of users’ responses to their questionnaire, they argued that the presence of a peer support system reduced the negative impact of bullying on victims and made it more acceptable for them to report it, especially as it was perceived by both users and potential users that peers are able to detect bullying at a much earlier stage than adults could. Lane-Garon and Richardson (2003) studied the impact of a peer mediation scheme on school climate in a sample of 300 elementary school pupils in the US. Both mediators and nonmediators perceived the school climate to be safer than had been reported in the year prior to the introduction of the peer mediation scheme. This represented an increase from 56% (in 1999) to 66% (in 2001) of pupils who either agreed or strongly agreed that they felt safe on campus. Responses to the items Other students treat me with respect at school and I feel like I belong here both increased from 47% to 58% over this period. Smith and Watson (2004) found that almost all staff (94%) and a significant majority of pupils (72%) felt it had been a good idea to implement a peer support scheme within their school. Pupil support was highest in primary girls (82%) and lowest in secondary boys (59%). Generally, support was higher in those trained in peer support (90%), and also in those who had used the peer support system (84%). Only 4% of pupils generally were opposed to the idea (highest in secondary boys at 7%); not a single member of staff questioned felt the scheme had been a bad idea. Many teachers reported on how the environment felt safer. Despite a lack of direct, objective evidence, staff often reported reductions in the occurrence of smaller, petty bullying incidents, with pupils more capable of resolving situations by themselves in a peaceful way. Vulnerable pupils could be spotted more easily, in part due to the increased awareness of pupils, and could be supported quickly by the existing network. When asked whether the peer support scheme was helping to stop bullying in school, 52% of staff and 43% of pupils said yes, but roughly 45% of all participants were unsure, and 11% of pupils (highest in secondary boys at 19%) and 3% of staff said no.
Peer Support as a Means of Improving School Safety 185 Houlston and Smith (2008) found that most staff members in an all-girls secondary school (79% from 34 responses) thought that it was a good idea to have the peer support scheme in the school; and a majority (62%) thought that it helped to stop bullying. Over half of pupils thought that the peer support scheme was a good idea, but there was a significant age difference (74% in year 7, 53% in year 8, 51% in year 9). A minority of students in each year group (5% to 8%) did not think the scheme was a good idea. There was also a significant age difference in whether students thought that the scheme helped to stop bullying, this being highest in year 7 at 28%. Many students in each year group were unsure (44% to 70%), and a substantial minority (16% to 38%) thought it did not stop bullying. These are all rather subjective reports; do they hold up when some controlled comparisons are used? One study compared two secondary schools with a peer support system with two schools without; Cowie, Hutson, Oztug, and Myers (2008) surveyed around 900 secondary school pupils in total, and found that the pupils in the non-peer support control schools actually reported that they felt safer in the toilets, the playground, corridors and in lessons than their counterparts in schools with peer support. However, within the peer support schools there were significant differences in perceptions of safety between the substantial minority of pupils who were unaware that their school had a peer support system and those who were aware of it. The pupils who were aware felt safer in lessons, perceived school as a friendlier place to be, and worried significantly less about being bullied in comparison with those who were unaware. They were also much more likely to tell someone when bad things happened at school. A small number of studies have used pre- and post-tests to assess outcomes such as levels of victimization. Two have assessed peer-led interventions of a general nature. Peterson and Rigby (1999) measured victimization rates in years 7, 9, 10 and 11 over a two-year period in one Australian secondary school, following a multi-faceted intervention which included student-led activities and a peer helping scheme. There was no overall decrease in victimization, but there was a significant interaction with year group: victimization was less for year 7 pupils, but greater for year 9 pupils, at the post-test. Salmivalli (2001) reported effects of a small-scale (eight peer counsellors; one week) peer-led intervention in a Finnish secondary school, of a general awareness-raising nature. Seventh- and eight-graders (13–15 years) were assessed. For seventh-grade girls there were positive outcomes (reduction in self- and peer-reports of victimization), but these were not found in eighth-grade girls, or either year group of boys. Girls showed an increase in willingness to influence bullying problems; but boys actually increased in pro-bullying attitudes. However, this intervention was very short and there was no control group comparison. Cowie and Olafsson (2000), in their study of one secondary school with high levels of violence, administered the Olweus bullying questionnaire (Olweus, 1993) before the introduction of the peer support service and 7.5 months after. The high incidence of bullying in the school showed little change over the period when the peer support service was in operation. The pupils’ estimate of the number of victims in their own class was 2.64 in November and 2.63 in the following June; the estimated number of bullies in own class was 2.39 in November and 2.46 in June. When asked how often teachers, peer supporters and other young people tried to put a stop to someone being bullied, pupils tended to perceive all three parties as intervening less in June than in the previous November. On the positive side, those who had told no-one about being bullied decreased from 39% in November to 30% in June; the number of victims who had told teachers, peer supporters or someone at home increased from November (n=12) to June (n=18). The authors concluded that it was unrealistic to expect that a small
186 Helen Cowie and Peter K. Smith number of peer supporters could solve the problem of bullying in such a challenging context, especially when there was little evidence of supervision, monitoring, and support from adults in order to sustain the intervention over time. The school staff did not appear to apply sanctions against known bullies following the activities of the peer supporters, and this was noted negatively by the pupils (users and potential users alike). Houlston and Smith (2008), in their study of an all-girls secondary school, used pre- and post-test assessments of levels of bullying, and perceptions about it, with 416 pupils in grades 7, 8 and 9. There was no significant change in levels of reported victimization or bullying. However, perceptions of levels of bullying generally did decline, and perceptions that the school was doing something about bullying did increase. These improvements were most notable in year 7 pupils. Three studies have included non-intervention control classes. Menesini et al. (2003) assessed a class-based befriending intervention in sixth, seventh and eighth grades of two Italian middle schools over one year (October to May). Across the two schools, nine classes were in the program condition, and five classes were controls. Experimental classes showed a decrease in bullying and outsider roles, and less of an increase in reinforcer and assistant bullies, compared to controls; especially for boys. There were no significant changes in defender or victim roles overall, but both increased at sixth grade only. Attitudinal data showed an increase in anti-bullying attitudes only in sixth-graders. Ellis, Marsh, and Craven (2005) evaluated effects of a peer support program for year 7 students in three Australian secondary schools. Students in the year of implementation (experimental group) were compared with year 7 students from the year before implementation (control group). Improvements were found in experimental compared to control pupils in some aspects, including self-concept, and lower pro-bully attitudes, and these outcomes were retained over time; but there were no significant changes for pro-victim attitudes, or global self-esteem. This study did not assess levels of bullying. Andrès (2007) found mixed results in her longitudinal study of two Spanish schools, in one of which there was a well-established system of peer support. The perception of teachers and pupils in the experimental school was that convivencia increased during the period of the intervention. However, although social exclusion decreased in the experimental school, rates of physical bullying increased as did the incidence of aggressive conflicts. In summary, the outcomes of peer support schemes for school ethos are mixed. Well-controlled quantitative studies are few, and by no means give uniformly positive outcomes. Where studied, variations by year group are often reported. So, although many positive benefits have been documented about the effectiveness of peer support schemes, there is a clear need to explore in more detail how peer support systems work, which pupils benefit from them and which pupils do not benefit and why. In a climate in which it is widely held that peer support systems are effective, and many schools are implementing them with high hopes for their impact on the reduction of school violence and bullying, it is timely to ask whether their presence leads to an increased sense of safety at school and a greater willingness to tell another person about being bullied.
Discussion of Findings We first consider the findings so far regarding the three main outcomes of peer support systems, together with how these interact with details of how these operate. We discuss what further research is needed, and implications for practice given our present state of knowledge.
Peer Support as a Means of Improving School Safety 187 Those Trained in Peer Support The most well established finding is the benefit of peer support systems for the peer supporters. There is evidence for improved self-esteem; increased social and communication skills; greater empathy; and a sense of responsibility and doing something worthwhile in the school. These have been nearly universally reported in the studies reviewed. These benefits probably stem from the quality of training received (in most of the studies quoted the peer supporters rated their training very highly), continuing supervision, and the practice of skills in a context generally valued by other pupils and the school. These data are based on self-reports from peer supporters and observations by teachers, so there may be an element of social desirability present in responses; this is true even for Houlston and Smith (2008), where pupils used a selfreport self-esteem questionnaire. It would be useful to complement this with other measures of (for example) social competence and social skills, perhaps from other pupils and teachers, before and after training; and compared with control children (such as those on the waiting list for training at a later date). This is not to say that there are no problems for peer supporters. We have identified three main ones: status, gender imbalance, and anxieties about lack of usage. Regarding status, while many peer supporters feel valued and respected in their role, in some cases they can feel an isolated minority; as in the schools surveyed by Cowie and Olafsson (2000) and Naylor and Cowie (1999); or they can encounter some teasing about their role. This is clearly more likely in schools where the peer support system is not embedded in the school ethos. It is also more likely from secondary boys, who tend to have less positive attitudes towards peer support systems (Smith & Watson, 2004). A good gender balance is important here, and this is the second issue—it is widely reported to be easier to recruit girls as peer supporters than boys. Naylor and Cowie (1999) concluded that boys are perfectly capable of demonstrating the caring qualities of the peer supporter but that they often choose not to use these abilities unless they perceive that the circumstances in which they are to do so will not threaten their perception of what it is to be manly. One explanation might be their representations of masculinity and femininity as portrayed by parents, peers and the media. Important steps here are likely to be the way peer supporters are selected (e.g., should there be quotas for boys and girls?), and having a few high-status boy peer supporters who can help advertise the scheme through publicity and assemblies. Finally, peer supporters feel more respect and worth in their role if they are engaged and can put their skills to use. The dangers are, for example, that no-one comes to “buddy benches” in the playground, or peer support rooms in the school, through fear of being stigmatized; or that peer supporters get given more routine tasks when assigned to tutor groups. Such under-use or misuse can be avoided. Peer befrienders and supporters can play a more active role in organizing games and activities, or lunchtime clubs (as described in Demetriades, 1996), which can be attractive to many pupils while still allowing timid or bullied children to get support in a less obvious way. Counselling schemes can make use of a school intranet, or can be geared widely to support in a range of areas (academic as well as interpersonal), to avoid risks of stigmatizing those seeking it (Cartwright, 2005; Cowie & Hutson, 2005; Smith & Watson, 2004).
Users of Peer Support Most users of peer support systems report it as being helpful. The degree of helpfulness varies, but a majority would use the service again and would recommend it to a friend in need. A
188 Helen Cowie and Peter K. Smith minority, ranging from 6% in Smith and Watson (2004), and 18% in Naylor and Cowie (1999), up to 3/7 or 43% in the challenging school surveyed by Cowie and Olafsson (2000), report not finding it helpful. We lack detail on how often use of the peer support service has actually stopped experiences of being bullied. We also need to know more about why some users had negative experiences, but some at least blame the attitude of peer supporters, or lack of follow-through to deal with bullying—issues that can potentially be dealt with by good training and supervision of the peer supporters, and integration of the system in the wider school ethos and anti-bullying policy. School Ethos In comparison with the data on benefits for peer supporters and for users—where data based on self-report have some face validity—the findings for more general impact on school ethos are more indirect. Many staff and pupils think that there are positive effects on general levels of school bullying or peer relationships, but many are also unsure. There are anecdotal reports of how individual pupils have benefited, but lack of more general data based on more objective measures. Only a few studies have done the latter. Of these, no study comes out with across-the-board positive findings. Only Menesini et al. (2003) and Ellis, Marsh, and Craven (2005) came out with some positive and no negative findings; Menesini et al. used a rather atypical class-based program, and Ellis, Marsh and Craven did not assess bullying levels. Two studies, Peterson and Rigby (1999) and Salmivalli (2001), assessed peer-led interventions of a general nature. They report a mixture of positive and negative findings, with interactions by year group (generally, younger pupils showing more positive changes), as did Andrès (2007). Cowie, Hutson, Oztug, and Myers (2008) found that pupils who were not aware that their school had a peer support system in place (NAPS) were significantly more likely to worry a lot about being bullied than the pupils who were aware (APS). Although there were no differences in terms of perceptions of safety in corridors, toilets and playground, the APS felt significantly safer in lessons and were significantly more likely to report that school was a friendly place to be. The APS pupils were significantly more likely to tell someone when bad things happened to them and, if they did something bad themselves to another person, to confide that to someone else, usually a member of their family or a close friend. Cowie and Olafsson (2001) actually found some increase in bullying, although there was no control group comparison. The fact that rates of bullying remained similar over the period of study in this troubled school might indicate that the peer support intervention prevented the situation from becoming worse rather than failing to make a difference. Finally, Houlston and Smith (2008) found no changes in personal experiences of being a bully or victim, despite general perceptions shifting positively. At one level, it is clear that in many schools, peer support systems are both known by most pupils (in terms of how they function, how to use them), and they are seen in a generally favorable way. However, there is also evidence that a substantial minority in some schools remain unaware of the school peer support system and that these pupils are significantly more likely to feel unsafe at school and to worry about being bullied, and are less likely to tell someone when bad things happen to them (Cowie, Hutson, Oztug, & Myers, 2008). Most pupils (even secondary school boys!) do dislike bullying, and most pupils do see peer support systems as a good idea. But a minority of pupils (presumably including many who do the bullying) appear skeptical of or resistant to peer support schemes (Andrès, 2007; Smith & Watson, 2004). Roberts, Liabo, Lucas, DuBois, and Sheldon (2004) argued that peer mentoring interventions may fail to reach certain groups of disaffected young people. At a deeper level, we lack
Peer Support as a Means of Improving School Safety 189 objective evidence of the effects on school climate, liking of school and perceived safety in school. As with levels of bullying, we generally have positive staff and pupil perceptions on these issues, but a lack of pre-post data using more objective measures of school liking, school climate, or school safety.
Issues Affecting the Success of Peer Support Schemes The degree to which the peer support strategy has been integrated into the whole school policy or “ethos” is often a contributing factor to its success. From the studies reviewed, schools that make pupils aware of the scheme, through the use of assemblies, newsletters, posters and presentations, often find that the scheme becomes more accepted, and the peer mentors earn respect and credibility from fellow pupils. However, it is rare to find any interaction between schools in terms of planned sharing of expertise, experience and examples of good practice. Few schools appear to offer mentors the opportunity to exchange ideas with pupils from other schools. Furthermore, there is little continuity between primary and secondary sectors, with secondary schools failing to capitalize on the skills of peer mentors moving up from primary education. The active support of the head teacher or a senior leadership figure also appears to be a crucial factor, either directly, or through clearly providing time and resources for dedicated scheme co-ordinator(s). The latter can undertake the day-to-day overseeing of the program, and provide support and continued training for the peer mentors, thus reducing the pressure and responsibilities placed on them. Additionally, it may be that it is the awareness that peer supporters are there to help that enables pupils to create a social construction that school is a safer place to be. The findings from the Cowie, Hutson, Oztug, and Myers (2008) study suggest that for those pupils who know about their school’s peer support system one important outcome is that they feel empowered to talk about negative things that happen to them, or that they do to others, with someone else, not necessarily a peer supporter. In other words, the observation (and in some cases the experience) of the helpfulness of sharing worries and anxieties with another has become an accepted method for coping with issues of concern in that particular school context. Given the extensive evidence from earlier studies of the impact of peer support training on the young people who take part, there is a case for arguing that peer supporters should be given additional training on how to challenge bullies and bystander apathy as well as the more traditional forms of training in active listening and empathy. A range of different strategies is essential if schools and their pupils are to be successful in the ongoing effort to create and sustain social and learning environments that are friendly and safe. There may also be an argument for the training to be carried out with a much wider population of young people. Research into peer mediation programs indicates that training only a small number of mediators is not preventative of violence or favorable to optimum developmental outcomes and that, as the number of trained mediators grows in proportion to the school population, so school climate effects are more likely (Lane-Garon & Richardson, 2003). In other words, the extent to which peer support is actually available seems to influence these outcomes.
Suggestions for Future Research We now have enough information of a general nature to point us toward the major likely outcomes, benefits and difficulties of peer support systems in schools. We have suggested
190 Helen Cowie and Peter K. Smith three main outcome areas, with sub-divisions within each of these. Evidence is stronger in the first two areas (benefits for peer supporters and users) than in the latter area (benefits for school ethos, including peer relationships and bullying), but in all areas there is now scope for more focused and objective research. A part of such a research effort should be more quantitative, pre- and post-test designs, measuring aspects of peer supporter skills and characteristics, user experiences, peer relationship issues including levels of bullying, and school climate. This “traditional” kind of approach has been noticeably lacking in the area, with the exception of the half-dozen studies reviewed above, each of which has shortcomings. There are of course difficulties with this approach. Peer support systems usually run alongside other anti-bullying initiatives. Control groups (such as pupils selected for training at a later date; or non-users of peer support systems) may not be fully equivalent. Nevertheless, without some supportive evidence from such measures, “objective” in the sense of being at one remove from direct reports vulnerable to self-report biases and social desirability of responses, the benefits of peer support systems may remain unconvincing to sceptics. We certainly do not advocate a wholesale switch to these quantitative experimental approaches. Precisely because of their own vulnerabilities, such methods need to be complemented by qualitative methods and case study approaches that give insight into processes and the complexity of interactions in individual schools and contexts (Smith, 2003). Another suggestion is to make more use of young people as researchers (Greene & Hogan, 2005). In the past decade, there has been a shift in the ways in which children in our culture are perceived. This can be seen through policies to enhance the rights of the child, as in the U.K. Children Act (2005), which recognize that children are people, that they should be consulted on decisions that affect them, and that they play an active part in the creation of their social worlds. The principle of the child’s right to participate in decision-making is stated in Article 12.1 of the U.N. Convention on the Rights of the Child (United Nations, 1991) where it is recommended that “the views of the child be given due weight, in accordance with the age and maturity of the child.” The way in which researchers see children has a powerful impact on how they study them— for example, in the methods they choose, the research population under investigation and the interpretation of the data gathered (James & Prout, 1997). Traditionally, adults as experts in child development gathered evidence about children “objectively.” More recently, researchers have seen the need to record children’s own perspectives on the grounds that children themselves are the most important source of evidence on how they experience their lives (Jennifer & Cowie, 2009). In other words there is a movement to engage in research with rather than on children (e.g., Veale, 2005) where children are active participants in the project. In our culture, we do not have a strong track record of listening to children or of understanding children’s lives in their own terms and as a primary source of evidence. Nevertheless most of the studies reported here relied extensively on the perspectives of the young people involved in peer support both as users and as practitioners, and this particular field seems to be an ideal arena in which to put more innovative child-centered methods to the test, for example with the peer supporters in the role of active researchers into their own experience. More use could be made of anonymous feedback on the part of users while still respecting the confidentiality of their interactions with peer supporters. Recent developments in the use of the internet as a vehicle for peer support could be mobilized in this domain. This brings us back to the moral issues raised in the introduction. Qualitative responses by peer supporters have indicated their awareness of the moral dilemmas faced by bystanders when they observe pupils being mistreated and abused by peers. The practice of peer support
Peer Support as a Means of Improving School Safety 191 appears to give direction to young people’s altruistic wishes to address injustices such as bullying and deliberate social exclusion in their school community. This is the moral stance taken by those bystanders who—unlike the silent majority—are prepared to demonstrate publicly their stance against injustice (Cowie & Hutson, 2005). In England recently, peer support has contributed to government strategies and initiatives that demonstrate commitment to involving young people in decisions that affect their lives, for example Every Child Matters (DfES, 2003) and Working Together: Giving Children and Young People a Say (DfES, 2004). The opportunity to be a peer supporter is viewed by some as an important pathway for the inclusion of children and young people in policymaking, and is central to the vision of initiatives by major charities such as ChildLine, National Society for the Prevention of Cruelty to Children (NSPCC) and the National Children’s Bureau (NCB). There is great scope within these initiatives, and corresponding initiatives in other countries, for researchers to build on the framework available from the research to date, and embark now on a variety of more thorough studies on the effectiveness of this kind of involvement and participation on the part of young people and to evaluate successes and failures in their implementation.
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10 The Developmental Implications of Classroom Social Relationships and Strategies for Improving Them Jan N. Hughes and Lisa K. Barrois, Texas A&M University
Classrooms are, by definition, social contexts. Students’ social relationships at school impact their social and emotional adjustment as well as their academic motivation and learning (Connell & Wellborn, 1991; Hughes & Kwok, 2007; Ladd, 1990; Wentzel, 1999). Affectively positive and supportive relationships with teachers and classmates promote a sense of school belonging and a positive student identity (Furrer & Skinner, 2003; Connell & Wellborn, 1991), which engender the will to participate cooperatively in classroom activities and to try hard and persist in the face of challenges (Anderman & Anderman, 1999; Birch & Ladd, 1997; Hughes, Luo, Kwok, & Loyd, 2008; Skinner & Belmont, 1993). In addition to the motivational aspects of positive social relatedness at school, close and supportive school relationships may impact achievement through more responsive and appropriate instruction (Hughes, Gleason, & Zhang, 2005; Itskowitz, Navon, & Strauss, 1988; Jussim, 1986; Matsumura, Slater, & Crosson, 2008) and greater access to learning resources (Gest, Domitrovich, & Welsh, 2005; Hughes, Dyer, Luo, & Kwok, in press; Plummer & Graziano, 1987). The overall level of social support provided to students in a classroom, an aspect of classroom climate, has also been linked to students’ motivation and learning (Battistich, Solomon, Watson, & Schaps, 1997; Hamre & Pianta, 2005). Given the importance of classroom social relationships to social and academic outcomes, it is important to identify interventions that promote supportive relationships between teachers and students and among students. Such efforts are most likely to be successful when based on a good understanding of the dimensions of social relationships in a classroom and the processes by which they impact student motivation and learning. Therefore, this chapter first provides an integrative summary of the literature on the links between classroom social relationships and students’ academic and social competencies before critically reviewing research on the efficacy of interventions that attempt to promote supportive, positive classroom relationships. We begin our summary of the empirical literature on classroom social relationships with teacher–student relationships before addressing peer relationships and, finally, the overall social-emotional climate. Teacher–Student Relationships and School Adjustment An extensive research documents links between the quality of students’ relationships with their teachers and children’s concurrent and future academic and social outcomes (for review see Hamre & Pianta, 2006; Pianta, 1999). Children who experience supportive, positive relationships with their teachers have more positive attitudes toward school (Ryan Stiller, & Lynch, 1994), are more academically engaged and achieve more (Hughes & Kwok, 2007; Hughes et al., 2008; Skinner, Zimmer-Gembeck, & Connell, 1998), enjoy higher levels of peer
The Developmental Implications of Classroom Social Relationships 195 acceptance (Hughes, Cavell, & Willson, 2001; Hughes & Kwok, 2006), and are less likely to engage in substance abuse, early sex, and other risky behaviors (Resnick et al., 1997). Conversely, students whose relationships with teachers are characterized by conflict are more likely to drop out of school, be retained in grade, experience peer rejection, and increase externalizing behaviors (Ladd, Birch, & Buhs, 1999; Pianta, Steinberg, & Rollins, 1995; Silver, Measelle, Armstrong, & Essex, 2005). Importantly, the association between teacher–student relationship quality and subsequent adjustment holds when previous levels of adjustment are statistically controlled (Ladd et al., 1999; Hughes, Cavell, & Jackson, 1999; Hughes & Kwok, 2006; Hughes et al., 2008; Meehan, Hughes, & Cavell, 2003). The benefits of a supportive, low-conflict relationship with one’s teacher are important from the earliest school years (Birch & Ladd, 1998; Howes, Hamilton, & Matheson, 1994) through adolescence (Resnick et al., 1997; Ryan et al., 1994; Wentzel, 1998). The dimensions of teacher–student relationships and the mechanisms by which the relationship affects adjustment, however, may differ at different developmental periods. Researchers studying younger children have drawn from attachment theory (Bowlby, 1980) in positing that a close and supportive relationship with one’s teacher promotes a child’s emotional security and confidence (Howes et al., 1994; Pianta & Steinberg, 1992). A secure relationship with the teacher may serve as a resource that permits young students to actively explore their environment and to cope more effectively with novel academic and social demands (Little & Koback, 2003). Researchers studying pre-adolescent and adolescent students draw on social-cognitive and motivational theories in explaining the impact of teacher–student relationship qualities on student social and academic outcomes (Ryan et al., 1994; Skinner et al., 1998). According to self system motivational theory (Connell & Wellborn, 1991), students who perceive their teachers as meeting their basic psychological needs for competence, autonomy, and relatedness are most likely to identify with school, invest in the school’s agenda, and achieve more. Longitudinal studies support tenets of this theory, finding that middle school students who perceive their teachers as more involved with them and as granting them greater autonomy are more effortfully engaged in classroom activities and achieve more (Skinner et al., 1998). Although the teacher–student relationship is important at all ages, early relationships may be especially important to long-term adjustment. Hamre and Pianta (2001) found an effect for teacher–student relationship conflict assessed in first grade on achievement seven years later, controlling for relevant baseline child characteristics. The long-term effect may be due to the reciprocal causal processes between relationship quality and student engagement and achievement. Support for this interpretation comes from a study that assessed teacher–student relationship support, student effortful engagement, and academic achievement each year for three consecutive years from first to third grade (Hughes, Loyd, & Buss, 2007). In addition to reciprocal effects among the variables and mediational effects (with first-grade teacher support predicting third-grade achievement via its effect on second-grade effortful engagement), first-grade teacher support had a direct effect on third-grade achievement, and teacher– student relationship support, above the year-to-year stability of the variables. This lag effect suggests that teacher–student relationship quality in first grade shapes children’s patterns of engagement in learning that, in turn, leads both to more supportive relationships with subsequent teachers and to higher levels of achievement. Although most of the research on teacher–student relationships focuses on the motivational aspects of a supportive relationship, it is likely that relationship quality also influences the quality of the instruction the child receives. For example, first-grade teachers are likely to hold higher achievement expectations for students, relative to students’ assessed achievement, when they have a positive, supportive relationship with the student (Hughes et al., 2005).
196 Jan N. Hughes and Lisa K. Barrois Teacher expectations, in turn, influence the quality of teachers’ instruction to students (for reviews see Brophy, 1983; Jussim, 1986). For example, in interacting with students for whom they hold high expectations, relative to students for whom they hold low expectations, teachers wait longer for answers to a question, assign more challenging work, attribute poor performance to effort rather than to ability, and provide more praise and less correction for the same behaviors. Drawing from resiliency literature, several researchers have documented that a positive teacher–student relationship can function as a protective factor that buffers children from the effects of known risk factors (Copeland-Mitchell, Denham, & DeMulder, 1997; Fallu & Janosz, 2001; Hughes et al., 1999; Ladd & Burgess, 2001). Reasoning that children with poor self-regulatory control might especially benefit from a warm relationship with their teachers due to their greater reliance on external resources to regulate their attention and behavior, Chen, Liew, and Hughes (2007) found that first-grade children with poor self-regulatory control improved more in reading the following year when they experienced a warm relationship with their first-grade teacher. A similar benefit was not found for children with average and high levels of regulatory control. Similarly, children with externalizing problems benefit more from the provision of a close teacher–student relationship than do children without such difficulties (Silver, Measelle, Armstrong, & Essex, 2005). Classroom Peer Relationships and School Adjustment Every child in a classroom can be thought of as having a position within that class on various dimensions of peer relatedness. The most extensively researched peer group status variable is one’s level of acceptance, or liking, within the group (for reviews see Ladd, 1990; Parker, Rubin, Erath, Wojslawowicz, & Buskirk, 2006). Low peer acceptance (or high peer rejection) and its associated lack of a sense of belonging to school forecasts school avoidance and disaffected patterns of engagement from kindergarten through the middle grades (Buhs & Ladd, 2001; Furrer & Skinner, 2003; Guay, Boivin, & Hodges, 1999; Ladd et al., 1999; Wentzel, 1998). In a longitudinal sample from kindergarten to grade 5, the effect of early negative peer experiences on achievement was mediated by declining classroom participation and school avoidance (Buhs, Ladd, & Herald, 2006). An additional longitudinal study has found that the direct effect of peer acceptance on achievement may be mediated by the effect of peer acceptance on self-perceived academic competence (Flook, Repetti, & Ullman, 2005). In addition to one’s level of social acceptance in the classroom, students develop reputations among their classmates based on their behaviors, traits, and interactions with other students that also predict academic outcomes (Hamm & Faircloth, 2005). In the elementary grades, a student’s peer reputation for academic competence has been found to predict changes in children’s academic motivation and achievement, above levels of their peer acceptance (Gest et al., 2005). Children who are perceived as academically competent by their peers develop greater confidence in their academic abilities, which leads, in turn, to greater engagement and achievement (Hughes et al., in press). Classrooms differ in the degree to which social comparison cues regarding children’s achievement are available to students and, therefore, the salience of individual differences in academic abilities (Mac Iver, 1988). Teacher practices that provide more social comparison cues include providing more frequent and public feedback on performance, grouping students of similar ability for instruction, grading students in reference to comparison with others rather than in relation to personal improvement, and providing more response opportunities to higher-ability students than to lower-ability students (Ames, 1992; Marsh & Craven, 2002; Urdan & Midgley, 2003). Lower-performing
The Developmental Implications of Classroom Social Relationships 197 children may fare worse when placed in classrooms where such social comparison cues are more available than in classrooms in which such cues are less available (Hughes & Zhang, 2007). Classroom Emotional Climate and School Adjustment Conceptually, a given student’s relationship with the teacher and with peers can be distinguished from the typical, or normative, level of teacher and peer support in the classroom. For example, each child in a classroom has a unique relationship with the teacher; yet, every child in the classroom experiences the same classroom climate, defined in terms of the teacher’s general tendency to interact with students in a warm and respectful manner. Similarly, each child has a particular peer status; yet, the classroom can also be described in terms of the general provision of peer social support to students. The distinction between individual and normative levels of teacher warmth was supported in a study finding that normative or typical teacher warmth made an independent, or unique, contribution to students’ peer acceptance and motivated patterns of engagement, above students’ individual level of teacher warmth (Hughes, Zhang, & Hill, 2006). Additional studies have found that when teachers provide a positive classroom climate, children are more engaged in learning and are more successful in meeting classroom challenges (Rimm-Kaufman, La Paro, Downer, & Pianta, 2005). Furthermore, a positive emotional climate, defined in terms of teacher sensitivity, child-centered instruction, warmth and fun, and low punitive control, is particularly important to the academic and social adjustment of children at risk for school failure due to background variables (Hamre & Pianta, 2005). Importantly, a positive social and emotional climate does not come at the expense of instructional quality. In preschool and early grades, observed measures of emotional and instructional quality are moderately and significantly correlated (Mashburn et al., 2008; Hamre & Pianta, 2005). Matsumura et al. (2008) found that middle school teachers who are respectful of and caring toward students also tend to provide more rigorous instruction, defined in terms of presenting students with a challenging curriculum and pressing students to engage in critical thinking. In these classrooms, interactions among students are more respectful and supportive and students are more engaged (Matsumura et al., 2008). Thus, social and instructional processes seem to support each other, creating learning environments that promote student social and academic adjustment (Urdan & Schoenfelder, 2006). Teachers establish caring classroom communities not only by providing supportive and positive relationships with students but also by respecting student autonomy and providing students with challenging, relevant work (Battistich & Horn, 1997). The concept of pedagogical caring (Noddings, 1992) emphasizes that teachers communicate caring for students by interest in student input, clarity in classroom rules and expectations, adjusting instruction to individual differences, and providing effective feedback. In such a classroom environment, students develop the intrinsic motivation necessary for continued learning and feel a sense of safety that allows them to take the academic risks necessary for learning to occur (Urdan & Schoenfelder, 2006). Several studies have demonstrated that classrooms characterized by caring and supportive interpersonal relationships and opportunities for autonomy and challenge are associated with student academic motivation and engagement, prosocial behaviors, higher achievement, and low levels of problem behaviors (for reviews see Brophy, 2004; Schaps, Battistich, & Solomon, 2004).
198 Jan N. Hughes and Lisa K. Barrois
Promoting Positive Classroom Social Relationships Progress has been made in identifying teacher practices and behaviors that promote respectful and supportive relationships between teachers and students and among students. Recently developed observational tools, such as the Classroom Assessment Scoring System (CLASS; Pianta, La Paro, & Hamre, 2008), that are based on the body of research on effective teacher practices for promoting positive learning environments, have become available to educators and researchers. The CLASS assesses those dimensions of classroom social-emotional and instructional quality (e.g., teacher sensitivity, positive climate, encouragement of child responsibility, positive discipline practices) that have been found to promote student academic and social competencies. The next step in making such classroom environments available to more students is to identify prevention interventions that improve teachers’ abilities to engage in these behaviors and to create caring classroom environments. In considering this challenge, it is important to acknowledge that teacher–student interactions are embedded in larger systems that may promote or impede teachers’ efforts to create positive teacher–student relationships and classroom environments. For example, when teachers have limited time to get to know students individually due to frequent class changes or large class sizes, or when teachers work under stressful conditions with little emotional support and guidance, they may be less able to create positive emotional climates for their students (Pianta, 1999). Classrooms with higher numbers of students with problematic behaviors pose an additional risk for poor teacher– student relationships, especially for students with higher levels of externalizing behaviors (Buyse, Verschueren, Doumen, Damme, & Maes, 2008). Teachers often receive little pre-service or in-service training in how to create a positive social and emotional climate. Recent research on teacher retention suggests that difficulty in creating a positive social environment in the classroom, including relating to students, maintaining discipline, creating a sense of community among students, and motivating students, is one of the primary reasons that new teachers leave the teaching profession (Kersaint, Lewis, Potter, & Meisels, 2007; Mitchell & Arnold, 2004; Murray, 2005). Nationally as many as onethird of teachers leave the teaching profession within their first three years; nearly half leave within five years (Ingersoll, 2001). Interventions that improve teachers’ abilities to connect positively with students and to create positive classroom environments are expected to improve teachers’ well-being while promoting students’ school adjustment. Prevention Interventions to Improve Classroom Social and Emotional Climate A majority of schools in the United States implement programs designed to improve relationships and the social and emotional climate of classrooms. However, only a minority of schools select programs supported by sound evidence of efficacy and effectiveness (Greenberg, 2004). The lack of accessible information on evidence-based programs is one of several factors that contribute to the under-adoption of empirically supported prevention programs. To meet this need, governmental agencies and research organizations have created guidelines for evaluating effectiveness claims. Examples include the Collaborative for Academic, Social, and Emotional Learning’s Safe and Sound: An Educational Leader’s Guide to SEL Programs (2003), the U.S. Department of Education’s (2003) guide to identifying effective programs, and the Substance Abuse and Mental Health Services Administration’s (SAMSHA) Registry of Evidence-based Programs and Practices (2008). Because these guides use different criteria for the selection of effective programs and different terms to indicate level of rigor (e.g.,
The Developmental Implications of Classroom Social Relationships 199 promising, exemplary, model, probably efficacious, efficacious), they yield low correspondence when evaluating the same program (Flay et al., 2005). To reduce the resulting confusion, the Society for Prevention Research’s Task Force on Standards of Evidence determined the most appropriate criteria for prevention programs and policies to be judged efficacious, effective, or ready for dissemination (Flay et al., 2005): “Efficacy refers to the beneficial effects of a program or policy under optimal conditions of delivery, whereas effectiveness refers to effects of a program or policy under more real-world conditions” (Flay et al., 2005, p. 153). These classifications are hierarchical in that for a program to be found “effective” it must also meet the criteria for efficacious programs, and for a program to be ready for broad dissemination (going to scale), it must also meet all the criteria for effective programs. Selection of Programs to Review In this review we applied criteria for efficacy to school-based, universal prevention programs that have as a primary aim increasing positive social interactions in the classroom and/or improving the social-emotional climate of the classroom. Programs that assessed only negative behaviors (e.g., aggression, delinquency) were excluded, as were programs that provided the intervention only to students selected on the basis of risk rather than to intact classrooms. Only programs that were implemented by teachers and that utilized a comparison or control group and for which at least one efficacy study appeared in a peer-reviewed journal were considered. The following steps were followed to identify programs that met these criteria. The PsycINFO and ERIC databases were searched for available programs. Additionally, existing reviews such as Safe and Sound: An Educational Leader’s Guide to Social and Emotional Learning Programs (CASEL, 2003) were consulted. A total of eight programs met the inclusionary criteria. These programs, the articles that formed the basis of the review, and descriptive information about each program are included in Table 10.1. These eight programs vary considerably in their emphasis on teachers’ behaviors and interactions with students. Typically the emphasis in these programs is on the impact of the curriculum on students’ prosocial behaviors and skills rather than on teacher–student relationships or the classroom social-emotional context, per se. Thus, in addition to evaluating program efficacy, we describe each study’s approach to improving teachers’ abilities to improve classroom social relationships, including the level of teacher training and support and the program’s focus on preparing teachers to teach, model, prompt, and reinforce targeted skills outside the formal lessons. In other words, we address the study’s relative emphasis on program implementation versus teacher professional development. Criteria for Efficacy We applied the efficacy standards created by the Society for Prevention Research (Flay et al., 2005) to identify programs with the greatest support for efficacious use in the schools. Following is a brief description of how we applied each standard to the eight prevention programs that met our inclusionary criteria. Details for coding each standard are provided in Flay et al. In order to meet the criteria for the “Intervention Description and Outcomes” standard, a detailed description of the intervention including such details as intended population, content, organization, goals and duration must be available. The study must measure those behaviors and outcomes that the program intends to alter. The use of quality measures must
200 Jan N. Hughes and Lisa K. Barrois Table 10.1 Study Characteristics Program
Study
PATHS
Domitrovich et al., 2007 Pre-K
SSDP
ICPS
PreK-K PreK-K 2nd–4th
Social skills; Pro-social behavior, Academic engagement and performance Social skills; Problem behavior Social skills; Problem behavior; Academic engagement and performance; Peer acceptance; Classroom climate Social skills; Problem behavior Problem behavior; Academic engagement and performance; School attitudes and belonging Problem behavior; Academic engagement and performance Academic engagement and performance; School attitudes and belonging Social skills; Problem behavior; Pro-social behavior Social skills; Problem behavior; Pro-social behavior Social skills; Problem behavior; Pro-social behavior Social skills; Problem behavior; School attitudes and belonging; Academic engagement and performance Problem behavior; School attitudes and belonging Social skills; Problem behavior Social skills; Problem behavior Academic engagement and performance
3rd 4th
Social skills; Problem behavior Social skills; Problem behavior
Kam et al., 2004 CPPRG, 1999
1st–3rd 1st
Greenburg et al., 1995 Hawkins et al., 2001
2nd–3rd 1st–6th
Hawkins et al., 1992
1st–5th
Abbott et al., 1998
5th–6th
Second step Frey et al., 2005
CDP
Age at Intervention Outcomes Assessed Delivery
2nd–5th
Taub, 2001
3rd–6th
Grossman et al., 1997
2nd–3rd
Battistich et al., 2004
3rd–6th
Battistich et al., 2000
3rd–6th
Shure & Spivack, 1980 Shure & Spivack, 1979 Responsive Rimm-Kauffman et al., Classroom 2007 T.J. Dilworth et al., 2002 Open Circle Hennessey, 2007
be demonstrated by evidence of construct validity and reliability of measures. Additionally, to avoid potential demand characteristics, at least one form of data must be collected by individuals not involved in the delivery of the intervention. To meet criteria for the “Clarity of Causal Inference” standard, the study design must include a control condition. The assignment to the control versus intervention group must be done in a way that reduces the possibility of biased results and allows for confidence in results. This assignment may be random with processes for group assignment well explained. Or, the use of match control designs with demonstrated pre-test equivalence is acceptable assuming group assignment does not result in unintended relationships between group and other variables. The “Generalizability of Findings” standard was met if the authors specified the study sample and how it was obtained. For our purposes, a study sample is considered specified if descriptions of race, socioeconomic status and age are provided. For school-wide interventions, we did not consider report of gender necessary as most schools are gender-balanced. In order to meet the standard for the “Statistical Analysis” category, the analysis must include all intended participants and take into account the level at which participants were randomized to study condition in order to avoid violating the assumption of statistical
The Developmental Implications of Classroom Social Relationships 201 independence of observations. In the case of school-wide interventions, accounting for the clustering of students into classroom groups is necessary. When multiple outcomes are assessed, it is necessary to adjust for multiple comparisons to ensure that findings exceed what would be expected by chance. Also, measurement of attrition is necessary to insure there are no differences in the nature or extent of attrition between groups which may bias results. To meet the “Statistically Significant Effects” standard, results must be reported for every measured outcome and a pattern of statistically significant positive effects should be demonstrated. We considered a pattern to be evident if over 50% of findings were in the expected direction with at least one statistically significant finding that was free of demand characteristics. There must be no negative effects on critical study outcomes. Additionally, we noted if at least one outcome was assessed at least six months following the end of the intervention with statistically significant findings, indicating that the program has some effect on developmental trajectories.
Results Each study was independently rated by each author with respect to each standard. Disagreements were resolved by discussion. Rating results are reported in Table 10.2. Below a summary evaluation is provided for each program. Promoting Alternative Thinking Strategies (PATHS) The PATHS curriculum (Kusché & Greenberg, 1994) aspires to increase social and emotional competence in students by targeting social problem-solving, social skills, emotional awareness and understanding as well as self-control. The PATHS program is based on an ecobehavioral systems orientation which posits that by changing the child, change will be created in the ecology and in their interaction. Ideally, the PATHS program is implemented as students start grade school and continues through the fifth grade. The PATHS curriculum instructs students on the expression, understanding and regulation of emotions using an affective-behavioralcognitive-dynamic framework. Sixty lessons are taught three times per week for 20–30 minutes throughout the school year. Lessons are organized into units such as self-control, emotions and problem-solving. Teachers present lessons using a variety of didactic instruction, class discussion, modeling, role play, social and self-reinforcement, and worksheets. In addition to teaching lessons, teachers are encouraged to generalize their use of PATHS concepts across the school day. Teachers receive two and one-half days of training just before school starts and then receive weekly consultations throughout the year, including observations by staff members followed by feedback (Conduct Problems Prevention Group, 1999). The Conduct Problems Prevention Research Group (1999) evaluated the effects of the program after one year on a group of first-grade students. On sociometric measures, the program students showed less hyperactive-disruptive behavior and less aggression than control students, with no statistically significant differences in exhibited prosocial behavior. No differences were evidenced on teacher-report measures. Additionally, observers rated PATHS classrooms as having a more positive atmosphere than control classrooms (i.e., following rules, ability to express feelings appropriately, level of interest and enthusiasm, and ability to stay focused and on-task). Greenberg, Kusché, Cook, and Quamma (1995) found that thirdgraders exposed to the PATHS program for one to two years were able to generate more words to describe positive and negative feelings, were better able to describe negative feelings,
Domitrovich et al., 2007 Kam et al., 2004 CPPRG, 1999 Greenburg et al., 1995 Hawkins et al., 2001 Abbott et al., 1998 Hawkins et al., 1992 Frey et al., 2005 Taub, 2001 Grossman et al., 1997 Battistich et al., 2004 Battistich et al., 2000 Shure & Spivack, 1980 Shure & Spivack, 1979 Rimm-Kauffman et al., 2007 Dilworth et al., 2002 Hennessey, 2007
PATHSa Y YY Y Y Y Y Y Y Y YY Y Y Y Y Y
Replicability Y Y Y Y Y Y Y Y N Y Y N Y Y Y N Y
Measurement
Description and Outcome
Y Y Y Y Y N Y Y N Y N N N N N N N
Causal Inference
Y N Y Y Y Y Y Y Y Y N N Y Y Y N Y
Generalizability
N N Y N N N N Y N Y N N N N N N N
Statistical Analysis
Y Y Y Y Y N Y Y N Y Y N Y Y Y Y N
Significant Effects
N Y N N Y N N Y N Y Y N N N N N N
Duration
Precision of Outcomes
Note: a Indicates a program for which positive outcomes have been replicated with a different sample. A Y– indicates that criteria were met with reservations.
Responsive Class T.J. Open Circle
ICPS
CDP
Second stepa
SSDP
Study
Program
Table 10.2 Evaluation of Studies
The Developmental Implications of Classroom Social Relationships 203 provide examples of their own feelings and understand the emotions can be hidden or changed. However, no differences were found in students’ explanations of how to recognize emotions or understand simultaneous feelings. Kam, Greenberg, and Kusché (2004) reported that, at two years post-intervention, the special education program students had a reduced growth rate of depressive symptoms and increased growth rate of vocabulary words to describe negative feelings compared to special education control students. There were no differences in growth rates of positive feeling vocabulary words or social problem-solving skills. Additionally, Domitrovich, Cortes, and Greenberg (2007) evaluated a modified PATHS program for preschool students and found that, compared to control students, intervention students were rated by teachers as more socially competent and as less socially withdrawn and demonstrated better emotion knowledge skills. Overall, the studies of the PATHS program demonstrate methodological rigor. All allowed for replicability by describing the program and targeted outcomes well and using valid and reliable measures for program analysis. All but one study utilized random assignment to intervention or control group status. Kam et al. (2004) demonstrated pre-test equivalence on study variables, thus allowing for causal inference. Additionally, all but Kam et al. provided adequate description of the study sample allowing for generalizability. The Conduct Problems Prevention Research Group (1999) used multi-level analysis to account for the nesting of the data into classroom groups, thus ensuring precision of outcomes. The remaining three studies did not account for nesting of the data. All studies showed a pattern of statistically significant positive effects. Seattle Social Development Project (SSDP) The SSDP (Hawkins, Kosterman, Catalano, Hill, & Abbott, 2005) aims to promote positive social development while strengthening bonds between school, home and family, thereby preventing adolescent behavior and health problems, such as drug abuse or delinquency. Based on social development theory, the intervention aims to increase protective factors and decrease risk factors associated with behavior and health problems. Implementation of the SSDP involves the combination of three component parts: utilizing classroom management and instructional practices; implementing a cognitive behavioral instructional program addressing self-control and social competencies; and providing parent workshops. Teachers attended a five-day training program addressing classroom management, direct instruction strategies and cooperative learning. In addition, teachers implemented the Interpersonal Cognitive Problem Solving program to teach ways to effectively handle conflict with peers. The SSDP places a greater emphasis on teachers’ application of targeted teacher practices throughout the day than on teaching lessons on problem-solving. Teachers are taught to establish classroom routines at the beginning of the year, to develop clear and explicit expectations for behavior, to praise positive behavior, and to provide frequent assessments of student learning and feedback. Teachers’ use of targeted practices throughout the day is observed periodically, followed by feedback to teachers (Abbott et al., 1998). Thus SSDP places a greater emphasis on teacher professional development than on implementation of a packaged curriculum. In sixth grade, the program was supplemented with a four-hour training from SSDP staff about resisting negative peer influences. Finally, developmentally appropriate parent training programs were offered to parents. In a series of quasi-experimental studies (Hawkins, Kosterman, Catalano, Hill, & Abbott, 2005), a group of students receiving the intervention from first to sixth grade were compared to a matched control group of students on a variety of outcomes from second grade to age 21.
204 Jan N. Hughes and Lisa K. Barrois At the end of second grade, males in the experimental group demonstrated less aggressive and externalizing antisocial behavior than those males in the control group. Girls in the intervention group were reported to be less self-destructive than control group girls. At the beginning of fifth grade, initiation of alcohol use and delinquency was higher amongst control group students than intervention group students. California Achievement Test scores were higher amongst control females versus intervention group females, although these differences were not demonstrated in sixth grade. At the end of sixth grade, analyses of program effects on lowincome students revealed that low-income males had fewer antisocial friends, demonstrated better social and schoolwork skills, obtained higher achievement test scores and reported more commitment to school. Low-income females in the intervention group participated more in the classroom environment, reported more bonding and commitment to school as well as classroom and team learning opportunities. Low-income females were less likely to use cigarettes or have exposure to marijuana than controls. At age 18, six years after the conclusion of the intervention, program group students reported better school grades and achievement, more commitment and attachment to school and less misbehavior at school than control group students. Additionally, program students reported less violent behavior, sexual activity and involvement with multiple sexual partners across their lifetimes than controls. Intervention group students were also less likely to have engaged in heavy alcohol use in the past year. At age 21, nine years after the completion of the intervention, former program students were more likely to be high school graduates, have completed some college, be employed in the past month and had been employed longer at their present jobs. Reported mental health was better among former program students than controls. Although no statistically significant effects were evident for substance use, other findings evidenced a decrease in risky behavior. Former program students had fewer sexual partners and were more likely to use a condom when engaging in sexual activity. Females reported fewer pregnancies and births. Additionally, former program students were less likely to have a court charge ever, to commit a high variety of crimes or to sell drugs in the past year. The one study that assessed the effect of SSDP on teachers’ behaviors failed to find an effect (Abbott et al.,1998). Control teachers and program teachers did not differ on observed measures of teacher use of the targeted practices. Consistent with the program’s theory, students in classrooms in which teachers engaged in these practices, whether these teachers were in the control group or the experimental group, demonstrated greater school bonding. Overall, the intervention program and outcome goals are well described in these studies. Valid and reliable measures are utilized to measure program outcomes. Ability to make causal inferences is adequate as assignment of schools to conditions was largely random. The sample was well described. Across the years, the studies generally demonstrated a consistent pattern of effects on students over time. However, some studies demonstrated methodological issues leading to reduced confidence in results. The single study that took into account the nesting of data into classes (e.g., Hawkins et al., 1992) did not result in a consistent pattern of statistically significant findings. Additionally, some analyses did not address the potential effects of attrition on measurement of study variables (e.g., Abbott et al., 1998; Hawkins et al., 1992). Talking with TJ The Talking with TJ program (The Hallmark Corporate Foundation, 1994a; The Hallmark Corporate Foundation, 1994b) consists of two components: “Teamwork Building” intended for second- and third-grade students and “Conflict Resolution” intended for fourth- and fifth-grade students. Both components aim to increase social and emotional competence in
The Developmental Implications of Classroom Social Relationships 205 program participants by developing skills in the areas of group planning, diversity and inclusion as well as cooperative team play. Each component consists of six lessons, lasting 45–60 minutes each. Lessons are led by project staff instead of teachers. Each lesson plan includes a 15-minute video clip providing examples of successful and unsuccessful skill use, an in-class discussion of the skills from the video and guided practice activities to promote generalization of learned skills. In addition, posters with “TJ Teamwork Tips” are displayed throughout the classroom and comic books addressing program goals are sent home to be shared with parents. Although teachers do not deliver the lessons, they are provided with a list of activities for teaching social and emotional competencies and are encouraged to incorporate teamworkbuilding activities into school activities, such as games or problem-solving discussions. The level of teacher training is not described in the studies reviewed. Dilworth, Mokrue, and Elias (2002) evaluated the effectiveness of the Teamwork-Building component with an urban sample of third-grade students. The Social Skills Rating System— teacher (SSRS) form was utilized as a measure of students’ social skills and problem behaviors. Students completed the self-concept scale as well as the anger inventory. Overall, no significant differences were observed on the teacher-reported SSRS ratings. However, program students reported higher self-concept than control students. No differences were indicated between groups on anger. The intervention and outcome goals were well described by the authors. Reliable and valid measures were used for outcome analysis. Student self-report measures demonstrate a pattern of positive effects. However, obstacles to causal reasoning do not allow clear interpretation of results on these outcomes. Data were collected from teachers who were involved in delivering the intervention and from students by undergraduate and graduate students. Because it was unclear whether the undergraduate and graduate students collecting the student measures were different from those delivering the intervention, these data cannot be considered free of demand characteristics. Outcomes measures were administered two to three weeks after the conclusion of the intervention; thus, the potential decay of effects over time cannot be assessed. Schools were not randomly assigned to conditions, and pre-test equivalence was not demonstrated. It was not specified how participating schools were obtained. Furthermore, analysis of the data did not account for the level of randomization or adjust for pre-test differences. Open Circle The Open Circle program (Hennessey, 2007) strives to increase social and emotional competence with grade-differentiated curriculum for kindergarten through fifth grade. Specifically, the intervention targets peer relations, decision-making and problem-solving. Open Circle is intended to be implemented throughout the school year, across years. There are 35 core lessons and several supplemental topics. Throughout the year, teachers have bi-weekly circle time for 15 minutes to address curriculum objectives and allow students to express ideas and opinions and engage in joint problem-solving. Hennessey (2007) evaluated the effects of the Open Circle program on a sample of fourthgrade students. The Social Skills Rating System teacher and student forms were utilized as a measure of students’ social skills and problem behaviors. Teachers’ ratings of program students were higher than those not exposed to intervention. Students’ ratings did not indicate a statistically significant difference. The level of teacher training is not described in this study, which states that teachers received consultation and “peer observation” to encourage teachers to reflect on their practices.
206 Jan N. Hughes and Lisa K. Barrois The lessons were well described and outcome goals were clearly stated. Reliable and valid measures were selected to assess outcomes. The sample was well defined. Yet, some methodological challenges reduce confidence in the results from this study. Program and control schools were not randomly assigned to conditions. Schools implementing the program were selected on the basis of their experience with the program, with some having up to 10 years’ experience of implementing the intervention. Only four classrooms were included in each condition and analyses did not account for the nested nature of the data (i.e., students nested in classrooms). No data were provided to assess the long-term effects of the intervention. Also, it is important to note that all findings were based on the reports of teachers delivering the intervention and may be prone to demand effects. Responsive Classroom Approach The Responsive Classroom Approach (Northeast Foundation for Children, 1996) is intended to incorporate social and academic learning to bolster students’ academic achievement. The program is not a packaged curriculum; rather, it relies on the teacher’s implementation of principles and practices. There are seven principles that include the themes of a focus on the importance of how students learn, relationships inside and outside school, and sensitivity to diversity. Teachers implement the practices including: a daily morning meeting to create community, classroom rules with logical consequences and emphasizing students’ efforts rather than products. The program is less focused on teaching specific skills than on applying the seven principles throughout the day. By implementing these principles and practices, children are expected to have academically motivating experiences in caring environments. These experiences are expected to increase students’ engagement in learning and use of social and self-regulatory strategies, thereby increasing academic achievement. Rimm-Kaufman, Fan, Chiu, and You (2006) investigated the effects of the Responsive Classroom Approach over three years on a sample of second- through fifth-grade students. Scores on two district-administered standardized assessments, the Degrees of Reading Power test and the CMT-Math test, were used to compare intervention and control students. On the Degrees of Reading Power test and CMT-Math test, the second- and third-graders who received the intervention for three and two years, respectively, performed better than control students, while the fourth-graders receiving the intervention for one year did not perform different than controls. Additionally, comparison of the predicted attainment of math proficiency levels (Goal, Proficient, Remedial) of program students versus controls at fifth grade indicated that program students were more likely to achieve above the remedial level. Importantly, program teachers were observed to implement the seven principles more frequently throughout the day than were control teachers. The article provides a thorough program description and utilizes valid and reliable outcome measures. Also, the study sample is well defined. The article also demonstrated that the program is able to produce a consistent, reliable pattern of effects. Yet, some issues with methodological rigor lead to reduced confidence in these results. Participating schools were not randomly assigned and differences between the intervention and control group students were evident on pre-test measures of study variables. Outcomes were only assessed immediately after the intervention, so it is not possible to assess the longevity of effects. Also, the authors did not employ necessary multi-level analysis of the data to account for the level of randomization of participants.
The Developmental Implications of Classroom Social Relationships 207 Child Development Project (CDP)/Caring School Community The CDP (Battistich, Schaps, Watson, Solomon, and Lewis, 2000; renamed Caring School Community in 2007) strives to make elementary schools “caring communities of learners” characterized by caring collaborations between students, schools and parents; a commitment to caring, justice, responsibility and learning; responding to developmental and sociocultural needs of students; use of engaging curriculum; and opportunities for students to be involved mentally and socially in the school environment. Stable, warm, and supportive relationships between teachers and students and among students are key program goals. The caring community of learners is expected to facilitate students’ intellectual and sociomoral development as well as fulfill students’ need for belonging, autonomy and competence, thereby ensuring students’ attachment to the school environment. To implement the project, schools follow four program principles: establish supportive, warm, stable relationships; teach students to be moral, caring and disciplined; follow a constructivist approach to learning by allowing students to learn in the most suitable way while learning from the diversity of others; and foster intrinsic motivation within students. Schools develop individualized approaches to implement these four program principles. Battistich, Schaps, Watson, Solomon, and Lewis (2000) evaluated the effects of the program on developed sense of community and presence of problem behaviors in fifth- and sixth-grade students. Sense of community was evaluated via a student report scale. Results showed that students at intervention schools exhibiting high levels of program implementation were more likely to report higher levels of sense of community than controls. However, reports of sense of school community by students at intervention schools exhibiting low levels of implementation declined compared to control students. Problem behaviors were assessed using a student self-report of use of alcohol, cigarettes and marijuana as well as 10 antisocial behaviors such as skipping school, damaging property or hurting someone. Taken as a whole, there was no statistically significant difference between the reports of problem behaviors by intervention and control group students. However, students at schools exhibiting high levels of implementation did see a difference in reported alcohol and marijuana use compared to controls. Battistich, Schaps, and Wilson (2004) reported program-related outcomes two years after the conclusion of the intervention. Outcomes included student-reported school-related attitudes, social and personal attitudes as well as the positive and negative behaviors of students and their friends. Teachers reported on students’ behaviors related to assertiveness, aggressiveness, involvement in school and concern for others. Finally, grades in core subjects were obtained from school records. Overall, four of the 40 comparisons favored program students over control students with no comparisons favoring control students. Specifically, program students reported better teacher–student relationships, liking for school, sense of efficacy and involvement in youth activities. No teacher-reported outcomes statistically significantly favored program students versus control students. Both studies provide rich discussion of the program and description of outcome goals. However, both studies of the effects of the Child Development Program evidence obstacles to causal reasoning which lessen confidence in these results. The Battistich et al. (2000) study provided no evidence that targeted outcome measures were reliable or valid. Schools were assigned to the intervention group based on faculty interest and ability to successfully implement the program rather than being randomly assigned. Furthermore, there was no test of the equivalence of the intervention and control group student on outcome measures at pre-test. Although the gender and racial composition of the sample was adequately described, there was no description of the socioeconomic status of the sample. The authors did not use multi-level
208 Jan N. Hughes and Lisa K. Barrois analysis to account for the level of randomization. There was not a consistent pattern of results and the findings reported were not greater than what would be expected by chance. Additionally, some negative effects of the program were evident. For example, studentreported sense of school community actually declined at some schools. The follow-up study by Battistich et al. (2004) showed some additional obstacles. Reliability information was reported for most measures, but was not reported for any teacher variables or two student variables. Analysis only included the three program schools with high implementation. The authors did not report whether attrition differed by intervention status. A consistent pattern of effects was not evident; only four of 82 tested outcomes were statistically significant. Second Step Violence Prevention Program (Second Step) Although the Second Step program (Committee for Children, 2002) has a strong emphasis on decreasing antisocial behavior, it was included in this review because it also seeks to increase students’ social competence by improving their competencies in the areas of social problemsolving, perspective-taking, impulse control, and anger management. The age-differentiated curriculum for Preschool to eighth-grade students contains 13 to 25 lessons, depending on student grade level, that last around 30 minutes each. The curriculum set provides teachers with photo lesson cards with age-appropriate skills printed on the front for use with students; some lessons including a video portion as well. The back of the card provides teachers with directions for class generalization activities such as modeling, practicing, and reinforcing newly learned skills. The level of teacher training varies from study to study. The Frey et al. (2005) study provided two days of training at the beginning of the school year and twicemonthly teacher consultations with program staff. The Second Step website (www.cfchildren.org) has many teacher resources, including tips for teachers on how to transfer program skills to other areas of academic learning. Additionally, the website contains information on workshops held at several locations across the country for teachers (one day) and for trainers of teachers (two days). Grossman et al. (1997) and Frey, Nolen, Edstrom, and Hirschstein (2005) conducted rigorous evaluations of the Second Step program. Both used random assignment, multi-level models, and psychometrically sound measures. Grossman found positive effects of the program on observed levels of second- and third-graders’ classroom aggressive and prosocial behavior, but no effects on teacher- or parent-rated behaviors. Furthermore, these effects persisted for six months after the treatment ended. Using a more extensive assessment protocol that assessed program effects on students’ social cognition as well as behavior, Frey et al. (2005) evaluated the effects of the Second Step program on a sample of second- through fifthgrade students over two years. Teachers rated students’ pro- and anti-social behaviors on the School Social Behavior Scale (SSBS). Additionally, students’ prosocial goals and beliefs were assessed via questionnaires and observations of students as they engaged in various games and vignettes involving peer interactions. Students reported on the hostility of the peer in the vignette and the extent to which they would react to the peer’s actions using a violent means. Students also engaged in a prisoner’s dilemma game from which behavioral observations and further student surveys were conducted. Finally, students were asked to negotiate a prize division in pairs and, then, asked to rate their satisfaction with the results. Teacher reports on the SSBS indicated that the program students exhibited more socially competent behaviors than control students. Also, unbiased observations of students indicated that program students were more likely to prefer prosocial goals and to solve conflicts cooperatively. Generally intervention effects were stronger for the first year than for the second year. In conclusion, the
The Developmental Implications of Classroom Social Relationships 209 intervention indicated a broad range of positive effects both on behavior and on students’ social cognition. In a study with significant methodological limitations, Taub (2001) evaluated the Second Step program with a group of third- through fifth-grade students. To measure students’ use of social skills, teachers completed the School Social Behavior Scale (SSBS) for each student and observers conducted observations of four student behaviors: responding to directions from adults, engaging appropriately with peers, following classroom rules and bothering/annoying/distracting other students. Teachers rated intervention students higher than control students on the SSBS Social Competence and Antisocial Behavior scales. Behavioral observations indicated that intervention group students were observed to appropriately engage with peers and follow directions from adults more often than control students, with no statistically significant differences between groups on other observed variables. However, methodological aspects of the Taub et al. study decrease confidence in their findings. The collected data may be affected by demand characteristics as all outcomes measures were completed by teachers as well as the project coordinator and trained undergraduate assistants who were responsible for delivering the intervention. The authors did not describe how schools were selected for either the intervention or comparison condition, and pre-test equivalence of these groups was not demonstrated. The data analysis did not use multi-level techniques to adjust for possible cluster effects. A pattern of positive effects was not demonstrated, and possible negative effects were reported. In light of the positive findings from the Frey et al. and Grossman et al. studies, which are methodologically sound, and the equivocal results of the less rigorous Taub study, a conclusion that the Second Step program is efficacious appears warranted. Interpersonal Problem Solving (ICPS) The ICPS curriculum (Shure, 2000; Shure, 2001) for nursery and kindergarten students attempts to teach students a problem-solving style of thinking. The curriculum is delivered by teachers in daily 20-minute lessons over the course of about three months. Teachers promote problem-solving by teaching students to develop alternative solutions, consequential thinking and causal thinking through lessons using pictures, puppets and role play techniques. Additionally, teachers are trained to implement program concepts when students exhibit problems in the school environment. Information on the level and type of training provided to teachers was not included in the efficacy studies. Shure and Spivack (1979, 1980, 1982) reported the effects of the ICPS program in a group of preschool and kindergarten students. Program students exhibited better interpersonal problem-solving skills at the conclusion of the intervention than control group students. Specifically, program students were able to generate more alternative solutions and displayed more consequential and causal thinking than control group students. Behavioral observations indicated that program students were less impulsive and inhibited than control group students. The program is well described and reliable; valid measures are used to assess program outcomes. Additionally, the study sample was well defined. The study also demonstrated that the program produced a pattern of positive effects. However, methodological difficulties reduce confidence in the results of this study. It was not explained how students were assigned to intervention or control group status. However, pre-test equivalence on measures was demonstrated. Analysis did not account for randomization by group with multi-level techniques. Also, no analysis was provided of those students who attrited to ensure that observed effects were not biased by differential measurement attrition.
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Discussion The Flay et al. (2005) criteria for efficacy are rigorous, and some of the standards for efficacy are especially challenging for universal school-based prevention interventions. Specifically, analysis at the level of randomization requires a large number of classrooms or schools for interventions that are delivered at the classroom or school level. Only three programs met this criterion for at least one efficacy study (PATHS, Second Step, and SSDP). A second challenge is the requirement for assessment of outcomes at least six months after the intervention. Interventions that occur for multiple years are most highly recommended (Collaborative for Academic, Social, and Emotional Learning, 2003). For example, the PATHS program is intended to be used for grades K–5. Longitudinal designs of this duration are not only expensive and difficult to implement; problems with selective attrition of subjects over several years may threaten the internal validity of results. Nevertheless, PATHS, SSDP, Second Step, and CDP found that intervention effects persisted for at least six months after the intervention. Despite the rigorous standards for efficacy applied to these programs, Paths and Second Step met all standards and are, therefore, deemed “efficacious.” A determination of efficacious means that the program produces benefits when delivered under conditions of high experimenter control. It is important to remember that a finding of efficacy does not mean that a given school will obtain the same results when they implement the program, under conditions and with populations that may differ substantially from those of the efficacy trials. However, a finding that program benefits are attributable to the program and not to some other factor, such as pre-existing differences between intervention and comparison schools or demand characteristics in the measurement of outcomes, is a necessary “first step” in the search for effective programs. Fortunately, both PATHS and Second Step have been adopted by many schools (Frey et al., 2005; The Prevention Research Center at Penn State: http://prevention.psu.edu/projects/PATHS.html), demonstrating that the interventions are acceptable to schools and feasible. Additionally, studies have identified mediators responsible for program benefits (Frey et al., 2005, for Second Step and Riggs, Greenberg, Kusché, & Pentz, 2006, for PATHS), thereby increasing confidence in the theory that underlies the interventions. Therefore schools considering programs to improve classroom climate are advised to give careful consideration to these programs. The eight programs reviewed all aim to improve the social interactions in classrooms in the direction of more cooperation and task engagement and less conflict and aggression. However, few studies assessed classroom-level effects; rather studies assessed the effect of the intervention on individual students; exceptions are PATHS, Second Step, and SSDP. Of the three programs that analyzed classroom effects, PATHS and Second Step found an effect for the intervention. Both studies found intervention effects for observed classroom interactions. These same two programs meet standards for efficacy. Thus one can conclude that they “deliver” on the goal of improving classroom social interactions. Some studies only examined intervention effects for high-implementation teachers. Such designs likely overestimate intervention effects, because teachers who implement interventions effectively may just be more effective teachers in general. In support of this argument, Battistich et al. (2000) found a negative effect of the CDP on students’ sense of school belonging for low implementation schools, relative to control schools. Perhaps schools that were unsuccessful in implementing the CDP were generally less effective schools. Designs that include all teachers assigned to the intervention condition, regardless of whether they implemented the program or not, are referred to as “intent to intervene” designs and offer high external validity regarding the likely outcome of the intervention in a given school.
The Developmental Implications of Classroom Social Relationships 211 Each program involves a teacher-delivered curriculum, and most programs assessed teacher implementation of the curriculum. The programs differ, however, in their emphasis on changing teacher behaviors beyond delivering the “packaged” curriculum. If one is interested in changing classroom climate, one would want to know whether the intervention had an effect on teachers’ everyday interactions in the classroom. The distinction between compliance with the scripted curriculum versus putting intervention principles into action throughout the day has been referred to as “talking the talk” versus “walking the talk” (Hirschstein, Van Schoiack Edstrom, Frey, Snell, & MacKenzie, 2007). Surprisingly, only one study (SSDP; Abbott et al., 1998) actually examined whether intervention teachers engaged in the targeted teacher behaviors more than control teachers. Targeted teacher behaviors included proactive classroom management and frequent recognition of student positive behaviors. Although these researchers found the expected relationships across intervention and control conditions between targeted teacher behaviors and student outcomes (i.e., student bonding to school and perceived opportunities for involvement and reinforcement), they found no effect of the intervention on teacher behaviors. That is, children in both intervention and control classrooms in which teachers engaged in more of the targeted behaviors improved more on measures of school bonding and social competence, but the intervention did not effect these teaching behaviors, nor was an intervention effect found for theoretically relevant student outcomes. The authors concluded that their theory was correct (i.e., the relationship between teaching strategies and student outcomes), but their intervention was not successful in changing the targeted teacher behaviors. Conclusions and Future Directions A growing body of research has identified teaching behaviors that promote student academic and social competencies (for review see Brophy, 2004). In a series of studies, Pianta and colleagues have found an effect for two dimensions of the quality of teacher–student interactions on children’s social and academic learning (Mashburn et al., 2008 ). Specifically, children who are in classrooms in which teacher–student interactions are more sensitive, responsive, affectively positive, and respectful gain more in social competencies, and this effect is stronger for children at-risk for poor school adjustment due to behavioral or family background factors. It is fair to say that we know a great deal more about which teacher behaviors promote positive classroom environments and student social and academic learning than we do about how to promote these teaching behaviors. Teachers report receiving very little training in how to relate to students, maintain discipline, create a sense of community among students, and motivate students (Murray, 2005). Furthermore, teachers generally report that in-service professional development programs are of little value, perhaps due to the relatively brief nature of instruction, little to no opportunity for teachers to practice new approaches with ongoing support, and poor integration of in-service content into school practices (Neff, 1990). The programs reviewed in this chapter provide some insights regarding effective strategies for promoting teachers’ abilities to create positive classroom climates. The PATHS program, which had an effect on classroom climate (and presumably on teachers’ behaviors, although this was not assessed) included intensive teacher preparation and ongoing individual consultation support during teachers’ first year of the program, with frequent and non-evaluative feedback. The consultation was embedded in the teacher’s classroom context and was personalized, collaborative, and interactive. School psychologists and other school mental health professionals have a potentially important role to play in promoting teachers’ abilities to create positive classroom climates
212 Jan N. Hughes and Lisa K. Barrois and to relate to and motivate students. Consultee-centered consultation, in which the consultant responds sensitively and respectfully to the teacher’s request for assistance, is particularly well suited to this task (Caplan, 1970; Hughes et al., 2007). The consultant’s role in this model is to establish an egalitarian and interactive relationship with the teacher in which the consultant provides information and emotional support to the teacher who wishes to implement new classroom approaches to improve classroom climate and student motivation. The individual nature of consultee-centered consultation helps to ensure that strategies that emerge from the consultation are not only based on good science but are also consistent with the teacher’s beliefs and philosophy of teaching and well-suited to that particular classroom context. The importance of matching the approach to the teacher’s beliefs is supported by a study finding that teachers were more likely to implement the PATHS program when their pre-existing beliefs about teaching emotions were consistent with the program (Buss & Hughes, 2007). The consultant also assists the teacher in implementing new approaches through the collection and analysis of data, including observations and the provision of nonevaluative feedback. The consultant and the teacher reflect together on the teacher’s experiences, thereby increasing the teacher’s self-awareness and problem-solving skills. The development and evaluation of such individualized and responsive approaches to assisting teachers in creating positive social environments, fostering positive relationships among students and with students, and motivating students to become engaged learners represents a critical direction for future research.
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11 Factors Influencing Teacher Interventions in Bullying Situations Implications for Research and Practice Jodi Burrus Newman, Karin S. Frey, and Diane Carlson Jones, University of Washington Students at school are often involved in and harmed by peer bullying (Hanish & Guerra, 2002; Nishina, Juvonen, & Witkow, 2005; O’Connell, Pepler, & Craig, 1999; Pepler, Jiang, Craig, & Connolly, 2008). Bullying is the act of intentionally and repeatedly hurting someone with less power (Solberg & Olweus, 2003). It can be physical (kicking, slapping, taking belongings), verbal (ridiculing, insulting, mean-spirited teasing), or social/relational (ostracizing, spreading rumors). Large-scale studies in the US indicate that peer bullying increases during the late elementary years and peaks in middle school (Espelage, Bosworth, & Simon, 2001; Frey, Hirschstein, Edstrom, & Snell, 2009; Nansel, Overpeck, Pilla, Ruan, Simon-Morton, et al., 2001). Approximately 30% to 40% of students claim regular victimization at school (Davidson & Demaray, 2007; Swearer & Cary, 2003). Teachers are key players in efforts to prevent bullying and limit its negative effects (Doll, Song, & Siemers, 2004; Hirschstein, Edstrom, Frey, Snell, & MacKenzie, 2007; Kallestad & Olweus, 2003; Kochenderfer-Ladd & Pelletier, 2008; Orpinas, Horne, & Staniszewski, 2003). In fact, teachers are frequently relied upon as “first responders” to instances of bullying both in the classroom (Atlas & Pepler, 1998) and in the larger school context (Parault, Davis, & Pelligrini, 2007). Teacher intervention plays a critical role in representing adult authority and guidance so that the power differential between bullies and targets can be addressed. However, teacher interventions in student bullying vary widely in terms of likelihood, specific strategies employed, and effectiveness (Bradshaw, Sawyer, & O’Brennan, 2007; Craig, Henderson, & Murphy, 2000; Mishna, Scarcello, Pepler, & Wiener, 2005). This chapter critically reviews the literature on teacher interventions in bullying and examines specific factors that account for differences in intervention practice and outcomes. We first provide background information on the effects of student bullying. We then propose a theoretical model depicting teacher interventions in relation to students, classes, and the school community. Our analysis of the literature reveals that these interrelated social contexts influence interventions, and that supportive relationships and practices may effectively reduce bullying behavior.
Outcomes Associated with Bullying Involvement Students who are targets of bullying endure frequent harassment from their peers and often lack the assertiveness and power to end a bullying episode (Olweus, 1993). The negative effects of being targeted may be considerable. Targets often experience decreased psychological wellbeing, disrupted social connections, and compromised opportunities to learn. Psychological problems experienced by some targets include depression, lower self-worth, social anxiety, and loneliness (Hanish & Guerra, 2002; Juvonen, Nishina, & Graham, 2000; Kochenderfer & Ladd, 1996; Nishina et al., 2005). Students who are targets may develop maladaptive ways of
Factors Influencing Teacher Interventions in Bullying Situations 219 coping with the emotional trauma (Hanish & Guerra, 2002; Juvonen et al., 2000). With continued victimization, behavior problems increase and worsen over time (Schwartz, McFaydem-Ketchum, Dodge, Pettit, & Bates, 1998). Class participation (Buhs, Ladd, & Herald, 2006), school attendance (Kochenderfer & Ladd, 1996; Smith, Talamelli, Cowie, Naylor, & Chauhan, 2004), and academic performance decline among the chronically bullied (Nishina et al., 2005; Schwartz, Gorman, Nakamoto, & Toblin, 2005). Some students may attempt to escape daily harassment by dropping out of school (Slee, 1994). Students who bully use aggressive tactics against their peers to secure resources and attain power (Nishina, 2004; Olweus, 1993; Pellegrini, 2002). Some bullies have social-cognitive skill deficits, including hostile biases and poor perspective-taking (Crick & Dodge, 1994; Jolliffe & Farrington, 2006). Others appear to be socially skilled manipulators who understand, but do not care, that their actions hurt people (Gianluca, 2006; Hawley, 2003; Sutton, Smith, & Swettenham, 1999). Short-term outcomes associated with bullying behavior are varied. Some bullies are rejected by their classmates. Others, however, are accepted, supported, and even regarded as popular among peers (Demaray & Malecki, 2003; Rodkin, 2004). In the long run, students who bully may become reliant on coercion, learn to use aggression to harm others, and fail to develop positive relationship skills (Pepler et al., 2008)—failure that may be played out in dating relationships (Pepler et al., 2006), families (Duncan, 1999), and student-teacher relationships (Frey & Nolen, in press). Students who witness bullying may also be adversely affected. Emboldened by the success of others, some student bystanders may become bullies themselves (Bradshaw et al., 2007). Schools may develop “cultures of bullying” (Unnever & Cornell, 2003) in which abusive treatment is expected and tolerated. Other bystanders may be disturbed by fear, guilt, and moral confusion (O’Connell et al., 1999; Jeffrey, Miller, & Linn, 2001). Anxiety and dislike of school increase on days in which middle school students witness others being bullied (Nishina & Juvonen, 2005). Although some adults argue that bullying is beneficial because it strengthens students’ abilities to handle adverse situations (Hazler, Miller, Carney, & Green, 2001), the evidence strongly suggests otherwise. Research clearly indicates that bullying can have a detrimental impact on the emotional, social, and academic lives of targets, bullies, and witnesses.
Teachers Play a Pivotal Role When teacher interventions occur in the context of a comprehensive school-wide bullying prevention program, they can effectively aid students by providing emotional support (Hunter, Boyle, & Warden, 2004), facilitating student problem-solving (Hirschstein et al., 2007), fostering prosocial interactions (Frey et al., 2005), and decreasing bullying behavior (Frey et al., 2005; Olweus, 1993). Unfortunately, this potential is often unrealized because teachers vary in the degree to which they acknowledge, interpret, and intervene to limit bullying behavior (Bradshaw et al., 2007; Craig et al., 2000; Mishna et al., 2005). Many teachers choose not to intervene or express uncertainty about how to respond to bullying (Mishna et al., 2005; Rigby & Bagshaw, 2003). In fact, observations of classrooms indicated that teachers only intervened to stop 18% of bullying interactions (Atlas & Pepler, 1998). The effectiveness of specific intervention strategies is also variable. Nearly 45% of British students who reported that a teacher intervened to stop bullying, felt that the intervention either changed nothing, or made the situation worse (Smith & Shu, 2000). Furthermore, commonly employed “zero-tolerance policies” and exclusionary punishments such as suspension appear to have little merit. These practices are related to negative school climate, unruly student behavior, and lowered achievement (Skiba, Ritter, Simmons, Peterson, & Miller 2006).
220 Jodi Burrus Newman et al. Finally, teachers at schools that are attempting to implement school-wide prevention programs may see few, if any, beneficial outcomes (Smith, Schneider, Smith, & Ananiadou, 2004). What factors account for variation in the likelihood and effectiveness of teachers’ bullying interventions? We propose a model to address this question that is grounded conceptually in socioecological theory (Swearer & Espelage, 2004), a relational perspective on motivation (Baumeister & Leary, 1995; Birch & Ladd, 1996; Connell & Wellborn, 1991; Pianta & Stuhlman, 2004), and a transactional model of development (Sameroff & MacKenzie, 2003). These approaches stress that social interactions and relationships are contextually situated and that individuals and social contexts powerfully affect one another.
The Social Ecology Socioecological theory provides an organizing framework of the multiple embedded contexts, from direct interactions among individuals to the broader culture, which interrelate to influence bullying behavior and intervention practice (Bronfenbrenner, 1979; Swearer & Espelage, 2004). This theory has informed our understanding of who is involved in bullying at school and the relational contexts in which bullying prevention efforts occur. The model presented in Figure 11.1 draws from the work of Frey and Nolen (in press), but we position the teacher at the center of the social ecology. In addressing the role of the teacher, we specify three overlapping relational contexts. The first relational context entails dyadic interactions between teachers and targets, and teachers and bullies. The second context includes the teacher’s interactions with the entire class, as when facilitating peer relationships or establishing classroom norms. Teacher– student and class-wide interactions are situated within and are further influenced by the third context, which includes the support that teachers receive for their bullying interventions from School community School-wide consistency Support for teacher interventions Classroom norms and relationships
Teacher characteristics • Empathy • Efficacy • Seriousness of bullying
Teaching practices with individuals • Recognition • Coaching • Monitoring
Supportive teacherstudent relationships • Responsive • Caring • Authoritative guidance
Teaching practices class-wide • Promoting positive peer relationships • Norm setting • Group instruction • Monitoring
Bully Target Peer relationships Reward or repudiate bullying
Figure 11.1 Relationships Affecting Teacher Interventions in Bullying Situations.
Factors Influencing Teacher Interventions in Bullying Situations 221 school community members such as administrators and other teachers. In each of these multiple contexts, we describe practices that are recommended for bullying prevention. Although it is likely that family influences and the broader culture also affect intervention efforts, we are restricting our analysis to interactions that occur within the school context.
Teacher–Student Relationships that Motivate Socially Responsible Behavior The quality of teacher–student relationships is a central component of our model, a contextual factor that may interact with specific intervention practices. In particular, we propose that supportive teacher–student relationships serve as models for future relationships and help motivate students to adopt prosocial norms (Birch & Ladd, 1996; Connell & Wellborn, 1991; Crosnoe, Johnson, & Elder, 2004; Doll et al., 2004; Hamre & Pianta, 2005; Hughes & Kwok, 2006; Hughes, Lou, Kwok, & Loyd, 2008; Pianta & Stuhlman, 2004; Wentzel, 1997). Supportive teacher–student relationships are defined by three key elements which are depicted in Figure 11.1: responsiveness, caring, and authoritative guidance. The first element entails being sensitive and responsive to students’ needs (Hamre & Pianta, 2005). For example, a teacher who accurately assesses low social-emotional competence among students may respond by teaching the requisite skills (Connell & Wellborn, 1991; Frey et al., 2005). Support also involves having a caring connection with students that is evidenced in a respect for the students and a positive emotional climate (Birch & Ladd, 1996; Hughes et al., 2008; Noddings, 2005; Wentzel, 1997). Finally, supportive relationships necessitate authoritative communication that provides behavioral guidance and sets high social and academic expectations (Birch & Ladd, 1996; Hughes, 2002; Wentzel, 2002). In contrast, unsupportive teacher–student relationships frequently involve adversarial conflict that is discordant and angry (Birch & Ladd, 1996; Hamre, Pianta, Downer, & Mashburn, 2008; Hughes et al., 2008). When teachers have supportive relationships with their students and engage in low levels of adversarial conflict, students are more accepting of peers, prosocial, and competent in social and academic spheres (Birch & Ladd, 1996; Furrer & Skinner, 2003; Hamre & Pianta, 2005; Hughes et al., 2008; Hughes & Kwok, 2006; Malecki & Demaray, 2003). As shown in Figure 11.1, supportive practices within the dyadic teacher–student context consist of recognizing that bullying has occurred, coaching individual students involved in bullying episodes, and monitoring intervention effectiveness. Within the classroom context, supportive practices to reduce bullying involve supporting prosocial peer interactions (Frey et al., 2005; Frey & Nolen, in press), proactive norm-setting, group instruction on social-emotional skills, as well as increased supervision and monitoring (Olweus, 1993). We propose that positive relationships with teachers motivate internalization of prosocial norms and encourage students to attempt new behaviors. The motivating influence of supportive relationships has been studied extensively with respect to promoting academic gains and prosocial interactions at school (Hughes & Barrois, this volume). However, the quality of the teacher–student relationship has received little attention in the bullying literature on teacher interventions. Research on relational contributions to motivation suggests that existing relational contexts and supportive intervention practices may foster beneficial transformational outcomes for students engaged in bullying.
Transactional Model of Intervention Practices: Two Examples The transactional model provides insight into how interactions between individuals and their environment affect development (Sameroff & MacKenzie, 2003). A tenet of the transactional
222 Jodi Burrus Newman et al. model is that individuals bring particular characteristics (e.g., beliefs, skills, processing biases) to interactions that shape the dynamics of the exchange. Furthermore, the environment in which people are situated shapes the beliefs of those involved (Sameroff, 1995). In our model, the outcome of a teacher’s intervention in a bullying situation is a product of bidirectional influences between the teacher and others in the three relational contexts. A description of a four-step hypothetical sequence helps to illustrate the ways in which the transactional dynamic can unfold for a teacher in a classroom. The individual characteristics of the teacher and students and the quality of their ongoing relationships represent the starting point. Next, the teacher recognizes a bullying situation that is occurring among students. The teacher then responds in some manner. Finally, transformational outcomes are observed. Two contrasting scenarios depicting bi-directional influence will further highlight the nature of transactional dynamics. The first example describes a teacher who does not believe that effective interventions are available, and feels overwhelmed in the face of classroom bullying (Mishna et al., 2005). Next, the teacher hears that one student is repeatedly harassed by the other students but does not view the situation as serious. The teacher responds to the situation dismissively (Mishna et al., 2005) and tells the target to “ignore it” (Kochenderfer-Ladd & Pelletier, 2008). Transformational outcomes might include the target using ineffective strategies such as crying or hitting, which could result in increased harassment from the peer group (Wilton, Craig, & Pepler, 2000). The poor outcome may lower the teacher’s self-efficacy regarding bullying interventions, which could make future interventions less likely (Yoon, 2004). In this case the teacher and social environment interacted to create a negative spiral where the relationships between the target, peers, and teacher deteriorated. A more positive scenario is also plausible. The teacher, instead of being overwhelmed by aggressive students, might feel efficacious and able to respond with several intervention strategies (Yoon, 2004). Next, when hearing about the bullying situation, the teacher investigates and actively intervenes. The teacher might provide assertiveness training to the target (Egan & Perry, 1998), separate the target and bully (Kochenderfer-Ladd & Pelletier, 2008), help the targeted student develop friendships (Boulton, Trueman, Chau, Whitehand, & Amatya, 1999), and endeavor to establish more prosocial classroom norms (Roland & Galloway, 2002). Following the intervention, bullying interactions among students may decrease (Kochenderfer-Ladd & Pelletier, 2008; Roland & Galloway, 2002). Furthermore, targeted students may form positive relationships with other students that buffer them from future bullying episodes (Goldbaum, Craig, Peper, & Connolly, 2003). Finally, students who trust that bullying situations will be handled effectively may be more likely to report incidents (Hunter et al., 2004). In both scenarios the existing characteristics of and relationships among the participants influenced the teachers’ response to bullying and practices employed, and the interventions led to widely divergent transformational outcomes. What are the factors that shape the unfolding dynamic of teacher interventions? We now explore the potential for differing outcomes by examining how individual teacher characteristics might influence bullying interventions. Next, we analyze the contribution of our three relational contexts to intervention practice. Examples from evaluations of the Steps to Respect (Committee for Children, 2001) bullying prevention program are used to illustrate how supportive interactions among teachers, students, classes, and the school community can motivate socially responsible behavior.
Teacher Characteristics The transactional model proposes that individual factors influence the dynamics of social interactions (Sameroff, 1995). We therefore begin our analysis of teacher interventions in
Factors Influencing Teacher Interventions in Bullying Situations 223 student bullying episodes by detailing the characteristics of teachers that might impact intervention practice, including empathy, efficacy, and perceptions of the seriousness of the bullying situation. Empathy. Examinations of pre-service teachers’ responses to bullying scenarios indicate that teacher empathy for the target is positively related to the likelihood of intervention (Bauman & Del Rio, 2006; Craig et al., 2000). These results are corroborated by interview data of practicing teachers (Mishna et al., 2005). Teachers who empathize with targets may be more responsive to students’ needs and provide assertiveness instruction, while less empathic teachers may dismiss bullying as unimportant. Efficacy. Some teachers may want to intervene, but lack confidence that they can handle bullying situations (Nicolaides, Toda, & Smith, 2002). Teachers with high self-efficacy are more likely to take action (Yoon, 2004) and are more confident in the effectiveness of their interventions (Bradshaw et al., 2007). Training provided as part of school-wide bullying prevention programs can bolster teachers’ perceptions that they can intervene effectively (Hirschstein & Frey, 2005; Newman-Carlson & Horne, 2004). Although teachers are more likely to intervene with individual students involved in bullying following training (Hirschstein & Frey, 2005), the evidence is less clear on whether the effectiveness of their actions also increases. Teacher beliefs about effective courses of action in bullying situations are also likely to influence intervention practice. For example, teachers who believe that children can avoid bullying by simply avoiding perpetrators are more likely to change seating in order to separate bullytarget dyads (Kochenderfer-Ladd & Pelletier, 2008). Other examples of problem- or skillfocused strategies (Lazarus & Moskowitz, 2000) are assertiveness training or increasing peer empathy for victimized students. An emotion-focused approach may include providing sympathy or reducing feelings of self-blame for victimization. These approaches appear successful in reducing aggression, victimization, and destructive bystander behavior (e.g., Frey et al., 2005; Frey et al., in press; Hirschstein, et al., 2007). As such, they are likely to be preferred by educators who are familiar with research findings. Avoidant responses (e.g., ignoring the problem) and exclusionary punishments may be adopted because teachers do not know which actions are effective, believe that there is no need for teacher intervention, or believe that supportive teacher interventions are ineffective or counterproductive. Unfortunately, the use of avoidant strategies and punishments such as suspension is related to high levels of problematic student behavior (Kochenderfer-Ladd & Pelletier, 2008; Skiba et al., 2006). Seriousness of Bullying. Teachers are likely to intervene in a bullying episode if they believe that the situation is serious (Holt & Keyes, 2004). Two factors inform a teacher’s definition of seriousness: the particular form of bullying and personal witnessing of the episode (Bauman & Del Rio, 2006; Craig et al., 2000; Mishna et al., 2005; Yoon & Kerber, 2003). There is general agreement among students and teachers that physical attacks and verbal insults involving profanity constitute serious bullying and warrant teacher intervention (Bauman & Del Rio, 2006; Hazler et al., 2001; Naylor, Cowie, Cossin, Bettencourt, & Lemme, 2006; Newman & Murray, 2005; Yoon & Kerber, 2003). Students and teachers do not agree, however, on the severity of other forms of bullying such as relational aggression and meanspirited teasing (Mishna et al., 2005). Relational aggression involves actions such as exclusion and gossip (Crick & Grotpeter, 1996). Mean-spirited teasing is a type of verbal attack that incorporates both humor and aggression (Shapiro, Baumeister, & Kessler, 1991). Many students report that these forms of bullying are as harmful as physical aggression (Crick & Grotpeter, 1996; Crick et al., 2001; Newman & Murray, 2005).
224 Jodi Burrus Newman et al. In contrast to the perceptions of many students, teachers tend to view relational aggression as less serious than physical bullying (Bauman & Del Rio, 2006; Craig et al., 2000; Mishna et al., 2005) and may even find teasing to be humorous (Pexman, Glenwright, Krol, & James, 2005), resulting in fewer interventions (Bauman & Del Rio, 2006; Craig et al., 2000; Yoon & Kerber, 2003). The perceived seriousness of physical attacks may be related to the greater likelihood of teachers directly observing the events. It may be more difficult for teachers to see gossip and ostracism. Teachers must rely on reports from students to learn about these types of events and their impact. Regardless of the form of aggression, teachers rate witnessed events as more serious than reported events (Craig et al., 2000). Summary. The evidence suggests that teachers who are empathic, efficacious, and who witness bullying episodes that they deem to be serious are likely to intervene. However, the research linking teacher characteristics to bullying intervention practice is not without limitations. There is a need for longitudinal research and multi-method assessments because many of the studies are cross-sectional and based on self-report data. Furthermore, the literature has focused primarily on predicting the likelihood that a teacher will intervene. Although this is an important issue, there is very little information on the process by which teachers decide to intervene or select a particular intervention strategy for a given situation. Finally, the actual effectiveness of the interventions employed needs to be evaluated. Despite these limitations, the data warrant a call for increased teacher training on bullying issues. Greater understanding of the harm done to targets by teasing, gossip, and exclusion may engender increased recognition of bullying, empathy for targets, and perceptions of seriousness. Furthermore, better preparing teachers to deal effectively with bullying could also increase the likelihood of intervention and encourage teachers to use more supportive practices.
Teachers in Relation to Students, Classes, and the School Community The Teacher–Student Relational Context Within the dyadic relational context, teachers and students may develop perceptions of one another that influence the likelihood and effectiveness of bullying interventions. Specifically, teachers’ perceptions of students may influence their ability to respond to bullying situations in a supportive manner (Frey, 2005; Frey & Nolen, in press; Mishna et al., 2005; Nesdale & Pickering, 2006). Furthermore, positive outcomes such as reduced emotional distress for targets (Davidson & Demaray, 2007; Malecki & Demaray, 2004) appear to be more likely when students perceive teachers as supportive. Teachers’ Perceptions of Students. Teacher perceptions of students may impact intervention practice (Mishna et al., 2005; Nesdale & Pickering, 2006). Research on the personal characteristics of targets and bullies has confirmed that there is not a single constellation of attributes that uniformly describes each group. Some targets, for example, are withdrawn and suffer from internalizing symptoms. Other targeted students, typified by disruptive and aggressive behavior, report the highest levels of social-emotional dysfunction (Schwartz, Proctor, & Chien, 2001). Teachers who expect that all targets are meek and withdrawn may be unable to recognize bullying when the students involved do not conform to these stereotyped expectations. Teacher judgments about student behavior are also embedded in their evaluation of students as “good” or “bad” children (Nesdale & Pickering, 2006) so that teachers may have a more difficult time identifying popular and cooperative students as perpetrators (Frey &
Factors Influencing Teacher Interventions in Bullying Situations 225 Nolen, in press). Preconceived notions about students, then, can affect teachers’ interpretation of aggression or disruptive behavior as benign or ambiguous, e.g., “That student is a good kid and didn’t mean to do it,” or “I know those kids aren’t a problem” (Frey & Nolen, in press; Mishna et al., 2005). If teachers fail to recognize bullying behavior due to an erroneous belief about the students involved, then opportunities to intervene and provide support may be missed. Students’ Perceptions of Teachers. Perceived teacher support appears to aid students who are involved in bullying situations. Malecki and Demaray (2004) found that the relationship between victimization and academic maladjustment was fully mediated by perceived teacher support. Other research has demonstrated that perceived teacher support moderated the relationship between victimization and emotional well-being among boys. Specifically, frequently targeted boys who experienced low levels of teacher support reported more internalizing problems than frequently targeted boys who experienced higher levels of teacher support. (Davidson & Demaray, 2007). Targets are not the only students to benefit from perceived teacher support. Doll et al. (2004) found that aggressive behavior was reduced when students reported high levels of teacher support. Unfortunately, relationships between teachers and the students involved in bullying are often unsupportive (Hanish, Kochenderfer-Ladd, Fabes, Martin, & Denning, 2004). Perceived teacher support is lowest among students who bully (Demaray & Malecki, 2003). In addition, the more students are involved in bullying, the less likely they are to view teacher interventions in bullying episodes as helpful (Rigby & Bagshaw, 2003; Swearer & Cary, 2003). The negative perceptions of teachers held by students who are highly involved in bullying could have a detrimental impact on future teacher–student interactions (Rigby & Bagshaw, 2003). If students feel that teacher interventions are unhelpful, they may be less likely to seek adult assistance with bullying situations (Hunter et al., 2004). The lack of perceived teacher support among bullies and targets, in conjunction with research indicating that teacher support improves emotional outcomes for students (Birch & Ladd, 1996; Hamre & Pianta, 2008; Malecki & Demaray, 2004), highlights the importance of being responsive to the needs of students who are involved in bullying. When teachers maintain close relationships with these students, they can also monitor the effectiveness of their intervention efforts and make adjustments as necessary to deter future bullying involvement. Steps to Providing Support for Students Involved in Bullying. The coaching model proposed in the Steps to Respect program provides educators with guidelines for brief sessions that provide supportive guidance to targets and bullies separately. The coaching model encourages teachers to: (1) affirm the target’s emotional response; (2) assess the history of the problem and current safety needs; (3) have students generate solutions; (4) practice necessary skills such as assertive responding; and (5) check-in with students to ensure that the plan is working (Hirschstein et al., 2007). Coaching helps teachers respond to the needs of those who are involved in bullying by assessing which skills require development, teaching students those skills, and working with students to ensure that competence is attained. Emotional needs are also met in that teachers are prompted to listen empathically and affirm the student’s emotional reaction. Checking with students to see if the intervention is working can foster a sense of trust with targeted children, and demonstrate teacher commitment to aggressive students who may hope that their teachers have short attention spans. The coaching model allows teachers to intervene following relatively minor incidents, which enables constructive problem-solving approaches, rather than waiting until the behavior is egregious enough to warrant punishments such as detention or suspension (Frey & Newman, 2008). Adversarial conflict is absent from the
226 Jodi Burrus Newman et al. coaching model. Although not incompatible with reprimands, parental notification, or even loss of privileges for repeat offenders, coaching promotes the development of skills such as assertiveness, social problem-solving, and emotion regulation in the context of a supportive teacher–student relationship (Committee for Children, 2001). Research confirms the effectiveness of the coaching model. Teachers who used the Steps to Respect program and reported brief coaching sessions more than once a week saw greater decreases in victimization, aggressive responding, and encouragement of bullying than their colleagues who used the program but coached students less frequently (Hirschstein et al., 2007). Though this study points toward the benefits of coaching, the authors stress that coaching is just one aspect of a school-wide intervention. Interactions at the class and school levels may be critical to the reductions in bullying found in schools that use the Steps to Respect program. Summary. Teacher–student interactions have the potential to attenuate the negative emotional effects of bullying (Davidson & Demaray, 2007; Malecki & Demaray, 2004) and reduce bullying behavior (Doll et al., 2007), provided they take place within the context of a supportive relationship. Teachers may be able to increase student perceptions of teacher support by accurately recognizing bullying situations and monitoring the effectiveness of their interventions. The coaching model used with the Steps to Respect program provides educators with specific guidelines for engaging in supportive one-on-one sessions with bullies and targets. The effectiveness of this approach suggests that more teachers should be trained in the coaching model (Hirschstein et al., 2007). Further research on teacher interventions with individual students is necessary. First, there have been very few studies documenting the effectiveness of specific strategies that teachers use when intervening in bullying. Although we know how general constructs such as responsiveness, caring, and authoritative guidance affect student outcomes, we know very little about how specific teacher intervention practices are perceived by students involved in bullying and the factors that affect student perceptions of teacher support. Second, the effectiveness of the coaching model has only been documented within the context of a bullying prevention program that includes classroom lessons and school-wide rules (Hirschstein et al., 2007). Evaluation study designs that enable program component analyses are rare (for an exception, see Webster-Stratton, Reid, & Hammond, 2004), but necessary in order to establish the effectiveness of the coaching method under other setting conditions. This fact dovetails with a third issue. Dyadic teacher–student interactions, even when they foster social-emotional skills and provide concrete evidence of teacher support, do not address factors related to the larger social ecology. Because bullying reflects power and status concerns within peer groups (Nishina, 2004; Pellegrini, 2002), the classroom provides an important venue for teacher intervention. The Teacher–Class Relational Context Teachers not only have relationships with individual students, but with students as a group. The teacher–class relationship can be considered an element of the classroom climate that reflects the normative quality of support that the teacher enacts across students (Hughes, Zhang, & Hill, 2006). In addition, teacher practices that promote prosocial values, empathy, cooperation, and social responsibility (Rimm-Kaufman, Fan, Chiu, & You, 2007; Solomon, Battistich, Kim, & Watson, 1997) contribute to the social-emotional climate of the classroom and reflect the norms that enhance positive relations among students. These two elements of the teacher–class relational context, teacher connections with the class as a whole and peer relationships, are depicted in our model (see Figure 11.1). It is our contention that a
Factors Influencing Teacher Interventions in Bullying Situations 227 supportive classroom environment characterized by caring teacher and peer relationships, responsiveness to student needs, and authoritative teacher guidance (Hughes, 2002; Wentzel, 2002) will provide a context in which effective anti-bullying interventions can occur. Furthermore, when class-wide interventions incorporate these elements and are implemented within the context of a school-wide bullying prevention program, reductions in bullying are evident (Frey et al., 2005). Peer Relationships. Peers play an active role in assuaging and aggravating bullying. An observational study of elementary students in class indicates that peers are involved, either actively or passively, in 85% of bullying episodes (Atlas & Pepler, 1998). Peers can reject or support targets (Malecki & Demaray, 2004; Salmivalli, Lagerspetz, Bjorkqvist, Osterman, & Kaukialnen, 1996). Although chronic targets are frequently lonely and isolated by their peers (Boivin, Hymel, & Hodges, 2001; Salmivalli et al., 1996), some targets maintain their friends and extract themselves from bullying involvement (Boulton et al., 1999). Furthermore, bullying behavior can be rewarded or rebuffed by peers (Hanish et al., 2004; Pellegrini, 2002; Salmivalli et al., 1996). Socially savvy adolescents often engage in bullying to attain or maintain high peer status (Nishina, 2004; Pellegrini, 2002; Rodkin, 2004). The peer group often assists bullies, inadvertently or consciously, in accruing resources and power. In contrast, younger students often isolate aggressive peers (Hanish et al., 2004), particularly in classes that have established prosocial norms (Henry et al., 2000). Student perceptions of and experiences in peer contexts influence behavioral outcomes associated with bullying. Bullying behavior occurs more often in classes where aggression is accepted as the norm. The prevalence of argumentative behavior is associated with increases in peer bullying (Frey & Nolen, in press). Class-wide endorsements of pro-violence attitudes (e.g., “Sometimes it’s OK to beat people up”) predict high levels of aggressive behavior among adolescents (Bernburg & Thorlindsson, 2005) and preadolescents, even when accounting for prior behavior (Huesmann & Guerra, 1997). In contrast, class-wide student norms against bullying may deter bullying behavior. A scenario-based study of late elementary Finnish students found that high support for group anti-bullying norms predicted peer defense of targets (Salmivalli & Voeten, 2004). Furthermore, student-reported higher levels of peer inclusion predicted lower rates of class-wide aggression (Doll et al., 2004). Finally, students in classes characterized by high levels of prosocial behavior between classmates displayed increased levels of social competence (Hoglund & Leadbeater, 2004). These results suggest that the classroom peer ecology impacts how individual students behave toward each other, for better or for worse. Teacher Influence in the Classroom Context. Teachers appear to deter bullying and promote socially responsible behavior when they promote positive peer relationships (Boulton et al., 1999; Doll et al., 2004), respond to student needs via monitoring and skill instruction (Frey et al., 2005; Olweus, 1993), and provide authoritative guidance (Hughes, 2002; Wentzel, 2002) through norm-setting. Positive peer relationships may be facilitated by arranging group partners and seating to encourage friendships with the target (Doll et al., 2004). When teacher appraisals of students and class participation structures are altered, there is an increased likelihood of inclusion for all students (Cazden, 1993; Cohan & Lotan, 1995; Olweus, 1993). Teachers may also promote positive peer relationships by engaging in caring behavior in their interactions with students class-wide (Hughes et al., 2006). Teachers can be responsive to student needs by monitoring peer interactions and responding immediately to bullying situations (Olweus, 1993). Furthermore, teachers may address skill deficits via class-wide instruction. Regularly scheduled class meetings can provide a forum for building social competence by teaching all students the skills necessary to thwart bullying such as assertiveness and friendship-building (Frey et al., 2005). Some researchers
228 Jodi Burrus Newman et al. have argued that instructing socially savvy bullies in social skills as part of class-wide curriculum may create more effective bullies (Sutton et al., 1999). An alternative perspective is that some students who bully have leadership skills and need to be taught more mature and respectful means of influence. In addition, targets who engage in reactive aggression (Schwartz et al., 2001) may benefit from explicit instruction in emotion regulation (Wilton et al., 2000). Class-wide interventions that provide bystanders and targets with the social-emotional skills to handle bullying situations assertively have been shown to be effective in reducing bullying behavior (Frey et al., 2005; Leadbeater & Hoglund, 2006), when taught in conjunction with school-wide bullying prevention programs. Teachers provide authoritative guidance when they lead students in developing class norms against bullying and for social responsibility. Henry et al. (2000) found that classrooms where both the teacher and students explicitly stated prosocial norms showed the greatest reductions in aggressive behavior. The teacher’s role in establishing these norms and maintaining them is critical. First, positive student-teacher relationships are associated with greater cooperation on the part of students (Wentzel, 1997). Second, teachers must consistently monitor and enforce class norms. When students are targeted despite being in classrooms where most interactions are prosocial, the negative emotional effects may be worse than when students are targeted in classrooms where harassment is normative (Bellmore, Witkow, Graham, & Juvonen, 2004). Steps to Providing Support for the Entire Class. The Steps to Respect program provides educators with guidance and tools for fostering a supportive classroom community by providing a class curriculum and guidelines for teacher-class interactions. Steps to Respect responds to student needs for social-emotional skill competence by teaching friendship-building, assertiveness, emotion regulation, and constructive problem-solving. When social problems arise, teachers are encouraged to draw upon the skills taught in previous lessons and facilitate student use of the concepts in actual bullying situations. The classroom lessons, especially ones on friendship and constructive problem-solving, are designed to promote caring and positive relationships among students. Finally, authoritative guidance is promoted in that prosocial norms for behavior are explicitly defined, discussed, and enforced. Adherence to the Steps to Respect curriculum has been shown to increase teacher ratings of students’ prosocial skills (Hirschstein et al., 2007). Summary. Teachers who support student needs and promote positive peer relationships so that the classroom becomes an inclusive community rather than a status-driven hierarchy are likely to observe positive social, emotional, and academic outcomes (Cohan & Lotan, 1995; Demaray, Malecki, Davidson, Hodgson, & Rebus, 2005; Doll et al., 2004; Hamre & Pianta, 2005; Hughes & Barrois, this volume; Hughes et al., 2006; Juvonen, Le, Kaganoff, Augustine, & Constant, 2004; Patrick, Ryan, & Kaplan, 2007). Furthermore, the skills gained via classwide interventions may serve to deter bullying behavior by teaching targets and bystanders how to assertively end a bullying episode (Frey et al., 2005), thereby transforming the classroom exchanges. Further research is needed to explain the mechanisms underlying how supportive teacherclass interactions, such as norm-setting and friendship-building, influence bullying behavior, especially among middle school students. Young adolescents experience the highest levels of bullying (Nansel et al., 2001) and are also likely to reward bullying behavior by bestowing high status on those who employ bullying tactics (Pellegrini, 2002). Longitudinal research is needed to analyze how individual teacher and student characteristics interact within classroom and school contexts to bolster or attenuate bullying behavior among adolescents. Maintaining a positive relationship with each student may not be sufficient to thwart bullying. Teachers need to be aware of and effectively manage peer relationships within the
Factors Influencing Teacher Interventions in Bullying Situations 229 classroom and ensure that students have the skills to competently rebuke bullying behavior. Although the idea that a supportive classroom context is foundational for academic learning has been put forth and endorsed by master educators (Paley, 1992) and has received empirical support in the research literature (Birch & Ladd, 1996; Juvonen et al., 2004), some teachers fear that intervening will require too much time and detract from academic subjects (Limber, 2004). These concerns can be addressed by providing teachers with accurate information and implementation support. The School Community Relational Context Teachers and students operate within a school community that helps determine the likelihood of intervention and the effectiveness of these efforts. School-wide bullying prevention programs may incorporate the intervention strategies described above such as individual skills training and establishing prosocial classroom norms (e.g., Frey et al., 2005; Olweus, 1993; Leadbeater & Hoglund, 2006). In addition, they tend to include teacher training, adoption of school-wide policies, and agreement among staff members to implement the program consistently. These activities that occur throughout the school are represented in our model as the outermost circle labeled “School Community” (see Figure 11.1). Consistency in expectations across all domains of school life, from the classroom to the playground, is what sets school-wide programs apart from smaller-scale interventions. A child who learns to respond to bullying with a strong and calm voice can expect that most other students from different classes will abide by the same norms when they are together in the lunch room or on the bus. Thus, instead of having widely divergent sets of norms that students must navigate, the entire school community is working together to support students and reduce bullying behavior. For these reasons, researchers endorse the school-wide approach to bullying intervention (Hirschstein et al., 2007; Greenberg et al., 2003; Olweus, 1993). Some educators point out that considerable effort can go into implementing and sustaining a school-wide bullying prevention program (Limber, 2004). Others argue that without a school-wide intervention more effort is required because of the repeated disruptions that detract from academic work. In any case, it can be difficult for educators to maintain their motivation for using a school-wide bullying prevention program if benefits are not immediately visible. An evaluation of the Steps to Respect program found that many of the positive program effects were not apparent until 18 months after the program began (Frey et al., in press). Successful implementation of a school-wide bullying prevention program may require that members of the school community make a long-term commitment to intervention and support one another over time. Supportive School-Wide Interactions. Teachers need the support of their principal and colleagues in order to make bullying prevention a priority and sustain quality implementation over time (Kam, Greenberg, & Walls, 2003). Supportive interactions in the school community context entail responsively meeting teachers’ needs for assistance with the implementation process, fostering positive relationships among school staff, and monitoring progress toward program goals (Smith et al., 2004; Knapp, Swinnerton, Copland, & Monpas-Huber, 2006; Payne, Gottfredson, & Gottfredson, 2006). Some teachers are concerned that they lack the skills to perform interventions effectively (Mishna et al., 2005). These concerns reflect needs for professional development activities that teach intervention skills, raise self-efficacy, and demonstrate how to integrate the program into daily activities. Both teacher training and program support from school administrators have been shown to positively impact the degree to which prevention programs are
230 Jodi Burrus Newman et al. incorporated into existing routines (Payne et al., 2006). Data specifically related to bullying intervention practice indicate that teacher training can help raise self-efficacy (Hirschstein & Frey, 2005; Newman-Carlson & Horne, 2004), and that teachers with high self-efficacy are more likely to take action when confronted with a bullying episode (Bradshaw et al., 2007; Yoon, 2004). Positive relationships among teachers are instrumental in facilitating improved student outcomes and transformative changes in schools (Lee & Smith, 1996; Louis, Marks, & Kruse, 1996). Teachers who work cooperatively to enhance their teaching practice and the educational experience of students create the type of community that is credited with fostering student success (Louis et al., 1996). Communication among teachers and administrators can facilitate program implementation (Payne et al., 2006). Kallestead and Olweus (2003) found that school-wide levels of teacher openness to communication supported the implementation of the Olweus bullying prevention program. Communication regarding the school’s progress toward meeting program goals may be especially critical. A review of bullying prevention program implementation studies found that monitoring outcomes greatly enhanced program effectiveness (Smith et al., 2004). This finding makes sense in light of the extensive research on data-informed decision-making for school reform (Knapp et al., 2006). Reform efforts are more effective when a culture of inquiry is nurtured and data are used to inform decisions regarding teaching practice and program improvement (Copland, 2003). With respect to bullying programs, a 10-step rubric for data-informed decision-making is outlined by Swearer and Espelage (2004). The process includes conducting a multi-informant baseline assessment of bullying, using the data to develop context-specific bullying interventions, sharing the data with key constituencies such as parents and staff, and continually collecting data to refine intervention efforts. Bullying intervention presents a unique challenge because the greatest change is likely to be out of sight in halls and playgrounds and some benefits may take more than a year to detect. This may be frustrating, as educators need verification that their efforts are fruitful. Furthermore, one of the easiest monitoring methods, collecting self-reports of victimization, may be unlikely to detect positive results. Evaluations of the Steps to Respect program found that observed rates of bullying and victimization decreased over the course of 18 months, while self-reports did not change (Frey et al., in press). Therefore, educators should be encouraged to look at alternative outcomes (Leff, Power, & Goldstein, 2004). For example, one school asked students: “What can the adults do to make bullying happen less often?” Student comments (e.g., “If someone tells you that they are being bullied, listen and pay attention! Don’t just tell the bully to stop, make sure they stop, and check-in on the person who was being bullied to make sure it stopped!”) suggested that teachers and administrators were not sufficiently responsive and that there was insufficient follow-up on cases. The school staff then used the student feedback to refine their efforts (Frey & Newman, 2008). Such monitoring strategies may help schools persist through the implementation process and sustain the program over time. Overall, the literature indicates that supportive relationships among educators, which generate a collective commitment to improving school programs and teaching practices, are associated with effective program outcomes. Furthermore, program monitoring may be essential to the success of anti-bullying programs (Smith et al, 2004), and should provide educators with ideas for how to refine their intervention practice (Frey & Newman, 2008). Steps to Supporting Educators. The Steps to Respect bullying prevention program was designed with implementation and sustainability in mind. The program meets teachers’ needs by providing training and a thorough manual. Furthermore, the program comes with evalua-
Factors Influencing Teacher Interventions in Bullying Situations 231 tion tools and examples of effective school-wide procedures. When combined with supportive school leadership, these resources help teachers implement the program with fidelity. Summary. Research demonstrates that bullying behavior can harm targets and perpetrators. It also shows that educators can successfully intervene to support students and prevent bullying, particularly with the use of school-wide interventions (Greenberg et al., 2003). Supportive leadership and program monitoring may help to ensure high-quality implementation. Additional research is needed to determine how teachers can be better supported by the school community in their intervention efforts.
Implications and Ideas for Further Research Bullying is a pernicious problem that, if ignored, can lead to detrimental student outcomes. Teacher interventions have the potential to reduce bullying and assuage its negative effects. This chapter has demonstrated how the individual characteristics and practices of teachers interact with the teacher–student, classroom, and school community relational contexts to affect bullying dynamics and outcomes. Over time, being responsive to the needs of all members of the school community, fostering caring relationships, and providing authoritative guidance may improve intervention efforts. The practices described in this chapter such as coaching, monitoring, skill instruction, and prosocial norm development may promote supportive relationships and deter bullying behavior when implemented in the context of a school-wide program. Throughout this chapter we have emphasized topics that are deserving of further research. In our opinion, a few areas are most pressing. First, mechanisms describing how classroom cultures shift from being bully-tolerant to bully-resistant are clearly needed. The literature points to some factors that influence this shift, but research is still in its infancy. Second, our knowledge of factors related to the effectiveness of specific teacher intervention practices is limited. Specifically, more research is necessary regarding teacher empathy and efficacy. Furthermore, it is time to move beyond assessing the likelihood of teacher intervention toward an understanding of the factors that improve actual intervention practice. Finally, more work is required to identify the needs of teachers as they attempt to support students and reduce bullying at their schools. It is vital that researchers continue to support educators in these efforts because positive relationships among students and teachers within the classroom context, and among educators themselves, serve as the foundation for student learning and well-being.
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12 Development, Evaluation, and Diffusion of a National AntiBullying Program, KiVa Christina Salmivalli and Antti Kärnä, Department of Psychology, University of Turku Elisa Poskiparta, Centre for Learning Research, University of Turku Bullying is a specific subtype of aggressive behavior, which has at least three universally accepted defining characteristics: (1) intent to harm, (2) repetition over time, and (3) a power differential, that is, the victim finds it difficult to defend him- or herself against the perpetrator. One of the key features that differentiate bullying from conflicts, quarrels, or fights, is thus the imbalance of power between the perpetrator and the victim. On average, around 11% of school-aged children are bullied repeatedly (Craig & Harel, 2004), while bullies represent another 11%. Approximately 4% to 6 % of children can be classified as bully-victims who both bully others and are bullied themselves (Haynie et al., 2001; Nansel et al., 2001). Research has shown that victimization has several negative consequences both in the short and in the long term (e.g., Hawker & Boulton, 2000; Isaacs, Hodges, & Salmivalli, 2008; Olweus, 1994; Salmivalli & Isaacs, 2005), and it is widely recognized as a serious problem that needs to be tackled through effective prevention and intervention. After the first large-scale intervention study in the 1980s by Dan Olweus in Norway (Olweus, 1994), an increasing number of intervention programs has been developed and evaluated in different countries. Unfortunately, the results have been much more modest than was hoped for (Smith, Pepler, & Rigby, 2004; Smith, Schneider, Smith, & Ananiadou, 2004). In Finland, the Ministry of Education has been funding the development and evaluation of a national anti-bullying program since 2006. The program, named KiVa (an acronym for Kiusaamista Vastaan, against bullying), has been developed and initially evaluated in the University of Turku, in collaboration between the Department of Psychology and the Centre for Learning Research. The KiVa project is co-led by the first and the third authors, and the evaluation of program effectiveness is the topic of the PhD of the second author. We have just renewed our contract with the Ministry to include also the initial phase of program diffusion. In the present chapter, we describe the theoretical basis and the main contents of KiVa and present our large-scale study to evaluate its effectiveness, along with the plan regarding the diffusion of KiVa for national use.
Background of KiVa The KiVa program is based on our group’s long research tradition on bullying as a group phenomenon. In the early 1990s, we started to examine how children who are neither victims nor bullies behave when witnessing bullying, and how their actions (or lack of them) might
Development of a National Anti-Bullying Program, KiVa 239 influence the maintenance of bullying or the feelings and adjustment of the victim. In the early studies, we identified six different participant roles children may have in bullying situations. To put it shortly, a child might take on the role (or be forced into a role) of a victim, a bully, an assistant of the bully, a reinforcer of the bully, an outsider, or a defender of the victim (Salmivalli, Lagerspetz, Björkqvist, Österman, & Kaukiainen, 2006). Since then, numerous studies have shown that rather than supporting the victim, many children act in ways that encourage and maintain bullying (Andreou & Metallidou, 2004; Camodeca & Goossens, 2005; Goossens, Olthof & Dekker, 2006; Menesini, Codecasa, Benelli, & Cowie, 2003; Salmivalli, Kaukiainen, Kaistaniemi & Lagerspetz, 1999; Salmivalli, Lappalainen & Lagerspetz, 1998; Salmivalli & Voeten, 2004; Schäfer & Korn, 2004; Sutton & Smith, 1999). The behavior of onlookers does matter. The victims who have classmates supporting and defending them are better off than victims without defenders. The defended victims are less depressed and anxious, they have a higher self-esteem, and they are less rejected by peers than victims without defenders (Sainio, Veenstra, Huitsing, & Salmivalli, submitted). Furthermore, it has been shown that in classrooms where reinforcing the bully is normative behavior (i.e., typical of many children), the likelihood of victimization is higher (Kärnä, Salmivalli, & Poskiparta, 2008). In addition, Kärnä, Voeten, Poskiparta, and Salmivalli (2010) have shown that individual-level risk factors, such as anxiety and peer rejection, are more likely to lead to victimization in classrooms where reinforcing is common, whereas a high level of defending in a classroom minimizes the effects of such individual risk factors. An important message from these studies is that to reduce victimization, we do not necessarily need to change the victims and make them “less vulnerable.” The behavior of the aggressive bullies, on the other hand, might be difficult to change directly, if the peer context is ignored. Influencing the behaviors of classmates can reduce the rewards gained by the bullies and consequently, their motivation to bully in the first place. Although individual characteristics of children, such as attitudes, self-efficacy, and empathy towards victims, predict variation in the participant roles they take on (Caravita, DiBlasio, & Salmivalli, 2008; Pöyhönen & Salmivalli, 2008; Salmivalli, Kaukiainen, Kaistaniemi, & Lagerspetz, 1999), classroom context seems to matter as well. Classrooms differ from each other in the levels of reinforcing the bully or defending the victim (Salmivalli & Voeten, 2004). In a recent study, we found that the proportions of variance at the classroom level, so-called intra-class correlations, for reinforcing and defending were as high as .19 and .35, respectively (Kärnä et al., 2010). This means that although two-thirds (65%) of the total variation in defending behavior, for instance, is due to individual differences, the rest (35%) is due to differences between different classrooms and (to a small extent) schools. There is something in individual children, but also something in the classroom context that drives the behavior of children in bullying incidents. In the KiVa program, there is a strong emphasis on influencing the onlookers, who are neither bullies nor victims, to make them show that they are against bullying and to make them support the victim, rather than encourage the bully. Toward this end, we have developed several universal actions, such as student lessons, and an anti-bullying computer game. However, we believe that indicated actions are also needed to tackle the actual cases of bullying that come to light. The indicated actions include individual and small group discussions with the bullies, victims, and prosocial classmates who are challenged to support the victim in the future. These discussions are effectuated by so-called school teams, together with classroom teachers. The schools are provided with support both before and during the implementation of the program.
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Contents of KiVa: Universal Actions Student Lessons The KiVa program has three different developmentally appropriate versions for grade levels 1–3, 4–6, and 7–9. In Finland, children start school at the age of seven, and grades 1–6 represent the primary school years whereas grades 7–9 constitute the secondary school in the basic education. In both primary school versions (grades 1–3 and 4–6), the universal actions of the KiVa program include 20 hours of student lessons (10 double lessons) that are given during one school year. The lessons are carried out by the classroom teachers and they involve discussion, group work, short films about bullying, and role-play exercises. The topics of the lessons proceed from more general topics, such as the importance of respect in relationships and group communication and group pressure, to bullying and its mechanisms and consequences. For instance, in the short films that are viewed and discussed together adults who were bullied as children tell about their schooldays and how their experiences have affected their life even decades later. Several lessons concern the role of the group in either maintaining bullying or putting an end to it. The group exercises involve, among other things, brainstorming different ways to support and help the bullied victims, and practicing these ways. As the lessons proceed, class rules are adopted one by one. Each rule is based on the central topic of the corresponding lesson(s). At the end of the school year the class rules are put together as the KiVa contract, which is signed by everyone. In the secondary school (grades 7–9), the program involves four central themes. The program manual gives recommendations regarding the time to be used for working on each theme, but the schools themselves decide how they organize the school year around the themes (as a sequence of lessons, several theme days, and so on). The central aims of the student lessons (as well as the themes) are: (a) to raise awareness of the role that group plays in maintaining bullying; (b) to increase empathy towards victims; (c) to promote children’s strategies of supporting the victim and thus their self-efficacy to do so; and (d) to increase children’s coping skills when victimized. Essentially, the lessons try to help children resolve the social dilemma they are faced with, that is, doing what they know is right or doing what seems to be normative in the group. The Anti-Bullying Computer Game A unique feature of the KiVa program is the anti-bullying computer game (Figure 12.1) included in the primary school versions of the program. The students play the game during and between the lessons described above. The game involves five levels, each of which is played as soon as particular lessons have been given in the classroom. Additionally, students who have internet access can play the game in their free time at home as well. In the version of the KiVa game created for grades 4–6, each level includes three components that have been named I KNOW, I CAN, and I DO. In the “I Know” component, the students learn new facts about bullying but also examine what they have learnt from the lessons thus far. They are asked questions about the content of the lessons in game-like tasks, and they can test themselves with respect to different characteristics (e.g., how well you can resist group pressure; what kind of classmate you are). In the “I Can” component, the students move around in a virtual school and face different challenging situations in the school corridors, playgrounds, and lunchrooms. They make decisions regarding how to respond in these situations, what to say and what to do, and get
Development of a National Anti-Bullying Program, KiVa 241
Figure 12.1 A Scene from the KiVa Computer Game (“I Can” Component), Version for Grade Levels 4–6.
feedback based on the choices they make. They can also examine the feelings and thoughts of other characters in the game before and after their own actions. The third component, “I Do,” is designed to encourage students to make use of their knowledge and skills in real-life situations. This happens by asking them to report—at each level of the game—which ones of the learned skills they have put into practice—for instance, whether they have treated others with respect, whether they have resisted group pressure, or whether they have supported someone who was victimized. Again, the students get feedback based on their reports. For secondary school students, there is a different virtual learning environment called KiVa Street. It is an internet forum where the students sign in and go around, visiting different places. For instance, they can go to a library and find information about bullying, or they can enter a movie theatre and watch short films about bullying. Similar to the computer game, the KiVa Street aims at providing knowledge, skills, and motivation to change one’s own behavior related to bullying. Involving Both School and Parents To prevent bullying in the schoolyard, we provide vests for teachers supervising the recess, in order to enhance their visibility and to signal that bullying is taken seriously in the school. There are other symbols, such as posters, reminding the students and the school personnel about KiVa. We provide schools with PowerPoint slides they can use when introducing the program for the whole personnel. The parents are also involved in the universal part of the program. A parents’ guide is sent to each home that includes information about bullying and advice concerning ways in which the parents can prevent and reduce the problem.
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The Indicated Actions: Tackling the Acute Cases To effectuate the indicated actions of the KiVa intervention program, there is a team of three teachers (or other school personnel) in each participating school that tackles, together with the classroom teacher, the cases of bullying that come to light. This happens through a set of individual and group discussions that one or two team members have with the victim and with the bullies, and systematic follow-up meetings. In addition to these discussions, the classroom teacher arranges a meeting with 2–4 classmates in order to encourage them to support the victimized child. The teacher manuals and the training provided (see below) include detailed information about how the discussions are carried through. The indicated actions of KiVa are similar in all grade levels. As bullying often occurs when adults are not around and thus remains unnoticed by teachers and parents, it is important to encourage the students to report bullying. We believe that when children are told about the KiVa program, early in the first student lesson, and reminded about it throughout the school year (by the lessons, the computer game, the posters hanging on the school wall, etc.) they come to believe that adults at the school take bullying seriously and the victims are likely to get help. Consequently, both victims as well as onlookers who merely observe bullying will be more likely to report it. Furthermore, both school staff and parents are given information about bullying and advice concerning how to detect it, which hopefully leads to more awareness and skill in identifying the bullying that is going on. The core components of KiVa (both universal and indicated actions) are described in Table 12.1.
Table 12.1 The Core Components (Universal and Indicated Actions) of the KiVa Anti-Bullying Program Universal
Indicated
Target
All children
Individual bully/ies and victim
+ Selected (prosocial, high-status) classmates
Aim
Reducing pro-bullying behaviors Increasing peer support for victims Influencing classroom norms BY – increasing awareness, empathy, and efficacy to intervene immediately
Stopping the ongoing bullying Supporting the victim
Increasing peer support for the victim
BY – making clear that bullying is not tolerated and has to stop
BY – using high-status peers as protective friends and as models for others
Means
Student lessons Anti-bullying computer game Parents’ guide
Individual and small group discussions Follow-up discussions
Small-group discussion
Agent
Classroom teacher
School team member
Classroom teacher
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Training Days and School Network Meetings During the evaluation phase of KiVa, the teachers and school teams from the pilot schools were supported in the implementation in several ways. There were two full days of face-to-face training organized in each province. Furthermore, networks of school teams were created, in which each network consisted of three school teams (i.e., nine teachers or other adults working in the school). The network members met three times during the school year, with one person working in the KiVa project serving as the “key person” and guiding the network. We have found the meetings to be highly beneficial for ourselves (the program developers) as well. We have gained first-hand experience of the successes and possible obstacles in program implementation. The experiences from the training as well as from school network meetings were utilized when preparing the final materials and training model for national diffusion.
Evaluation of KiVa The evaluation study of the KiVa program will provide novel information about the effects of anti-bullying actions. Previous studies of anti-bullying intervention programs (for reviews, see e.g., J. D. Smith, Schneider, Smith, & Ananiadou, 2004; P. K. Smith, Pepler, & Rigby, 2004) have been so-called black box evaluations (Chen, 2005; Rossi, Lipsey, & Freeman, 2004), in that they mainly address the relationship between the intervention and the outcome, ignoring research on underlying processes. Furthermore, the development of individual students’ bullying-related behaviours has not been followed over time. These limitations have left us with contradictory results concerning the effectiveness of anti-bullying interventions. Nevertheless, the overall picture has led Smith and colleagues (2004) to conclude that interventions can be successful, “but not enough is known to indicate exactly how and when.” The KiVa evaluation study overcomes many of the previous limitations by (a) measuring the hypothesized mediators and moderators of program effects and (b) following the development of individual students over time. Theory-based research on the processes underlying program effects (Chen, 2005; Rossi et al., 2004) can provide us with important knowledge about key factors in bullying problems. In addition, it can be assumed that the program effects vary across different students and school classes, and we can learn about these differential effects on the students’ and classes’ trajectories by following them longitudinally. In this way, the design enables to answer three major questions: 1 2 3
Is the program generally effective? For whom is it effective? How does the program produce its effects?
Answering these questions will address several important issues, both applied and theoretical ones. The applied research questions include whether the KiVa program is truly effective and thus ready for broad dissemination (Flay et al., 2005). In addition to knowledge about the program effectiveness, the implementers of the intervention also need to know how to implement the program in order to gain the best results. In the literature this has been referred to as the implementation fidelity-adaptation debate (e.g., Dusenbury, Brannigan, Falco, & Hansen, 2003). The main question in this debate is whether program adaptation increases or decreases program effectiveness. By using detailed measures of implementation and outcomes, the KiVa
244 Christina Salmivalli et al. evaluation study aims at providing an answer to this question for its part. In this way, the school staff can be given advice about the best practices of program implementation. Furthermore, it is being investigated which factors predict the implementation of the KiVa program. Knowledge of the predictors of implementation allows one to estimate what kind of staff members and schools are likely to implement the program to a large extent and are thereby more probable to benefit from it (e.g., Kallestad & Olweus, 2003). Conversely, by identifying schools likely to fall short of implementation, support can be tailored to the needs of the specific schools. This knowledge can then be used to make decisions about introducing the program and allocating resources to support its implementation. The more theoretical research questions of the evaluation also have practical relevance in that the results can be used to pinpoint the key factors in bullying problems, which can then become the targets of intervention measures. If the intervention succeeds in influencing its hypothesized mediators of effects, the associations between these mediators and outcomes can be assessed. This makes it possible to test theories about bullying problems. To put it briefly, it is hypothesized that the implemented intervention actions (at individual and classroom levels) influence social cognitions (at individual and classroom levels) which influence bullies’ and bystanders’ behaviour in bullying situations. Positive changes in these behaviors are expected to decrease victimization and its adverse consequences. Congruent with the view of bullying as a group phenomenon, the emphasis will be on group factors, such as classroom norms and bystanders’ behaviors (e.g., supporting and defending the victim). Thus, investigating the program processes allows many interesting hypotheses to be tested. A further advantage of this kind of theory-driven evaluation is that it increases the internal validity of research by examining whether the program effects unfold in the hypothesized ways (Chen, 2005; Rossi et al., 2004).
Sample All primary and secondary schools in the mainland of Finland were invited to participate in the evaluation of KiVa as either an experimental school or a control school. Nearly 300 schools announced their willingness to participate. Stratified random sampling was used to categorize 234 schools into 117 pilot and 117 control schools, representing all provinces of mainland Finland (Table 12.2). To ensure a good response rate to the questionnaire, schools providing only special education were excluded from the sample. In the first phase (2007–2008) the program was piloted in grades 4–6 in the experimental schools and in the second phase (2008–2009) in grades 1–3 and 7–9. In this manner, all grade levels in the Finnish comprehensive school system are included in the study. As the sample in the first phase consisted of over 7,000 students from over 400 classrooms in 78 schools, the total sample can be estimated to amount to about 1,200 classrooms and more than 20,000 students. In addition, altogether about 1,500 teachers and other participating school staff members will be asked to complete questionnaires concerning the program, themselves, their students, and their schools. Table 12.2 The Study Sample in the Two Phases of Program Evaluation 1 2 Altogether
2007–08 2008–09
4–6 1–3 7–9
39 39 39 117
39 39 39 117
Development of a National Anti-Bullying Program, KiVa 245
Design Two designs are used to evaluate the effects of the KiVa program: a randomized experimental design and a cohort-longitudinal design with adjacent cohorts. In the cohort-longitudinal design, post-test data from students in each cohort are compared with baseline data from same-aged students from the same schools (i.e., in the previous cohort), who have not yet been exposed to the intervention (Olweus & Alsaker, 1991; Salmivalli, Kaukiainen, & Voeten, 2005). There are two reasons for making these different kinds of comparisons. First, the designs complement each other in the sense that, for practical reasons, pre-test/post-test comparison is impossible in grade 1 and cohort-longitudinal design is not being used in grades 3 and 6. Second, the consistency of results from these two designs is an interesting topic in its own right. According to Rossi, Lipsey and Freeman (2004), there are few studies in which results of quasi-experiments are compared with those of randomized experiments. On the basis of the existing studies, it seems that quasi-experiments can yield estimates of program effects that are comparable to those of randomized designs, but they can also produce seriously erroneous results (Aiken, West, Schwalm, Carroll, & Hsiung, 1998; Fraker & Maynard, 1985; Heckman & Hotz, 1989; Heinsman & Shadish, 1996; LaLonde, 1986; Lipsey & Wilson, 1993). The adequacy of the cohort-longitudinal design for evaluating anti-bullying interventions is a particularly interesting issue. This is because the effectiveness evidence for the most widely-known anti-bullying program, the Olweus Bullying Prevention Program, consists mainly of studies using the cohort-longitudinal design (Olweus & Alsaker, 1991; Olweus, 2004; Olweus, 2005).
Measures Most of the data collection is done with internet-based questionnaires. The data includes self-, peer-, and teacher-reports regarding the students’ attributes and behaviors, as well as teachers’ and other school personnel’s reports of their own beliefs and actions. All study participants receive their own personal user ID, which they use as a password for the questionnaires, and so the individual participants can be identified at the various time points while they remain in practice anonymous to the researchers. Students give self- and peer-reports three times during the year. In addition, the bully-victim dyads will be identified by asking children questions such as: “Who do you bully?” or “Who are the ones that bully you?” This allows us to follow the changes that take place in particular bully-victim dyads and whole “bullying networks” of classrooms during the intervention. The follow-up procedure described above is a significant improvement compared with previous anti-bullying intervention studies, which can be demonstrated with an example of students’ outcome measures. The previous bullying intervention studies have often examined the prevalence of bullies and victims as their outcome variables. The designs have, however, not allowed examining whether possible decreases in bullying others are due to some of the bullies stopping bullying, or rather, some of the potential new bullies not starting to bully others in the first place. Similarly, we do not usually know whether decreases in victimization are caused by some of the victims escaping the victim role, or some of the potential victims not ending up as victims at all. Following particular individuals from pre- to post-test measurements will allow differentiation between these trajectories. Examining these alternative processes will provide important knowledge concerning the extent to which the effects of an anti-bullying program are preventive or interceptive.
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Diffusion of KiVa Diffusion has been defined as the process by which members of a social system learn about, decide about, and act on new ideas or practices (Rogers, 1995). The diffusion of the KiVa program for national use has its unique challenges. On the other hand, we have strong backing from both the Ministry of Education and the Finnish National Board of Education (FNBE). The latter organization (working under the auspices of the ministry) is the agency responsible for the development of education in Finland. It draws up national core curricula, which determine the core objectives, contents and guidelines for teaching in Finland. Education providers prepare their own local curricula based on these national documents. We collaborated closely with the FNBE during the development of KiVa, and there is one representative from FNBE in the steering group of the KiVa project. It has been ascertained, for instance, that the topics covered by our student lessons are in accordance with the national core curricula. This allows us to present the KiVa program to teachers and school principals as an effective tool for something they should be doing already, rather than as an extra burden to be carried in addition the to curricula. The Finnish Ministry of Education has provided the University of Turku with funding to initiate large-scale diffusion (i.e., for the first two years of the process), and our aim is to have the program adopted as widely as possible by Finnish comprehensive schools during this period. After that, further funding will be applied for future training, conference days, etc. related to the KiVa program. In the evaluation study, KiVa student lessons were being piloted in each grade level in the experimental schools. When the program is diffused more widely, the students in KiVa schools will have the student lessons three times during their basic education: the first time in grade 1 (program version for grades 1–3), the second time in grade 4 (program version for grades 4–6), and finally, at time of the transition to secondary school in grade 7 (program version for grades 7–9). Following the four-stage process of program diffusion (Rohrbach, D’Onofrio, Backer, & Montgomery, 1996) we will next describe the strategies to promote the (1) dissemination, (2) adoption, (3) implementation, and (4) maintenance of KiVa in Finnish schools (see also Table 12.3). Table 12.3 Diffusion of KiVa: Strategies to Promote the Dissemination, Adoption, Implementation, and Maintenance of the Program Dissemination Press conference Articles in national and local newspapers and in teachers’ journals Newsletters to all schools and municipalities Adoption Evidence of effectiveness Free material and training—low total costs Feasible, user-friendly and attractive materials Implementation Pre-implementation training Program manuals Implementation manual Maintenance Virtual training Internet-based discussion forum Tools to monitor own progress Biannual KiVa conference
Development of a National Anti-Bullying Program, KiVa 247
Dissemination: Raising Awareness of KiVa Among Finnish Schools and Municipalities The diffusion of the program started in the fall of 2008 in the form of a national information campaign. There was a press conference organized by the Ministry of Education, where the program developers presented the first findings regarding the effectiveness of KiVa to national media (at this point the highly promising findings regarding the effects in grades 4–6 are available, see Kärnä, Voelen, Little, Poskiparta, Kalijonen, & Salmivalli, in press). To maximize publicity, this event took place some days prior to the beginning of the school year, when the media is usually very interested in news related to school bullying. In addition, the program developers wrote short articles about KiVa for national and local newspapers as well as teachers’ journals. KiVa was also presented in several national conferences and meetings during the fall. After the press conference and national and local publicising, newsletters were sent to all Finnish schools giving comprehensive education (at that time, 3,226 schools). The newsletter includes a description of KiVa, including program content, the implementation process, and the total costs of implementation. Furthermore, the newsletter provided evidence of the effectiveness of KiVa and user experiences from selected pilot schools. Finally, the newsletter informed the schools about the opportunity to register as KiVa schools by the end of the year and start implementing KiVa next fall, in the beginning of the school year in August 2009. Similar newsletters were sent to the municipalities, which are the local authorities responsible for organising basic education for all children residing within their area. According to Rohrbach et al. (1996), program adoption at the administrative level may be a necessary (although not sufficient) condition for implementation. It was thus important to inform the municipalities about KiVa and encourage them to support registration by the schools in the district as KiVa schools.
Adoption: Encouraging the Schools to Make a Commitment Our aim was to have 600 new KiVa schools starting to implement the program in the fall of 2009 and another 600 schools a year later. Overall, we hoped to have 1,200 schools adopting the KiVa program during the first two years of diffusion. However, as many as 2,300 schools wanted to start implementing KiVa during that period, with 1,400 of them starting in 2009. Evidence of Effectiveness We believe that evidence of the program effectiveness encouraged Finnish schools to adopt KiVa. The Finnish Basic Education Act (since 1999) states that every student has the right to a safe school environment. Education providers have the responsibility of making sure that students do not experience acts of violence or bullying while at school. The legislation concerns all educational levels. It was further amended in 2003, stating that “the education provider shall draw up a plan, in connection with curriculum design, for safeguarding pupils against violence, bullying and harassment, execute the plan and supervise adherence to it and its implementation.” Tools to efficiently tackle bullying had been lacking, however, and, despite the legislative changes of the past decade, bullying and victimization had not decreased in Finland. Thus, efficient tools to fulfill the responsibilities defined by legislation were needed and had long been requested.
248 Christina Salmivalli et al. Free Material and Training—Low Total Costs In order to promote the adoption of KiVa, all materials included in the program as well as the staff training were provided for free for schools registering themselves as KiVa schools during the first two years of the national diffusion. These schools would start implementing KiVa either in the fall of 2009 or in the fall of 2010. Although schools need to take care of the substitute costs and travel costs (created, for instance, by the staff training days), the total costs of the program will be kept as low as possible even after the initial two-year period. Feasible, User-Friendly, and Attractive Materials It is important for program adoption that all materials are user-friendly, attractive, and presented in language and format that are convenient to practitioners. It has been found that in the early stages of decision-making about an innovation, teachers and other school staff might pay even more attention to the practical characteristics of the innovation than to evidence of its effectiveness (Rohrbach et al., 1996). Thus, from the very beginning of developing the KiVa materials, we have tried to ensure high quality and an appearance that is both affirming and appealing.
Supporting Implementation Pre-Implementation Training Program adoption does not guarantee successful implementation. Studies have shown, however, that implementation is a critical factor in the effectiveness of bullying interventions (Eslea & Smith, 1998; Olweus, 2004; Salmivalli, Kaukiainen, & Voeten, 2005). Pre-implementation training tends to increase program implementation (Connell, Turner, & Mason, 1985; Flay et al., 1987). In order to enable schools to implement the KiVa program with fidelity, their staff were provided with two full days of face-to-face training before the implementation. It was noticed during the evaluation phase of KiVa, for instance, that some teachers felt discomfort about the interactive methods such as drama and role-play included in the student lessons. Pre-implementation training helps to reduce this uncertainty. Overall, it is likely to increase the teachers’ feelings of efficacy toward program implementation. The training took place during the spring and early fall of 2009 in several provinces of Finland, based on the locations of the registered schools. With a pool of trained educators among the people working in the KiVa project, we organized 33 separate training days in the spring, and another 33 days in the fall of 2009 across the provimces. The content of the training was similar to what was provided to the pilot schools during the evaluation phase. The first training day was in April, followed by the second day in August, at the beginning of the school year. The first day concentrated on the universal actions of KiVa (e.g., student lessons), while the second focused more on indicated actions (e.g., resolving bullying cases which come to light). Program Manuals KiVa includes comprehensive and detailed program manuals, separately for grades 1–3, 4–6, and 7–9. The manuals describe the contents of the KiVa program (both universal and indicated actions) in such detail that they can be carried out with fidelity by teachers, even without
Development of a National Anti-Bullying Program, KiVa 249 the training. During the development of manuals, several teachers have been consulted regarding their structure and layout, in order to make sure that they are perceived as convenient and user-friendly by the implementers. In addition to the program manuals, all registered schools get an implementation manual which describes the core components of KiVa and helps to understand the program and the process of implementing it as a whole. This manual also gives guidelines for preparing to use the program.
Maintenance: Encouragement to Continue Using KiVa Maintenance of the program by the schools that have adopted it is a challenge of its own. After the initial interest in registered KiVa schools, it is highly likely that implementation will gradually decrease and its fidelity will suffer without special efforts to prevent that. Not only might the schools might gradually lose their interest as time passes since the training, but as a consequence of staff turnover, for instance, the new teachers or other personnel will not necessarily be aware of KiVa and its implementation. Over time, this increases the likelihood of dropping KiVa. Virtual Training We are currently constructing a virtual learning environment at our website (www. kivakoulu.fi) for schools registered as KiVa users. This learning environment will provide KiVa schools with virtual training regarding KiVa and its implementation. The virtual training can be used by new staff in schools already implementing KiVa, as well as the new schools adopting the program. The training contents are similar to those of the face-to-face training organized in the initial phase of diffusion. In addition to the virtual training, the website will also provide access to internet-based questionnaires, a discussion forum, and all curriculum materials along with the KiVa computer game. Furthermore, the website includes a discussion forum for the staff of registered KiVa schools. In this forum they can share experiences and discuss problematic issues. Tools to Monitor Implementation and Outcomes Importantly, KiVa schools have the ability to monitor both their implementation process and the outcomes obtained by using the program. They are provided with an evaluation tool including web-based questionnaires for students and staff. The questionnaires include some of the key measures utilized in the pilot phase of KiVa, now modified to meet the needs of a more applied setting. The implementers get immediate feedback on the prevalence of bullying and victimization in their school, which they can compare with the norm data collected during the evaluation period. They can also follow the implementation process itself, and make alterations to it when needed. The data collected in new KiVa schools will be available to program developers as well. This makes it possible to study the diffusion of KiVa in Finnish schools as well as the outcomes obtained at a national level. KiVa Conference Days Finally, the plan is to organize biannual KiVa conference days in different regions of Finland. Personnel from the registered KiVa schools can take part in these gatherings to hear about the
250 Christina Salmivalli et al. latest research on bullying, to share their experiences and present their obtained outcome, and to get face-to-face training (for instance, for teachers from KiVa schools who never attended the pre-implementation face-to-face-training). The first KiVa days take place in Turku in August 2010.
Conclusions and Future Challenges KiVa is a national anti-bullying program developed at the University of Turku and funded by the Finnish Ministry of Education. KiVa is strongly research-based, and it involves both universal and indicated measures to stop ongoing bullying, to prevent the emergence of new cases, and to ease the plight of the victims. The emphasis of the universal interventions lies in influencing all children’s reactions when witnessing bullying (such as providing safe strategies to support the victimized peer), whereas the aim of the indicated interventions is to stop ongoing bullying that has came to light. KiVa contains an exceptionally large set of concrete tools for educators, including a series of student lessons, a virtual learning environment, and guidelines for effective tackling of the identified cases of bullying. According to Flay et al. (2005), in order to be ready for broad dissemination a program should meet stringent criteria for effectiveness and be supported by relevant provider materials and by evidence that the program can be implemented with fidelity. The nationwide diffusion of KiVa started in a situation when we only had evidence of program effectiveness from three grade levels (grades 4–6, see Kärnä et al., in press). Our evaluation study will continue for quite a while before we have the results ready for each grade level and can make inferences about the mechanisms behind the changes accomplished. Besides utilizing our exceptional data set collected in the KiVa project, another research challenge will be to study the diffusion process itself, as well as the maintenance of KiVa in schools that have adopted it. The forthcoming years will show how the schools will maintain the implementation of KiVa and after the intial stages and whether the program effects will eventually be seen in the national prevalence rates of bullying and victimization in Finland.
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13 Promoting the Well-Being of School Communities A Systemic Approach Chryse Hatzichristou, Konstantina Lykitsakou, Aikaterini Lampropoulou, and Panayiota Dimitropoulou, University of Athens, Greece “I am indebted to my father for living, but to my teacher for living well.” —Alexander the Great, fourth century BC
In recent years, traditional school mental health services have proven to be inadequate to respond to the increased challenges present in the school environment. Several studies in different countries have emphasized that there is a growing number of children with unmet socioemotional needs and that the services provided to them are often inappropriate, insufficient, and poorly coordinated (e.g., health care, educational, juvenile justice and child welfare systems) (Hatzichristou, 2000; Koyanagi, 1995; Oakland & Jimerson, 2007; Pfeiffer & Reddy, 1998; Rog, 1995). As a result, efforts have been made to reform psychological services in order to achieve the optimum fit between children’s developmental needs and the structures, goals and services provided by the school (Baker, Dilly, Aupperlee, & Patil, 2003). The current theoretical models and practices emphasize the need for holistic approaches to service provision in the school context that focus on system interventions and enhance the collaboration among all members of the school community. In particular, recent emphasis has been given to the promotion of children’s well-being. The development and implementation of multi-level prevention programs also reflect these worldwide trends in school mental health. The growing body of research has emphasized a number of contextual and individual characteristics that promote school well-being such as school climate, resilience, social and emotional skills, and academic and psychosocial competencies. However, the field lacks comprehensive models that integrate these parameters within the school setting (Baker et al., 2003). In the following sections, we will: (a) describe the current trends in school mental health related to the promotion of school community well-being; (b) present core theoretical approaches that are prerequisites for the development of effective system interventions for the promotion of school well-being; (c) describe a paradigm of system intervention in the Greek and Cypriot educational and cultural settings; and (d) propose a new and broad approach to school community well-being.
Current Trends in Psychology and School Mental Health Positive Psychology One of the most recent approaches in psychology is positive psychology. Positive psychology is defined as the scientific study of ordinary human strengths and virtues (Sheldon & King,
254 Chryse Hatzichristou et al. 2001). It consists of three domains: positive subjective experiences, positive individual traits, and the institutions that promote these (Seligman & Csikszentmihalyi, 2000). The aim of positive psychology is to “catalyze a change from a preoccupation only with repairing the worst things in life to also building the best qualities in life” (Seligman, 2002, p.3) and to understand and foster the factors that allow individuals, communities and societies to flourish (Fredrickson, 2001). As is evident in both the definition and the goals of positive psychology, its fundamental contribution is the shift from clinical perspectives and illness models of human functioning, that prevailed until recently in psychology, to a mental health model. Traditional psychology emphasized deficits and “fixing” the problem, which was typically identified within the individual. According to illness models, the absence of problems is sufficient for considering an individual to be well-adjusted. Within positive psychology, on the other hand, the mere absence of a mental illness does not necessarily imply well-being. As noted by many positive psychologists, “efforts to improve children’s lives must also focus on developing strengths, facilitating positive responses to adversity and strengthening the important institutions in children’s lives” (Huebner, Suldo, Smith, & McKnight, 2004, p. 81). Therefore, concepts such as resiliency, hope, love, optimism, and forgiveness are important research topics of positive psychology because these represent means for achieving wellness (Snyder & Lopez, 2001). One of the most important concepts in positive psychology is subjective well-being, that is, how and why people experience their lives in positive ways (Gilman & Huebner, 2003). This concept has become an area of increasing interest among researchers who investigate the degree to which positive subjective experiences of individuals lead to a higher sense of wellbeing. Subjective well-being is the basic indicator for evaluating individuals’ wellness and is distinguished from objective indicators such as income level. Subjective well-being is regulated by internal mechanisms and is considered a basic prerequisite for the promotion of people’s mental health (Diener, Lucas, & Oishi, 2002). A number of models and theoretical approaches have been developed to study, explain and understand the structure and correlates of subjective well-being. The most commonly accepted model conceptualizes subjective well-being as a synthesis of two independent components: emotional and cognitive. The emotional component includes the long-term frequency of positive and negative affect while the cognitive component includes the cognitive appraisal of life satisfaction at a cognitive level (Diener & Diener, 1998). According to this perspective, people with a high level of subjective well-being experience positive feelings such as joy or happiness most of the time and evaluate their lives in positive and satisfactory ways. Regardless of the theoretical perspective, research examining subjective well-being initially focused on adults and the study of well-being from an individual-centered perspective. Gradually, positive psychologists also became interested in the subjective well-being of children and adolescents and focused on systems and the interactions that take place within these systems as well as on the individual. This led to further development in the field of well-being. New research efforts considered salient psychological environments as well as aspects of the individual. Schools, families and community were seen as the most important environments that could affect children’s subjective well-being (Marjoribanks, 2004). Most studies of the subjective well-being of children and adolescents examine characteristics of the systems that influence, directly or indirectly, their wellness. However, more recent efforts seek to extend the construct of subjective well-being by proposing more complicated conceptual frameworks or introducing dimensions of well-being such as family well-being, community well-being or school well-being (Bal, Crombez, Van Oost, & Debourdeaudhuij, 2003; Behnke & MacDermid, 2004; Konu, Lintonen, & Autio, 2002).
Promoting the Well-Being of School Communities 255 The aforementioned efforts, despite their differences, have established that ecological orientations and a systems focus are particularly important for the development of effective interventions that promote children’s mental health and well-being. This is particularly true for schools and has important implications for school mental health practice. Systems Interventions Systems interventions are change efforts that make a difference in how human organizations operate and have goals either to improve performance or to enhance the viability and resiliency of the system (Borgelt & Conoley, 1999). A number of possible strategies for developing efficient systems interventions have been proposed (Curtis & Stollar, 1995). However, while systems interventions are easily listed, they are difficult to construct for many reasons (Borgelt & Conoley, 1999). In order to plan systems interventions, a framework is necessary that describes well-functioning systems. Biologically-based systems theory, ecological psychology, family-systems theory, and organizational psychology have provided various conceptual frameworks for understanding the functions of systems. They have also provided important theoretical and practice information that is useful in designing and evaluating systems interventions. Their conceptual principles have been especially useful in designing systems interventions to use within school contexts, since schools are systems that play a significant role in children’s development (Fraser, 1995). Positive psychology perspectives propose approaches to the school system and to systems interventions that have a primary mission of promoting school community well-being. This is particularly important for today’s schools that, in all educational and cultural settings, are expected to serve a wider range of students’ diverse needs than they served in the past (Hatzichristou, Lampropoulou, & Lykitsakou, 2004). Interventions that promote well-being at a school must consider both the common and diverse needs of the school’s members in order to be effective. Culture is a common source of diversity described in the school mental health literature. The development of cultural awareness and understanding requires acknowledgement of similarities and differences between one’s own and other cultures, and it is critical for effective systems intervention (Hatzichristou, Lampropoulou, & Lykitsakou, 2006; Hatzichristou, Karadimas, et al., 2001). This is even more important in positive psychology, since beliefs about “good life” and high levels of subjective well-being might differ among cultures (Diener, Oishi, & Lucas, 2003). Although culture is one of the most prominent dimensions of diversity that has attracted the interest of school mental health researchers and practitioners, several other factors also have critical implications for systemic interventions. These diversity factors have been described in a synthetic approach by Hatzichristou, Lampropoulou, and Lykitsakou (2004). At the individual level, diversity is linked to the characteristics of the students (physical, cognitive, academic, personality, learning style, interests, etc.) and the teachers (personality, age, teaching experience, training, and teaching style). At the family level, differences are related to socioeconomic status, family structure and type, parenting styles, and parental involvement. Diversity regarding the school includes differences in school climate, communication, administrative organization, and community characteristics. Finally, at the level of service delivery, diversity refers to the implementation of different levels of prevention and intervention programs such as universal or selective intervention or the in-service training of school personnel. Through this particular perspective, diversity is viewed broadly and includes a variety of critical features that should be taken into account for developing systems interventions in the school environment.
256 Chryse Hatzichristou et al.
Systems theory System-level intervention
Positive psychology Well-being
SCHOOL COMMUNITY WELL-BEING
Resilience Effective schools
Social and emotional learning
Schools as caring communities
Figure 13.1 A Synthetic Approach to School Community Well-Being.
In the following section, basic theoretical components of the proposed conceptual approach to school community well-being are presented (see Figure 13.1). These theoretical components share common or complementary concepts and elements, even though they have often been considered to be distinct in prior literature. Therefore, this approach synthesizes these elements into a set of guidelines for the development of systems interventions in the school environment.
Prerequisites for Promoting School Well-Being Resilience Promoting school well-being is a difficult task because many critical features must be considered when developing interventions for the school environment. Some basic prerequisites that promote children’s well-being have been identified in the literature. Resilience is one of these prerequisites and refers to the process of positive adaptation under difficult and adverse circumstances (Masten, 2001). Building new strengths in individuals, families and communities has an important protective effect against life contingencies (Masten & Coatsworth, 1998). O’Dougherty Wright and Masten (2005) present a short list of the correlates of resilience that serve a protective function for children at various levels including the community level. Community characteristics that foster children’s resilience include high neighbourhood quality, employment opportunities, good public health care, access to emergency services, and multiple connections of children to caring adult mentors and prosocial peers. Longitudinal studies with high-risk children verify the protective function of supportive systems that counteract environmental adversities (Durlak, 1997; Weissberg & Greenberg, 1998). Schools and classrooms can also function as resilient communities that provide support and guidance for all children (Henderson & Milstein, 1996). Doll, Zucker and Brehm (2004) define resilient classrooms as those having the following characteristics: academic efficacy, academic self-determination, behavioral self-control, caring and authentic teacher–student
Promoting the Well-Being of School Communities 257 relationships, ongoing and rewarding relationships with classroom peers, and strong homeschool collaboration. They note that, since a classroom is a system, neither the child nor the classroom can change without changing the other and argue that “when the changes made by teachers, parents and students complement and support each other, that change can persist and have an enduring impact on the routines and practices of the classroom”(p. 4). Effective Schools The research on resilience also suggests that effective schools are an important protective factor and a prerequisite for promoting children’s well-being. There has been increasing interest in the characteristics of effective schools. Families are not the only ones to “blame” for children’s difficulties (or credit with their successes) and schools’ responsibility is also recognized. This new approach is based on the fundamental assumption that all children are able to benefit from education, including children with severe disabilities (Bickel, 1999; Bickel & Beaujean, 2005). Empirical findings suggest that effective schools have the following characteristics: (a) school climates that promote learning without violence or discipline problems; (b) teachers’ expectations that all students can learn; (c) emphases on basic skills training and more time spent by students on school studying; (d) clear educational goals that make it easier to follow and assess students’ performance; and (e) administrators with leadership skills who pose goals, preserve discipline, visit classrooms frequently, observe classroom processes, and create motives for learning (Bossert, 1985). In addition, the effective schools literature emphasizes understanding the individual needs of students, celebrating diversity as a strength, and creating the appropriate circumstances that promote learning and development (Creemers, Scheerens, & Reynolds, 2000). Schools as Caring Communities Another important factor that influences subjective well-being is the degree to which students and teachers feel their school is a community that cares for its members. The term community refers to a network of relationships connecting individuals and allowing them to form common values and ideals aiming to achieve an important, common goal (Sergiovanni, 1994). A caring community’s members care and support each other, are strongly involved in its activities and decisions, identify themselves with these, have a sense of belonging, and share common norms, goals and values (Goodenow, 1993a; 1993b; McMillan & Chavis, 1986; Solomon, Watson, Battistisch, Schaps, & Delucchi, 1992; Wehlage, Rutter, Smith, Lesko, & Fernandez, 1990). Schools that are considered to be “caring communities” place greater emphasis on relationships among school community members and the promotion of school climate, set concrete educational goals, emphasize skill development in various domains, set goals corresponding to children’s needs, support home-school-community partnerships, and focus on teachers’ helping skills. The importance of this emotional dimension of schools is evident from the fact that characteristics of resilient and effective schools are principally psychological dimensions that relate to emotions and relationships.
Social and Emotional Learning Social-emotional learning is another fundamental prerequisite for the well-being of the school community and is considered important to children’s positive adjustment. It has roots in a
258 Chryse Hatzichristou et al. progressive educational tradition as well as the primary prevention and social competence promotion literatures within psychology, and it is centered on promoting children’s social and emotional well-being (Kress & Elias, 2006). Emotional learning is very significant for children’s well-being. Most of the characteristics that have been used to describe schools that are resilient, effective, or caring communities refer to emotions and relationships among the members of the school community. The emphasis placed on emotional aspects of schooling is also evident in the increasing interest in school climate, school connectedness, and school bonding. The development and implementation of school-based interventions contribute significantly to the promotion of social and emotional learning and school well-being. Therefore, it is critical to develop empirically based interventions that promote children’s mental health and well-being. Recent emphases on resilience, effective schools, and social emotional learning are also reflected in changes in school psychological practice and service delivery in which these shift from the traditional tasks of assessment, classification and counseling to the provision of alternative psychological services (Hatzichristou, 2002). Emerging school mental health practices emphasize strengths, positive responses to adversity, and a focus on systems rather than individual interventions. These provide a new perspective that identifies the purpose of school mental health practice as strengthening the well-being of the whole school community. Resilient, effective schools that are caring communities and promote social and emotional learning are necessary for the promotion of students’ psychological wellness. The proposed model of school community well-being suggests that the aforementioned concepts are integrated in system-level interventions in order to enhance the positive contribution of each domain and provide an advanced synthetic effect on school community wellness. In the following section, a system intervention paradigm is presented that focuses on prevention, resiliency-building and enhancement of the community in the school.
A Systems Intervention Paradigm in the Greek Educational System An Alternative Model for the Provision of School Mental Health Services There is considerable variability among countries in the role and training of school psychologists, the types of school psychological services offered, and the utilization of services (Farrell, Jimerson, & Oakland, 2007; Hatzichristou, 2002; Oakland & Saigh, 1989). In particular, during the past few years, the field of psychology has rapidly expanded in Greece. However, the provision of school psychological services in mainstream public schools is limited despite the progress that has been made (Hatzichristou, Polychroni, & Georgouleas, 2007). This constituted a challenge to develop an alternative service delivery model that would address the growing and unmet needs of different populations of the Greek educational system (Hatzichristou, 1998; Hatzichristou, 2004b). The integrative framework that guided the development of this alternative service delivery model was proposed by Hatzichristou (1998). It synthesizes and expands the following principles: (a) the scientist-practitioner model for school mental health; (b) a systemic (i.e., social, cultural, ethnic, national, ecological) approach to assessment and intervention practices; (c) the evolving roles and functions of school psychologists in research, practice, and training; and (d) a systemic approach to professional development and identity of school psychologists. This integrative conceptual framework led to the development of a data-based model of alternative school mental health services that links theory, research and practice to provide an array of services including assessment, psychological consultation, prevention, intervention,
Promoting the Well-Being of School Communities 259 crisis counseling, research, training, supervision, management and advocacy (Hatzichristou, 2004a). The data-based model of alternative school psychological services was developed in four phases. The three first phases of the model documented the needs of Greek students, teachers and families, as well as their attitudes toward mental health services and professionals. In Phase 1, an empirical data base was developed to describe the profiles of school adjustment and performance of “average” Greek students. In Phase 2, the profiles of at-risk students with unmet needs were described, and in Phase 3, profiles were developed of the particular needs of specific school districts in communities where various intervention programs were being implemented. Throughout the years, each phase was enriched by new research domains and additional goals. In the fourth phase, empirical data derived from the first three phases of the model were integrated into a comprehensive prevention-consultation approach that led to the foundation of the Center for Research and Practice of School Psychology (CRPSP) in the Department of Psychology at the University of Athens. The main goals of the Center are: (a) to promote education, pre-service and in-service training for graduate students, school psychologists, teachers, and parents; (b) to foster University-schools-community service partnerships and collaboration; (c) to conduct scientific research and publish results; and (d) to develop, implement and evaluate multi-level interventions in the school community. One of the major goals of the CRPSP is the development, implementation and evaluation of universal and selective evidence-based interventions in the Greek schools. These interventions include: (a) programs for the promotion of mental health and learning (Hatzichristou, 2004c, 2004d); (b) inter-cultural programs for the support of immigrant and remigrant students (Giavrimis, Konstantinou, & Hatzichristou, 2003; Hatzichristou, Gari, et al., 2001); (c) programs for sex and health education; (d) programs for the inclusion of children with special educational needs in mainstream schools (Hatzichristou & Polychroni, 2007); and (e) crisis intervention programs (Hatzichristou, 2000). In addition, a cross-cultural program was implemented during the Olympic Games of 2004 in Athens, titled The Olympic Spirit Through Children’s Voice, with the purpose of capturing children’s and adolescents’ awareness concerning the Olympic values and ideals through art and literature works (Hatzichristou, 2004e). One of the main prevention programs that was developed by the scientific team of the CRPSP and implemented in public mainstream schools of Greece and Cyprus for many years was the Program for the Promotion of Mental Health and Learning: Social and Emotional Learning in Schools. In the following section, this program will be described in detail. Program for the Promotion of Mental Health and Learning (PPMHL) The Program for the Promotion of Mental Health and Learning (PPMHL) integrates empirical data with recent theoretical approaches in school mental health. The program’s particular characteristics include linking current relevant theory and research with practice, adjusting to the needs of students in the Greek cultural and educational setting, emphasizing “typical” instead of atypical behavior, and using multi-dimensional and multi-method assessment (evidence-based intervention). The program’s purpose is to promote children’s mental health and learning, and to create a positive climate in the school environment (Hatzichristou, 2004b, 2004c, 2004d). It consists of 10 thematic units: (i) communication skills; (ii) identification, expression, and dealing with feelings; (iii) self-concept and self-esteem; (iv) coping strategies; (v) conflict resolution; (vi) diversity in culture; (vii) diversity in individual, family and social characteristics; (viii) learning/study skills; (ix) social skills; (x) crisis intervention in the school community. For each thematic unit a specialized educational curriculum includes a literature
260 Chryse Hatzichristou et al. review, practical guidelines for implementing the program, and classroom activities with specific goals and methods for preschool, primary and secondary students. PPMHL Development: Levels of Intervention First Level. The first implementation of PPMHL used different models of intervention that corresponded to schools’ resources, the various needs of the students, and feedback from the evaluation of previous implementations of PPMHL. Initially, it was implemented by school psychologists who were members of the scientific team of the CRPSP. Then, during the following years, graduate students of school psychology and teachers were trained to implement PPMHL under the supervision of the CRPSP scientific team. The graduate students attended university courses on primary and secondary prevention, models of consultation, and promotion of children’s mental health in school environments. In addition, they received specialized training in the implementation of PPMHL in the classrooms and regular supervision from the CRPSP scientific team throughout the implementation. In its latest implementation in Greek and Cypriot elementary schools, the program was implemented by teachers who received specialized training by members of the CRPSP scientific team. In addition, a network of the participating schools was developed to facilitate sharing of ideas and experience and to disseminate the program to other teachers in the school community. At the end of the academic year, parents, students, and teachers participated in a closing ceremony in which PPMHL activities were described (Dimitropoulou, Lykitsakou, & Hatzichristou, 2005). Second Level. This last model for PPMHL implementation produced a greater impact than when it was implemented by graduate students or CRPSP researchers (Hatzichristou, et al., 2002), in part because the intervention became a “school matter.” In response, we searched for a new system-wide approach that would further maximize the effects of the program, entitled Program for the Promotion of School Community Well-being (PPSCW). PPSCW included two axes of intervention: (a) the implementation of PPMHL by teachers in their classrooms; and (b) the promotion of resilience of the school community and the creation of broader school networks. Elements of systems theory, schools as caring communities, resilience, and well-being provided the theoretical background of this project. To promote resilience in the schools, teachers were trained to use the problem-solving model that was presented at the Invitational Conference on the Future of School Psychology (Hatzichristou & Lampropoulou, 2004) in order to develop action plans for enhancing the sense of community in the schools. Teachers of each school evaluated critical domains of resilience (Henderson & Milstein, 1996), set priorities and goals, and planned to take specific actions in response to the particular needs of their school. Coordinators (educators and administrators) from each school participated in regular meetings with the scientific team of the CRPSP to share ideas about problems that emerged in the process, as well as possible solutions. To implement PPMHL in their classrooms: (a) a limited number of schools were selected to participate in the program; (b) all teachers and administrators in those schools received awareness-building workshops and special training on the promotion of school well-being (instead of selecting a limited number of participants from more schools); (c) teachers implemented the PPMHL program in the classrooms; (d) the PPMHL program was disseminated to the parents and teachers of other schools; (e) materials related to PPMHL were uploaded to the program internet site; and (f) various group projects were presented by students and teachers in a closing ceremony at the end of the program.
Promoting the Well-Being of School Communities 261 An important component of program design is program evaluation. The need for evidencebased interventions has been particularly emphasized during the last decade. Researchers have defined concepts, terms, and issues that are meaningful and realistic criteria for judging the efficacy of intervention and prevention programs (Kratochwill & Stoiber, 2002). The CRPSP developed a multi-level assessment model including process and outcome evaluation; evaluation by teachers and students; pre-, post-, and during the program assessment; and use of a control group. Data are collected by different instruments and methods (questionnaires, diaries and logs, personal reports from teachers) during PPMHL supervision, activities and work projects. These data constitute valuable feedback for program improvement and refinement. PPMHL Evaluation In the following section, results of the evaluation of two prevention programs implemented in Athens, Greece, and Nicosia, Cyprus, are presented. Both projects included intervention programs to promote mental health and learning through the enhancement of children’s social and emotional skills within a network of caring community schools. The target groups, goals, and content of the interventions varied in response to the particular needs of the participants and the goals of the program (see also Hatzichristou, Lampropoulou, & Lykitsakou, 2006). The Athens program was implemented in schools with a high percentage of migrant and immigrant students and particularly emphasized the promotion of intercultural understanding and communication. Therefore, the hypotheses tested in these evaluations were that prepost assessment comparisons would reveal significant benefits for students and teachers in domains corresponding to the specific aims of each intervention program. Evaluation designs differed in the two programs. In the Cypriot project, certain schools were participating in the program for the second consecutive year, whereas in the Athens program, the evaluation design included use of a student control group. Thus, program efficacy was also examined by comparing first-to-second years of intervention and experimental-to-control groups. Method Cyprus Participants. In the Cyprus program, matched data were collected for 66 teachers and 706 students of grades 4–6 in 18 mainstream elementary schools. Five hundred and twenty students (73.6%) participated in the program for the first time and 186 continued the intervention from the previous academic year. Athens Participants. In the Athens program, participants were 85 elementary and kindergarten teachers and 1,486 students of grades K–6. Because of the large number of participating students, a smaller sample of fourth- to sixth-graders from randomly selected schools and classrooms were included in the evaluation process. Paired data were recorded for 319 students of the experimental group and 197 students of the control group. Measures Student Instruments. All students completed the PPMHL student questionnaire before and after the intervention, and an additional final report of process evaluation. The PPMHL questionnaire was constructed by the CRPSP team and includes open-ended and Likert scale items that assess knowledge and attitudes about the topics discussed in the classroom during PPMHL. The Cypriot and Greek projects had slightly different content and goals, and
262 Chryse Hatzichristou et al. therefore the content of the questionnaires differed as well to match the respective topics. In addition, Cypriot students completed the Social Skills Rating System—Student Form for grades 3–6 (SSRS; Gresham & Elliott, 1990) to provide estimates of cooperation, self-control, assertion and empathy skills. A smaller sample of 252 of these students (n = 252) completed a sociometric survey to assess peer acceptance using statements of preference in questions such as “name 3 classmates that you would prefer to play with during recess/to sit next to in the classroom.” Also for these students, content analysis was conducted for the coding of qualitative data. The Athens questionnaire included additional questions to assess changes in attitudes and social interaction among students of different cultural groups. In this chapter, selected qualitative and quantitative results of program evaluations will be presented. Teacher Instruments. At the beginning and end of their training, teachers completed a PPMHL teacher questionnaire that was constructed by the CRPSP scientific team, including various qualitative and quantitative items assessing the PPMHL program and implementation procedures. In addition, teachers’ personal and professional efficacy, beliefs about the school climate, and educational goals and values were also assessed. Only results of Cypriot teachers’ pre- and post-assessment of school climate will be presented in this chapter. For the assessment of school climate the “School as a Caring Community Profile” (SCCP-II; Lickona & Davidson, 2001) was used. The SCCP-II evaluates the sense of community in the school along five Likert-type subscales: perceptions of student respect, perceptions of student friendship and belonging, perceptions of students’ shaping of the environment, perceptions of support and care by and for faculty/staff, and perceptions of support and care by and for parents. In addition, estimates of teachers’ efficacy and their perceptions of the PPMHL implementation procedure will be presented. Implementation and Assessment Procedure For both projects program planning begun with goal-setting, selection of participants (schools, teachers, and students) and decisions about the content of and timetables for the intervention. Next, teachers’ awareness workshops and training were conducted, including an initial two-day general awareness seminar for most teachers and school administrators, and a two-day special seminar for a selected group of teachers who would implement the program in the schools. After this initial training, teachers began the implementation of PPMHL with their students. During the intervention, four additional seminars were conducted for teachers (one session per month). All participants (teachers and students) received and elaborated the PPMHL educational material designed by the CRPSP scientific team (Hatzichristou et al., 2004). The Cypriot program included five thematic units: (a) communication skills; (b) identification, expression and dealing with feelings; (c) self-concept and self-esteem; (d) coping strategies; and (e) conflict resolution. The first three units were also included in the Athens project along with a fourth unit on issues of diversity and culture. Classroom intervention took place once a week on a designated day and during a designated academic period and included classroom discussions and other activities (e.g., group or individual activities, roleplaying, and games). In the first session, children discussed the program rules and signed a classroom “contract.” Then, three or four sessions were dedicated to each theme and a final session was spent on the program closing. The first thematic unit was Communication skills. The topics discussed in the class were: meaning, elements, means and types of communication, verbal and non-verbal communication, identification of non-verbal messages, and realization of others’ perspective (empathy).
Promoting the Well-Being of School Communities 263 The second thematic unit was Identification, expression and management of emotions. The goals of this unit are to help children enrich their emotional vocabulary, distinguish between pleasant and unpleasant feelings (not good or bad, positive or negative), realize that it is acceptable to have and express all of them, identify their own feelings as well as feelings of others through non-verbal elements, and realize and accept the diversity of own or others’ emotions in a certain situation. The goals of the third thematic unit, Self-concept and self-esteem, were to enhance self-image and self-esteem, to help children realize the dimensions of self-concept (personal, social, ideal) and the factors that influence it, value more important inner qualities, identify and accept their strengths and weaknesses, and feel more competent talking about or presenting themselves to a group of people. The goals of the Diversity and Culture Unit were to help students realize the various levels and positive aspects of diversity, understand the nature and consequences of stereotypes, familiarize themselves with other cultures, discover differences and similarities with their own, and interact better with their classmates from different cultural backgrounds. In addition to training and implementing the school program, teachers in Cyprus were assigned some additional tasks: (a) presenting the program to parents; (b) uploading material about the program to the PPMHL website; and (c) preparing a short multimedia presentation of PPMHL, as implemented in their schools, for other participating teachers, program coordinators, and education officials and administrators. The Athens teachers also made a multimedia presentation at a closing ceremony. The Athens event was open to a wider audience (teachers, parents, students, program coordinators, and other education stakeholders) who attended students’ and teachers’ creative projects inspired by the implementation of the program (e.g., PowerPoint presentations, theatrical play, songs, storytelling, pantomime, etc.). Teachers completed pre-PPMHL measures at the beginning of the initial seminar while students completed pre-program measures before the beginning of the intervention in the classroom. Respectively, post-PPMHL teacher measures were collected at the end of the training and the post-PPMHL student measures were collected at the end of the intervention in the schools. Results Student Reports. Content analysis, conducted for students’ responses to open questions on the PPMHL student questionnaire, identified a limited number of response categories for each question. Frequencies were then estimated for every category and pre-post changes in responses were tested with the McNemar test (suitable for two related dichotomous variables; detects changes using the chi-square distribution). For quantitative data pre-post comparisons of means were conducted using the paired samples t-test. For the assessment of the Communication Skills Unit a representative question was: How do we communicate with other people? As shown in Table 13.1, pre-post comparisons of children’s responses revealed significant changes consistent with the intervention goals: After the intervention, a significant increase was found for response categories “Verbally” [χ2(1) = 4.05, p = .000], “With technical means” [χ2(1) = 7.89, p = .000], and “Non-verbally” [χ2(1) = 17.82, p = .000]. A representative item for the unit describing the identification, expression, and management of emotions required that children write as many feelings words as they could think of. Two major categories of the responses were pleasant and unpleasant emotions and scores for
264 Chryse Hatzichristou et al. Table 13.1 Frequencies of Children’s Pre–Post Responses to Indicative Open Questions of the Thematic Units “Communication Skills” and “Self-Concept”
Response categoriesc
“How do we communicate with other people?” Pre Post χ2 % % (df = 1)
p
Verbally Technical means Relating, hanging out with others Good manners, positive feelings Non-verbally
12.3 45.6 16.7 12.7 5.6
.000 .000 .229 .212 .000
External appearance Interests, hobbies School performance General estimation of self Personality/character traits
24.2 64.7 12.7 16.7 20.2
4.05 7.89 3.46 8.28 17.82
“When I describe myself, I say that I am . . .” Pre Post χ2 % % (df = 1)
p
34.5 7.1 12.7 25.8 46.8
.000 .135 .169 .000 .000
48.8 11.5 17.1 41.7 73.0
11.04 0.67 7.76 14.23 17.82
c = Cypriot sample.
this question were the number of emotions that were mentioned. As shown in Table 13.2, there was a significant increase in the number of emotions mentioned after the intervention for both pleasant [t(251) = –3.11, p = .002] and unpleasant emotions [t(251) = –7.07, p = .000] for the Athens experimental group but not for the Athens control group. Similar findings were noted for the Cypriot sample. A significantly higher percentage of the students mentioned both pleasant [χ2(1) = 13.86, p = .003] and unpleasant emotions [χ2(1) = 11.36, p = .000] after the intervention. An interesting finding was that a significantly greater percentage of children with low peer acceptance (0–3 preferences from classmates) mentioned unpleasant emotions after the intervention, whereas no such change was noted for pleasant emotions. Similarly, for the Athens sample, immigrant students mentioned significantly more unpleasant emotions at the end of the intervention. Table 13.2 also presents the results of the pre-post comparisons for the Self-Concept and Self-Esteem question When I describe myself, I say that I am … and shows significant changes consistent with the intervention goals. Students reported significantly more traits of external appearance (tall, blond, blue eyes etc) [χ2(1) = 11.04, p = .000], descriptions of self [χ2(1) = 14.23, p = .000], and character [χ2(1) = 17.82, p = .000] after the intervention. For the last two thematic units of the Cypriot intervention program (Coping strategies and Conflict resolution) the analysis revealed non-significant trends towards positive change. As shown in Table 13.3, results were quite satisfactory for the items of the Diversity and Culture Unit in the Athens intercultural program, After the intervention, children reported that they were more willing to accept invitations of classmates from other countries to their homes [t(306) = –2.55, p = .011], to spend more time with them outside school [t(306) = –2.41, p = .016], to play together in the neighborhood [t(307) = –3.06, p = .002], and to help each other with homework [t(307) = –3.61, p = .000]. No significant changes were detected for the control group. Scale reliability for this set of items was α = .89.
Promoting the Well-Being of School Communities 265 Table 13.2 Pre–Post Comparisons of Students’ Responses to an Open Question of the Unit “Identification, Expression and Management of Emotions” for the Experimental and Control Group, for Migrant and Native Students (Athens Sample), and for Students with Low and High Peer Acceptance (Cypriot Sample) “Name as many feelings as you can think of” Experimental Groupg Control Groupg Pre
Post t
Response categories Pleasant Unpleasant
Ma 2.56 2.74
M 3.33 3.77
–5.12*** –5.44***
313 304
Pleasant Unpleasant
2.46 2.69
Post
–1.63 –2.07*
77 73
Post
2.49 2.28
Pre
Post
M
M
2.59 2.76
Low peer acceptancec (0–3 preferences from peers) Pre
M
df
M 2.90 3.35
M
t
df
0.00 –0.67
173 169
t
df
–4.87 –4.98
234 229
Native studentsg t
Ma
Post
2.49 2.18
Migrant studentsg Pre
Pre df
3.47 3.90
High peer acceptancec (4–7 preferences from peers)
χ2
Pre
Post
χ2
%
%
(df = 1)
34.8 21.4
47.3 47.3
12.49 8.94
p Pleasant Unpleasant
%
%
39.2 25.5
49.0 51.0
p
(df = 1) 1.59 2.32
.383 .007
.005 .000
*p < .05. ***p < .001. c = Cypriot sample. g = Greek sample. a = Means of number of mentioned emotions.
Table 13.3 Pre–Post Comparisons for Items of the Thematic Unit “Diversity and Culture” Experimental Groupg
Control Groupg
With classmates from other countries I would like to . . .
Pre M
Post M
t
df
Pre M
Post M
t
df
Play together at recess Sit at the same desk Invite them to my home Be invited to their home Spend time outside school Work together in school activities Play together in the neighborhood Help each other with homework
3.80 3.25 3.34 3.27 3.55 3.82
3.82 3.38 3.43 3.48 3.78 3.87
–0.37 –1.44 –1.19 –2.55* –2.41* –0.56
317 316 316 306 306 305
3.68 3.14 3.23 3.14 3.46 3.74
3.81 3.27 3.34 3.25 3.62 3.79
–1.29 –1.18 –1.03 –1.10 –1.18 –0.39
193 192 192 189 187 191
3.51
3.77
–3.06**
307
3.51
3.69
–1.49
191
3.68
3.96
–3.61***
307
3.82
3.70
1.09
193
Note Scale from 1 = not at all to 5 = very much. g = Greek sample. *p
