Physical Therapy- Journal of the APTA- September 2009, Volume 89, Issue 9

September 2009 Volume 89 Number 9 Reprint 873 PRISMA Statement Research Reports 934 Rehabilitation After Hallux V...

Author: APTA

250 downloads 1731 Views 9MB Size Report

This content was uploaded by our users and we assume good faith they have the permission to share this book. If you own the copyright to this book and it is wrongfully on our website, we offer a simple DMCA procedure to remove your content from our site. Start by pressing the button below!
Report copyright / DMCA form

DOWNLOAD PDF

September 2009

Volume 89

Number 9

Reprint 873

PRISMA Statement

Research Reports

934

Rehabilitation After Hallux Valgus Surgery

946

Job Strain in Physical Therapists

957

Interpretation of Lower-Extremity Functional Scale–Derived Computerized Adaptive Test

969

Self-Report Measure of Fearful Activities for Patients With LBP

884

Physical Therapist–Directed Exercise Counseling Combined With Fitness Center– Based Exercise Training

893

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury

Perspective

906

Clinical Identifiers for Adhesive Capsulitis

980

918

Evidence-Based Practice in Pediatric Physical Therapy

TBI and Vestibular Pathology as Comorbidity Following Blast Exposure

Gain quick and easy access to clinical research. Get free access to full-text articles in more than 1,000 health care periodicals with APTA’s Open Door portal. Open Door also features full-text Cochrane systematic reviews, Medline, an expanded Current Research in Physical Therapy section, open access resources, and more.

Access Hooked on Evidence, APTA’s online database, which contains current research evidence on the effectiveness of physical therapy interventions. Plus, you can earn free CEUs for your contributions.

Visit Physical Therapy (PTJ) on the Web, powered by HighWire Press, which hosts more than 900 journals and the largest repository of free, full-text, peer-reviewed content, including BMJ and JAMA.

Experience the Beneﬁts of APTA Membership! For more details about any of APTA’s exclusive member beneﬁts, visit www.apta.org.

Get Hooked. Get Evidence for Your Practice. Patient clinical scenarios for conditions commonly seen in practice are now available to provide immediate access to evidence of effectiveness of physical therapy interventions. APTA members can search the clinical scenarios and search the database of more than 5,250 extractions of research articles at www.hookedonevidence.org.

www.hookedonevidence.org

The Bottom Line The Bottom Line is a translation of study findings for application to clinical practice. It is not intended to substitute for a critical reading of the research article. Bottom Lines are written by invitation only. On “Development of a Self-Report Measure of Fearful Activities for Patients With Low Back Pain: The Fear of Daily Activities Questionnaire ” What problems did the researchers set out to study, and why? Evidence from prospective trials supports the use of the fear-avoidance model (FAM) of musculoskeletal pain to explain the development and maintenance of chronic low back pain. Although validated questionnaires exist that assess an individual’s general attitude and beliefs related to the FAM, these tools do not address specific daily activities, and the utility of these tools is limited when attempting to develop interventions. The researchers set out to assess the psychometric properties of a novel self-report measure for fear of activities for patients with low back pain. Who participated in this study? Two cohorts of individuals from outpatient clinics affiliated with the University of Florida who had acute, subacute, or chronic low back pain participated in this study. The reliability cohort consisted of 50 individuals with chronic low back pain between 15 and 60 years of age, and the validity cohort consisted of 108 individuals between 15 and 60 years of age with acute or subacute low back pain with or without radiating symptoms. What new information does this study offer? The Fear of Daily Activities Questionnaire (FDAQ), a 12-item self-report measure, is a potentially viable measure to quantify fear associated with specific activities. Graded on a scale of 1 to 100, this tool might be appropriate for developing graded exposure interventions and measuring changes in fear levels throughout an episode of care. This tool, however, is not indicated as a screening tool, because baseline values did not explain variability in disability and physical impairment outcomes. What new information does this study offer for patients? It is important to assess fear related to low back pain to help manage and prevent chronic low back pain. Existing tools assess a patient’s general fear related to their pain. The FDAQ will allow clinicians to develop specific interventions because it provides reliable and valid information about specific daily activities that a patient may be fearful about. How did the researchers go about the study? Baseline measures of pain (using a numeric rating scale), disability (using the Oswestry Disability Questionnaire), physical impairment (using the Physical Impairment Scale), fear avoidance (using the Fear-Avoidance Beliefs Questionnaire), and pain catastrophizing (using the Pain Catastrophizing Scale) were completed by both cohorts. The reliability cohort completed the FDAQ at examination, then completed a second FDAQ 48 hours later. The validity cohort completed a FDAQ at baseline and then received 4 weeks of physical therapy intervention, after which time all measures were re-administered. Data analysis to determine the psychometric properties of the FDAQ was performed.

September 2009

For more Bottom Lines on articles in this and other issues, visit www. ptjournal.org.

Volume 89 Number 9 Physical Therapy ■ 881

The Bottom Line How might these results be applied to physical therapist practice? Use of the FDAQ can be a way to use patient input to develop interventions related to fear about specific activities. A graded exposure approach to patients with high fear levels can have a positive impact on treatment. The FDAQ can be used to monitor changes in fear levels throughout an episode of care when used in conjunction with other tools such as the Fear-Avoidance Beliefs Questionnaire, which can help identify those individuals with high fear avoidance. What are the limitations of the study, and what further research is needed? One limitation of this study was the fact that the cohorts consisted primarily of individuals with moderate disability levels, and so the utility of this tool should be examined with respect to other levels of disability. Additionally, open-ended questions that were part of the FDAQ tool were not included in the analysis and the reason underlying a patient’s report of fear was not considered in the scope of this article, but may be clinically relevant. Future research should continue to investigate the utility of the FDAQ in other populations of patients with low back pain. Eric K. Robertson E.K. Robertson, PT, DPT, OCS, is Assistant Professor, Department of Physical Therapy, Texas State University, San Marcos, Texas. This is the Bottom Line for: George SZ, Valencia C, Zeppieri Jr G, Robinson ME. Development of a SelfReport Measure of Fearful Activities for Patients With Low Back Pain: The Fear of Daily Activities Questionnaire. Phys Ther. 2009;89:969–979.

On “Impact of Physical Therapist–Directed Exercise Counseling Combined With Fitness Center–Based Exercise Training on Muscular Strength and Exercise Capacity in People With Type 2 Diabetes: A Randomized Clinical Trial” What problems did the researchers set out to study, and why? Exercise, along with medical nutrition therapy and pharmacological interventions, is an important component in the clinical management of type 2 diabetes. Determining the best method of providing exercise instruction is clinically relevant to this population. However, there currently are no studies investigating the impact of physical therapist–directed exercise counseling on exercise capacity and muscle strength in people with type 2 diabetes. Furthermore, many insurance programs do not reimburse for physical therapist–directed exercise counseling programs. With these factors in mind, the researchers set out to compare the effect of physical therapist– directed exercise counseling combined with fitness center–based exercise training to the effect of physical therapist–supervised exercise training on muscle strength and exercise capacity in people with type 2 diabetes. Who participated in this study? Twenty-four adult subjects with type 2 diabetes participated in this study. The subjects met the American Diabetes Association diagnostic criteria for type 2 diabetes and had no medical conditions in which exercise was contraindicated. Individuals with fasting plasma glucose levels greater than 250 mg/dL (ie, uncontrolled diabetes) also were excluded from this study.

882 ■

Physical Therapy Volume 89 Number 9

September 2009

The Bottom Line What new information does this study offer? The results of this trial suggest that physical therapist–directed exercise counseling combined with fitness center–based exercise training can improve muscle strength and exercise capacity similar to a supervised, laboratory-based exercise program. What new information does this study offer for patients? The results from this study support exercise counseling by a physical therapist combined with exercise at a fitness center as an effective means of improving strength and exercise capacity for people with type 2 diabetes. Providing exercise instruction in this way may be more cost-effective and offer improved access for patients compared with supervised exercise programs, as they include exercise in the clinical management of type 2 diabetes. How did the researchers go about the study? Twenty-four participants with type 2 diabetes were randomly assigned to either receive exercise counseling and fitness center–based exercise training or receive a supervised, laboratory-based exercise training intervention. Strength training consisted of leg presses, chest presses, and rows. Aerobic training consisted of running or jogging on a treadmill. Physical therapists provided exercise instruction and follow-up phone calls for the exercise counseling group. The researchers controlled for overall exercise dosage between both groups. Outcome measures were: (1) 1-repetition maximum strength assessments for the chest press, row, and leg press and (2) duration on a graded exercise capacity test following 2 months of intervention. How might these results be applied to physical therapist practice? Physical therapists should consider providing exercise counseling combined with fitness center– based exercise as form of clinical management for people with type 2 diabetes. The study also suggests that careful dosing of exercise programs is more important than the manner in which the exercise is provided. What are the limitations of the study, and what further research is needed? This study did not blind subjects, therapists, or data recorders to group allocation, and the sample size was small. These two factors limit the ability to generalize these results. A larger, multicenter randomized clinical trial with longer outcome data points should be performed to strengthen the external validity of these results. Eric K. Robertson E.K. Robertson, PT, DPT, OCS, is Assistant Professor, Department of Physical Therapy, Texas State University, San Marcos, Texas. This is the Bottom Line for: Taylor JD, Fletcher JP, Tiarks J. Impact of Physical Therapist–Directed Exercise Counseling Combined With Fitness Center–Based Exercise Training on Muscular Strength and Exercise Capacity in People With Type 2 Diabetes: A Randomized Clinical Trial. Phys Ther. 2009;89:884–892.

September 2009


Physical Therapy Journal of the American Physical Therapy Association

Editorial Office

Editor in Chief

Managing Editor / Associate Director of Publications: Jan P. Reynolds, [email protected]

Rebecca L. Craik, PT, PhD, FAPTA, Philadelphia, PA [email protected]

PTJ Online Editor / Assistant Managing Editor: Steven Glaros

Deputy Editor in Chief

Associate Editor: Stephen Brooks, ELS Production Manager: Liz Haberkorn Manuscripts Coordinator: Karen Darley Permissions / Reprint Coordinator: Michele Tillson Advertising Manager: Julie Hilgenberg Director of Publications: Lois Douthitt

APTA Executive Staff Senior Vice President for Communications: Felicity Feather Clancy Chief Financial Officer: Rob Batarla Chief Executive Officer: John D. Barnes

Advertising Sales Ad Marketing Group, Inc 2200 Wilson Blvd, Suite 102-333 Arlington, VA 22201 703/243-9046, ext 102 President / Advertising Account Manager: Jane Dees Richardson

Board of Directors President: R. Scott Ward, PT, PhD Vice President: Paul A. Rockar Jr, PT, DPT, MS Secretary: Babette S. Sanders, PT, MS Treasurer: Connie D. Hauser, PT, DPT, ATC Speaker of the House: Shawne E. Soper, PT, DPT, MBA Vice Speaker of the House: Laurita M. Hack, PT, DPT, MBA, PhD, FAPTA Directors: Sharon L. Dunn, PT, PhD, OCS; Kevin L. Hulsey, PT, DPT, MA; Dianne V. Jewell, PT, DPT, PhD, CCS, FAACVPR; Aimee B. Klein, PT, DPT, DSc, OCS; Kathleen K. Mairella, PT, DPT, MA; Stephen C.F. McDavitt, PT, DPT, MS, FAAOMPT; Lisa K. Saladin, PT, PhD; Mary C. Sinnott, PT, DPT, MEd; Nicole L. Stout, PT, MPT, CLT-LANA

Daniel L. Riddle, PT, PhD, FAPTA, Richmond, VA

Editor in Chief Emeritus Jules M. Rothstein, PT, PhD, FAPTA (1947–2005)

Steering Committee Anthony Delitto, PT, PhD, FAPTA (Chair), Pittsburgh, PA; J. Haxby Abbott, PhD, MScPT, DipGrad, FNZCP, Dunedin, New Zealand; Joanell Bohmert, PT, MS, Mahtomedi, MN; Alan M. Jette, PT, PhD, FAPTA, Boston, MA; Charles Magistro, PT, FAPTA, Claremont, CA; Ruth B. Purtilo, PT, PhD, FAPTA, Boston, MA; Julie Whitman, PT, DSc, OCS, Westminster, CO

Editorial Board Rachelle Buchbinder, MBBS(Hons), MSc, PhD, FRACP, Malvern, Victoria, Australia; W. Todd Cade, PT, PhD, St. Louis, MO; James Carey, PT, PhD, Minneapolis, MN; John Childs, PT, PhD, Schertz, TX; Charles Ciccone, PT, PhD, FAPTA (Continuing Education), Ithaca, NY; Joshua Cleland, PT, DPT, PhD, OCS, FAAOMPT, Concord, NH; Janice J. Eng, PT/OT, PhD, Vancouver, BC, Canada; G. Kelley Fitzgerald, PT, PhD, OCS, FAPTA, Pittsburgh, PA; James C. (Cole) Galloway, PT, PhD, Newark, DE; Steven Z. George, PT, PhD, Gainesville, FL; Kathleen Gill-Body, PT, DPT, NCS, Boston, MA; Paul J.M. Helders, PT, PhD, PCS, Utrecht, The Netherlands; Maura D. Iversen, PT, ScD, MPH, Boston, MA; Diane U. Jette, PT, DSc, Burlington, VT; Christopher Maher, PT, PhD, Lidcombe, NSW, Australia; Christopher J. Main, PhD, FBPsS, Keele, United Kingdom; Kathleen Kline Mangione, PT, PhD, GCS, Philadelphia, PA; Patricia Ohtake, PT, PhD, Buffalo, NY; Carolynn Patten, PT, PhD, Gainesville, FL; Linda Resnik, PT, PhD, OCS, Providence, RI; Val Robertson, PT, PhD, Copacabana, NSW, Australia; Patty Solomon, PT, PhD, Hamilton, Ont, Canada

Statistical Consultants Steven E. Hanna, PhD, Hamilton, Ont, Canada; John E. Hewett, PhD, Columbia, MO; Hang Lee, PhD, Boston, MA; Xiangrong Kong, PhD, Baltimore, MD; Paul Stratford, PT, MSc, Hamilton, Ont, Canada; Samuel Wu, PhD, Gainesville, FL

The Bottom Line Committee Eric Robertson, PT, DPT, OCS; Joanell Bohmert, PT, MS; Lara Boyd, PT, PhD; James Cavanaugh IV, PT, PhD, NCS; Todd Davenport, PT, DPT, OCS; Ann Dennison, PT, DPT, OCS; William Egan, PT, DPT, OCS; Helen Host, PT, PhD; Evan Johnson, PT, DPT, MS, OCS, MTC; M. Kathleen Kelly, PT, PhD; Catherine Lang, PT, PhD; Tara Jo Manal, PT, MPT, OCS, SCS; Kristin Parlman, PT, DPT, NCS; Susan Perry, PT, DPT, NCS; Maj Nicole H. Raney, PT, DSc, OCS, FAAOMPT; Rick Ritter, PT; Kathleen Rockefeller, PT, MPH, ScD; Michael Ross, PT, DHS, OCS; Katherine Sullivan, PT, PhD; Mary Thigpen, PT, PhD; Jamie Tomlinson, PT, MS; Brian Tovin, DPT, MMSc, SCS, ATC, FAAOMPT; Nancy White, PT, MS, OCS; Julie Whitman, PT, DSc, OCS

868 ■ Physical Therapy Volume 89 Number 9

September 2009

Subscriptions

Physical Therapy (PTJ) (ISSN 00319023) is published monthly by the American Physical Therapy Association (APTA), 1111 North Fairfax Street, Alexandria, VA 22314-1488, at an annual subscription rate of $15 for members, included in dues. Nonmember rates are as follows: Individual (inside USA)— $99; individual (outside USA)—$119 surface mail, $179 air mail. Institutional (inside USA)—$129; institutional (outside USA)—$149 surface mail, $209 air mail. Periodical postage is paid at Alexandria, VA, and at additional mailing offices. Postmaster: Send address changes to Physical Therapy, 1111 North Fairfax Street, Alexandria, VA 22314-1488. Single copies: $15 USA, $15 outside USA; with the exception of January 2001: $50 USA, $70 outside USA. All orders payable in US currency. No replacements for nonreceipt after a 3-month period has elapsed. Canada Post International Publications Mail Product Sales Agreement No. 0055832.

Members and Subscribers Send changes of address to: APTA, Attn: Membership Dept, 1111 North Fairfax St, Alexandria, VA 22314-1488. Subscription inquiries: 703/684-2782, ext 3124. PTJ is available in a special format for readers who are visually impaired. For information, contact APTA’s Membership Department at 703/684-2782, ext 3124.

Mission Statement

Physical Therapy (PTJ) engages and inspires an international readership on topics related to physical therapy. As the leading international journal for research in physical therapy and related fields, PTJ publishes innovative and highly relevant content for both clinicians and scientists and uses a variety of interactive approaches to communicate that content, with the expressed purpose of improving patient care.

Readers are invited to submit manuscripts to PTJ. PTJ’s content—including editorials, commentaries, letters, and book reviews—represents the opinions of the authors and should not be attributed to PTJ or its Editorial Board. Content does not reflect the official policy of APTA or the institution with which the author is affiliated, unless expressly stated.

Full-text articles are available for free at www.ptjournal.org 12 months after the publication date. Full text also is provided through DataStar, Dialog, EBSCOHost Academic Search, Factiva, InfoTrac, ProFound, and ProQuest.

Reprints

PTJ Online at www.ptjournal.org PTJ Online is available via RSS feeds. PTJ posts articles ahead of print and rapid reader responses to articles. Articles, letters to the editor, and editorials are available in full text starting with Volume 79 (1999) and in searchable PDF format starting with Volume 60 (1980). Entire issues are available online beginning with Volume 86 (2006) and include additional data, video clips, and podcasts.

Indexing and Document Delivery

Readers should direct requests for reprints to the corresponding author of the article. Students and other academic customers may receive permission to reprint copyrighted material from this publication by contacting the Copyright Clearance Center Inc, 222 Rosewood Dr, Danvers, MA 01923. Authors who want reprints should contact June Billman, Cadmus Communications, at 800/487-5625, or [email protected]. Non-academic institutions needing reprint permission information should go to www.ptjournal.org/misc/terms.dtl.

Advertising

PTJ is indexed and/or abstracted by Abridged Index Medicus, Abstracts of Health Care Management Studies, AgeLine, AMED (Allied and Complementary Medicine Database), Bibliography of Developmental Medicine and Child Neurology, Current Contents, Cumulative Index to Nursing and Allied Health Literature (CINAHL), EMBASE/Exerpta Medica, Exceptional Child Education Resources, Focus on: Sports Science and Medicine, General Science Index (GSI), Health Index, Hospital and Health Administration Index, Index Medicus, Inpharma Weekly, International Nursing Index, ISR, Medical & Surgical Dermatology, MEDLINE, Neuroscience Citation Index, Personal Alert: Automatic Subject Citation Alert (ASCA), Pharmacoeconomics and Outcomes News, Physical Education Index, Reactions Weekly, RECAL Bibliographic Database, Science Citation Index (SCI), Social Sciences Citation Index (SSCI), and SportsS. Article abstracts are available online at www.ptjournal.org (1980 through present) and via DataStar, Dialog, FirstSearch, Information Access, Ovid

September 2009

Technologies. Ingenta provides online document delivery for articles published since September 1988.

Advertisements are accepted by PTJ when they conform to the ethical standards of the American Physical Therapy Association. PTJ does not verify the accuracy of claims made in advertisements, and acceptance does not imply endorsement by PTJ or the Association. Acceptance of advertisements for professional development courses addressing advanced-level competencies in clinical specialty areas does not imply review or endorsement by the American Board of Physical Therapy Specialties.

Statement of Nondiscrimination APTA prohibits preferential or adverse discrimination on the basis of race, creed, color, gender, age, national or ethnic origin, sexual orientation, disability, or health status in all areas including, but not limited to, its qualifications for membership, rights of members, policies, programs, activities, and employment practices. APTA is committed to promoting cultural diversity throughout the profession.


Editorial PRISMA: Helping to Deliver Information That Physical Therapists Need

S

taying up to date as a physical therapist is a challenge because the research underpinning the science and practice of our profession is growing exponentially.1 The growth is well illustrated by the history of randomized controlled trials (RCT). In 1929, there was only 1 RCT evaluating a physical therapy treatment; by 1972, there were 100; by 1986, 1,000; by 2005, 10,000; and today, there are more than 12,000 RCTs. As a consequence, a “mid-career” physical therapist (who graduated in 1980) now has access to 25 times more RCTs compared with when they graduated. Even with the advent of physical therapy–specific databases such as Hooked on Evidence and PEDro, it has become impossible to keep up to date by reading primary research papers: the job has just gotten too big.

An efficient way for physical therapists to keep up to date is to read recent systematic reviews. For people with little spare time, systematic reviews are a godsend because they can distill the evidence from dozens of primary studies. Although systematic reviews on the effectiveness of interventions2 are probably the most common, there also are reviews that focus on cost-effectiveness,3 the views of patients,4 prognosis,5 diagnosis,6 clinical prediction rules,7 psychometric properties of scales8 or measures,9,10 cross-cultural adaptation of self-report measures,11 definitions of epidemiological terms,12 and practice guidelines.13 Most questions that arise in physical therapist practice lend themselves to evaluation within a systematic review. Well-conducted systematic reviews identify, appraise, and summarize research in an unbiased fashion and so provide reliable information to guide clinical decision making. Unfortunately, though, not all systematic reviews are well conducted.14 And that is where the PRISMA statement comes in. The PRISMA statement provides a checklist of items for reporting systematic reviews and meta-analyses. When this key information is reported in a review, readers are in a much better position to judge the strength and weaknesses of a review and, most importantly, to judge whether the information provided is relevant to the specific clinical question they want to answer. About PRISMA The Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) statement evolved from the earlier QUOROM (Quality of Reporting of Meta-analyses) statement. QUOROM was a reporting checklist for meta-analyses of RCTs; however, as noted earlier, not all systematic reviews take this form. Beyond the expanded scope, other important differences with PRISMA are items for the review protocol and registration, for the specific electronic search strategy, and for describing sources of funding. More information on PRISMA is contained in the reprinted article in this issue15 and also at the PRISMA Web site (http://www.prisma-statement.org).

To comment, submit a Rapid Response to this editorial posted online at www.ptjournal.org.

870 ■

Reports of systematic reviews that attend to the PRISMA statement will provide readers with the key information they need in order to judge the value of a systematic review. It is for this reason that PTJ joins with other journals such as BMJ, Annals of Internal Medicine, PLoS Medicine, and Journal of Clinical Epidemiology in endorsing PRISMA. We will ask our authors to follow this statement when preparing manuscripts reporting a systematic review.


September 2009

Editorial Those of you who have recently viewed our instructions for authors will know that PTJ has endorsed a range of reporting checklists analogous to PRISMA. PTJ asks authors to attend to the STARD statement when they report a diagnostic study, the STROBE statement when they report an observational study, and the CONSORT statement when they report an RCT. There are a number of extensions to the CONSORT statement that focus on the additional information required for reports of cluster trials and non-inferiority and equivalence trials and for trials evaluating herbal medicines or nonpharmacological interventions. Why Read a Checklist? Checklists like PRISMA are obviously of value to physical therapists who are preparing a manuscript; however, they do have other uses. For researchers, they provide an excellent reminder of the sorts of issues to consider when submitting a grant application to an agency such as the Foundation for Physical Therapy or National Institutes of Health. They also are useful for our reviewers and others who critically appraise research reports because the checklists specify the salient issues that need to be considered. However, reporting checklists are not designed to assess the quality of a published study. There are separate scales to assess the risk of bias (methodological quality) of a study. Examples include the QUADAS scale for diagnostic studies16 and the PEDro scale for RCTs.17,18 At the end of the day, the primary purpose of PTJ is to improve patient care. PTJ has adopted the PRISMA statement to help us better communicate our content to the physical therapists who provide that care. Christopher Maher, PT, PhD Editorial Board Member, PTJ References 1 Maher CG, Moseley AM, Sherrington C, et al. A description of the trials, reviews, and practice guidelines indexed in the PEDro database. Phys Ther. 2008;88:1068–1077. 2 Macedo LG, Maher CG, Latimer J, McAuley JH. Motor control exercise for persistent, nonspecific low back pain: a systematic review. Phys Ther. 2009;89:9–25. 3 Peterson LE, Goodman C, Karnes EK, et al. Assessment of the quality of cost analysis literature in physical therapy. Phys Ther. 2009;89:733–755. 4 Verbeek J, Sengers MJ, Riemens L, Haafkens J. Patient expectations of treatment for back pain: a systematic review of qualitative and quantitative studies. Spine. 2004;29:2309–2318. 5 Pengel LHM, Herbert RD, Maher CG, Refshauge KM. Acute low back pain: systematic review of its prognosis. BMJ. 2003;327:323–327. 6 Henschke N, Maher CG, Refshauge KM. A systematic review identifies five “red flags” to screen for vertebral fracture in patients with low back pain. J Clin Epidemiol. 2008;61:110–118. 7 Beneciuk JM, Bishop MD, George SZ. Clinical prediction rules for physical therapy interventions: a systematic review. Phys Ther. 2009;89:114–124. 8 Olivo SA, Macedo LG, Gadotti IC, et al. Scales to assess the quality of randomized controlled trials: a systematic review. Phys Ther. 2008;88:156–175. 9 Costa LOP, Maher CG, Latimer J, Smeets RJEM. Reproducibility of rehabilitative ultrasound imaging for the measurement of abdominal muscle activity: a systematic review. Phys Ther. 2009;89:756–769. 10 Blum L, Korner-Bitensky N. Usefulness of the Berg Balance Scale in stroke rehabilitation: a systematic review. Phys Ther. 2008;88:559–566. 11 Costa LCM, Maher C, McAuley J, Costa LOP. Systematic review of cross-cultural adaptations of McGill Pain Questionnaire reveals a paucity of clinimetric testing. J Clin Epidemiol. 2009;62:934–943. 12 Stanton TR, Latimer J, Maher CG, Hancock M. Definitions of recurrence of an episode of low back pain: a systematic review. Spine. 2009;34:E316–E322. 13 Koes BW, van Tulder MW, Ostelo R, et al. Clinical guidelines for the management of low back pain in primary care: an international comparison. Spine. 2001;26:2504–2513.

September 2009


Editorial 14 Moseley AM, Elkins MR, Herbert RD, et al. Cochrane reviews used more rigorous methods than nonCochrane reviews: survey of systematic reviews in physiotherapy. J Clin Epidemiol. 2009 Mar 10 [Epub ahead of print]. 15 Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. Phys Ther. 2009;89:873–880. 16 Whiting P, Rutjes AW, Reitsma JB, et al. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003;3:25. 17 Maher CG, Sherrington C, Herbert RD, et al. Reliability of the PEDro Scale for rating quality of randomized controlled trials. Phys Ther. 2003;83:713–721. 18 de Morton N. The PEDro scale is a valid measure of the methodological quality of clinical trials: a demographic study. Aust J Physiother. 2009;55:129–133. [DOI: 10.2522/ptj.2009.89.9.870]

872 ■


September 2009

Reprint Reprint—Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement David Moher, Alessandro Liberati, Jennifer Tetzlaff, Douglas G. Altman, and the PRISMA Group Editor’s Note: PTJ’s Editorial Board has adopted PRISMA to help PTJ better communicate research to physical therapists. For more, read Chris Maher’s editorial starting on page 870. Membership of the PRISMA Group is provided in the Acknowledgments. This article has been reprinted with permission from the Annals of Internal Medicine from Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. Ann Intern Med. Available at: http://www.annals.org/cgi/content/full/151/4/264. The authors jointly hold copyright of this article. This article has also been published in PLoS Medicine, BMJ, Journal of Clinical Epidemiology, and Open Medicine. Copyright © 2009 Moher et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

D. Moher, PhD, Ottawa Methods Centre, Ottawa Hospital Research Institute, The Ottawa Hospital, General Campus, Critical Care Wing (Eye Institute), 6th Floor, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada; e-mail, [email protected]. A. Liberati, MD, DrPH, Universita` di Modena e Reggio Emilia and Centro Cochrane Italiano, Istituto Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milan, Italy. J. Tetzlaff, BSc, Ottawa Methods Centre, Ottawa Hospital Research Institute, The Ottawa Hospital, General Campus, Critical Care Wing (Eye Institute), 6th Floor, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada. D.G. Altman, DSc, Centre for Statistics in Medicine, University of Oxford, Wolfson College Annexe, Linton Road, Oxford OX2 6UD, United Kingdom. [Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. Ann Intern Med. Jul 2009. Available at: http:// www.annals.org/cgi/content/ full/151/4/264.] © 2009 American Physical Therapy Association

Post a Rapid Response or find The Bottom Line: www.ptjournal.org September 2009

Volume 89

Number 9

Physical Therapy f

873

PRISMA Statement

S

ystematic reviews and metaanalyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers’ ability to assess the strengths and weaknesses of those reviews.

Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in four leading medical journals in 1985 and 1986 and found that none met all eight explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in six domains. Reporting was generally poor; between one and 14 characteristics were adequately reported (mean⫽7.7; standard deviation⫽2.7). A 1996 update of this study found little improvement.7 In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance Available With This Article at www.ptjournal.org • The PRISMA Explanation and Elaboration Document • Table S1 Downloadable template for researchers to re-use • Figure S1 Downloadable template for researchers to re-use

874

f

Physical Therapy

Volume 89

called the QUOROM Statement (QUality Of Reporting Of Metaanalyses), which focused on the reporting of meta-analyses of randomized, controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1).

Terminology The terminology used to describe a systematic review and meta-analysis has evolved over time. One reason for changing the name from QUOROM to PRISMA was the desire to encompass both systematic reviews and meta-analyses. We have adopted the definitions used by the Cochrane Collaboration.9 A systematic review is a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant research, and to collect and analyze data from the studies that are included in the review. Statistical methods (meta-analysis) may or may not be used to analyze and summarize the results of the included studies. Meta-analysis refers to the use of statistical techniques in a systematic review to integrate the results of included studies.

Developing the PRISMA Statement A three-day meeting was held in Ottawa, Ontario, Canada, in June 2005 with 29 participants, including review authors, methodologists, clinicians, medical editors, and a consumer. The objective of the Ottawa meeting was to revise and expand the QUOROM checklist and flow diagram, as needed. The executive committee completed the following tasks, prior to the meeting: a systematic review of stud-

Number 9

ies examining the quality of reporting of systematic reviews, and a comprehensive literature search to identify methodological and other articles that might inform the meeting, especially in relation to modifying checklist items. An international survey of review authors, consumers, and groups commissioning or using systematic reviews and metaanalyses was completed, including the International Network of Agencies for Health Technology Assessment (INAHTA) and the Guidelines International Network (GIN). The survey aimed to ascertain views of QUOROM, including the merits of the existing checklist items. The results of these activities were presented during the meeting and are summarized on the PRISMA Web site (www.prisma-statement.org). Only items deemed essential were retained or added to the checklist. Some additional items are nevertheless desirable, and review authors should include these, if relevant.10 For example, it is useful to indicate whether the systematic review is an update11 of a previous review, and to describe any changes in procedures from those described in the original protocol. Shortly after the meeting a draft of the PRISMA checklist was circulated to the group, including those invited to the meeting but unable to attend. A disposition file was created containing comments and revisions from each respondent, and the checklist was subsequently revised 11 times. The group approved the checklist, flow diagram, and this summary paper. Although no direct evidence was found to support retaining or adding some items, evidence from other domains was believed to be relevant. For example, Item 5 asks authors to provide registration information about the systematic review, includSeptember 2009

PRISMA Statement ing a registration number, if available. Although systematic review registration is not yet widely available,12,13 the participating journals of the International Committee of Medical Journal Editors (ICMJE)14 now require all clinical trials to be registered in an effort to increase transparency and accountability.15 Those aspects are also likely to benefit systematic reviewers, possibly reducing the risk of an excessive number of reviews addressing the same question16,17 and providing greater transparency when updating systematic reviews.

The PRISMA Statement The PRISMA Statement consists of a 27-item checklist (Table 1; see also Table S1 for a downloadable Word template for researchers to re-use) and a four-phase flow diagram (Figure 1; see also Figure S1 for a downloadable Word template for researchers to re-use). The aim of the PRISMA Statement is to help authors improve the reporting of systematic reviews and meta-analyses. We have focused on randomized trials, but PRISMA can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions. PRISMA may also be useful for critical appraisal of published systematic reviews. However, the PRISMA checklist is not a quality assessment instrument to gauge the quality of a systematic review.

From QUOROM to PRISMA The new PRISMA checklist differs in several respects from the QUOROM checklist, and the substantive specific changes are highlighted in Table 2. Generally, the PRISMA checklist “decouples” several items present in the QUOROM checklist and, where applicable, several checklist items are linked to improve consistency across the systematic review report.

Box 1: Conceptual Issues in the Evolution from QUOROM to PRISMA Completing a Systematic Review Is an Iterative Process The conduct of a systematic review depends heavily on the scope and quality of included studies: thus systematic reviewers may need to modify their original review protocol during its conduct. Any systematic review reporting guideline should recommend that such changes can be reported and explained without suggesting that they are inappropriate. The PRISMA Statement (Items 5, 11, 16, and 23) acknowledges this iterative process. Aside from Cochrane reviews, all of which should have a protocol, only about 10% of systematic reviewers report working from a protocol.22 Without a protocol that is publicly accessible, it is difficult to judge between appropriate and inappropriate modifications. Conduct and Reporting Research Are Distinct Concepts This distinction is, however, less straightforward for systematic reviews than for assessments of the reporting of an individual study, because the reporting and conduct of systematic reviews are, by nature, closely intertwined. For example, the failure of a systematic review to report the assessment of the risk of bias in included studies may be seen as a marker of poor conduct, given the importance of this activity in the systematic review process.37 Study-Level Versus Outcome-Level Assessment of Risk of Bias For studies included in a systematic review, a thorough assessment of the risk of bias requires both a “study-level” assessment (eg, adequacy of allocation concealment) and, for some features, a newer approach called “outcome-level” assessment. An outcome-level assessment involves evaluating the reliability and validity of the data for each important outcome by determining the methods used to assess them in each individual study.38 The quality of evidence may differ across outcomes, even within a study, such as between a primary efficacy outcome, which is likely to be very carefully and systematically measured, and the assessment of serious harms,39 which may rely on spontaneous reports by investigators. This information should be reported to allow an explicit assessment of the extent to which an estimate of effect is correct.38 Importance of Reporting Biases Different types of reporting biases may hamper the conduct and interpretation of systematic reviews. Selective reporting of complete studies (eg, publication bias)28 as well as the more recently empirically demonstrated “outcome reporting bias” within individual studies40,41 should be considered by authors when conducting a systematic review and reporting its results. Though the implications of these biases on the conduct and reporting of systematic reviews themselves are unclear, some previous research has identified that selective outcome reporting may occur also in the context of systematic reviews.42

The flow diagram has also been modified. Before including studies and September 2009

Volume 89

Number 9

Physical Therapy f

875

PRISMA Statement Table 1. Checklist of items to include when reporting a systematic review or meta-analysis Section/Topic

Item #

Checklist Item

Reported on page #

TITLE Title

1

Identify the report as a systematic review, meta-analysis, or both.

2

Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number.

Rationale

3

Describe the rationale for the review in the context of what is already known.

Objectives

4

Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).

Protocol and registration

5

Indicate if a review protocol exists, if and where it can be accessed (eg, Web address), and, if available, provide registration information including registration number.

Eligibility criteria

6

Specify study characteristics (eg, PICOS, length of follow-up) and report characteristics (eg, years considered, language, publication status) used as criteria for eligibility, giving rationale.

Information sources

7

Describe all information sources (eg, databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

Search

8

Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

Study selection

9

State the process for selecting studies (ie, screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).

Data collection process

10

Describe method of data extraction from reports (eg, piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

Data items

11

List and define all variables for which data were sought (eg, PICOS, funding sources) and any assumptions and simplifications made.

Risk of bias in individual studies

12

Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

Summary measures

13

State the principal summary measures (eg, risk ratio, difference in means).

Synthesis of results

14

Describe the methods of handling data and combining results of studies, if done, including measures of consistency (eg, I2) for each meta-analysis.

Risk of bias across studies

15

Specify any assessment of risk of bias that may affect the cumulative evidence (eg, publication bias, selective reporting within studies).

Additional analyses

16

Describe methods of additional analyses (eg, sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.

Study selection

17

Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.

Study characteristics

18

For each study, present characteristics for which data were extracted (eg, study size, PICOS, follow-up period) and provide the citations.

Risk of bias within studies

19

Present data on risk of bias of each study and, if available, any outcome-level assessment (see Item 12).

Results of individual studies

20

For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group and (b) effect estimates and confidence intervals, ideally with a forest plot.

Synthesis of results

21

Present results of each meta-analysis done, including confidence intervals and measures of consistency.

ABSTRACT Structured summary

INTRODUCTION

METHODS

RESULTS

(Continued)

876

f

Physical Therapy

Volume 89

Number 9

September 2009

PRISMA Statement Table 1. Continued Reported on page #

Section/Topic

Item #

Checklist Item

Risk of bias across studies

22

Present results of any assessment of risk of bias across studies (see Item 15).

Additional analysis

23

Give results of additional analyses, if done (eg, sensitivity or subgroup analyses, meta-regression [see Item 16]).

Summary of evidence

24

Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (eg, health care providers, users, and policy makers).

Limitations

25

Discuss limitations at study and outcome level (eg, risk of bias), and at review level (eg, incomplete retrieval of identified research, reporting bias).

Conclusions

26

Provide a general interpretation of the results in the context of other evidence, and implications for future research.

27

Describe sources of funding for the systematic review and other support (eg, supply of data); role of funders for the systematic review.

DISCUSSION

FUNDING Funding

providing reasons for excluding others, the review team must first search the literature. This search results in records. Once these records have been screened and eligibility criteria applied, a smaller number of articles will remain. The number of included articles might be smaller (or larger) than the number of studies, because articles may report on multiple studies and results from a particular study may be published in several articles. To capture this information, the PRISMA flow diagram now requests information on these phases of the review process.

The PRISMA Explanation and Elaboration Paper In addition to the PRISMA Statement, a supporting Explanation and Elaboration document has been produced18 following the style used for other reporting guidelines.19 –21 The process of completing this docu-

ment included developing a large database of exemplars to highlight how best to report each checklist item, and identifying a comprehensive evidence base to support the inclusion of each checklist item. The Explanation and Elaboration document was completed after several face-to-face

Endorsement The PRISMA Statement should replace the QUOROM Statement for those journals that have endorsed QUOROM. We hope that other journals will support PRISMA; they can do so by registering on the PRISMA Web site. To underscore to authors, and others, the importance of transparent reporting of systematic reviews, we encourage supporting journals to reference the PRISMA Statement and include the PRISMA Web address in their instructions to authors. We also invite editorial organizations to consider endorsing PRISMA and encourage authors to adhere to its principles. September 2009

Figure 1. Flow of information through the different phases of a systematic review.

Volume 89

Number 9

Physical Therapy f

877

PRISMA Statement Table 2. Substantive Specific Changes Between the QUOROM Checklist and the PRISMA Checklista Section/ Topic

Item

QUOROM

PRISMA

⻬

⻬

QUOROM and PRISMA ask authors to report an abstract. However, PRISMA is not specific about format.

Abstract Introduction

Objective

⻬

This new item (4) addresses the explicit question the review addresses using the PICO reporting system (which describes the participants, interventions, comparisons, and outcome(s) of the systematic review), together with the specification of the type of study design (PICOS); the item is linked to Items 6, 11, and 18 of the checklist.

Methods

Protocol

⻬

This new item (5) asks authors to report whether the review has a protocol and if so how it can be accessed.

Methods

Search

⻬

⻬

Although reporting the search is present in both QUOROM and PRISMA checklists, PRISMA asks authors to provide a full description of at least one electronic search strategy (Item 8). Without such information it is impossible to repeat the authors’ search.

Methods

Assessment of risk of bias in included studies

⻬

⻬

Renamed from “quality assessment” in QUOROM. This item (12) is linked with reporting this information in the results (Item 19). The new concept of “outcome-level” assessment has been introduced.

Methods

Assessment of risk of bias across studies

⻬

This new item (15) asks authors to describe any assessments of risk of bias in the review, such as selective reporting within the included studies. This item is linked with reporting this information in the results (Item 22).

⻬

Although both QUOROM and PRISMA checklists address the discussion section, PRISMA devotes three items (24–26) to the discussion. In PRISMA the main types of limitations are explicitly stated and their discussion required.

⻬

This new item (27) asks authors to provide information on any sources of funding for the systematic review.

⻬

Discussion

Funding a

Comment

A tick indicates the presence of the topic in QUOROM or PRISMA.

meetings and numerous iterations among several meeting participants, after which it was shared with the whole group for additional revisions and final approval. Finally, the group formed a dissemination subcommittee to help disseminate and implement PRISMA.

preted it appropriately.30 Although the absence of reporting such an assessment does not necessarily indicate that it was not done, reporting an assessment of possible publication bias is likely to be a marker of the thoroughness of the conduct of the systematic review.

Discussion

Several approaches have been developed to conduct systematic reviews on a broader array of questions. For example, systematic reviews are now conducted to investigate costeffectiveness,31 diagnostic32 or prognostic questions,33 genetic associations,34 and policy making.35 The general concepts and topics covered by PRISMA are all relevant to any systematic review, not just those whose objective is to summarize the benefits and harms of a health care

The quality of reporting of systematic reviews is still not optimal.22–27 In a recent review of 300 systematic reviews, few authors reported assessing possible publication bias,22 even though there is overwhelming evidence both for its existence28 and its impact on the results of systematic reviews.29 Even when the possibility of publication bias is assessed, there is no guarantee that systematic reviewers have assessed or inter878

f

Physical Therapy

Volume 89

Number 9

intervention. However, some modifications of the checklist items or flow diagram will be necessary in particular circumstances. For example, assessing the risk of bias is a key concept, but the items used to assess this in a diagnostic review are likely to focus on issues such as the spectrum of patients and the verification of disease status, which differ from reviews of interventions. The flow diagram will also need adjustments when reporting individual patient data meta-analysis.36 We have developed an explanatory document18 to increase the usefulness of PRISMA. For each checklist item, this document contains an example of good reporting, a rationale for its inclusion, and supporting evidence, including references, whenSeptember 2009

PRISMA Statement ever possible. We believe this document will also serve as a useful resource for those teaching systematic review methodology. We encourage journals to include reference to the explanatory document in their Instructions to Authors. Like any evidence-based endeavor, PRISMA is a living document. To this end we invite readers to comment on the revised version, particularly the new checklist and flow diagram, through the PRISMA Web site. We will use such information to inform PRISMA’s continued development. Author and Article Information: The following people contributed to the PRISMA Statement: Doug Altman, DSc, Centre for Statistics in Medicine (Oxford, United Kingdom); Gerd Antes, PhD, University Hospital Freiburg (Freiburg, Germany); David Atkins, MD, MPH, Health Services Research & Development Service, Veterans Health Administration (Washington, DC); Virginia Barbour, MRCP, DPhil, PLoS Medicine (Cambridge, United Kingdom); Nick Barrowman, PhD, Children’s Hospital of Eastern Ontario (Ottawa, Ontario, Canada); Jesse A. Berlin, ScD, Johnson & Johnson Pharmaceutical Research and Development (Titusville, New Jersey); Jocalyn Clark, PhD, PLoS Medicine (at the time of writing, BMJ; London, United Kingdom); Mike Clarke, PhD, UK Cochrane Centre (Oxford, United Kingdom) and School of Nursing and Midwifery, Trinity College (Dublin, Ireland); Deborah Cook, MD, Departments of Medicine, Clinical Epidemiology and Biostatistics, McMaster University (Hamilton, Ontario, Canada); Roberto D’Amico, PhD, Universita` di Modena e Reggio Emilia (Modena, Italy) and Centro Cochrane Italiano, Istituto Ricerche Farmacologiche Mario Negri (Milan, Italy); Jonathan J. Deeks, PhD, University of Birmingham (Birmingham, United Kingdom); P.J. Devereaux, MD, PhD, Departments of Medicine, Clinical Epidemiology and Biostatistics, McMaster University (Hamilton, Ontario, Canada); Kay Dickersin, PhD, Johns Hopkins Bloomberg School of Public Health (Baltimore, Maryland); Matthias Egger, MD, Department of Social and Preventive Medicine, University of Bern (Bern, Switzerland); Edzard Ernst, MD, PhD, FRCP, FRCP(Edin), Peninsula Medical School (Exeter, United Kingdom); Peter C. Gøtzsche, MD, MSc, The Nordic Cochrane Centre (Copenhagen, Denmark); Jeremy Grimshaw, MBChB, PhD, FRCFP, Ottawa

September 2009

Hospital Research Institute (Ottawa, Ontario, Canada); Gordon Guyatt, MD, Departments of Medicine, Clinical Epidemiology and Biostatistics, McMaster University (Hamilton, Ontario, Canada); Julian Higgins, PhD, MRC Biostatistics Unit (Cambridge, United Kingdom); John P.A. Ioannidis, MD, University of Ioannina Campus (Ioannina, Greece); Jos Kleijnen, MD, PhD, Kleijnen Systematic Reviews Ltd (York, United Kingdom) and School for Public Health and Primary Care (CAPHRI), University of Maastricht (Maastricht, the Netherlands); Tom Lang, MA, Tom Lang Communications and Training (Davis, California); Alessandro Liberati, MD, Universita` di Modena e Reggio Emilia (Modena, Italy) and Centro Cochrane Italiano, Istituto Ricerche Farmacologiche Mario Negri (Milan, Italy); Nicola Magrini, MD, NHS Centre for the Evaluation of the Effectiveness of Health Care–CeVEAS (Modena, Italy); David McNamee, PhD, The Lancet (London, United Kingdom); Lorenzo Moja, MD, MSc, Centro Cochrane Italiano, Istituto Ricerche Farmacologiche Mario Negri (Milan, Italy); David Moher, PhD, Ottawa Methods Centre, Ottawa Hospital Research Institute (Ottawa, Ontario, Canada); Cynthia Mulrow, MD, MSc, Annals of Internal Medicine (Philadelphia, Pennsylvania); Maryann Napoli, Center for Medical Consumers (New York, New York); Andy Oxman, MD, Norwegian Health Services Research Centre (Oslo, Norway); Ba’ Pham, MMath, Toronto Health Economics and Technology Assessment Collaborative (Toronto, Ontario, Canada; at the time of the first meeting of the group, GlaxoSmithKline Canada [Mississauga, Ontario, Canada]); Drummond Rennie, MD, FRCP, FACP, University of California, San Francisco (San Francisco, California); Margaret Sampson, MLIS, Children’s Hospital of Eastern Ontario (Ottawa, Ontario, Canada); Kenneth F. Schulz, PhD, MBA, Family Health International (Durham, North Carolina); Paul G. Shekelle, MD, PhD, Southern California Evidence-Based Practice Center (Santa Monica, California); Jennifer Tetzlaff, BSc, Ottawa Methods Centre, Ottawa Hospital Research Institute (Ottawa, Ontario, Canada); David Tovey, FRCGP, The Cochrane Library, Cochrane Collaboration (Oxford, United Kingdom; at the time of the first meeting of the group, BMJ [London, United Kingdom]); and Peter Tugwell, MD, MSc, FRCPC, Institute of Population Health, University of Ottawa (Ottawa, Ontario, Canada). Grant Support: PRISMA was funded by the Canadian Institutes of Health Research; Universita` di Modena e Reggio Emilia, Italy; Cancer Research UK; Clinical Evidence BMJ Knowledge; The Cochrane Collaboration; and GlaxoSmithKline, Canada. Dr. Liberati is funded, in part, through grants of the Italian

Ministry of University (COFIN-PRIN 2002 prot. 2002061749 and COFIN-PRIN 2006 prot. 2006062298). Dr. Altman is funded by Cancer Research UK. Dr. Moher is funded by a University of Ottawa Research Chair. None of the sponsors had any involvement in the planning, execution, or write-up of the PRISMA documents. Additionally, no funder played a role in drafting the manuscript. Potential Financial Conflicts of Interest: None disclosed.

References 1 Oxman AD, Cook DJ, Guyatt GH. Users’ guides to the medical literature. VI. How to use an overview. Evidence-Based Medicine Working Group. JAMA. 1994;272: 1367–1371. [PMID: 7933399]. 2 Swingler GH, Volmink J, Ioannidis JP. Number of published systematic reviews and global burden of disease: database analysis. BMJ. 2003;327:1083–1084. [PMID: 14604930]. 3 Canadian Institutes of Health Research. Randomized controlled trials registration/application checklist. December 2006. Accessed at www.cihr-irsc.gc.ca/e/ documents/rct_reg_e.pdf on 19 May 2009. 4 Young C, Horton R. Putting clinical trials into context. Lancet. 2005;366:107–108. [PMID: 16005318]. 5 Mulrow CD. The medical review article: state of the science. Ann Intern Med. 1987;106:485– 488. [PMID: 3813259]. 6 Sacks HS, Berrier J, Reitman D, AnconaBerk VA, Chalmers TC. Meta-analyses of randomized controlled trials. N Engl J Med. 1987;316:450–455. [PMID: 3807986]. 7 Sacks HS, Reitman D, Pagano D, Kupelnick B. Meta-analysis: an update. Mt Sinai J Med. 1996;63:216 –224. [PMID: 8692168]. 8 Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, Stroup DF. Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. Quality of Reporting of Metaanalyses. Lancet. 1999;354:1896 –1900. [PMID: 10584742]. 9 Green S, Higgins J, eds. Glossary. In: Cochrane Handbook for Systematic Reviews of Interventions 4.2.5. The Cochrane Collaboration; 2005. Accessed at www.cochrane.org/resources/glossary.htm on 19 May 2009. 10 Strech D, Tilburt J. Value judgments in the analysis and synthesis of evidence. J Clin Epidemiol. 2008;61:521–524. [PMID: 18471654]. 11 Moher D, Tsertsvadze A. Systematic reviews: when is an update an update? Lancet. 2006;367:881– 883. [PMID: 16546523]. 12 University of York Centre for Reviews and Dissemination. 2009. Accessed at www. york.ac.uk/inst/crd/ on 19 May 2009. 13 The Joanna Briggs Institute protocols & work in progress. 2009. Accessed at www.joannabriggs.edu.au/pubs/systematic_reviews_prot.php on 19 May 2009.

Volume 89

Number 9

Physical Therapy f

879

PRISMA Statement 14 De Angelis C, Drazen JM, Frizelle FA, Haug C, Hoey J, Horton R, et al; International Committee of Medical Journal Editors. Clinical trial registration: a statement from the International Committee of Medical Journal Editors [Editorial]. CMAJ. 2004; 171:606 – 607. [PMID: 15367465]. 15 Whittington CJ, Kendall T, Fonagy P, Cottrell D, Cotgrove A, Boddington E. Selective serotonin reuptake inhibitors in childhood depression: systematic review of published versus unpublished data. Lancet. 2004;363:1341–1345. [PMID: 15110490]. 16 Bagshaw SM, McAlister FA, Manns BJ, Ghali WA. Acetylcysteine in the prevention of contrast-induced nephropathy: a case study of the pitfalls in the evolution of evidence. Arch Intern Med. 2006;166: 161–166. [PMID: 16432083]. 17 Biondi-Zoccai GG, Lotrionte M, Abbate A, Testa L, Remigi E, Burzotta F, et al. Compliance with QUOROM and quality of reporting of overlapping meta-analyses on the role of acetylcysteine in the prevention of contrast associated nephropathy: case study. BMJ. 2006;332:202–209. [PMID: 16415336]. 18 Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche P, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med. 2009;151. 19 Altman DG, Schulz KF, Moher D, Egger M, Davidoff F, Elbourne D, et al; CONSORT GROUP (Consolidated Standards of Reporting Trials). The revised CONSORT statement for reporting randomized trials: explanation and elaboration. Ann Intern Med. 2001;134:663–94. [PMID: 11304107]. 20 Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig LM, et al; Standards for Reporting of Diagnostic Accuracy. The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Ann Intern Med. 2003;138:W1–W12. [PMID: 12513067]. 21 Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, et al; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Ann Intern Med. 2007;147: W163–W194. [PMID: 17938389].

880

f

Physical Therapy

Volume 89

22 Moher D, Tetzlaff J, Tricco AC, Sampson M, Altman DG. Epidemiology and reporting characteristics of systematic reviews. PLoS Med. 2007;4:e78. [PMID: 17388659]. 23 Bhandari M, Morrow F, Kulkarni AV, Tornetta P 3rd. Meta-analyses in orthopaedic surgery. A systematic review of their methodologies. J Bone Joint Surg Am. 2001;83A:15–24. [PMID: 11205853]. 24 Kelly KD, Travers A, Dorgan M, Slater L, Rowe BH. Evaluating the quality of systematic reviews in the emergency medicine literature. Ann Emerg Med. 2001;38:518 – 526. [PMID: 11679863]. 25 Richards D. The quality of systematic reviews in dentistry. Evid Based Dent. 2004; 5:17. [PMID: 15238972]. 26 Choi PT, Halpern SH, Malik N, Jadad AR, Trame`r MR, Walder B. Examining the evidence in anesthesia literature: a critical appraisal of systematic reviews. Anesth Analg. 2001;92:700–709. [PMID: 11226105]. 27 Delaney A, Bagshaw SM, Ferland A, Manns B, Laupland KB, Doig CJ. A systematic evaluation of the quality of meta-analyses in the critical care literature. Crit Care. 2005; 9:R575–582. [PMID: 16277721]. 28 Dickersin K. Publication bias: recognizing the problem, understanding its origins and scope, and preventing harm. In: Rothstein HR, Sutton AJ, Borenstein M, eds. Publication Bias in Meta-Analysis—Prevention, Assessment and Adjustments. Chichester, UK: J Wiley; 2005:11–33. 29 Sutton AJ. Evidence concerning the consequences of publication and related biases. In: Rothstein HR, Sutton AJ, Borenstein M, eds. Publication Bias in MetaAnalysis—Prevention, Assessment and Adjustments. Chichester, UK: J Wiley; 2005:175–192. 30 Lau J, Ioannidis JP, Terrin N, Schmid CH, Olkin I. The case of the misleading funnel plot. BMJ. 2006;333:597– 600. [PMID: 16974018]. 31 Ladabaum U, Chopra CL, Huang G, Scheiman JM, Chernew ME, Fendrick AM. Aspirin as an adjunct to screening for prevention of sporadic colorectal cancer. A cost-effectiveness analysis. Ann Intern Med. 2001;135:769–781. [PMID: 11694102]. 32 Deeks JJ. Systematic reviews in health care: Systematic reviews of evaluations of diagnostic and screening tests. BMJ. 2001; 323:157–162. [PMID: 11463691].

Number 9

33 Altman DG. Systematic reviews of evaluations of prognostic variables. BMJ. 2001; 323:224 –228. [PMID: 11473921]. 34 Ioannidis JP, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG. Replication validity of genetic association studies. Nat Genet. 2001;29:306–309. [PMID: 11600885]. 35 Lavis J, Davies H, Oxman A, Denis JL, Golden-Biddle K, Ferlie E. Towards systematic reviews that inform health care management and policy-making. J Health Serv Res Policy. 2005;10 Suppl 1:35– 48. [PMID: 16053582]. 36 Stewart LA, Clarke MJ. Practical methodology of meta-analyses (overviews) using updated individual patient data. Cochrane Working Group. Stat Med. 1995;14:2057– 2079. [PMID: 8552887]. 37 Moja LP, Telaro E, D’Amico R, Moschetti I, Coe L, Liberati A. Assessment of methodological quality of primary studies by systematic reviews: results of the metaquality cross sectional study. BMJ. 2005;330: 1053. [PMID: 15817526]. 38 Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al; GRADE Working Group. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924 –926. [PMID: 18436948]. 39 Schu ¨ nemann HJ, Jaeschke R, Cook DJ, Bria WF, El-Solh AA, Ernst A, et al; ATS Documents Development and Implementation Committee. An official ATS statement: grading the quality of evidence and strength of recommendations in ATS guidelines and recommendations. Am J Respir Crit Care Med. 2006;174:605– 614. [PMID: 16931644]. 40 Chan AW, Hro ´ bjartsson A, Haahr MT, Gøtzsche PC, Altman DG. Empirical evidence for selective reporting of outcomes in randomized trials: comparison of protocols to published articles. JAMA. 2004; 291:2457–2465. [PMID: 15161896]. 41 Chan AW, Krleza-Jeric K, Schmid I, Altman DG. Outcome reporting bias in randomized trials funded by the Canadian Institutes of Health Research. CMAJ. 2004;171: 735–740. [PMID: 15451835]. 42 Silagy CA, Middleton P, Hopewell S. Publishing protocols of systematic reviews: comparing what was done to what was planned. JAMA. 2002;287:2831–2834. [PMID: 12038926].

September 2009

Research Report Impact of Physical Therapist–Directed Exercise Counseling Combined With Fitness Center–Based Exercise Training on Muscular Strength and Exercise Capacity in People With Type 2 Diabetes: A Randomized Clinical Trial J. David Taylor, James P. Fletcher, Jakesa Tiarks J.D. Taylor, PT, PhD, CSCS, is Assistant Professor, Department of Physical Therapy, University of Central Arkansas, 201 Donaghey Ave, Physical Therapy Center, Room 319, Conway, AR 72035 (USA). Address all correspondence to Dr Taylor at: [email protected]. J.P. Fletcher, PT, PhD, ATC, is Assistant Professor, Department of Physical Therapy, University of Central Arkansas. J. Tiarks, ATC, is a DPT student, Department of Physical Therapy, University of Central Arkansas. [Taylor JD, Fletcher JP, Tiarks J. Impact of physical therapist– directed exercise counseling combined with fitness center– based exercise training on muscular strength and exercise capacity in people with type 2 diabetes: a randomized clinical trial. Phys Ther. 2009;89:884 – 892.] © 2009 American Physical Therapy Association

Background. Assessing muscular strength (force-generating capacity) and exercise capacity in response to an intervention for people with type 2 diabetes is clinically important in the prevention of type 2 diabetes-related complications. Objective. The purpose of this study was to investigate the impact of physical therapist– directed exercise counseling combined with fitness center– based exercise training on muscular strength and exercise capacity in people with type 2 diabetes.

Design. This study was a randomized clinical trial. Setting. The study was conducted on a university campus, with patient recruitment from the local community.

Patients. Twenty-four people with type 2 diabetes were randomly allocated to either a group that received physical therapist– directed exercise counseling plus fitness center– based exercise training (experimental group) or a group that received laboratory-based, supervised exercise (comparison group).

Intervention. The experimental group received physical therapist– directed exercise counseling on an exercise program and was provided access to a fitness center. The comparison group received the same exercise program as the experimental group while under supervision. Measurements. For all participants, chest press, row, and leg press muscular strength (1-repetition maximum [in kilograms]) and exercise capacity (graded exercise test duration [in minutes]) testing were conducted at baseline and 2 months later. Results. No significant differences in improvements in muscular strength were found for the chest press (adjusted mean difference⫽1.2; 95% confidence interval [CI]⫽⫺5.5 to 7.8), row (adjusted mean difference⫽0.1; 95% CI⫽⫺9.0 to 9.1), or leg press (adjusted mean difference⫽2.7; 95% CI⫽⫺9.1 to 14.6) between the groups. No significant difference in improvement in exercise capacity (adjusted mean difference⫽0.2; 95% CI⫽⫺0.9 to 1.2) was found between the groups.

Limitations. Lack of group allocation blinding and the small sample size were limitations of this study.

Post a Rapid Response or find The Bottom Line: www.ptjournal.org 884

f

Physical Therapy

Conclusions. The results suggest that physical therapist– directed exercise counseling combined with fitness center– based exercise training can improve muscular strength and exercise capacity in people with type 2 diabetes, with outcomes comparable to those of supervised exercise.

Volume 89

Number 9

September 2009

Physical Therapist–Directed Exercise Counseling Combined With Fitness Center–Based Exercise Training

T

ype 2 diabetes is a chronic, metabolic disease characterized by hyperglycemia resulting from insulin resistance. Research studies indicate that complications such as cardiovascular disease,1 peripheral vascular disease,2 retinopathy,3 and loss of physical function4 are associated with type 2 diabetes. An additional complication of type 2 diabetes is a decline in muscular strength (force-generating capacity). The results of previous studies5,6 suggest that people with type 2 diabetes have less muscular strength than people without type 2 diabetes. Deficits in muscular strength are clinically relevant for people with type 2 diabetes due to evidence indicating that loss of muscular strength has been associated with increased risk of loss of physical function7,8 in people with and without type 2 diabetes. Another complication of type 2 diabetes is a loss of exercise capacity. Research suggests that people with type 2 diabetes have decreased exercise capacity compared with people without type 2 diabetes.9,10 Loss of exercise capacity also is clinically relevant for people with type 2 diabetes because loss of exercise capacity has been shown to increase the risk of mortality11–13 in people with and without type 2 diabetes. Therefore, assessing changes in muscular strength and exercise capacity in response to an intervention for people with type 2 diabetes is clinically important because of the poten-

Available With This Article at www.ptjournal.org • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on July 9, 2009, at www.ptjournal.org.

September 2009

tial to prevent loss of physical function and mortality. Clinical management of people with type 2 diabetes consists of medical nutrition therapy, pharmacological therapy, and exercise.14 The American Diabetes Association and the American College of Sports Medicine have published position statements recommending the use of exercise as an intervention for the clinical management of people with type 2 diabetes.15,16 The findings of previous research studies provide supportive evidence for the use of supervised exercise programs to improve muscular strength17,18 and exercise capacity18 in people with type 2 diabetes. However, health insurance programs such as Medicare do not currently reimburse clinicians, such as physical therapists, for supervised exercise training to improve muscular strength and exercise capacity to prevent type 2 diabetes–related complications. Evidence exists that suggests that counseling interventions can serve as an alternative to supervised interventions for people with type 2 diabetes. Previous studies have investigated the impact of exercise counseling on physical activity in people with type 2 diabetes. In 2 studies, Kirk and colleagues19,20 investigated the impact of exercise counseling on physical activity at 6 months20 and 12 months19 in people with type 2 diabetes. In both studies, they used an exercise counseling intervention consisting of face-to-face counseling to encourage physical activity and periodic exercise counseling by phone. Their findings suggest that exercise counseling can increase physical activity in people with type 2 diabetes at 6 months20 and 12 months.19 Although these studies provide evidence for the use of exercise counseling to increase physical activity

in people with type 2 diabetes, no studies of the impact of exercise counseling on muscular strength and exercise capacity in people with type 2 diabetes exist. Exercise counseling to increase muscular strength and exercise capacity in people with type 2 diabetes is clinically relevant because increasing muscular strength and exercise capacity would reduce the risk of loss of physical function and mortality. Furthermore, physical therapist– directed exercise counseling would be more cost-effective because health insurance programs such as Medicare do not currently reimburse physical therapists for supervised exercise training to prevent type 2 diabetes-related complications. Therefore, the purpose of this randomized clinical trial was to investigate the impact of a novel intervention consisting of physical therapist– directed exercise counseling combined with fitness centerbased exercise training on muscular strength and exercise capacity in people with type 2 diabetes. In this study, exercise counseling, by a physical therapist, combined with fitness center– based exercise training was compared with supervised exercise training.

Method Design Overview This investigation was a randomized clinical trial of the impact of physical therapist– directed exercise counseling combined with fitness center– based exercise training on muscular strength and exercise capacity in people with type 2 diabetes. Participants were randomly allocated to either a group that received 2 months of physical therapist– directed exercise counseling combined with fitness center-based exercise training (experimental group) or a group that received 2 months of laboratory-based, supervised exercise training (comparison group). Neither the investigators, who delivered the interventions and

Volume 89

Number 9

Physical Therapy f

885

Physical Therapist–Directed Exercise Counseling Combined With Fitness Center–Based Exercise Training assessed the outcomes, nor the participants were blinded to group allocation. The current treatment (medical nutrition therapy or pharmacological therapy) of each participant was not changed during the course of this randomized clinical trial. Muscular strength and exercise capacity outcomes for all participants were assessed at baseline and 2 months after baseline. Setting and Participants This randomized clinical trial was conducted on the campus of the University of Central Arkansas, Conway, Arkansas. Participants were recruited from the Conway, Arkansas, geographic area by posting study recruitment flyers at local medical clinics and community centers and by study recruitment announcements through local university electronic mail. All participants met the American Diabetes Association diagnostic criteria for type 2 diabetes.14 The American Diabetes Association type 2 diabetes diagnostic criteria are: (1) symptoms of type 2 diabetes plus casual plasma glucose level of ⱖ200 mg/dL, (2) fasting plasma glucose level of ⱖ126 mg/dL, or (3) plasma glucose level of ⱖ200 mg/dL during a 2-hour oral glucose tolerance test using a 75-g glucose load. Casual was defined as any time of day, without regard to time since last meal. Symptoms of type 2 diabetes include polyuria, polydipsia, and unexplained weight loss. Fasting was defined as no caloric intake for at least 8 hours.14 Furthermore, a physician considered each participant to be medically stable to participate in this investigation. Any individual with a history of a medical condition identified by the American Heart Association as an absolute contraindication to exercise testing was excluded from this study.21 Furthermore, any individual with uncontrolled hypertension, proliferative retinopathy, severe 886

f

Physical Therapy

Volume 89

peripheral neuropathy, nephropathy, or autonomic neuropathy, or who was unable to participate in this study due to a physical impairment, was excluded from this investigation. In addition, the American Diabetes Association states that exercise is contraindicated if fasting plasma glucose levels are greater than 300 mg/dL or 250 mg/dL and ketosis is present.22 In this study, any individual with a fasting plasma glucose level greater than 250 mg/dL was excluded. Any individual involved in resistance or aerobic training on 2 or more days per week at the time of this investigation also was excluded. Each participant was required to complete a written, informed consent form. Randomization Random allocation was performed using a computer-generated randomized sequence of group allocation created before the beginning of this study. As each participant entered this randomized clinical trial, he or she was randomly allocated to either the experimental group or the comparison group according to the computer-generated sequence of group allocation. As previously mentioned, neither the investigators, who delivered the interventions and assessed the outcomes, nor the participants were blinded to group allocation. Interventions For all participants, exercise training consisted of a prescribed exercise program entailing resistance and aerobic training as recommended by the American Diabetes Association and American College of Sports Medicine for people with type 2 diabetes.15,16 In an effort to address participant safety, resistance training exercises were performed using range-of-motion–limiting equipment, which provided a controlled resistance through a limited range of motion, as opposed to free weights. The

Number 9

resistance training component of the exercise program consisted of chest press, row, and leg press exercises. Initially, 4 sets of up to 8 repetitions of each exercise using 80% of the 1-repetition maximum (1-RM) on 2 nonconsecutive days per week for 2 months were prescribed. When 4 sets of 8 repetitions using 80% of the 1-RM were performed, resistance was progressively increased by 2.27 to 4.54 kg (5–10 lb) during the next training day and each subsequent training day whenever 4 sets of 8 repetitions were performed. The prescribed rest period between sets of exercise was 1 to 3 minutes. The aerobic training component of the exercise program consisted of walking or jogging on a treadmill at a speed and percent grade that correlated to a rating of perceived exertion (RPE) of 12 (“somewhat hard”) using the Borg RPE Scale23 for 20 minutes on the same days as resistance training was prescribed. The speed or percent grade was progressively increased to each participant’s tolerance during each subsequent training day but did not exceed an RPE of 12. Each participant in the experimental group received exercise counseling from the same physical therapist, which was based on the 5 A’s strategy for health behavior counseling (address the agenda, assess, advise, assist, and arrange follow-ups) used in previous research.24,25 Each participant received a face-to-face exercise counseling session with the physical therapist at baseline and 1 month after baseline, which lasted approximately 30 minutes per session. During the initial exercise counseling session, each participant was provided a written copy of the prescribed exercise program. In addition to the face-to-face exercise counseling sessions, each participant received weekly exercise counseling telephone calls from the physical therapist, which lasted approxiSeptember 2009

Physical Therapist–Directed Exercise Counseling Combined With Fitness Center–Based Exercise Training mately 10 minutes. During each exercise counseling session, the physical therapist addressed the benefits of exercise for people with type 2 diabetes, advised each participant to adhere to the prescribed exercise program, and assisted each participant by reviewing the prescribed exercise program. For each participant in the experimental group, the stage of exercise behavior also was assessed using a reliable and valid questionnaire.26,27 The questionnaire classified each participant into 1 of 5 stages: precontemplation (not exercising and does not intend to exercise), contemplation (not exercising, but intends to start exercising), preparation (exercising, but not regularly), action (exercising regularly, but for less than 6 months), and maintenance (exercising regularly for 6 months or more). In this study, exercising was defined as resistance training or aerobic training. Exercising regularly was defined as exercising on 2 days or more per week. Exercise counseling was tailored to the stage of exercise behavior, as described in previous literature.25 Each participant in the experimental group also was provided 7-day-perweek access to a local fitness center, which contained the resistance training equipment and treadmills needed to complete the prescribed exercise program. Prior to beginning the exercise program, each participant was oriented to the use of the resistance training equipment and treadmills. Staff members of the fitness center were on-site in case any participant experienced an adverse event while exercising. No staff member assisted any participant with the prescribed exercise program, nor did any participant consult with a staff member. During exercise counseling, each participant was instructed to carry a glucose food source in case of hypoglycemia during exercise. Each participant also was instructed to imSeptember 2009

mediately inform the fitness center staff if any adverse events were experienced while exercising and to consult a physician if needed. If any adverse events were experienced while exercising, each participant also was instructed to contact the principal investigator (a physical therapist) of this study. Participants who were randomly allocated to the comparison group received a 2-month supervised exercise program. Each participant in the comparison group received the same prescribed exercise program as the experimental group and was supervised during each exercise training session by a trained coinvestigator in a controlled exercise laboratory setting. Outcomes Primary outcomes of this investigation were muscular strength and exercise capacity. Muscular strength for each participant was quantified using 1-RM testing of exercises for multiple muscle groups of the upper body and lower body. Upper-body muscular strength testing consisted of the chest press and row exercises. Lower-body muscular strength testing consisted of the leg press exercise. Prior to muscular strength testing, a physical therapist instructed each participant on proper technique for the chest press, row, and leg press exercises. Each participant also was required to practice each exercise while being observed by the physical therapist to ensure that he or she was familiarized with proper technique of each exercise. After demonstrating proper technique of each exercise, each participant underwent 1-RM testing procedures for each exercise. During 1-RM testing, each participant initially performed one repetition of each exercise with a weight perceived by the participant as “somewhat easy.” Next, each participant rested for 1 to 3 minutes. Then, the

physical therapist increased the weight for each exercise by 2.27 to 4.54 kg (5–10 lb). Each participant then attempted to perform another repetition of each exercise. The 1-RM testing procedures for each exercise were continued until each participant either failed to perform one repetition or voluntarily stopped the 1-RM testing procedures. The 1-RM for each exercise was defined as the maximum amount of weight that was performed for one repetition. For each participant, muscular strength was expressed as 1-RM (in kilograms) for each exercise. For all participants, muscular strength testing was conducted at baseline and 2 months after baseline. Previous literature indicates that 1-RM testing is reliable28 and is a standard for measuring muscular strength.23 Exercise capacity for each participant also was quantified using a graded exercise test, which was conducted by a physical therapist. A modified Bruce treadmill protocol29 was the graded exercise test utilized to measure exercise capacity for each participant. In an effort to address participant safety, the graded exercise test was continued until each participant either reached 85% of age-predicted maximum heart rate (220 ⫺ age in years)30 or voluntarily stopped the graded exercise test. Heart rate (in beats per minute) of each participant was constantly measured throughout the graded exercise test using a digital electronic heart rate monitor. Blood pressure of each participant also was monitored during the graded exercise test. Graded exercise test duration was constantly measured using a digital electronic timer. Exercise capacity was defined as the total duration (in minutes) of the graded exercise test. For all participants, exercise capacity testing was conducted at baseline and 2 months after baseline. Previous literature suggests that graded exercise testing using the modified

Volume 89

Number 9

Physical Therapy f

887

Physical Therapist–Directed Exercise Counseling Combined With Fitness Center–Based Exercise Training Bruce treadmill protocol is reliable31 and is a standard for measuring exercise capacity.21 Secondary outcomes of this study were participant adherence and adverse events. During each weekly exercise counseling telephone call, each participant in the experimental group was asked the date on which each exercise training day of the exercise program was completed and the length of time spent during each exercise training day, and these data were used to assess the experimental group’s adherence to the exercise program. The coinvestigator, who supervised the comparison group, recorded the date of each completed exercise training session of the exercise program and the length of time spent during each exercise training session, and these data were used to assess the comparison group’s adherence to the exercise program. Adverse events were reported to the principal investigator and to the institutional review board that approved this study. Data Analysis In order to retain data of all randomly allocated participants, an intentionto-treat analysis of the data was performed using the last observation carried forward approach, meaning baseline data were carried forward to represent the missing data that were lost to follow-up. An analysis of covariance (ANCOVA) with an alpha level set at .05 was used to compare follow-up muscular strength and exercise capacity scores between the experimental group and comparison group, with baseline scores included as covariates to control for baseline group differences. A paired t test with an alpha level set at .05 was used to compare baseline and follow-up muscular strength and exercise capacity scores within the experimental group and comparison group. Ninety-five percent confidence intervals for differences in 888

f

Physical Therapy

Volume 89

between-group changes and withingroup changes in muscular strength and exercise capacity also were calculated. Adherence to the exercise program for the experimental group and comparison group was expressed as the total number of training days that each participant completed out of the 16 prescribed training days and total exercise time during the 2-month exercise program. An unpaired t test with an alpha level set at .05 was used to compare adherence between the experimental group and comparison group. Statistical analyses were conducted using SPSS for Windows, version 15.0.*

comparison group are reported in Table 1. After allocation, 2 participants in the experimental group and 3 participants in the comparison group withdrew from this investigation for reasons unrelated to this study. Reasons for participants in the experimental group withdrawing from this investigation were lack of time due to work schedule (n⫽1) and orthopedic injury while at home (n⫽1). Reasons for participants in the comparison group withdrawing from this study were surgery (n⫽1), spontaneous worsening of rheumatoid arthritis (n⫽1), and reoccurrence of preexisting shoulder pain (n⫽1).

An a priori power analysis was conducted to estimate the number of participants needed to obtain a statistical power of 0.90 at an alpha level of .05. A meta-analysis study32 of the effect of resistance training on muscular strength calculated a standardized effect size of 2.0 for improvement in muscular strength, which was a primary outcome in this investigation. The a priori power analysis estimated a sample size of 10 participants in the experimental group and 10 participants in the comparison group would detect a 2.0 standardized effect size with a statistical power of at least 0.90 at an alpha level of .05.

Muscular strength and exercise capacity outcome scores of the experimental group and comparison group are outlined in Table 2. The ANCOVA indicated no significant differences in improvements in muscular strength for the chest press (P⫽.71), row (P⫽.98), or leg press (P⫽.63) exercise between the groups. Furthermore, the ANCOVA indicated no significant differences in improvements in exercise capacity (P⫽.72) between the groups. However, significant improvements (P⬍.05) in all primary outcomes were found in both groups.

Results A flowchart that illustrates this randomized clinical trial is presented in the Figure. A total of 25 potential participants with type 2 diabetes were assessed for eligibility, of which 1 person was excluded. Eleven participants were randomly allocated to the experimental group, and 13 participants were randomly allocated to the comparison group. Baseline demographic characteristics of participants in the experimental group and * SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

Number 9

The experimental group participated in a mean of 12.6 training days (SD⫽6.3) and spent a mean total exercise time of 568.6 minutes (SD⫽283.4) during the 2-month exercise program. The comparison group participated in a mean of 12.1 training days (SD⫽6.9) and spent a mean total exercise time of 543.5 minutes (SD⫽310.4) during the 2-month exercise program. The unpaired t test indicated no significant difference (P⬎.05) in adherence in terms of training days or exercise time between the groups. No adverse events were reported over the course of this investigation.

September 2009


Figure. Randomized clinical trial flowchart.

Discussion This investigation is the first randomized clinical trial of the impact of physical therapist– directed exercise counseling combined with fitness center– based exercise training on muscular strength and exercise capacity in people with type 2 diabeSeptember 2009

tes. The results of this investigation indicated significant improvements in muscular strength and exercise capacity within the experimental group and comparison group. However, no significant differences in muscular strength or exercise capacity outcomes between the experi-

mental group and comparison group were found. Participant adherence to the exercise program was high within the experimental group and comparison group, and no adverse events were reported in this investigation.

Volume 89

Number 9

Physical Therapy f

889

Physical Therapist–Directed Exercise Counseling Combined With Fitness Center–Based Exercise Training Table 1. Participant Characteristics at Baselinea Experimental Group

Characteristic

Comparison Group

No. of participants

11

13

Sex (male:female)

4:7

8:5

Age (y)

52.2 (6.9)

58.0 (8.4)

Body mass (kg)

94.0 (15.4)

106.7 (16.4)

164.1 (10.4)

170.2 (10.5)

Height (cm) Muscular strength (kg) Chest press

33.1 (15.9)

37.3 (11.9)

Row

40.9 (14.5)

48.9 (14.3)

90.5 (22.2)

100.3 (20.0)

10.5 (2.7)

9.3 (3.4)

Leg press Exercise capacity (min) a

Data are reported as mean (standard deviation) for continuous variables and counts for dichotomous variables.

The finding of no significant differences in improvements between the experimental group and comparison group suggests that the determining factor for improving muscular strength and exercise capacity in people with type 2 diabetes is participation in an effectively dosed exercise program. In this study, although the exercise program was delivered differently, the dose of the exercise program was identical for the experimental group and comparison group. Furthermore, participant adherence was high for both groups. Thus, the delivery of an effectively dosed exercise program, either by physical therapist– directed exercise counseling combined with fitness center– based exercise training or supervised exercise training, can result in high adherence and significant improvements in muscular strength and exercise capacity in people with type 2 diabetes. Physical therapist– directed exercise counseling combined with fitness center-based exercise training resulted in high adherence and significant improvements in muscular strength and exercise capacity in people with type 2 diabetes, with outcomes comparable to those of su890

f

Physical Therapy

Volume 89

pervised exercise training. Thus, physical therapists have the ability to make an evidence-based choice of prescribing either exercise counseling combined with fitness center– based exercise training or supervised exercise training for people with type 2 diabetes. Potential factors for physical therapists in choosing either exercise counseling combined with fitness center– based exercise training or supervised exercise training are time and financial costs of the interventions and availability of resources, any of which may affect patient adherence. Currently, physical therapists are not reimbursed by health insurance programs such as Medicare for supervised exercise training to improve muscular strength and exercise capacity to prevent complications of type 2 diabetes. Thus, future research is needed to compare the costeffectiveness of physical therapistdirected exercise counseling combined with fitness center– based exercise training with that of supervised exercise training for people with type 2 diabetes. The clinical significance of the findings of this investigation was considered. No research on the minimal

Number 9

clinically important difference in muscular strength and exercise capacity for people with type 2 diabetes exists. However, Sayer et al8 found that men with type 2 diabetes had significantly less muscular strength and were more likely to experience loss of physical function compared with men without type 2 diabetes. Church et al11 found an inverse relationship between exercise capacity and mortality in men with diabetes. The current investigation showed significant improvements in muscular strength and exercise capacity within the experimental group and comparison group. Thus, the delivery of an exercise program, either by physical therapist– directed exercise counseling combined with fitness center– based exercise training or supervised exercise training, can improve muscular strength and exercise capacity in people with type 2 diabetes, which may prevent loss of physical function and mortality. The findings of this study suggest that physical therapists may utilize either exercise counseling combined with fitness center– based exercise training or supervised exercise training to improve muscular strength and exercise capacity in people with type 2 diabetes and possibly prevent complications of type 2 diabetes. The findings of this investigation are similar to the findings of previous research. Maiorana et al18 used an exercise program that entailed combined resistance and aerobic training to improve muscular strength and exercise capacity in people with type 2 diabetes. The prescribed exercise program used in this randomized clinical trial also consisted of combined resistance and aerobic training, which resulted in improvements in muscular strength and exercise capacity in people with type 2 diabetes. A difference between our investigation and the study conducted by Maiorana et al18 is that they used an exercise program that September 2009

2.7 (⫺9.1 to 14.6)

0.2 (⫺0.9 to 1.2)

14.9 (7.3 to 22.5)

1.2 (0.4 to 2.1)

consisted of directly supervised sessions to improve muscular strength and exercise capacity in people with type 2 diabetes. Our investigation provides evidence that physical therapist– directed exercise counseling combined with fitness center– based exercise training can be used to effectively deliver an exercise program without directly supervised sessions to improve muscular strength and exercise capacity in individuals with type 2 diabetes.

Data are reported as mean (SD). Data are reported as mean (95% confidence interval) based on paired t-test results. Data are reported as adjusted mean (95% confidence interval) based on analysis of covariance results. c

b

a

10.5 (3.0) 11.4 (2.6) 9.3 (3.4)

0.8 (0.1 to 1.6)

115.2 (22.1) 107.9 (28.6) 100.3 (20.0)

10.5 (2.7) Exercise capacity (min)

Leg press

90.5 (22.2)

17.4 (8.0 to 26.7)

1.2 (⫺5.5 to 7.8)

0.1 (⫺9.0 to 9.1)

9.3 (5.1 to 13.4)

10.4 (4.8 to 16.0)

9.6 (3.4 to 15.8)

11.0 (3.6 to 18.3)

46.6 (13.8)

59.3 (13.9)

42.7 (22.4)

51.9 (19.7)

37.3 (11.9)

48.9 (14.3)

33.1 (15.9)

40.9 (14.5)

Chest press

Muscular strength (kg)

Outcome

September 2009

Row

Comparison Group Experimental Group Comparison Group Experimental Group Comparison Group Experimental Group

Baselinea

Outcome Scores in the Experimental Group and Comparison Group

Table 2.

2 Months After Baselinea

Within-Group Changesb

Between-Group Differences in Changesc


The results of studies by Kirk and colleagues indicate that exercise counseling can increase physical activity at 6 months20 and 12 months19 in people with type 2 diabetes. In those studies, exercise counseling consisted of face-to-face counseling and periodic counseling by telephone. Similar to their studies, counseling in our investigation consisted of face-to-face exercise counseling and weekly exercise counseling by telephone. However, our study is novel in that physical therapistdirected exercise counseling combined with fitness center– based exercise training, as performed in this investigation, improved the clinically important outcomes of muscular strength and exercise capacity in people with type 2 diabetes. The limitations of this investigation were considered. This investigation was not a double-blinded randomized clinical trial. Neither the investigators nor the participants were blinded to group allocation. Blinding participants to group allocation was not possible due to the nature of the interventions. During this investigation, the outcomes assessor was not blinded to the outcome data, which increased the chance of assessor bias. The relatively small sample size also was a limitation of this study, as a larger sample size may have been a better representation of the population. This investigation did not include a follow-up after the 2-month

outcome data were collected, which also was a limitation of this study. Lastly, this investigation was a singlecenter randomized clinical trial. A multicenter randomized clinical trial would provide further evidence regarding the external validity of this study.

Conclusions Although the results of this investigation suggest that physical therapist– directed exercise counseling combined with fitness centerbased exercise training can significantly improve muscular strength and exercise capacity in people with type 2 diabetes, with outcomes comparable to those of supervised exercise training, further research is needed. A study that addresses the limitations of this investigation would provide additional evidence for the use of physical therapistdirected exercise counseling combined with fitness center– based exercise training for people with type 2 diabetes. Assessing changes in muscular strength and exercise capacity in response to an intervention for people with type 2 diabetes is clinically important because of the potential to prevent type 2 diabetes–related complications. The results of this randomized clinical trial suggest that physical therapists can utilize exercise counseling combined with fitness center– based exercise training to improve muscular strength and exercise capacity in people with type 2 diabetes, with outcomes comparable to those of supervised exercise training. Dr Taylor and Dr Fletcher provided concept/ idea/research design and participants. All authors provided writing and data analysis. Dr Taylor and Ms Tiarks provided data collection. Dr Fletcher and Ms Tiarks provided consultation (including review of manuscript before submission).

Volume 89

Number 9

Physical Therapy f

891

Physical Therapist–Directed Exercise Counseling Combined With Fitness Center–Based Exercise Training This study was approved by the University of Central Arkansas Institutional Review Board. An oral presentation of the results of this study was given at the Combined Sections Meeting of the American Physical Therapy Association; February 9 –12, 2009; Las Vegas, Nevada. This article was received August 15, 2008, and was accepted May 19, 2009. DOI: 10.2522/ptj.20080253

References 1 Rius Riu F, Salinas Vert I, Lucas Martin A, et al. A prospective study of cardiovascular disease in patients with Type 2 diabetes. 6.3 years of follow-up. J Diabetes Complications. 2003;17:235–242. 2 Adler AI, Stevens RJ, Neil A, et al. UKPDS 59: hyperglycemia and other potentially modifiable risk factors for peripheral vascular disease in type 2 diabetes. Diabetes Care. 2002;25:894 – 899. 3 Guillausseau PJ, Massin P, Charles MA, et al. Glycaemic control and development of retinopathy in type 2 diabetes mellitus: a longitudinal study. Diabet Med. 1998;15: 151–155. 4 Bruce DG, Davis WA, Davis TM. Longitudinal predictors of reduced mobility and physical disability in patients with type 2 diabetes: the Fremantle Diabetes Study. Diabetes Care. 2005;28:2441–2447. 5 Cetinus E, Buyukbese MA, Uzel M, et al. Hand grip strength in patients with type 2 diabetes mellitus. Diabetes Res Clin Pract. 2005;70:278 –286. 6 Park SW, Goodpaster BH, Strotmeyer ES, et al. Accelerated loss of skeletal muscle strength in older adults with type 2 diabetes: the health, aging, and body composition study. Diabetes Care. 2007;30: 1507–1512. 7 Brill PA, Macera CA, Davis DR, et al. Muscular strength and physical function. Med Sci Sports Exerc. 2000;32:412– 416. 8 Sayer AA, Dennison EM, Syddall HE, et al. Type 2 diabetes, muscle strength, and impaired physical function: the tip of the iceberg? Diabetes Care. 2005;28: 2541–2542.

892

f

Physical Therapy

Volume 89

9 Fang ZY, Sharman J, Prins JB, Marwick TH. Determinants of exercise capacity in patients with type 2 diabetes. Diabetes Care. 2005;28:1643–1648. 10 Katoh J, Hara Y, Kurusu M, et al. Cardiorespiratory function as assessed by exercise testing in patients with non-insulindependent diabetes mellitus. J Int Med Res. 1996;24:209 –213. 11 Church TS, Cheng YJ, Earnest CP, et al. Exercise capacity and body composition as predictors of mortality among men with diabetes. Diabetes Care. 2004;27:83– 88. 12 Laukkanen JA, Lakka TA, Rauramaa R, et al. Cardiovascular fitness as a predictor of mortality in men. Arch Intern Med. 2001;161:825– 831. 13 Wei M, Gibbons LW, Kampert JB, et al. Low cardiorespiratory fitness and physical inactivity as predictors of mortality in men with type 2 diabetes. Ann Intern Med. 2000;132:605– 611. 14 American Diabetes Association. Standards of medical care in diabetes. Diabetes Care. 2005;28(suppl 1):S4 –S36. 15 Sigal RJ, Kenny GP, Wasserman DH, et al. Physical activity/exercise and type 2 diabetes: a consensus statement from the American Diabetes Association. Diabetes Care. 2006;29:1433–1438. 16 Albright A, Franz M, Hornsby G, et al. American College of Sports Medicine position stand: exercise and type 2 diabetes. Med Sci Sports Exerc. 2000;32:1345–1360. 17 Dunstan DW, Daly RM, Owen N, et al. High-intensity resistance training improves glycemic control in older patients with type 2 diabetes. Diabetes Care. 2002; 25:1729 –1736. 18 Maiorana A, O’Driscoll G, Goodman C, et al. Combined aerobic and resistance exercise improves glycemic control and fitness in type 2 diabetes. Diabetes Res Clin Pract. 2002;56:115–123. 19 Kirk AF, Mutrie N, MacIntyre PD, Fisher MB. Promoting and maintaining physical activity in people with type 2 diabetes. Am J Prev Med. 2004;27:289 –296. 20 Kirk A, Mutrie N, MacIntyre P, Fisher M. Increasing physical activity in people with type 2 diabetes. Diabetes Care. 2003;26: 1186 –1192.

Number 9

21 Fletcher GF, Balady GJ, Amsterdam EA, et al. Exercise standards for testing and training: a statement for healthcare professionals from the American Heart Association. Circulation. 2001;104:1694 –1740. 22 Zinman B, Ruderman N, Campaigne BN, et al. Physical activity/exercise and diabetes. Diabetes Care. 2004;27(suppl 1): S58 –S62. 23 Whaley MH, Brubaker PH, Otto RM, Armstrong LE; American College of Sports Medicine. ACSM’s Guidelines for Exercise Testing and Prescription. 7th ed. Philadelphia, Pa: Lippincott Williams & Wilkins; 2006. 24 Pinto BM, Goldstein MG, Marcus BH. Activity counseling by primary care physicians. Prev Med. 1998;27:506 –513. 25 Shumaker SA. The Handbook of Health Behavior Change. 2nd ed. New York, NY: Springer Publishing Co; 1998. 26 Marcus BH, Simkin LR. The stages of exercise behavior. J Sports Med Phys Fitness. 1993;33:83– 88. 27 Marcus BH, Banspach SW, Lefebvre RC, et al. Using the stages of change model to increase the adoption of physical activity among community participants. Am J Health Promot. 1992;6:424 – 429. 28 Schroeder ET, Wang Y, Castaneda-Sceppa C, et al. Reliability of maximal voluntary muscle strength and power testing in older men. J Gerontol A Biol Sci Med Sci. 2007;62:543–549. 29 Bruce RA. Exercise testing of patients with coronary heart disease: principles and normal standards for evaluation. Ann Clin Res. 1971;3:323–332. 30 Astrand P-O, Rodahl K. Textbook of Work Physiology : Physiological Bases of Exercise. 3rd ed. New York, NY: McGraw-Hill; 1986. 31 Kraemer WJ, Volek JS, Clark KL, et al. Influence of exercise training on physiological and performance changes with weight loss in men. Med Sci Sports Exerc. 1999; 31:1320 –1329. 32 Rhea MR, Alvar BA, Burkett LN, Ball SD. A meta-analysis to determine the dose response for strength development. Med Sci Sports Exerc. 2003;35:456 – 464.

September 2009

Research Report Factors Associated With Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury: Results of a National Survey of Orthopedic Trauma Surgeons Kristin R. Archer, Ellen J. MacKenzie, Michael J. Bosse, Andrew N. Pollak, Lee H. Riley III

Background. Variation in referral rates for physical therapy exists at both the individual physician and practice levels. Objective. The purpose of this study was to explore the influence of physician and practice characteristics on referral for physical therapy in patients with traumatic lower-extremity injury.

Design. A cross-sectional survey was conducted. Methods. In 2007, a Web-based survey questionnaire was distributed to 474 surgeon members of the Orthopaedic Trauma Association. The questionnaire measured physician and practice characteristics, outcome expectations, and attitude toward physical therapy. Referral for physical therapy was based on case vignettes.

Results. The response rate was 58%. Surgeons reported that 57.6% of their patients would have a positive outcome from physical therapy and 24.2% would have a negative outcome. The highest physical therapy expectations were for the appropriate use of assistive devices (80.7%) and improved strength (force-generating capacity) (76.4%). The lowest outcome expectations were for improvements in pain (35.9%), coping with the emotional aspects of disability (44.1%), and improvements in workplace limitations (51.4%). Physicians reported that 32.6% of their patients referred for physical therapy would have no improvement beyond what would occur with a surgeon-directed home exercise program. Multivariate analyses showed positive physician outcome expectations to have the largest effect on referral for physical therapy (odds ratio⫽2.7, P⬍.001).

Conclusions. The results suggest that orthopedic trauma surgeons refer patients for physical therapy based mostly on expectations for physical and motor outcomes, but may not be considering pain relief, return to work, and psychosocial aspects of recovery. Furthermore, low referral rates may be attributed to a preference for surgeon-directed home-based rehabilitation. Future research should consider the efficacy of physical therapy for pain, psychosocial and occupational outcomes, and exploring the differences between supervised physical therapy and physiciandirected home exercise programs.

K.R. Archer, PT, PhD, DPT, is Assistant Professor, Department of Orthopaedics and Rehabilitation, Vanderbilt University Medical Center, Medical Center East– South Tower, Ste 4200, Nashville, TN 37232 (USA). Address all correspondence to Dr Archer at: [email protected]. E.J. MacKenzie, PhD, is Fred and Julie Soper Professor and Chair, Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. M.J. Bosse, MD, is Director of Clinical Research and Orthopaedic Traumatologist, Department of Orthopaedic Surgery, Carolinas Medical Center, Charlotte, North Carolina. A.N. Pollak, MD, is Associate Professor of Orthopaedics and Chief, Division of Orthopaedic Traumatology, R. Adams Cowley Shock Trauma Center, University of Maryland Medical Center, Baltimore, Maryland. L.H. Riley III, MD, is Associate Professor and Division Chief, Spine Surgery, Department of Orthopaedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland. [Archer KR, MacKenzie EJ, Bosse MJ, et al. Factors associated with surgeon referral for physical therapy in patients with traumatic lower-extremity injury: results of a national survey of orthopedic trauma surgeons. Phys Ther. 2009; 89:893–905.] © 2009 American Physical Therapy Association Post a Rapid Response or find The Bottom Line: www.ptjournal.org

September 2009

Volume 89

Number 9

Physical Therapy f

893

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury

V

ariation in referral rates for physical therapy exists at both the individual physician and practice levels.1– 6 Patient characteristics explain less than 25% of the observed variation.1,5,7–9 Research conducted to date has not fully elucidated the specific factors associated with variation in physical therapy referral. Evidence, however, suggests that physician characteristics, such as knowledge of therapeutic services and attitude toward physical therapy, may explain the residual variability in referral rates.3,5,9 –13 Researchers also have suggested that outcome expectations or the belief in the efficacy of physical therapy intervention may be an important contributor to the referral decision.6,14 Campbell and colleagues15–17 examined outcome expectations in a series of studies looking at referral of children with cerebral palsy for physical therapy, but their results did not support an association between utilization of services and beliefs regarding the value of physical therapy. Prior studies on clinical decision making have shown that physicians do not always make referrals consistent with their efficacy beliefs, especially if they are risk averse.18,19 Physicians may avoid referral if they believe an efficacious physical therapy program may involve negative outcomes or potentially harmful consequences. Physician outcome expectations have not been systematically studied in relation to the management of traumatic orthopedic injuries. Be-

Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on July 9, 2009, at www.ptjournal.org.

894

f

Physical Therapy

Volume 89

cause little evidence exists for the effectiveness of physical therapy for this patient population,20 physician beliefs in the value of physical therapy may yet explain variability in referral rates. The purpose of this study was to explore the influence of physician and practice characteristics on referral for physical therapy in patients with traumatic lower-extremity injury. This patient population was of particular interest because the physical disability resulting from these injuries often is significant and physical therapy has the potential to favorably affect the recovery process.21,22 Our primary hypothesis was that positive physician outcome expectations would be associated with an increased likelihood of referral for physical therapy, after controlling for physician attitude and practice characteristics. In addition, we hypothesized that negative outcome expectations would be associated with a decreased likelihood of referral. Regional differences in referral rates also were explored because the literature suggests that geographic location may account for differences in physician practice styles and health care delivery.5,23,24 The study’s findings have important implications not only for the management of patients with traumatic lower-extremity injury, but also for explaining the variation in physician referral rates for physical therapy.

Method Study Design A Web-based cross-sectional survey was distributed to orthopedic trauma surgeons from March to June of 2007. The sampling frame was a 777-person membership list maintained by the Orthopaedic Trauma Association (OTA). Participants were excluded if they were working outside the United States (15%), if they were research (2%) or health care profession (2%) members of OTA, if they were in residency (6%) or fel-

Number 9

lowship (9%) training, or if e-mail addresses were unavailable (5%). Exclusion criteria yielded a final population of 474 orthopedic trauma surgeons. Questionnaire Development and Content Case vignettes measured physical therapy referral as either “yes” or “no.” Surgeons were asked after each case “if they would refer this patient to any of the following providers.” These health care providers included a physical medicine and rehabilitation physician, an occupational therapist, a physical therapist, and a chiropractor. Surgeons also were provided with a no-referral category. Vignettes were constructed using an empirical model by Heverly et al25 in order to achieve sufficient referral variation. Each vignette was based on an actual patient with a femur, tibia, or ankle fracture treated by lower-extremity reconstruction that was abstracted from the Lower Extremity Assessment Project (LEAP) database.26,27 LEAP was a multicenter, prospective cohort study of 601 patients with severe lowerextremity trauma resulting in reconstruction or amputation. Sixteen case scenarios were reviewed and edited by 3 expert trauma surgeons. Eight vignettes were selected for the questionnaire based on the expectation of variability in physician referral for physical therapy. These vignettes included the following injuries: type IIIB tibia shaft fracture, type IIIA proximal tibia fracture, type IIIB tibia transverse fracture, type IIIB bicondylar plateau fracture of the tibia, type IIIA distal tibia extraarticular fracture, type IIIA metaphyseal distal articular tibia fracture, type IIIA talus fracture, and nondisplaced talar neck fracture. Three scales were included in the survey to measure physician outSeptember 2009

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury come expectations (positive and negative) and attitude toward physical therapy. The positive outcome expectations scale included 21 items that covered 4 broad categories of outcomes: (1) physical and motor (appropriate use of assistive devices, independent gait, decreased edema, prevention of contractures, increased endurance, and improved strength [force-generating capacity], range of motion (ROM), muscle tone [velocitydependent resistance to stretch], and balance); (2) pain (ability to manage pain, decreased acute pain, and prevention of chronic pain); (3) occupational (transition into part-time work, increased productivity and number of hours able to work, ability to meet physical demands of work, and return to full-time work); and (4) social and emotional (increased satisfaction with overall care, decreased self-perceived disability, and ability to manage physical and social/ emotional aspects of disability). Six of the items on assistive devices, muscle tone, endurance, contractures, and coping with the physical and social aspects of injury were derived from previous work by Campbell et al.17 The remaining items were selected based on a literature review on outcomes after traumatic injury and interviews with practicing trauma surgeons. The items for the negative outcome expectations scale were developed from open-ended interviews with trauma surgeons and consisted of the following 6 items: prolonged recovery, increased pain, increased medication use, inappropriate medical information, no improvement beyond what would occur with a home program, and no improvement beyond what would naturally occur. For both outcome expectations scales, surgeons were asked, “In what percentage of your patients with lowerextremity trauma will supervised physical therapy lead to the following outcomes?” Respondents were September 2009

given choices on a 6-point scale ranging from 0% (outcome would never occur) to 100% (outcome would always occur). The attitude scale consisted of 6 items: (1) physical therapists are useful to physicians in my specialty, (2) physical therapists are helpful as consultants in my practice, (3) physical therapists are competent to make decisions concerning patient care, (4) physical therapists play an important role in health care, (5) physical therapists are qualified to evaluate and treat as direct-access providers, and (6) physical therapists are capable of autonomous practice. Four of the items relating to the usefulness, competence, and importance of physical therapists were based on a General Favorability scale developed by Ritchey et al.2 Two of the items on physical therapists’ capability for autonomous practice were derived from open-ended interviews with trauma surgeons. Surgeons were asked to rate their general attitude toward physical therapy by agreeing or disagreeing with each item on the scale. Six response categories were provided, which ranged from “strongly disagree” to “strongly agree.” The last section of the questionnaire included demographic and practice questions predicated on prior surveys and a review of the health services research literature.2,18,28 –30 Questions gathered information on physician age, sex, board certification, fellowship training, years in practice, and practice type and trauma case workload. Additional questions were asked to examine financial interest in therapy practice, type and frequency of contact with physical therapists, and frequently requested treatment modalities. Surgeons also were asked what percentage of their physical therapy prescriptions were specific (frequency, duration, and treatment modalities), general (frequency and duration)

and open (evaluate and treat). Scales and demographic questions were reviewed and edited by 3 practicing trauma surgeons and one researcher with expertise in survey research. Procedure The survey with 8 case vignettes was pilot tested by 12 trauma surgeons and a random sample of 20 eligible OTA members. Five vignettes (Appendix) focusing on tibia or talus fractures were selected for inclusion in the final questionnaire. These vignettes were selected based on the variability in physician response (50%– 60% of physicians making a physical therapy referral). A pre-notice e-mail describing the purpose of the survey was sent to eligible OTA members, followed a few days later by a cover letter stating the goals and participants’ rights. Each cover letter contained a link to the Web-based survey. Follow-up e-mail reminders were sent to all nonresponders 7, 14, 24, and 45 days after initial contact. To protect the anonymity of each respondent, survey questionnaires were tracked by a Web-based system using randomly allocated numbers. Data Analysis Data analysis and interpretation of results were performed using Stata statistical software, version 9.0.* Descriptive techniques were used to determine the distribution of referral to health care providers for each vignette. The outcome of referral or no referral to a physical therapist then was abstracted for surgeons after each case vignette. Overall positive and negative physician outcome expectations scores were obtained by separately summing the ratings of 0% to 100% on the likelihood of 21 positive outcomes and 6 ratings of 1 to 6 for each item in the attitude scale. * Stata Corp, 4905 Lakeway Dr, College Station, TX 77845.

Volume 89

Number 9

Physical Therapy f

895

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury The internal consistency, construct validity, and factor structure of the 3 scales were explored with coefficient alpha (␣), scree plots, and principal components and factor analysis with varimax rotation.31 Bivariate and multivariate analyses included 1 positive outcome expectations scale and 2 negative outcome expectations and attitude scales derived from scree plots, principal components estimation, and factor analysis. Chi-square tests initially were used to investigate the association between the physical therapy referral/no-referral decision and physician sex, board certification, trauma fellowship, region of practice, practice location, type of practice, monthly trauma cases, frequency of communication and referral relationship with physical therapists, and financial interest in a physical therapist practice. Student t tests were used to investigate physician years in practice, positive outcome expectations scale, negative outcome expectations scales, and attitude scales. Bivariate mixed model logistic regression analyses then were conducted, which included a random intercept to account for the clustering of responses by physician. Covariates that were significant at P⬍.25 in bivariate analysis or considered relevant to the referral decision were entered into multivariate mixed-model forward and backward logistic regression models. The .25 level was used as a screening criterion to allow for the possibility that a collection of variables, each of which may be weakly associated with the outcome, may become important predictors when placed in a model together.32 Physician and practice factors were entered as a group, and likelihood ratio tests were conducted to remove the leastsignificant covariates. Models also were compared using goodness-of-fit tests, and multicollinearity was ex896

f

Physical Therapy

Volume 89

plored post-regression with the variance inflation factor. Interactions between age and years in practice, practice location and type of practice, and years in practice and monthly trauma cases were explored. Variables that were significant at P⬍.15 or with known clinical importance (communication with physical therapists) were retained. The stability of the final model was tested by adding back in each excluded variable one at a time. The level of significance was set at P⬍.05. Missing data for physician years in practice (1.1%), type of practice (2.2%), monthly trauma cases (3.3%), frequency of communication with physical therapists (1.8%), and financial interest in a physical therapist practice (1.8%) were handled using regression models that imputed the missing values as a function of the other covariates. Specifically, years in practice was imputed using a linear regression model that controlled for physician age, board certification, and attitude toward physical therapy, and trauma case workload was imputed based on practice location, trauma fellowship, and physician attitude. Missing values for type of practice were imputed as a function of practice location, trauma case volume, and financial ownership in a physical therapist practice. Missing values for frequency of communication were imputed as a function of physician years in practice, attitude toward physical therapy, and practice location.

Results Response Rate and Respondent Characteristics The response rate for eligible trauma surgeons was 58% (n⫽274). Demographic and professional characteristics and missing data are presented in Table 1. Overall, missing data were less than 4%. Responses were relatively well distributed across the 4

Number 9

geographic regions: 33.2% from the south, 24.9% from the west, 21.5% from the midwest, and 20.4% from the northeast. Eighty-eight percent of the surgeons were board certified, 65% had completed a fellowship in trauma, and the physicians had been in practice an average of 15 years (SD⫽9.0). Thirty-eight percent of the surgeons were seeing 40 or more trauma cases per month, and, on average, 71% of these cases were lower-extremity injuries. Seventy-three percent of the surgeons reported using specific prescriptions (frequency, duration, and treatment modalities) for referral for physical therapy, and 42.7% had a consistent referral relationship with a physical therapist practice. Only 12.4% reported having a financial interest in a physical therapist practice. The most frequently requested or expected physical therapy services for patients with traumatic lowerextremity injury were ROM exercises (95.1%), gait training (92.8%), joint mobilization (82.3%), and assistive device training (76.2%) (Tab. 2). The least-requested services were biofeedback (6.4%), electrical nerve stimulation (14%), and ultrasound diathermy (22.6%). Referral Rates The distribution of referral for each vignette is displayed in Table 3. The average physician referral rate for physical therapy based on the 5 case vignettes was 69.2%. Fewer than 1% of surgeons referred patients to an occupational therapist, and 2.8% of surgeons referred patients to a physical medicine and rehabilitation specialist. No statistical differences were found in vignette physical therapy referral rates across geographic regions.

September 2009

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury Positive Outcome Expectations of Physical Therapy On average, surgeons reported that 57.6% (SD⫽17%) of their patients with traumatic lower-extremity injury would have a positive outcome from physical therapy. The highest physical therapy expectations were for the appropriate use of assistive devices (80.7%) and improved strength (76.4%) and ROM (75.7%) (Tab. 4). The lowest outcome expectation of physical therapy was the prevention of chronic pain (34.4%). Overall, physicians reported that 35.9% of their patients would have improvements in pain (acute and chronic), 44.1% would have a greater ability to cope with the emotional aspects of disability, and 51.4% would have a reduction in workplace limitations through supervised physical therapy. Negative Outcome Expectations of Physical Therapy On average, surgeons reported that 24.2% (SD⫽13%) of their patients with traumatic lower-extremity injury would have a negative outcome from physical therapy. Surgeons believed that 32.6% of their patients referred for physical therapy would have no improvement beyond what would occur with a surgeon-directed home exercise program and that 27.2% of their patients referred for physical therapy would have no improvement beyond what would naturally occur (Tab. 4). Surgeons also reported that inappropriate medical information would be transmitted to 27.5% of their patients by physical therapists. Relatively few surgeons reported that patients would experience prolonged recovery (12%) following supervised physical therapy. Attitude Toward Physical Therapy The overall average of the summed attitude scores was 3.5 (SD⫽0.85) out of a maximum possible score of 6. Table 5 presents the average score September 2009

Table 1. Distribution of Respondents by Demographics, Training, and Practice Characteristics (n⫽274) Characteristic

Value

Mean age, y (SD)

47.5 (9.0)

Missing: 4 Sex, n (%) Female

17 (6.2)

Male

257 (93.8)

Board certified, n (%) No

32 (11.7)

Yes

242 (88.3)

Trauma fellowship, n (%) No

93 (33.9)

Yes

178 (65.0)

Missing

3 (1.1)

Mean years in practice (SD)

15.0 (9.0)

Missing: 3 Region of practice, n (%) South

91 (33.2)

West

68 (25.0)

Midwest

59 (21.5)

Northeast

56 (20.4)

Practice location, n (%) Inner city

157 (57.3)

Suburb

84 (30.7)

Rural

28 (10.2)

Missing

5 (1.8)

Type of practice, n (%) Academic setting

124 (45.3)

Group

79 (28.8)

Hospital-based

54 (19.7)

Solo

11 (4.0)

Missing

6 (2.2)

Monthly trauma cases, n (%) 0–10

37 (13.5)

11–20

61 (22.3)

21–40

86 (31.4)

41⫹

81 (29.5)

Missing

9 (3.3)

Mean % of monthly trauma cases that are lower extremity (SD)

71.0 (17.8)

Missing: 9 (continued)

Volume 89

Number 9

Physical Therapy f

897

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury Table 1. Continued Characteristic

Value

Type of physical therapy prescription, n (%) Specific (frequency, duration, treatment modalities)

201 (73.4)

General (frequency and duration)

39 (14.2)

Open (evaluate and treat)

24 (8.8)

Missing

10 (3.6)

Communicate with physical therapists, n (%) Never

19 (6.9)

Monthly

86 (31.4)

Weekly

127 (46.4)

Daily

37 (13.5)

Missing

5 (1.8)

Type of communication, n (%)a Notes (including prescription)

235 (85.8)

Telephone

153 (55.8)

Conversation in clinic

86 (31.4)

Rounds

74 (27.0)

E-mail

61 (22.3)

Meeting

20 (7.3)

Missing

5 (1.8)

Consistent referral to specific therapist, n (%) No

149 (54.4)

Yes

117 (42.7)

Missing

8 (2.9)

Financial interest in physical therapist practice, n (%) No

232 (84.7)

Yes

34 (12.4)

Missing

8 (2.9)

Mean positive outcome expectations score (SD)

57.6 (17)

Mean negative outcome expectations score (SD)

24.2 (13)

Mean attitude score (SD)

3.5 (0.85)

a

Percentages total more than 100% because some respondents reported more than one type of communication.

for each item in the physician attitude scale. Physicians agreed that physical therapists are useful to their practice (average score⫽5.2) and play an important role in health care (average score⫽4.8), but they were somewhat unsure of physical therapists’ ability to provide help as a consultant (average score⫽3.7) and make decisions about patient care (average score⫽3.2). Most physi898

f

Physical Therapy

within the positive outcome expectations scale with an eigenvalue of 11.6. This factor explained more than 55% of the variance in the items. Factor loadings for all items were greater than 0.60. One positive outcome expectations score was calculated for each surgeon by summing all of the 21 positive outcome expectations items. This score was used in the bivariate and multivariate analyses and retained in the final multivariate model. Coefficient ␣ for the one factor positive outcome expectations scale was .96.

Volume 89

cians disagreed with the statements that physical therapists are qualified to act as direct-access providers (average score⫽2.0) and are capable of autonomous practice (average score⫽2.1). Scree Plot, Principal Components and Factor Analysis Principal components analysis and a screen plot demonstrated one factor

Number 9

For the negative outcome expectations scale, principal components analysis and a scree plot demonstrated 2 factors with eigenvalues of 2.8 and 1.4, respectively. Factor 1 explained 47% of the variance in the items, and factor 2 explained 23% of the variance in the items. Factor loadings indicated that factor 1 consisted of 3 items (ie, no improvement beyond what would naturally occur, no improvement beyond what would occur with a home program, and provide inappropriate medical information) and that factor 2 consisted of 3 items (ie, increased pain, increased medication use, and prolonged recovery). Factor loadings for all items were greater than 0.40. Two negative outcome expectations scores were obtained for each surgeon by summing the 3 items corresponding to factor 1 and the 3 items corresponding to factor 2. The alpha coefficient for the factor 1 scale of no improvement and inappropriate information was .77 and the alpha coefficient for the factor 2 scale of increased pain and medication use and prolonged recovery was .74. Both of the negative outcome expectations scores were used in the bivariate and multivariate analyses, but only the factor 1 (no improvement and inappropriate information) scale was retained in the final multivariate model.

September 2009

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury Table 2. Description of Requested Physical Therapy Services for Patients With Traumatic Lower-Extremity Injury (n⫽265) n (%)a

Treatment Modality Range-of-motion exercise

252 (95.1)

Gait training

246 (92.8)

Joint mobilization

218 (82.3)

Crutch or cane training

202 (76.2)

Therapeutic exercise (including strength training)

177 (66.8)

Balance training

175 (66.0)

Soft tissue mobilization

150 (56.6)

Proprioceptive neuromuscular reeducation

101 (38.1)

Ultrasound diathermy

60 (22.6)

Electrical nerve stimulation

37 (14.0)

Biofeedback

17 (6.4)

a

Percentages total more than 100% because respondents reported more than one type of treatment modality.

Principal components analysis and a scree plot demonstrated 2 factors within the attitude scale with eigenvalues of 2.9 and 1.3, respectively. Factor 1 explained 48% of the variance in the items, and factor 2 explained 22% of the variance in the items. Factor loadings indicated that factor 1 consisted of 3 items (ie, physical therapists are useful to physicians in my specialty, physical therapists play an important role in health care, and physical therapists are helpful as consultants in my practice) and that factor 2 consisted of 3 items (ie, physical therapists are qualified to evaluate and treat as direct-access providers, physical therapists are capable of autonomous practice, and physical therapists are

competent to make decisions concerning patient care). Factor loadings for all items were greater than 0.50. Two attitude scores were obtained for each surgeon by summing the 3 items corresponding to factor 1 and the 3 items corresponding to factor 2. The alpha coefficient for the factor 1 scale of general attitude was .81, and the alpha coefficient for the factor 2 scale of attitude toward autonomous practice was .74. Both of the attitude scores were used in the bivariate and multivariate analyses, but only the factor 1 (general attitude) scale was retained in the final model.

Factors Associated With Physical Therapy Referral The final multivariate model included the following variables: positive outcome expectations scale, no improvement and inappropriate information scale, general attitude scale, years in practice, type of practice, monthly trauma cases, frequency of communication with physical therapists, and financial interest in a physical therapist practice. Results from this multivariate model are presented in Table 6. Positive outcome expectations had the largest effect on surgeon referral for physical therapy. Specifically, a 20% increase in positive outcome expectations was associated with a 2.7 increase in the likelihood of referral for physical therapy (P⬍.001). Negative outcome expectations in relation to no improvement and providing inappropriate medical information displayed a statistically significant negative effect on referral (odds ratio⫽0.66, P⫽.01). Surgeon attitude toward physical therapy was not statistically associated with referral (general attitude: odds ratio⫽0.83, P⫽.12). Physician years in practice and spending greater than 70% of their time in a solo practice were negatively associated with referral for physical therapy (P⬍.05). Monthly trauma volume of 40 or more cases exhibited a statistically significant positive association with physical therapy referral (odds ratio⫽1.7,

Table 3. Distribution of Orthopedic Surgeon Referral to Health Care Providers by Case Vignette (n⫽274)

a

Vignette

Physical Therapist n (%)

Occupational Therapist n (%)

PM&Ra Physician n (%)

Chiropractor n (%)

No Referral n (%)

1

151 (55.1)

3 (1.1)

8 (2.9)

0 (0.0)

112 (40.9)

2

207 (75.5)

3 (1.1)

9 (3.3)

0 (0.0)

55 (20.1)

3

190 (69.3)

0 (0)

8 (2.9)

0 (0.0)

76 (27.7)

4

190 (69.3)

1 (0.4)

3 (1.1)

0 (0.0)

80 (29.2)

5

211 (77.0)

2 (0.7)

11 (4.0)

0 (0.0)

50 (18.3)

PM&R⫽physical medicine and rehabilitation.

September 2009

Volume 89

Number 9

Physical Therapy f

899

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury Table 4. Physicians’ Outcome Expectations of Supervised Physical Therapy for the Treatment of Patients With Traumatic Lower-Extremity Injury (n⫽274) Average % of Patients With Outcomea

Expected Outcome Positive: physical and motor Appropriate use of assistive devices

80.7

Improved strength

76.4

Improved range of motion

75.7

Improved muscle tone

72.4

Independent gait

72.3

Increased endurance for physical activity

72.2

Improved balance and coordination

72.0

Prevention of contractures

61.0

Decreased edema

49.3

Positive: pain Ability to manage pain

36.8

Decreased acute pain

36.5

Prevention of chronic pain

34.4

Positive: occupational Transition into part-time work

51.7

Increased productivity at work

47.5

Increased number of hours able to work

49.6

Ability to meet physical demands of work

55.4

Return to full-time work

53.0

Positive: social and emotional Increased satisfaction with overall care

66.7

Ability to manage physical aspects of disability

58.3

Decreased self-perceived disability

46.3

Ability to cope with social or emotional aspects

41.9

Negative No improvement beyond what would occur with home exercise program

32.6

Inappropriate medical information

27.5

No improvement beyond what would naturally occur

27.2

Increased pain

23.6

Increased medication use

22.0

Prolonged recovery

12.0

a

Scores range from 0% to 100%, with a score of 0% indicating outcome would never occur and a score of 100% indicating outcome would occur in 100% of patients.

P⫽.02), whereas financial interest in a physical therapist practice showed only a moderate effect (odds ratio⫽ 1.7, P⫽.09).

Discussion Positive physician outcome expectations exhibited a significant effect on 900

f

Physical Therapy

Volume 89

referral of patients with traumatic lower-extremity injury for physical therapy, but only one of the negative outcome expectations scales significantly decreased the likelihood of referral. These findings suggest that surgeon referral rates can be in-

Number 9

creased with a better understanding of the positive effects of physical therapy. In addition, health care providers wanting to influence the practice of physical therapy referral may want to focus on educating surgeons about the information provided to patients during physical therapy treatment and on evidence supporting the efficacy of supervised physical therapy compared with standard care and independent home exercise programs. Surgeons appear to be referring patients for physical therapy based on the expectation of improvement in physical and motor outcomes. This conclusion is further supported by the distribution of frequently requested physical therapy services; greater than 60% of surgeons reported requesting treatment modalities consistent with ROM, gait, assistive device, strength, and balance outcomes. The findings, however, indicate that surgeons may not be considering physical therapy for pain relief, improvement in psychosocial aspects of recovery, and return to work. Future research might consider the effect of physical therapy on these outcomes, especially because high levels of chronic pain and psychological distress and poor return to work rates have been found among patients with traumatic lower-extremity injury.33–35 Furthermore, understanding how surgeons are currently addressing pain and psychosocial and occupational concerns has the potential to improve patient management throughout the recovery process. For negative outcome expectations, the findings provide insight into surgeons’ ambivalence toward physical therapy referral and provide direction for clinical research. Some surgeons may not be referring patients for physical therapy based on beliefs that patients will have increased pain and medication use and a proSeptember 2009

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury longed recovery. However, referral of patients with traumatic lowerextremity injury for physical therapy appears to be particularly affected by surgeons’ concerns over the provision of inappropriate medical information to patients. Qualitative findings suggest that this concern is specifically directed toward information on bone and soft tissue healing, surgical procedures, postsurgical contraindications and precautions, and recovery time. Furthermore, based on the finding that 20% of responding surgeons believe that more than 60% of their patients would have no improvement with physical therapy beyond what would occur with a home exercise program, surgeons may have a preference for physiciandirected rehabilitation over supervised physical therapy. Researchers looking at the efficacy of physical therapy for patients with traumatic injuries might consider comparing supervised rehabilitation with both usual medical care and the most commonly used physician-directed home exercise programs. Our study also showed significant associations between referral frequency and monthly trauma case volume, solo practice, and physician years in practice. The positive association with trauma case volume confirms the results of a study conducted by Kerssens and Groenewegen3 showing that physicians who frequently referred patients to physical therapists had busier practices. The negative association with solo practice supports the results from studies examining physician referral to specialists.28,36 However, in contrast to our findings, studies on physician referral to specialists have demonstrated a positive association between years in practice and referral.29,36,37 The negative relationship found in the current study could be attributed to a difference in training based on year of medical school graduation or possibly to moreSeptember 2009

Table 5. Average Score for Physicians’ Attitudes Toward Physical Therapists (n⫽274) Average Scorea

Item Physical therapists are useful to physicians in my specialty

5.2

Physical therapists play an important role in health care

4.8

Physical therapists are helpful as consultants in my practice

3.7

Physical therapists are competent to make decisions concerning patient care

3.2

Physical therapists are qualified to evaluate and treat as a direct-access provider

2.0

Physical therapists are capable of autonomous practice

2.1

a

Scores range from 1 to 6, with a score of 1 indicating strong disagreement with statement and a score of 6 indicating strong agreement with statement.

experienced surgeons feeling more comfortable overseeing a homebased exercise program. We did not find an association between referral and physician sex or practice location (rural versus urban), which is inconsistent with prior research on referral to specialists. Studies have shown that female

physicians and physicians practicing in larger communities have higher referral rates.29,38,39 Researchers suggest that specialist supply and differences in local medical culture may explain the influence of practice type on referral. In addition, an influence of geographic location on referral for physical therapy was not supported by our findings, and financial

Table 6. Multivariate Random-Effects Logistic Regression Model of Orthopedic Surgeon Referral for Physical Therapy (n⫽274)a Variable Positive physician outcome expectations scale

b

Negative physician outcome expectations scale: no improvement/ inappropriate medical informationb

OR (95% CI)

P

2.7 (1.9–3.7)

⬍.001

0.66 (0.50–0.88)

.01

Physician attitude scale: general attitudec

0.83 (0.66–1.1)

.12

Physician years in practice

0.97 (0.95–0.99)

.01

1.0 (0.62–1.7)

.98

Group practice (reference) Academic practice Hospital practice

1.2 (0.65–2.3)

Solo practice

0.16 (0.06–0.46)

.66 ⬍.01

No financial interest in physical therapist practice (reference) Financial interest in physical therapist practice

1.7 (0.87–3.1)

.09

1.7 (1.1–2.7)

.02

0.87 (0.45–1.7)

.69

Monthly communication with physical therapists

0.88 (0.44–1.9)

.73

No communication with physical therapists

0.51 (0.19–1.3)

.17

⬍40 trauma cases per month (reference) ⱖ40 trauma cases per month Daily communication with physical therapists (reference) Weekly communication with physical therapists

a

OR⫽odds ratio, CI⫽confidence interval. Scores range from 0% to 100%, with a score of 0% indicating outcome would never occur and a score of 100% indicating outcome would occur in 100% of patients. c Scores range from 1 to 6, with a score of 1 indicating strong disagreement with statement and a score of 6 indicating strong agreement with statement. b

Volume 89

Number 9

Physical Therapy f

901

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury interest in a physical therapist practice had only a moderate effect on referral. To our knowledge, this is the first study to systematically examine the relationship between financial interest in a physical therapist practice and referral. Because only 12% of the responding surgeons reported a financial interest in a physical therapist practice, additional work is needed to further explore this association. We also did not find increased communication, a close physiciantherapist relationship, or a positive attitude to be associated with patterns of physical therapy referral. These findings have important implications because the referral literature suggests that improving communication between physicians and physical therapists and physician attitude toward physical therapy may positively affect physical therapy referral rates.3,7,11–13 Although the results of our study do not support this hypothesis, it is important to recognize that these findings are in the context of treatment of patients with high-energy lower-extremity trauma. In the context of conditions more commonly treated by physical therapists, such as back pain or arthritis, the results may vary. Further study into the effects of communication and cooperation on the appropriateness of physical therapy referral is warranted. An interesting finding is the relatively low referral rate to occupational therapists and physical medicine and rehabilitation physicians compared with physical therapists. Less than 1% of the responding surgeons, on average, referred patients to occupational therapists, and less than 3% of the surgeons referred patients to physical medicine and rehabilitation physicians, whereas 69% of the surgeons referred patients to physical therapists. This distribution may be related to sur902

f

Physical Therapy

Volume 89

geons focusing more on lowerextremity ROM, strength, and gait after traumatic injury than on activities of daily living, which are under the purview of occupational therapists. The low referral rate to physical medicine and rehabilitation physicians is more difficult to explain and slightly surprising. An explanation may be that this specialty is less well understood among orthopedic trauma surgeons or possibly that surgeons rely on primary care physicians to recognize the need for this type of referral after patients are discharged from the hospital. Researchers might want to consider examining the use of physical medicine and rehabilitation physicians prior to hospital discharge and throughout the recovery period and, if underutilized for patients with traumatic lowerextremity injury, explore the possible contribution these physicians might have to long-term outcomes. Study Limitations Several limitations in our study warrant consideration. The main limitation stems from the survey design, which presented physicians with case vignettes. Patient scenarios are different from actual clinical encounters in several ways: they contain only a small portion of the information usually available to physicians, information is presented simultaneously instead of sequentially as in the medical setting, and they are unable to capture the physician-patient interaction. In addition, listing physical therapy as a referral option may have led physicians to indicate a referral decision they otherwise might not have made in the clinical environment. Even though vignettes are affordable and a valuable tool for representing the behavior of a group of physicians,40 – 42 we acknowledge there is some degree of uncertainty about the validity of our referral outcome.

Number 9

Another limitation is our survey’s convenience sample of orthopedic surgeons. Thus, our findings may not be generalizable to all orthopedic surgeons responsible for treating patients with traumatic lower-extremity injury. The sample, however, is likely representative of the surgeons who are treating the majority of the high-energy lowerextremity trauma—the condition described in the vignettes. Furthermore, even though our response rate of 58% was high relative to that of other physician surveys,43– 45 no information was available on nonrespondent demographics. As a result, we are unable to accurately assess the systematic differences between respondents and nonrespondents and appropriately acknowledge the potential bias of our findings.

Conclusions We recommend that efforts to influence the physical therapy referral process for patients with traumatic lower-extremity injury focus on surgeons’ beliefs about the positive outcomes of physical therapy. The results suggest that orthopedic trauma surgeons refer patients for physical therapy based mostly on expectations for improvement in physical and motor outcomes and that surgeons may not be considering physical therapy for pain relief, psychosocial aspects of recovery, and return to work. Furthermore, low referral rates may be attributed to a preference for surgeon-directed home-based rehabilitation and to the belief that physical therapists are providing inappropriate medical information to patients. Future research should consider the efficacy of physical therapy for pain and for psychosocial and occupational outcomes and should explore the differences between supervised physical therapy and the most commonly utilized physician-directed home exercise programs.

September 2009

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury Dr Archer, Dr MacKenzie, Dr Bosse, and Dr Riley provided concept/idea/research design. Dr Archer, Dr Bosse, Dr Pollak, and Dr Riley provided writing. Dr Bosse provided data collection. Dr Archer, Dr MacKenzie, Dr Bosse, and Dr Pollak provided data analysis. Dr MacKenzie provided fund procurement and institutional liaisons. Dr Archer, Dr Pollak, and Dr Riley provided consultation (including review of manuscript before submission). The authors thank Marc F. Swiontkowski, MD, and Elizabeth Ann Skinner, MSW, for their help with the case vignettes and the design of the survey. They also thank Suzann K. Campbell, PT, PhD, FAPTA, Peter Franks, MD, and Ferris J. Ritchey, PhD, for sharing their questionnaires and Christopher B. Forrest, MD, PhD, and Barbara S. Webster, PT, BSPT, PA-C, for providing valuable insight into physician referral and survey research. Finally, they thank the Orthopaedic Trauma Association for providing their membership list and supporting the survey design. The manuscript was developed from a series of 3 papers submitted as a dissertation to the Johns Hopkins University Bloomberg School of Public Health. Study protocols and materials were approved by the Johns Hopkins University Bloomberg School of Public Health’s Committee on Human Research. A platform presentation of this research was given at the Joint American Congress of Rehabilitation Medicine/ASNR Educational Conference; October 16, 2008; Toronto, Ontario, Canada. The research was supported with funds from the NIOSH Education and Research Center for Occupational Safety and Health at the Johns Hopkins Bloomberg School of Public Health (#T42OH00842428). This article was received October 7, 2008, and was accepted April 22, 2009. DOI: 10.2522/ptj.20080321

References 1 Freburger JK, Holmes GM, Carey TS. Physician referrals to physical therapy for the treatment of musculoskeletal conditions. Arch Phys Med Rehabil. 2003;84: 1839 –1849. 2 Ritchey FJ, Inkston D, Goldbaum JE, Heerten ME. Perceptual correlates of physician referral to physical therapy for role expansion. Soc Sci Med. 1989;28:69 – 80. 3 Kerssens JJ, Groenewegen PP. Referrals to physiotherapy: the relation between the number of referrals, the indication for referral, and the inclination to refer. Soc Sci Med. 1990;30:797– 804.

September 2009

4 Ward WM, Williams BT, Dixon RA. Physiotherapy: its prescription and implementation for orthopedic out-patients. Rheumatol Rehabil. 1978;17:14 –22. 5 Freburger JK, Carey TS, Holmes GM. Physician referrals to physical therapists for the treatment of spine disorders. Spine J. 2005;5:530 –541. 6 Pless BI, Satterwhite B, Van Vechten D. Chronic illness in childhood: a regional survey of care. Pediatrics. 1976;58:37– 46. 7 Jorgensen CK, Olesen F. Predictors for referral to physiotherapy from general practice. Scand J Prim Health Care. 2001;19: 48 –53. 8 Ehrmann-Feldman D, Rossignol M, et al. Physician referral to physical therapy in a cohort of workers compensated for low back pain. Phys Ther. 1996;76:150 –157. 9 Akpala CO, Curran AP. Physiotherapy in general practice: patterns of utilisation. Pub Health. 1988;102:263–268. 10 Carter RH, Densley JA, Galley CM, et al. Factors associated with GP referrals to physiotherapy. British Journal of Therapy and Rehabilitation. 2001;8:454 – 459. 11 Clemence ML, Seamark DA. GP referral for physiotherapy to musculoskeletal conditions: a qualitative study. Fam Pract. 2003; 20:578 –582. 12 Uili RM, Shepard KF, Savinar E. Physician knowledge and utilization of physical therapy procedures. Phys Ther. 1984;64: 1523–1529. 13 Stanton PE, Fox FK, Frangos KM, et al. Assessment of resident physicians’ knowledge of physical therapy. Phys Ther. 1985; 65:27–30. 14 Campbell SK, Anderson JC, Gardner HG. Use of survey research methods to study clinical decision making: referral to physical therapy of children with cerebral palsy. Phys Ther. 1989;69:610 – 615. 15 Campbell SK, Gardner HG, Ramakrishnan V. Correlates of physicians’ decisions to refer children with cerebral palsy for physical therapy. Dev Med Child Neurol. 1995; 37:1062–1074. 16 Campbell SK. Efficacy of physical therapy in improving postural control in children with cerebral palsy. Pediatr Phys Ther. 1990;2:135–140. 17 Campbell SK, Anderson JC, Gardner HG. Physicians’ beliefs in the efficacy of physical therapy in the management of cerebral palsy. Pediatr Phys Ther. 1990;2: 169 –173. 18 Goodman JF, Cecil HS. Referral practices and attitudes of pediatricians toward young mentally retarded children. J Dev Behav Pediatr. 1987;8:97–105. 19 Elstein AS, Holzman GB, Ravitch MM. Comparison of physicians’ decisions regarding estrogen replacement therapy for menopausal women and decisions derived from a decision analytic model. In: Dowie J, Elstein A, eds. Professional Judgment: A Reader in Clinical Decision Making. New York, NY: Cambridge University Press, 1988:298 –322.

20 Castillo RC, MacKenzie EJ, Archer KR, et al. Evidence of beneficial effect of physical therapy after lower-extremity trauma. Arch Phys Med Rehabil. 2008;89:1873– 1879. 21 Rice DP, MacKenzie EJ, and Associates. Cost of Injury in the United States: A Report to Congress. San Francisco, CA: Institute for Health and Aging, University of California, and Injury Prevention Center, The Johns Hopkins University; 1989. 22 Dillingam TR, Pezzin LE, MacKenzie EJ. Incidence, acute care length of stay, and discharge to rehabilitation of traumatic amputee patients: an epidemiologic study. Arch Phys Med Rehabil. 1998;79: 279 –287. 23 Wennberg J, Gittelsohn A. Variations in medical care among small areas. Sci Am. 1982;246:120 –134. 24 Wennberg DE. Variation in the delivery of health care: the stakes are high. Ann Intern Med. 1998;128:866 – 868. 25 Heverly MA, Fitt DX, Newman FL. Constructing case vignettes for evaluating clinical judgment: an empirical model. Eval Prog Plan. 1984;7:45–55. 26 Bosse MJ, MacKenzie EJ, Kellam JF, et al. An analysis of outcomes of reconstruction or amputation after leg-threatening injuries. N Engl J Med. 2002;347:1924 –1931. 27 MacKenzie EJ, Bosse MJ, Kellam JF, et al. Characterization of patients with highenergy lower extremity trauma. J Orthop Trauma. 2000;14:455– 466. 28 Forrest CB, Nutting PA, van Schrader S, et al. Primary care physician specialty referral decision making: patient, physician, and health care system determinants. Med Decis Making. 2006;26:76 – 85. 29 Franks P, Williams GC, Zwanziger J, et al. Why do physicians vary so widely in their referral rates? J Gen Intern Med. 2000;15: 163–168. 30 Forrest CB, Nutting PA, Starfield B, von Schrader S. Family physicians’ referral decisions: results from the ASPN referral study. J Fam Pract. 2002;51:215–222. 31 Netemeyer RG, Bearden WO, Sharma S. Scaling Procedures. Thousand Oaks, CA: Sage Publications; 2003. 32 Hosmer DW, Lemeshow S. Applied Logistic Regression. New York, NY: John Wiley & Sons Inc; 2000. 33 Castillo RC, MacKenzie EJ, Wegener ST, Bosse MJ. Prevalence of chronic pain seven years following limb threatening lower extremity trauma. Pain. 2006;124: 321–329. 34 MacKenzie EJ, Bosse MJ, Kellam JF, et al. Early predictors of long-term work disability after major limb trauma. J Trauma. 2006;61:688 – 694. 35 McCarthy ML, MacKenzie EJ, Edwin D, et al. Psychological distress associated with severe lower-limb injury. J Bone Joint Surg Am. 2003;85:1689 –1697. 36 Franks P, Clancy CM. Referrals of adult patients from primary care: demographic disparities and their relationship to HMO insurance. J Fam Pract. 1997;45:47–53.

Volume 89

Number 9

Physical Therapy f

903

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury 37 Bachman KH, Freeborn DK. HMO physicians’ use of referrals. Soc Sci Med. 1999; 8:547–557. 38 Iversen GD, Coleridge ST, Fulda KG, Licciardone JC. What factors influence a family physician’s decision to refer a patient to a specialist? Rural Remote Health. 2005; 5:413– 419. 39 Chan B, Austin P. Patient, physician and community factors affecting referrals to specialists in Ontario, Canada: a populationbased multi-level modeling approach. Med Care. 2003;41:500 –511.

40 Veloski J, Tai S, Evans AS, Nash DB. Clinical vignette-based surveys: a tool for assessing physician practice variation. Am J Med Qual. 2005;20:151–157. 41 Carey TS, Garrett J. Patterns of ordering diagnostic tests for patients with acute low back pain. Ann Intern Med. 1996;125: 807– 814. 42 Peabody JW, Luck J, Glassman P, et al. Measuring the quality of physician practice by using clinical vignettes: a prospective validation study. Ann Intern Med. 2004;141:771–780.

43 Cummings SM, Savitz LA, Konrad TR. Reported response rates to mailed physician questionnaires. Health Serv Res. 2001;35: 1347–1355. 44 Kellerman SE, Herold J. Physician response to surveys: a review of the literature. Am J Prev Med. 2001;20:61– 67. 45 Asch DA, Jedrziewski MK, Christakis NA. Response rates to mail surveys published in medical journals. J Clin Epidemiol. 1997;50:1129 –1136.

Appendix. Case Vignettes

Case A: Jim Jim, age 28 years, sustained a type IIIB tibia shaft fracture as a result of a motorcycle accident 8 weeks ago. ⬃ The tibia fracture was treated with a locked nail. ⬃ The soft-tissue defect was covered with a rectus muscle free flap. The flap is well healed without drainage, and there is no evidence of infection. Residual edema is mild. ⬃ Bilateral hip and knee range of motion is normal. ⬃ Involved ankle dorsiflexion and plantar flexion and subtalar motion are mildly limited. ⬃ The patient is currently weight bearing as tolerated. He is using axillary crutches for ambulation and is independent with transfers and gait. You have instructed him to increase his weight bearing to 22.68 kg (50 lb). There is a possibility that the patient will need further surgery for a bone graft.

Case B: Ralph Ralph, age 33 years, sustained a type IIIB bicondylar plateau fracture of the tibia as a result of a motorcycle accident 12 weeks ago. Extensive degloving was present. ⬃ The tibia fracture was stabilized with dual plating. ⬃ The soft-tissue defect was covered with a medial gastrocnemius muscle flap. Residual edema is mild, and there is no wound drainage. Current radiographs show early healing. ⬃ Patient is partially weight bearing and uses axillary crutches for ambulation. ⬃ He is completely independent with transfers and moderately independent with gait. ⬃ Involved knee flexion range of motion is 95 degrees. ⬃ Involved ankle dorsiflexion is 10 degrees, and plantar flexion is 30 degrees.

Case C: Paul Paul, age 31 years, sustained a nondisplaced talar neck fracture as a result of a motorcycle crash 12 weeks ago. The right calcaneus, cuboid, and cuneiform were fractured. ⬃ The foot fractures were all treated with open reduction internal fixation after initial treatment with an external fixation. Physical examination reveals no wound drainage, normal fracture alignment, and moderate edema. (Continued) 904

f

Physical Therapy

Volume 89

Number 9

September 2009

Surgeon Referral for Physical Therapy in Patients With Traumatic Lower-Extremity Injury Appendix. Continued

⬃ Patient is non–weight bearing. ⬃ He requires axillary crutches for ambulation, but is completely independent with all transfers and gait. ⬃ Bilateral hip and knee range of motion is within normal limits. ⬃ Involved ankle dorsiflexion is 5 degrees, plantar flexion is 20 degrees, and there is less than 50% of subtalar motion.

Case D: Peter Peter, age 28 years, sustained an open type IIIA pilon fracture, with a wound greater than 5 cm, and considerable muscle injury as a result of a motorcycle accident 12 weeks ago. ⬃ The tibia fracture was stabilized with a plate. ⬃ The wound was treated with a delayed primary closure. ⬃ Patient was treated on an outpatient basis for a wound infection several weeks ago. A clinical examination reveals mild edema and no wound drainage. You do not anticipate any additional surgery at this time. ⬃ The patient is fully weight bearing and ambulates independently with axillary crutches. ⬃ Involved knee flexion is 100 degrees. ⬃ Involved ankle dorsiflexion is 5 degrees, and plantar flexion is 20 degrees.

Case E: Robert Robert, age 33 years, sustained a type IIIA talus fracture as a result of a motor vehicle accident 12 weeks ago. The talar body and talonavicular joint were displaced. The fracture was treated with an internal fixation. Anteroposterior and lateral weight-bearing radiographs of the foot reveal good fracture alignment and progressive bone healing. There is no evidence of wound drainage, and the soft tissue coverage is stable. ⬃ The patient is non–weight bearing and uses a walker for ambulation. ⬃ He is independent with transfers and moderately independent with ambulation. ⬃ Involved knee flexion is 0 to 90 degrees. ⬃ Involved ankle dorsiflexion is 0 degrees, and plantar flexion is 40 degrees.

September 2009

Volume 89

Number 9

Physical Therapy f

905

Research Report

Adhesive Capsulitis: Establishing Consensus on Clinical Identifiers for Stage 1 Using the Delphi Technique Sarah Walmsley, Darren A. Rivett, Peter G. Osmotherly S. Walmsley, BSc, GradDipPhty, MAppSc(Ortho Phty), is a PhD candidate, School of Health Sciences, Faculty of Health, The University of Newcastle, University Drive, Callaghan, New South Wales 2308, Australia. Address all correspondence to Ms Walmsley at: [email protected]. D.A. Rivett, BAppSc(Phty), GradDipManipTher, MAppSc(Manip Phty), PhD, is Professor and Head, School of Health Sciences, Faculty of Health, The University of Newcastle. P.G. Osmotherly, BSc, GradDipPhty, MMedSc (Clin Epi), is Lecturer, Discipline of Physiotherapy, School of Health Sciences, Faculty of Health, The University of Newcastle. [Walmsley S, Rivett DA, Osmotherly PG. Adhesive capsulitis: establishing consensus on clinical identifiers for stage 1 using the Delphi technique. Phys Ther. 2009;89: 906 –917.] © 2009 American Physical Therapy Association

Background. Adhesive capsulitis often is difficult to diagnose in its early stage and to differentiate from other commonly seen shoulder disorders with the potential to cause pain and limited range of movement. Objectives. The purpose of this study was to establish consensus among a group of experts regarding the clinical identifiers for the first or early stage of primary (idiopathic) adhesive capsulitis.

Design. A correspondence-based Delphi technique was used in this study. Methods. Three sequential questionnaires, each building on the results of the previous round, were used to establish consensus.

Results. A total of 70 experts from Australia and New Zealand involved in the diagnosis and treatment of adhesive capsulitis completed the 3 rounds of questionnaires. Following round 3, descriptive statistics were used to screen the data into a meaningful subset. Cronbach alpha and factor analysis then were used to determine agreement among the experts. Consensus was achieved on 8 clinical identifiers. These identifiers clustered into 2 discrete domains of pain and movement. For pain, the clinical identifiers were a strong component of night pain, pain with rapid or unguarded movement, discomfort lying on the affected shoulder, and pain easily aggravated by movement. For movement, the clinical identifiers included a global loss of active and passive range of movement, with pain at the end-range in all directions. Onset of the disorder was at greater than 35 years of age.

Conclusions. This is the first study to use the Delphi technique to establish clinical identifiers indicative of the early stage of primary (idiopathic) adhesive capsulitis. Although limited in differential diagnostic ability, these identifiers may assist the clinician in recognizing early-stage adhesive capsulitis and may inform management, as well as facilitate future research.


f

Physical Therapy

Volume 89

Number 9

September 2009

Clinical Identifiers for Adhesive Capsulitis

A

dhesive capsulitis of the shoulder is a disorder frequently encountered by primary health care professionals. It often is difficult to identify and correctly diagnose in its early stage. Labeled “frozen shoulder” by Codman in 19341 but subsequently termed “adhesive capsulitis” by Neviaser2 to better describe the pathology, this condition generally is characterized by pain and a gradual progressive loss of shoulder active and passive range of motion.3 It has been reported that its prevalence is 2% to 3% in the general population.3–5 This figure is higher in the diabetic population,6 with a prevalence of 30% reported in patients with type 2 diabetes mellitus.7 Adhesive capulitis also is reported to be more common in women, especially between the ages of 40 to 60 years.3,5,8,9 The condition usually very slowly progresses toward spontaneous resolution; however, the findings of several long-term studies10 –14 suggest that ongoing impairment may persist in some patients. Adhesive capsulitis is described as being either primary or secondary.10,15,16 Primary adhesive capsulitis is due to an unknown cause (ie, it is idiopathic), whereas secondary adhesive capsulitis results from a known cause or surgical event.4 Published descriptions of the condition commonly further subdivide it into 3 or 4 stages. Following arthroscopic evaluation, Neviaser and Neviaser8 identified 4 stages of involvement.


September 2009

These 4 stages have been correlated with clinical examination findings and histological appearance of the tissues.4 The more-recent literature, however, generally describes adhesive capsulitis as consisting of 3 stages.3,5,15 These stages have been identified as the painful stage (first), the adhesive stage (second), and the resolution stage (third). The painful stage in this nomenclature includes both stage 1 (the pre-adhesive stage) and stage 2 as described by Neviaser and Neviaser.8 The current study was concerned with identifying primary adhesive capsulitis in the painful or first stage of the condition. Although “textbook” descriptions of diagnostic criteria for adhesive capsulitis, including variable pain and movement characteristics, are present in the literature, validation of these descriptions is lacking. Currently, the diagnosis of primary adhesive capsulitis is based on the findings of the patient history and physical examination. No specific clinical test or definitive investigation has been reported in the literature, and there remains no gold standard to diagnose this disorder. A varying range of “typical” signs and symptoms, such as pain aggravated by shoulder movement,4,5 pain at night,8 and multidirectional limitation of active and passive joint movement accompanied by pain at the extremes of range,3 have been proposed instead. To date, however, there are no agreed-upon or validated diagnostic criteria for the disorder. The lack of validity and reliability for the diagnostic classification of shoulder pain has been a topic of controversy for some time.17–22 In a study of interobserver agreement between general practitioners and physical therapists, this deficit has been particularly highlighted.23 However, the need for diagnostic labels for shoulder disorders has been questioned, as there is some evidence that the

outcomes of treatment may be similar for heterogeneous groups of patients with shoulder pain lacking a specific diagnosis.24 –27 Conversely, other authors28,29 have suggested that a uniform method of defining shoulder disorders is necessary. In a systematic review of randomized controlled trials of interventions for the painful shoulder,28 the authors commented that, in the studies sampled, no standard diagnostic definitions were used, and indeed conflicting criteria were used to define the same condition in various trials. These limitations make drawing conclusions across studies difficult. Although a set of diagnostic criteria may not exclusively represent a single pathological entity, it may represent a subgroup of patients to whom randomized controlled trials may be directed. Similarly, early and accurate identification of diagnostic criteria is recommended for determining prognosis as well as optimizing treatment outcomes in the clinic.30 Early presentation of shoulder disorders has been associated with a favorable outcome.31 Some authors4,8 have recommended that treatment and prognosis for adhesive capsulitis should be tailored to the stage of the disorder. Consequently, it is arguably appropriate to establish diagnostic criteria for each stage rather than for the disease process as a whole. The difficulty faced by clinicians in the diagnosis of shoulder disorders recently was addressed by Mitchell and colleagues.32 They proposed a simple model to assist in the diagnosis of rotator cuff, glenohumeral, and acromioclavicular joint disorders, as well as referred cervical spine pain. Although potentially facilitating aspects of the clinical reasoning process, this model fails to recognize the various stages of adhesive capsulitis. Agreed-upon diagnostic criteria for

Volume 89

Number 9

Physical Therapy f

907

Clinical Identifiers for Adhesive Capsulitis early-stage adhesive capsulitis, therefore, remain to be established. The aim of this study was to reveal such consensus that may currently exist among a group of experts regarding the clinical signs and symptoms indicative of the first stage of primary adhesive capsulitis. The establishment of such consensus is the first step in the process of identification and validation of agreed-upon diagnostic criteria for this disorder.

Method The Delphi technique was chosen to explore this issue because it is an established and recognized method of deriving the opinion of experts to determine the degree of consensus where there is a lack of empirical evidence.33,34 This technique has the advantages of maintaining anonymity among respondents, allowing time for participants to consider their response while not being influenced by dominant individuals and enabling recruitment from diverse geographical locations and clinical backgrounds.35,36 Using a panel of experts, the Delphi technique is a multistage process using a series of sequential questionnaires or rounds linked by feedback. Each round of the process builds on the results of the previous one and results in consensus by the final round. This technique has been widely used in establishing consensus on various diagnostic descriptors and clinical identifiers.37– 42 Participants The participants were a group of experts involved in the diagnosis and treatment of adhesive capsulitis and recruited from several disciplines. These disciplines included rehabilitation medicine, physical medicine, orthopedic surgery, physical therapy, chiropractic, and osteopathy. Medical practitioners invited to participate in the study were required to hold postgraduate qualifi908

f

Physical Therapy

Volume 89

cations in a relevant specialty or be members of a special interest group in a discipline relevant to the study. Rehabilitation medicine physicians were recruited from the Musculoskeletal Medicine and Pain Special Interest Group, a subgroup of the Australasian Faculty of Rehabilitation Medicine. Members of the Australasian Faculty of Musculoskeletal Medicine also were included, as were members of the College of Physical Medicine. As a special interest group of the Australian Orthopaedic Association, members of the Shoulder and Elbow Society of Australia were approached. Physical therapist participants were members of Shoulder and Elbow Physiotherapists Australia (a physical therapy subgroup of the Shoulder and Elbow Society of Australia), as well as coordinators of postgraduate musculoskeletal physical therapy programs at Australian and New Zealand universities. In addition, specialist musculoskeletal physical therapists recognized by the Australian Physiotherapy Association and the Australian College of Physiotherapists were included. Australian and New Zealand authors who had published on the topic of adhesive capsulitis in peer-reviewed journals or texts in the past 10 years also were invited to participate. These potential participants were identified by searching MEDLINE and CINAHL databases using the search terms “adhesive capsulitis” and “frozen shoulder.” Only articles published in the English language between February 1996 and February 2006 were identified. The reference lists of identified articles also were scrutinized in an attempt to identify any texts or other references that may have been published during this period. Where contact details indicated the authors were located in Australia or New Zealand, these individuals were included in the expert group. Finally, chiropractors and osteopaths who were coordinators of postgraduate musculoskeletal pro-

Number 9

grams offered at Australian and New Zealand universities were approached. A total of 185 potential participants were contacted in the first round. Pilot Study A pilot study, using a sample of convenience comprising 6 participants representative of the overall sample, was performed prior to the commencement of the main study to determine whether the instructions to participants were clear and to identify any improvements to the method. Following the pilot study, it was determined that 2 reminders should be issued to nonresponding participants to maximize the response rate. It also was determined that documents should be highlighted to more clearly indicate that stage 1 of adhesive capsulitis was being investigated, not the later, more easily recognizable stages. Procedure The study was correspondence based, and the questionnaires were distributed by the researchers to the participants’ work addresses. Addresses were obtained from the appropriate organizations, and all contact details were available in the public domain, with the exception of the rehabilitation medicine physicians, whose members were approached through the chairperson of the Musculoskeletal Medicine and Pain Special Interest Group. In this case, the letter of invitation was sent to the chairperson of the group, requesting it be forwarded to members. Those members who were potentially interested in participating were asked to contact the researchers directly. Members of the Faculty of Musculoskeletal Medicine also were approached through the chairperson of the faculty, who provided names and contact details of members. All of the participants who were clinicians were approached at their private clinics. September 2009

Clinical Identifiers for Adhesive Capsulitis Experts were asked to participate in 3 rounds of questionnaires. For the first round, potential participants were sent a letter of invitation along with the first questionnaire and were given 2 weeks to reply. Participants were given the opportunity to receive the subsequent questionnaires electronically and to supply a contact telephone number. A reminder was sent if a response was not received in the specified time, and, if necessary, a second reminder was issued after a further 2 weeks. The same approach and time frame for reminders were used for the 2 subsequent rounds. Telephone contact was used in the second and third rounds for the second reminder if a telephone number was made available by the participant. Round 1. The first questionnaire requested participants to list as many or as few diagnostic criteria as they considered necessary and sufficient to diagnose stage 1 primary adhesive capsulitis. Respondents were given the opportunity to provide a rationale for their criteria if they felt this appropriate. The responses were independently reviewed and collated by each of the 3 researchers, using a series of operational rules. These rules involved listing all of the criteria (individual responses) proposed, grouping the criteria into relevant clinical categories, eliminating single responses, merging repeated responses, and discarding unclear responses. Responses clearly inconsistent with the literature or obviously relating to secondary adhesive capsulitis or the later stages of the target disorder also were discarded. Following initial independent review, the researchers met and reached a consensus on the criteria to constitute the second round. Round 2. The second round used the criteria identified in round 1 by all participants. In this round, participants were asked to score the imSeptember 2009

portance of each criterion in the diagnosis of stage 1 adhesive capsulitis using the following 5-point Likert scale adapted from Cook et al39: 1. Strongly agree: the selected criterion is extremely important in the diagnosis of stage 1 of primary adhesive capsulitis. 2. Agree: the selected criterion is important in the diagnosis of stage 1 of primary adhesive capsulitis. 3. Undecided: uncertainty about the importance of the selected criterion in the diagnosis of stage 1 of primary adhesive capsulitis. 4. Disagree: the selected criterion is not important in the diagnosis of stage 1 of primary adhesive capsulitis. 5. Strongly disagree: there is absolutely no importance whatsoever of the selected criterion in the diagnosis of stage 1 of primary adhesive capsulitis. Round 3. The third round provided feedback to the participants in the form of the percentages for each of the 5 response options as to how all participants rated each criterion in round 2. In the light of this information, participants were requested to rescore each criterion on the same Likert scale used in round 2. Data Analysis The data were analyzed initially using simple descriptive statistics. The Cronbach coefficient alpha then was used as a measure of the level of consistency of opinion among the respondents regarding the agreedupon criteria. Finally, to determine the underlying structure of the criteria, a factor analysis was performed.

responses (48.1%) were received. From the 89 respondents from round 1, 75 responses (84.3%) were received following round 2. Seventy (93.3%) of these respondents completed the final round. Overall, 37.8% of the original sample completed all 3 rounds. The response rate of participants in each discipline is indicated in Table 1, and the flow of participants through the study is depicted in Figure 1. Following the first round, 367 criteria were generated. Collation of the data resulted in the establishment of 60 diagnostic criteria structured into 6 sections to form round 2. These criteria are outlined in Table 2. Following round 3, the data were analyzed initially using descriptive statistics. As the purpose of the study was to seek strongly held views of experts and the initial request had been for necessary and sufficient criteria, it was determined that only the “strongly agree” response would be analyzed. Therefore, the number of respondents scoring “strongly agree” was calculated and is graphically represented in Figure 2. In order to determine the criteria to be used in further analysis, several principles were applied. First, the Pareto principle,43 which suggests that 20% of the items would determine 80% of the value or benefit in deciding what is important in diagnosis, was used to commence analysis. By applying this principle, 12 criteria were identified. Second, the pattern of drop-off of frequency for these items resulted in a delineation at 10 criteria. As this delineation was in reasonable agreement with the Pareto principle, it was considered that this was an appropriate cutoff to select. As a result, 10 criteria (in descending order, criteria 13, 14, 25, 42, 12, 15, 34, 22, 60, and 26) were selected for further analysis.

Results From the 185 potential participants approached in the first round, 89

In order to measure the internal consistency of the criteria, Cronbach al-

Volume 89

Number 9

Physical Therapy f

909

Clinical Identifiers for Adhesive Capsulitis Table 1. Composition and Response Rate of Participants in Delphi Study Participants Approached, n (%)

Respondents Round 1, n (%)



3 (1.6)

2 (2.2)

1 (1.3)

1 (1.4)

Member of the Australasian Faculty of Musculoskeletal Medicine

28 (15.1)

11 (12.4)

9 (12)

7 (10)

Member of the Australian College of Physical Medicine

28 (15.1)

10 (11.2)

7 (9.3)

6 (8.6)

Member of the Shoulder and Elbow Society of Australia

81 (43.8)

36 (40.4)

28 (37.3)

27 (38.6)

Member of Shoulder and Elbow Physiotherapists Australia

12 (6.5)

10 (11.2)

10 (13.3)

9 (12.9)

Coordinator of a postgraduate musculoskeletal physical therapy program

11 (5.9)

11 (12.4)

11 (14.7)

11 (15.7)

Group Member of the Musculoskeletal and Pain Special Interest Group of the Australasian Faculty of Rehabilitation Medicine

Specialist musculoskeletal physical therapist

4 (2.2)

3 (3.4)

3 (4)

3 (4.3)

11 (5.9)

3 (3.4)

3 (4)

3 (4.3)

Coordinator of a postgraduate chiropractic program

5 (2.7)

3 (3.4)

3 (4)

3 (4.3)

Coordinator of a postgraduate osteopathic program

2 (1.1)

0 (0)

0 (0)

0 (0)

89

75

70

Author of publication on adhesive capsulitis in the past 10 years

Total

185

pha was used. Using SPSS version 15,* an analysis of the 10 selected criteria resulted in a Cronbach alpha value of .63. Stepwise removal of items whose inclusion reduced the alpha value was performed (criteria 42 and 60). Removal of these 2 criteria maximized Cronbach alpha to .71. Eight criteria were established as a result of this analysis and are presented in Table 3. As the underlying structure of these criteria was of interest and factor analysis was proposed, a Kaiser-Meyer-Olkin measure of sampling adequacy was performed to determine whether factor analysis would be of benefit. The value of this test was .661. A value above .60 indicates that it is worthwhile proceeding with factor analyis.44 A factor analysis using varimax rotation, therefore, was performed on the remaining 8 criteria to examine their underlying structure. * SPSS Inc, 233 S Wacker Dr, Chicago, Il 60606.

910

f

Physical Therapy

Volume 89

Figure 3 demonstrates the scree plot for this calculation. The result of this factor analysis determined 2 discrete dimensions of pain and movement into which the criteria clustered. This is represented in Figure 4. These factors together accounted for 56.3% of the total variance of the expert responses, with the pain factor accounting for 36% and the movement factor accounting for 20.3%. The relative weights of the 8 criteria are shown in Table 4, which provides factor loadings for each criterion in the 2-factor solution.

Discussion The Delphi technique was used successfully in this study to establish consensus among a group of musculoskeletal professionals on 8 clinical identifiers for the first stage of primary (idiopathic) adhesive capsulitis. Although the initial aim of the study had been to establish diagnostic criteria and instructions to par-

Number 9

ticipants had been to respond as such, following data analysis it was considered more appropriate to alter the nomenclature of the set of resultant criteria to clinical identifiers. In a recent Delphi study of lumbar zygapophyseal joint pain,42 a similar dilemma was encountered, with experts in medical disciplines applying different definitions to the term “diagnostic criteria.” Following the first round of that study, it was decided to replace the phrase “diagnostic criteria” with “criteria indicative” of lumbar zygapophyseal joint pain to more appropriately reflect the responses received. At the conclusion of the current study, the term “clinical identifiers” was similarly determined to be more appropriate for the set of criteria established, as they could not be regarded as a gold standard for diagnosis or provide a differential diagnosis, but rather are a set of clinical identifiers that may assist the cli-

September 2009

Clinical Identifiers for Adhesive Capsulitis nician in diagnosis, as well as help form the basis for further research. Unlike many earlier published studies using the Delphi technique, the application of rigorous statistical analysis, rather than only simple descriptive statistics, was used to determine consensus in this study. Notably, factor analysis in this study has resulted in identifiers clustering into 2 discrete domains of pain and movement. Clinically, diagnosis of adhesive capsulitis is made through the history and physical examination. Textbook descriptions of the clinical characteristics of adhesive capsulitis identify a number of features present in each of the various stages of the disorder.45 These features encompass onset and description of pain, as well as effect on movement. Similarly, in published studies such as a recent systematic review of physical therapy for adhesive capsulitis,46 many of the clinical identifiers proposed by respondents in the present study are described, despite a lack of validation. Although these identifiers (including descriptions of pain and movement) are commonly proposed, they have not previously been subjected to formal evaluation. Using the Delphi technique, the present study is the first to subject these descriptors to scrutiny and begin the process of validation.

Figure 1. Flow of participants through the study.

September 2009

To date, there has been no agreement on the necessary criteria or clinical identifiers required for diagnosing adhesive capsulitis in its early stage.20,45,47,48 However, it has been suggested that although the exact identifiers are poorly defined, pain is a significant feature in this stage.4 Our study supports this premise, with several dimensions of pain being qualified and achieving consensus. A strong component of night pain, a marked increase of pain with rapid or unguarded movements, disVolume 89

Number 9

Physical Therapy f

911

Clinical Identifiers for Adhesive Capsulitis Table 2. Items Generated Following Round 1 Category

Criterion/Descriptor

Patient-reported findings

1. Pain is generally located over the upper arm 2. Pain is predominantly over the lateral shoulder/deltoid region 3. Pain is predominately over the anterior shoulder 4. Pain may be referred distally into the forearm 5. Pain is diffuse or poorly localized 6. The pain is described as deep 7. The intensity of the pain is described as severe 8. The pain is constant or unrelenting in nature 9. The pain is described as an ache 10. The level of pain is progressively increasing 11. There is an intermittent catching or pinching pain 12. There is a strong component of night pain 13. There is a marked increase in pain with rapid or unguarded movements 14. It is uncomfortable to lie on the affected shoulder 15. The patient reports the pain is easily aggravated by movement 16. Once aggravated, the patient reports the pain is slow to settle 17. Function is limited by increasing stiffness in this stage 18. The history of onset of pain is spontaneous 19. Symptoms have been present for greater than 4 weeks 20. There is often a history of a minor trauma/precipitating event 21. The onset of the condition is sudden

Demographic factors

22. The onset is generally in people greater than 35 years of age 23. The onset is generally in people less than 60 years of age 24. The condition more commonly presents in females

Physical examination findings

25. On examination, there is a global loss of active and passive range of movement 26. On examination, there is pain at the end of range in all directions 27. On examination, there is no painful arc with shoulder elevation 28. There is protective muscle guarding with movement 29. The loss of movement in any direction is minor 30. The greatest loss of movement is in external rotation 31. There is painful limitation of active external rotation range performed in supine at 90° shoulder abduction 32. There is marked pain during isometric external rotation strength testing performed in supine at 90° shoulder abduction 33. The patient’s range of movement is progressively decreasing due to pain 34. There is a global loss of passive glenohumeral joint movement 35. The loss of movement is in a glenohumeral joint capsular pattern (ie, external rotation⬎abduction⬎internal rotation) 36. Resisted isometric muscle testing is pain-free 37. If pain is not inhibiting, muscle strength testing will be normal 38. There is diffuse tenderness to palpation around the shoulder 39. There is tenderness to palpation specifically over the anterior joint 40. The scapula position is elevated at rest or with movement 41. Provocative tests for tendinitis do not inform the diagnosis (continued)

912

f

Physical Therapy

Volume 89

Number 9

September 2009

Clinical Identifiers for Adhesive Capsulitis Table 2. Continued Category Associated factors

Criterion/Descriptor 42. There can be an association with diabetes 43. There may be a coexisting history of a thyroid condition 44. The onset of the condition is more common in spring and autumn 45. A minor viral illness may precede the onset 46. There is often a past history of adhesive capsulitis of the opposite shoulder 47. There is frequently a history of impingement syndrome in the same shoulder 48. The thoracic spine is kyphotic or hypomobile

Response to treatment

49. There is a nonresponse or an exacerbation of pain with treatment involving physical therapies 50. There is minimal or no response to usual analgesic medication 51. There is minimal or no response to nonsteroidal anti-inflammatory drugs (NSAIDs) 52. There is no response to subacromial steroid injection 53. There is a favorable response to a steroid injection into the glenohumeral joint

Investigations

54. A thickened joint capsule will be evident on magnetic resonance imaging (MRI) 55. A decreased joint volume will be evident on MRI 56. Ultrasound investigation does not inform the diagnosis 57. X-ray examination only excludes osteoarthritis and calcific tendinitis 58. There is a mild elevation of erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) 59. Blood factors exclude an infective or systemic inflammatory state 60. Arthroscopy reveals synovitis and inflammation of the joint capsule

comfort lying on the affected shoulder, and pain easily aggravated by movement were the 4 descriptors of pain on which consensus was achieved. Although not validated, night pain or sleep disturbance has been described previously as a feature of this disorder in the early stage.8,10,46,47 There also are de-

scriptions in the literature of pain easily aggravated by movement.4,5 Although probably not exclusive to adhesive capsulitis, these descriptors of pain may reflect the pathology of inflammatory synovitis that has been demonstrated at this stage.8,49 The panel of experts in this study concur that these identifiers are necessary to

diagnose early-stage primary adhesive capsulitis. Although the identifiers describing location and intensity of pain did not reach consensus, the pain identifiers described and for which consensus was reached may assist the clinician in the diagnosis of early-stage adhesive capsulitis.

Figure 2. Percentage of respondents scoring a criterion as “strongly agree” (n⫽70).

September 2009

Volume 89

Number 9

Physical Therapy f

913

Clinical Identifiers for Adhesive Capsulitis Table 3. Diagnostic Criteria Achieving Consensus Criterion

Descriptor

12

There is a strong component of night pain

13

There is a marked increase in pain with rapid or unguarded movements

14

It is uncomfortable to lie on the affected shoulder

15

The patient reports the pain is easily aggravated by movement

22

The onset is generally in people greater than 35 years of age

25

On examination, there is global loss of active and passive range of movement

26

On examination, there is pain at the end of range in all directions

34

There is global loss of passive glenohumeral joint movement

The exact characteristics of movement dysfunction in the early stage of adhesive capsulitis are not clearly described in the literature. Although the effect on movement in the later stages of the disorder usually is described and even quantified, description of any movement deficit in the early stage generally is minimal. Nonetheless, general restriction of movement in all directions at this early stage has been described previously.3,5,10 This study achieved consensus on the clinical identifiers of global loss of both active and passive ranges of movement, accompanied by pain at the end-range in all directions. Although no specific quantification of the loss at this stage has been determined, the fact that loss is global, rather than related to a specific direction, is the key feature in this clinical descriptor. Unlike many other shoulder pathologies, adhesive capsulitis is a disorder mainly affecting the glenohumeral joint capsule.8 Global loss of active and passive range of motion is consistent with pathology of this structure. In addition, pain at the end-range in all directions is a feature that also may raise the level of clinical suspicion of adhesive capsulitis and also is consistent with capsular pathology.3 Demographic factors of adhesive capsulitis, including the age of onset, are considered relevant clinical features important in diagnosis. Gener914

f

Physical Therapy

Volume 89

ally, it is suggested in the literature that patients affected by this disorder are over 40 years of age.3,4,8,9 Following round 1, a variety of responses quantifying age were received from the expert panel, such as “not seen less than 30 years of age,” “middle aged 45– 60,” and “age 50s.” The most-frequent response was captured in criterion 22 (“the onset is generally in people greater than 35 years of age”). Interestingly, criterion 23 (“The onset is generally in people less than 60 years of age”), which was descriptive of the upper age limit for this disorder, did not

achieve consensus. Therefore, in this study, there was consensus that the age of onset of the disorder generally is greater than 35 years. This finding is consistent with previous published literature, although no explanation was offered.3,4,8,9 The higher incidence of women in the 40- to 60-year age group, which failed to reach consensus, has been hypothesized to coincide with menopause and perimenopause,50 but as yet this hypothesis remains unproven. The factor analysis determined that those respondents who regarded clinical identifiers in the pain dimension as diagnostically important consistently reported age (criterion 22) alongside the pain identifiers. As pain behavior and age generally are considered patient-reported data and not physical examination findings, it is appropriate that the clinical identifier describing age clustered with identifiers describing pain rather than with movement findings. Interestingly, the 8 clinical identifiers established in this study did not include any negative findings. Instructions to participants were not

Figure 3. Scree plot of final components selected.

Number 9

September 2009

Clinical Identifiers for Adhesive Capsulitis shoulder disorders pathology.

Component plot of diagnostic criteria following factor analysis.

Table 4. Factor Loadings Following Principal Components Factor Analysis of Clinical Criteria Factor Pain (Eigenvalueⴝ2.88)

14

.719

22

.717

13

.695

12

.604

15

.595

Movement (Eigenvalueⴝ1.62)

34

.928

25

.888

26

.447

to limit responses to positive findings, and indeed negative findings were solicited; however, they failed to reach consensus. This finding is relevant, as the presence of pathology in structures other than the glenohumeral joint capsule may elicit differing clinical characteristics that would raise doubts about a diagnosis of adhesive capsulitis. Acute cervical radiculopathy or rotator cuff tendinitis, for example, may be recognized by other clinical features that would contribute to a differential diagnosis. As such features did September 2009

differing

The recent suggestion that attempting to place diagnostic labels on groups of patients in clinical research trials is of little value22 may overstate the case. Arguably, one of the aims of establishing diagnostic criteria is to identify a homogenous subgroup of patients with which to evaluate treatment outcomes and make comparisons across trials more meaningful. Although there is some evidence that the outcomes of treatment may be similar in heterogeneous groups,24 –27 it remains to be seen whether subgroups of patients with common clinical features experience greater benefits with particular interventions.

Figure 4.

Criterion

of

not reach consensus in the current study, the limitation of the results in assisting differential diagnosis is acknowledged. A further consideration is whether the resultant group of identifiers should be regarded as a set or as individual items. Instructions to participants had been to give a “set of necessary and sufficient diagnostic criteria”; however, it remains to be determined whether all or only some are necessary in diagnosis. This is particularly relevant, as some of the identifiers also may be present in other acutely presenting

The Delphi technique, and its application in this study, has a number of limitations. However, it was chosen because it enabled the engagement of a large number of musculoskeletal experts from a range of relevant professions and across a wide geographical area. One limitation often described is that there may be a poor response rate to the questionnaires.35,36 In this study, the initial round had a moderate response rate of 48.1%, whereas the second and third rounds had high response rates of 84.3% and 93.3%, respectively. It has been suggested that a poor response rate may characterize the final rounds35; however, this did not occur in the current study. The overall response rate for this study was 37.8%, which compares favorably with recent studies that also had a large sample but achieved a response rate of only 8.4%.38,39 Researcher bias also has been proposed as a weakness of the Delphi technique. The use of an open initial response in round 1 achieved a richness of collected data; however, this required care in reducing data to a more manageable volume for the subsequent rounds.

Volume 89

Number 9

Physical Therapy f

915

Clinical Identifiers for Adhesive Capsulitis Strict operational definitions were used by the 3 researchers to minimize bias. Furthermore, following round 3, rather than just using simple descriptive statistics as in many earlier studies, a more rigorous analysis was used to provide a more independent insight into the data. Composition and size of the expert panel in Delphi studies vary across the literature. In an article discussing the methodology of the Delphi technique, Williams and Webb51 noted that there is no agreement regarding the optimal size of an expert panel. They commented that the panel size of studies reported in the earlier literature varied from 10 to 1,685 participants. In the current study, the inclusion criteria for potential participants determined the size of the expert panel. These inclusion criteria were established to recruit musculoskeletal practitioners and leaders in several fields with expertise in clinical, research, and educational facets of shoulder pain. Although medical practitioners were represented, omission of rheumatologists, who may assess and treat musculoskeletal disorders, could be regarded as a limitation of this study. This omission occurred because it was not possible to identify a defined special interest group in musculoskeletal medicine or orthopedics within the Australian Rheumatology Association. Regional differences in prevalence or characteristics of adhesive capsulitis are not described in the literature. However, as the participants in this study were recruited from Australian and New Zealand experts, the results may reflect only views held in this region. The present study not only addressed the difficulty faced by clinicians in the diagnosis of shoulder disorders as described by Mitchell and colleagues,32 but also is the first of its kind to establish a set of clinical identifiers for the early stage of pri916

f

Physical Therapy

Volume 89

mary adhesive capsulitis. Although a specific diagnostic test or negative findings that may contribute to differential diagnosis did not achieve consensus in this study, several parameters of patient presentation have been established. These agreedupon clinical identifiers should assist in the clinical decision-making process and aid in the early recognition of this disorder. They also represent the first step in the longer process of identification and validation of the agreed diagnostic criteria for this disorder.

Conclusions The results of this study provide a framework for the validation of clinical identifiers for early primary adhesive capsulitis in further studies, as well as potentially facilitating comparisons across future clinical trials. Although the identifiers established in this study do not constitute an exclusive or discriminatory set of diagnostic criteria, they may be of assistance to the clinician confronted with the diagnostic dilemma of recognizing the early stage of primary adhesive capsulitis. All authors provided concept/idea/research design and data analysis. Ms Walmsley and Dr Rivett provided writing. Ms Walmsley provided data collection. Dr Rivett provided institutional liaisons. Dr Rivett and Mr Osmotherly provided consultation (including review of manuscript before submission). This study was approved by The University of Newcastle Human Research Ethics Committee. An interactive poster presentation of selected findings of this study was given at the International Federation of Orthopaedic Manipulative Therapists (IFOMT) Conference; June 8 –13, 2008; Rotterdam, the Netherlands. This article was received October 26, 2008, and was accepted May 19, 2009. DOI: 10.2522/ptj.20080341

Number 9

References 1 Codman EA. The Shoulder: Rupture of the Supraspinatus Tendon and Other Lesions in or About the Subacromial Bursa. Boston, MA: Thomas Todd; 1934. 2 Neviaser RJ. Adhesive capsulitis of the shoulder. J Bone Joint Surg. 1945;27: 211–222. 3 Pearsall AW, Speer KP. Frozen shoulder syndrome: diagnostic and treatment strategies in the primary care setting. Med Sci Sports Exerc. 1998;30(suppl 1):33–39. 4 Hannafin JA, Chiaia TA. Adhesive capsulitis: a treatment approach. Clin Orthop. 2000;372:95–109. 5 Siegel LB, Cohen NJ, Gall EP. Adhesive capsulitis: a sticky issue. Am Fam Physician. 1999;59:1843–1850. 6 Scarlat M, Goldberg B, Harryman D. Frozen shoulder in diabetic patients: handle with care. Journal of Musculoskeletal Medicine. 2000;17:484 – 498. 7 Aydogan A, Karan A, Ketenci A, et al. Factors affecting therapeutic response of adhesive capsulitis in type II diabetes mellitus. J Back Musculoskeletal Rehabil. 2003/2004;17:3–7. 8 Neviaser RJ, Neviaser TJ. The frozen shoulder diagnosis and management. Clin Orthop. 1987;223:59 – 64. 9 Dias R, Cutts S, Massound S. Frozen shoulder. BMJ. 2005;331:1453–1456. 10 Reeves B. The natural history of the frozen shoulder syndrome. Scand J Rheumatol. 1975;4:193–196. 11 Binder AI, Bulgen DY, Hazleman BL, Roberts S. Frozen shoulder: a long-term prospective study. Ann Rheum Dis. 1984;43: 361–364. 12 Hand C, Clipsham K, Rees JL, Carr AJ. Long-term outcome of frozen shoulder. J Shoulder Elbow Surg. 2008;17:231–236. 13 Vecchio PC, Kavanagh RT, Hazleman BL, King RH. Community survey of shoulder disorders in the elderly to assess the natural history and effects of treatment. Ann Rheum Dis. 1995;54:152–154. 14 Shaffer B, Tibone JE, Kerlan RK. Frozen shoulder: a long-term follow-up. J Bone Joint Surg Am. 1992;74:738 –746. 15 Chambler AFW, Carr AJ. Aspects of current management: the role of surgery in frozen shoulder. J Bone Joint Surg Br. 2003;85:789 –795. 16 Harrast M, Rao A. The stiff shoulder. Phys Med Rehabil Clin North Am. 2004;15: 557–573. 17 Buchbinder R, Goel V, Bombardier C, Hogg-Johnson S. Classification systems of soft tissue disorders of the neck and upper limb: do they satisfy methodological guidelines? J Clin Epidemiol. 1996;49: 141–149. 18 Walker-Bone K, Palmer K, Reading I, Cooper C. Criteria for assessing pain and nonarticular soft tissue rheumatic disorders of the neck and upper limb. Semin Arthritis Rheum. 2003;33:168 –184.

September 2009

Clinical Identifiers for Adhesive Capsulitis 19 de Winter A, Jans M, Scholten R, et al. Diagnostic classification of shoulder disorders: interobserver agreement and determinants of disagreement. Ann Rheum Dis. 1999;58:272–277. 20 Groeiner KH, Winters JC, MeyboomdeJong B. Classification of shoulder complaints in general practice by means of nonmetric multidimensional scaling. Arch Phys Med Rehabil. 2003;84:812– 817. 21 Winters JC, Groenier KH, Sobel JS, et al. Classification of shoulder complaints in general practice by means of cluster analysis. Arch Phys Med Rehabil. 1997;78: 1369 –1374. 22 Schellingerhout JM, Verhagen AP, Thomas S, Koes BW. Lack of uniformity in diagnostic labeling of shoulder pain: time for a different approach. Man Ther. 2008;13: 478 – 483. 23 Liesdek C, van der Windt DAWM, Koes BW, Bouter LM. Soft tissue disorders of the shoulder. Physiotherapy. 1997;83:12–16. 24 Hay E, Thomas E, Paterson S, Dziedzic K, Croft P. A pragmatic randomised controlled trial of local corticosteroid injection and physiotherapy for the treatment of new episodes of unilateral shoulder pain in primary care. Ann Rheum Dis. 2003;62:394 –399. 25 Ginn KA, Cohen ML. Conservative treatment for shoulder pain: prognostic indicators for outcome. Arch Phys Med Rehabil. 2004;85:1231–1235. 26 Ginn KA, Herbert RD, Khouw W, Lee R. A randomized, controlled clinical trial of a treatment for shoulder pain. Phys Ther. 1997;77:802– 809. 27 Thomas E, van der Windt D, Hay E, et al. Two pragmatic trials of treatment for shoulder disorders in primary care: generalisability, course and prognostic indicators. Ann Rheum Dis. 2005;64:1056 –1061. 28 Green S, Buchbinder R, Glazier R, Forbes A. Systematic review of randomised controlled trials of interventions for painful shoulder: selection criteria, outcome assessment, and efficacy. BMJ. 1998;318: 354 –360.

September 2009

29 Buchbinder R, Green S, Youd JM, Johnston RV. Oral steroids for adhesive capsulitis. Cochrane Database Syst Rev. 2006;4: CD006189. 30 van der Heijden GJMG. Shoulder disorders: a state-of-the-art review. Baillieres Best Pract Res Clin Rheumatol. 1999;13: 287–309. 31 Bulgen DY, Binder AI, Hazleman BL, et al. Frozen shoulder: a prospective clinical study with an evaluation of three treatment regimens. Ann Rheum Dis. 1984;43: 353–360. 32 Mitchell C, Adebajo A, Hay EM, Carr AJ. Shoulder pain: diagnosis and management in primary care. BMJ. 2005;331: 1124 –1128. 33 Brown AK, O’Connor PJ, Roberts TE, et al. Recommendations for musculoskeletal ultrasonography by rheumatologists: setting global standards for best practice by expert consensus. Arthritis Rheum. 2005; 53:83–92. 34 Powell C. The Delphi technique: myths and realities. J Adv Nur. 2003;41:376 –382. 35 McKenna HP. The Delphi technique: a worthwhile research approach for nursing? J Adv Nurs. 1994;19:1221–1225. 36 Sumsion T. The Delphi technique: an adaptive research tool. Br J Occup Ther. 1998;61:153–156. 37 McCarthy CJ, Rushton A, Billis V, et al. Development of a clinical examination in non-specific low back pain: a Delphi technique. J Rehabil Med. 2006;38:263–267. 38 Cook C, Brismee J, Fleming R, Sizer PS Jr. Identifiers of clinical cervical spine instability: a Delphi study of physical therapists. Phys Ther. 2005;85:895–906. 39 Cook C, Brismee J, Sizer PS Jr. Subjective and objective descriptors of clinical lumbar spine instability: a Delphi study. Man Ther. 2006;11:11–20. 40 Ferguson ND, Davis AM, Slutsky AS, Stewart TE. Development of a clinical definition for acute respiratory distress syndrome using the Delphi technique. J Crit Care. 2005;20:147–154.

41 Graham B, Regeher G, Wright JG. Delphi as a method to establish consensus for diagnostic criteria. J Clin Epidemiol. 2003; 56:1150 –1156. 42 Wilde VE, Ford JJ, McMeeken JM. Indicators of lumbar zygapophyseal joint pain: survey of an expert panel with the Delphi technique. Phys Ther. 2007;87:1348 –1361. 43 Rao AG, Carr LP, Dambolena I, et al. Total Quality Management: A Cross-Functional Perspective. New York, NY: John Wiley & Sons Inc; 1996. 44 Tabachnick BG, Fiddell LS. Using Multivariate Statistics. 3rd ed. New York, NY: Harper Collins College Publishers; 1996. 45 Murnaghan JP. Frozen shoulder. In: Rockwood CA, Matsen FA, eds. The Shoulder. Philadelphia, PA: WB Saunders Co; 1990: 837– 861. 46 Cleland J, Durall C. Physical therapy for adhesive capsulitis: systematic review. Physiotherapy. 2002;88:450 – 457. 47 Dudkiewicz I, Oran A, Salai M, et al. Idiopathic adhesive capsulitis: long-term results of conservative treatment. Isr Med Assoc J. 2004;6:524 –526. 48 Smidt N, Green S. Is the diagnosis important for the treatment of patients with shoulder complaints? Lancet. 2003;362: 1867–1868. 49 Hannafin JA, DiCarlo EF, Wickiewicz TL, Warren RF. Adhesive capsulitis: capsular fibroplasia of the glenohumeral joint [abstract]. J Shoulder Elbow Surg Suppl. 1994;3:S5. 50 Vad VB, Hannafin JA. Frozen shoulder in women: evaluation and management. Journal of Musculoskeletal Medicine. 2000;17:13–28. 51 Williams PL, Webb C. The Delphi technique: a methodological discussion. J Adv Nurs. 1994;19:180 –186.

Volume 89

Number 9

Physical Therapy f

917

Research Report

Strategies to Promote Evidence-Based Practice in Pediatric Physical Therapy: A Formative Evaluation Pilot Project Joe Schreiber, Perri Stern, Gregory Marchetti, Ingrid Provident J. Schreiber, PT, PhD, PCS, is Associate Professor, Department of Physical Therapy, Chatham University, Woodland Rd, Pittsburgh, PA 15232 (USA). Address all correspondence to Dr Schreiber at: [email protected]. This study was completed in partial fulfillment of the requirements for a doctoral degree in the School of Health Sciences, Duquesne University, Pittsburgh, Pennsylvania. P. Stern, OT, EdD, FAOTA, is Education Consultant, Pittsburgh, Pennsylvania. G. Marchetti, PT, PhD, is Associate Professor, Department of Physical Therapy, Rangos School of Health Sciences, Duquesne University, Pittsburgh, Pennsylvania. I. Provident, OT, EdD, is Assistant Professor and Academic Fieldwork Coordinator, Department of Occupational Therapy, Rangos School of Health Sciences, Duquesne University. [Schreiber J, Stern P, Marchetti G, Provident I. Strategies to promote evidence-based practice in pediatric physical therapy: a formative evaluation pilot project. Phys Ther. 2009;89:918 –933.] © 2009 American Physical Therapy Association

Background. The physical therapy profession has been perceived as one that bases its practice largely on anecdotal evidence and that uses treatment techniques for which there is little scientific support. Physical therapists have been urged to increase evidence-based practice behaviors as a means to address this perception and to enhance the translation of knowledge from research evidence into clinical practice. However, little attention has been paid to the best ways in which to support clinicians’ efforts toward improving evidence-based practice. Objectives. The purpose of this study was to identify, implement, and evaluate the effectiveness of strategies aimed at enhancing the ability of 5 pediatric physical therapists to integrate scientific research evidence into clinical decision making.

Design. This study was a formative evaluation pilot project. Methods. The participants in this study collaborated with the first author to identify and implement strategies and outcomes aimed at enhancing their ability to use research evidence during clinical decision making. Outcome data were analyzed with qualitative methods.

Results. The participants were able to implement several, but not all, of the strategies and made modest self-reported improvements in evidence-based practice behaviors, such as reading journal articles and completing database searches. They identified several barriers, including a lack of time, other influences on clinical decision making, and a lack of incentives for evidence-based practice activities.

Conclusions. The pediatric physical therapists who took part in this project had positive attitudes toward evidence-based practice and made modest improvements in this area. It is critical for the profession to continue to investigate optimal strategies to aid practicing clinicians in applying research evidence to clinical decision making.


f

Physical Therapy

Volume 89

Number 9

September 2009


P

hysical therapists have been criticized for not using available research to inform their clinical decision making.1–12 The profession has been perceived as one that bases its practice largely on anecdotal evidence and that uses treatment techniques for which there is little scientific support.6,8 –14 This issue was identified as early as 1969 by Eugene Michels in a presidential address delivered to the membership of the American Physical Therapy Association. Michels called on physical therapists to move away from practice based solely on the suggestions of colleagues or personal experience and toward practice based on scientific research.15 The importance of using research evidence to guide physical therapist practice has received much attention in the decades since Michels’ address. Numerous authors have stated that physical therapists have a moral, professional, and ethical obligation to provide evidence-based service and to move away from interventions based solely on anecdotal testimonies, expert opinion, or physiologic rationale.1–5,8 –11,14,16 –27 The American Physical Therapy Association has identified evidence-based practice as an important goal for the profession in its “Vision 2020” statement.28 Despite this attention, minimal research has been aimed at identifying optimal ways in which to assist clinicians in translating knowledge generated by scientific research into clinical practice and decision making. Clinicians have been urged to


September 2009

increase evidence-based practice behaviors, such as writing clinical questions, completing database searches, obtaining primary research articles and systematic review articles from peer-reviewed journals, and analyzing those articles for their level of evidence and quality.1,5,7,11,21,29,30 Clinicians have been expected to use a decision-making paradigm that integrates patient preferences, clinical circumstances, personal experience, and scientific evidence into an optimal clinical decision for an individual patient.29,31,32 However, little attention has been paid to the best ways in which to support physical therapist clinicians’ efforts in these areas. It may be simplistic to believe that simply publishing high-quality research will result in knowledge from that research being translated easily into routine practice.29 The concept of knowledge translation provides a framework that may be helpful in considering the challenges that clinicians are likely to face when attempting to implement evidence-based practice. Knowledge translation has been defined as the exchange, synthesis, and ethically sound application of knowledge— within a complex system of interactions among researchers and users— to accelerate capture of the benefits of research.33 Key aspects of this framework are acknowledging the user as an active problem solver and as a constructor of his or her own knowledge rather than as a passive receptacle of information and expertise.34,35 In addition, behavior change for the user is rarely a linear process that proceeds logically from knowledge dissemination to alterations in behavior and subsequent improved outcomes. Instead, it is much more likely to be dynamic, iterative, nonlinear, and emergent.36 Finally, the level of interaction and trust between the researcher generating knowledge, and the clinician using that knowledge, and the clini-

cian’s perception of the relevance of the research, also are important aspects of the knowledge translation framework.37 Other challenges to the ethically sound application of knowledge through evidence-based practice have been identified. Time constraints are almost universally identified by health care practitioners as a primary limiting factor.5,16,20,38 – 42 Clinicians across a variety of health care settings refer to the pressures of the health care environment and administrators’ emphasis on productivity as factors that directly inhibit their ability to search for, gather, read, and integrate scientific information relevant to daily practice.16,20,38,39,43,44 Physical therapists in settings not affiliated with teaching or research institutions often face challenges in accessing relevant scientific evidence.16 Older and more-experienced physical therapists may struggle with implementing evidence-based practice behaviors more so than their younger counterparts.20 The enormous volume of research literature, which continues to expand, also constitutes a barrier for practitioners. Approximately 30,000 biomedical journals are published each year, and one estimate is that a decision maker needs to read, on average, 19 articles each day to stay up-to-date in his or her field.45 In addition, physical therapists often have difficulty applying research findings to individual patients and are unclear about whether there is research evidence to support or refute the use of therapeutic interventions.20 Negative attitudes about research may further compound the difficulties in the implementation of evidence-based practice in physical therapy.21 The minimal research completed to date on strategies to enhance physical therapists’ evidence-based practice knowledge, attitudes, and be-

Volume 89

Number 9

Physical Therapy f

919

Evidence-Based Practice in Pediatric Physical Therapy haviors has produced mixed results. Stevenson et al46 found that physical therapists rated taking courses as the most important method of staying up-to-date in clinical practice and that research literature and Webbased information were ranked as least important. This attitude did not change despite the use of a training program focused on educating the participants in evidence-based practice principles.46 Other investigations demonstrated that changes in underlying knowledge about evidence-based practice occur more readily than changes in evidencebased practice behaviors.47,48 For health care practitioners in general, passive dissemination strategies and one-time continuing education sessions generally are ineffective. In contrast, strategies that are interactive, multifaceted, and targeted toward barriers to change are more likely to be successful in eliciting the use of knowledge for behavior change.48 –54 Also needed are a supportive organizational culture, commitment, and a credible change agent.36 It is not surprising that the evidence thus far suggests that physical therapists continue to make clinical decisions primarily on the basis of knowledge gained from peers, continuing education conferences, and entrylevel education rather than knowledge translated from research evidence.13,14,20,39,55–57 The purpose of this research project was to identify, implement, and evaluate the effectiveness of strategies aimed at enhancing the ability of 5 pediatric physical therapists to integrate scientific research evidence into clinical decision making. The significance of this study is the focus on pediatric physical therapists and the use of interactive, multifaceted, and targeted strategies developed in collaboration with the study participants and aimed toward barriers to change

920

f

Physical Therapy

Volume 89

that are unique to this practice setting.

Method This 3-phase formative evaluation pilot project was designed to evaluate the effectiveness of a program aimed at improving the evidence-based practice of a group of pediatric physical therapists working in school settings. Formative evaluations focus on ways of improving the effectiveness of a program, a policy, an organization, a product, or a staff unit. Such evaluations have a formal design, and the data are collected, analyzed, or both, at least in part, by an evaluator.58(p221) Input on the program was solicited from the 5 participants throughout the present project and specifically during the identification of feasible evidencebased practice strategies and relevant individual and group outcomes. This process was based, in part, on a participatory or action research approach, in which the purpose is to produce new knowledge that is directly pertinent and beneficial to the setting where the investigation takes place. The outcomes may or may not be relevant or transfer to other, similar settings.59 – 63 Therefore, participatory research emphasizes the production of knowledge to elicit change and improvement in the lives of those involved in the research process and is done with participants, never to or on subjects.62,63 Participants To identify potential participants for this project, we contacted the owner of a physical therapy private practice to gauge interest in identifying ways to enhance employees’ knowledge and use of evidence-based practice. This private practice employed more than 15 physical therapists, most on a part-time basis and most working in a variety of school placements and with minimal regular interaction with other physical therapists. The owner indicated an interest in this

Number 9

topic and collaborated with the first author in using a stratified purposeful sampling strategy58(p240) to identify employees potentially willing and able to take part in the project. The stratification was based on years of work experience as a pediatric physical therapist. Previous research had identified differences in attitudes and beliefs toward evidencebased practice between younger, less-experienced physical therapists and their older, more-experienced colleagues.20 Six potential participants, including the practice owner, were identified initially. When approaching the employees, the owner emphasized the voluntary nature of the project and the fact that there was no requirement to participate. One individual declined, and the remaining 5 are henceforth referred to as “participants.” Table 1 shows the demographic information for the participants. The therapists worked in a variety of pediatric school settings and had no regular interaction with each other during their daily clinical practice. Interaction with the practice owner also was minimal and consisted mainly of phone and e-mail contact. All of the participants read and signed an informed consent form before participating in the project. Phase 1: Establishment of Strategies and Outcome Measures During phase 1 of this 3-phase project, the participants completed a self-report evidence-based practice questionnaire that was developed by Jette et al20 and aimed at describing their evidence-based knowledge, beliefs, attitudes, and behaviors. In addition, the participants completed individual and group interviews with the first author; the interviews focused on the constructs of clinical decision making and the use of scientific research to guide clinical September 2009

Evidence-Based Practice in Pediatric Physical Therapy Table 1. Demographic Characteristics of Participantsa Years in Practice/Years in Pediatric Practice

Years as Employee of the Practice

APTA Member

Pediatric Certified Specialist

Terminal Physical Therapy Degree

Hours/Week

No. of Children in Caseload

K

6/3

3

N

N

MPT

19.5

28

Elementary school

N

A

1/1

1

N

N

MPT

45–50

30

Schools

Y

L

20/20

8

Y

N

MPT

30–35

30–35

Schools

N

R

19/4

4

N

N

BS

32

25–30

EI, schools, center-based school; rehabilitation facility

N for EI and schools, Y for rehabilitation facility

P

25/22

22

Y

Y

DPT

30

25

Schools, EI

N

Participant

a

Other Physical Therapists on Site

Setting

APTA⫽American Physical Therapy Association, N⫽no, Y⫽yes, EI⫽early intervention.

practice. The information from these activities was summarized and shared with all of the participants, leading to a team meeting during which specific individual and group strategies for enhancing evidencebased practice and project outcome measures were established. The strategies were intended to enhance each participant’s ability to use research evidence in daily clinical practice. The strategies were an evidence-based practice workshop, enhanced practice Web site resources, and an online evidencebased practice exercise. Three participant outcome measures also were identified; these measures were evidence-based practice ranking, individual goals and goal attainment scaling (GAS), and a self-report survey of baseline and follow-up evidence-based practice knowledge and behaviors. In addition to these outcome measures, the participants completed follow-up group and individual interviews with the first author and the questionnaire developed by Jette et al.20 Both were designated as study outcomes and described the participants’ perceptions of evidence-based practice at the conclusion of the project. Table 2 shows the strategies and outSeptember 2009

comes, and the Figure shows an overview of the project. Phase 2: Implementation of Strategies and Outcome Measures Evidence-based practice workshop. At the request of the participants, the first author provided a workshop aimed at improving participants’ skills relating to evidencebased practice. This 4-hour workshop took place during the participants’ non–work time (a Saturday morning). Before the workshop, the participants developed individual goals relating to their knowledge and implementation of evidence-based practice. The objectives of the workshop were developed to address these goals, with an emphasis on accessing and analyzing a variety of research evidence and integrating the knowledge gathered from that evidence into clinical decision making. The objectives of the workshop are shown in Appendix 1. Enhanced practice Web site resources. The participants also expressed a desire for additional activities to assist in the application of knowledge and skills acquired during the workshop. Activities included posting clinical questions and

case scenarios on the practice Web site and generating critically appraised topics that could also be posted and made available to all practice employees.64 This use of the Web site as an evidence-based practice resource did not exist at the time of the workshop, and the practice owner indicated a willingness to pursue this activity with her Web page consultant. Online evidence-based practice exercise. Another strategy that followed the workshop was an online evidence-based practice exercise. The purpose of this exercise was to provide a guided practice opportunity for new skills learned during the workshop. The exercise included several phases separated by 3- or 4-day intervals, was conducted through group e-mail communication with all of the participants, and was led by the first author. During the first phase, the first author created a hypothetical clinical case and developed a clinical question based on that case. During the second phase, the first author explicitly described the search strategies used to gather evidence to answer the clinical question. He then identified the research articles that were most appropriate to obtain and analyze to

Volume 89

Number 9

Physical Therapy f

921

Evidence-Based Practice in Pediatric Physical Therapy Table 2. Strategies and Outcomesa Strategies and Outcomes

Description

Strategies Continuing education workshop

● Provided by first author to all participants; open to other practice employees as well ● Addressed evidence-based practice skills and knowledge ● Led to commitment by participants to increase use of evidence-based practice resources during work hours and non–work hours

Enhanced practice Web site resources

● Practice owner to investigate potential for Web site to include online case discussion board and files accessible to all employees ● Explicit effort to integrate research evidence into case discussions ● Posting of critically appraised topics on practice Web site

Online evidence-based practice exercise

● Guided and collaborative evidence-based practice process, including development of PICO question, database search, analysis of evidence, and proposed integration into clinical practice

Participant outcomes Self-reported evidence-based practice ranking (scale of 0–10 from each individual interview)

● Comparison of baseline and follow-up rankings

Individual goals and goal attainment scaling

● Self-reported score for each individual goal

Survey of baseline and follow-up evidence-based practice knowledge and behaviors

● Questionnaire of Connolly et al56 at baseline and 6-mo follow-up

Study outcomes Phase 3 individual and focus group interviews at end of 6-mo time frame; questionnaire of Jette et al20 a

● Reflection on project, impact on practice, and future directions

PICO⫽patient/intervention/comparison/outcome.

answer the clinical question. During the final phase, the first author shared his critical analysis of the research articles and his answer to the clinical question, based on the evidence. The participants were encouraged to work along with the first author and to compare their efforts with his. This strategy was designed so that the process would be repeated over the 6-month time frame of the study, with one of the participants taking on the leadership role in identifying the clinical question, performing the search, and generating an evidence-based answer to the question. Evidence-based practice ranking. The first outcome measure chosen by the participants was a selfidentified evidence-based practice ranking. The baseline ranking was 922

f

Physical Therapy

Volume 89

determined during the initial individual interview and was presented as follows: “If you could place yourself on a continuum of evidence-based practice, with 1 being completely not being an evidence-based practitioner and 10 being an optimal evidence-based practitioner, where would you place yourself today?” The participants felt that an increase in this ranking would represent an improvement in knowledge and use of evidence-based practice. Individual goals and GAS. Each participant set specific individual goals relating to evidence-based practice. Goals may affect performance by focusing attention, directing effort, increasing motivation, and enabling the development of strategies to achieve objectives. Therefore, in the context of this project,

Number 9

setting individual goals may have served as an intervention strategy in addition to providing an outcome measure. In accordance with a suggestion from the first author, the participants used a GAS framework to establish individual goals.65,66 Researchers have used GAS as an option for establishing and monitoring individual goals in a variety of subject areas, including mental health, occupational therapy, physical therapy, special education, professional development, and rehabilitation.67–71 This framework requires that the identified goal be assigned a score of 0. Additional scores of ⫹1 and ⫹2 are assigned to outcomes that represent increases or improvements relative to the score of 0. Conversely, scores of ⫺1 and ⫺2 indicate either less than optimal progress or no progress toward the September 2009


Figure. Project overview. EBP⫽evidence-based practice, GAS⫽goal attainment scaling, IRB⫽institutional review board.

September 2009

Volume 89

Number 9

Physical Therapy f

923

Evidence-Based Practice in Pediatric Physical Therapy goal, respectively.65,66,68 This process takes goal achievement further by allowing a calibration of the degree of success, recognizing partial completion and additional achievement, as opposed to the “all-or-none” approach of most goal-setting systems.65,66,68 In the present project, each participant identified at least 2 goals that were measurable and attainable within a 6-month time frame. Once those goals were established, the participant worked with the first author to generate outcomes (individual goals) corresponding to the ⫺2, ⫺1, ⫹1, and ⫹2 scores. At the conclusion of the project, each participant reported his or her score for each individual goal. Self-report survey of knowledge and behaviors. The participants also identified the importance of establishing a measurable outcome for baseline and follow-up evidencebased practice knowledge and behaviors. A 10-item questionnaire originally developed and applied by Connolly et al56 was used for this purpose. This questionnaire is a selfreport measure of knowledge and behaviors relating to research and includes items concerning comfort level and confidence in reading and applying research findings, personal habits in reading professional literature, and beliefs about the importance of research to the profession. The questionnaire also attempts to measure a perceived source of authority for clinical decision making and beliefs about how research is viewed by physical therapist colleagues.56 The authors described a brief validation process for the use of this questionnaire to measure changes over time in entry-level physical therapist students’ attitudes and perceptions about research in physical therapy.56 Baseline and follow-up scores for each participant were compared for differences. On the basis of the categorization of the individual items in the questionnaire, 924

f

Physical Therapy

Volume 89

several items were combined so that, for example, the participants’ selfreported knowledge and behaviors relating to research could be evaluated for changes between the beginning and the end of the project. Phase 3: Follow-up Semistructured Interviews Finally, semistructured individual interviews and a group interview were conducted during phase 3 of this project, along with readministration of the evidence-based practice questionnaire developed by Jette et al20 to each participant. The purpose of this phase was to provide an opportunity for the participants to reflect on the impact of the project on their professional practice, their participation in the establishment of strategies and outcomes, and future directions for research and practice. Readministration of the questionnaire of Jette et al20 provided additional descriptive data about the participants’ beliefs, attitudes, and behaviors relating to evidence-based practice and allowed a comparison of quantitative data between phase 1 and phase 3. Data Analysis Because of the small sample size, the quantitative data were analyzed descriptively in conjunction with the qualitative interview data to describe the participants’ outcomes at the end of the 6-month program. The individual and group interviews were transcribed verbatim, and the transcripts for each participant were analyzed by the first author to identify broad, overarching initial impressions. A qualitative data analysis expert (fourth author) worked concurrently to review the interviews and the first author’s initial impressions. The interview transcripts and initial impressions were then sent to each participant for review to further ensure the accuracy of this initial stage of analysis. This “member checking”72 represented a first effort

Number 9

toward enhancing the trustworthiness of the data analysis and interpretation. After the initial member checking, the ATLAS.ti* qualitative data analysis program was used to aid in managing the volume of data. The first author began open coding of the interview transcripts.72 A coded piece of data is the smallest item of analyzed data in qualitative research. The process involved reading each participant’s individual interview transcript and the group interview transcript line by line and highlighting phrases, sentences, groups of sentences, small paragraphs, or a combination of these that contained a meaningful, distinct thought pertaining to evidence-based practice. Each distinct thought was labeled with a 1- or 2-word code that enabled the first author to later retrieve, sort, and organize data into larger categories containing similar ideas. The data analysis expert reviewed the coded data and verified agreement with the first author’s analysis of the data. After all of the data had been coded, the first author reassembled the coded data into larger, synthesized units of meaning. The data were grouped into categories of similar information labeled with a phrase or sentence that reflected the content of information in a category. For example, the category “application and utilization of evidence-based practice” included the following codes: EBP-angst, EBP-practices-Internet, EBP-practices, EBP needs, barriers, complacency, and ranking. Next, the categories for each participant were organized and synthesized to aid in cross-case analysis across each of the 5 participants. This cross-case analysis and the con* ATLAS.ti Scientific Software Development GmbH, Hardenbergstrasse 7, D-10623 Berlin, Germany.

September 2009

Evidence-Based Practice in Pediatric Physical Therapy Table 3. Participants’ Baseline and Final Mean Scores for Attitudes, Beliefs, and Knowledge Relating to Evidence-Based Practice (EBP) (Questionnaire of Jette et al20) Scorea Item

a

Baseline

Final

EBP is necessary

1.40

1.40

Literature and research findings are useful

2.00

1.60

EBP improves quality of care

1.80

1.60

Evidence helps in decision making

2.40

2.40

Using evidence places unreasonable demands on physical therapists

3.60

3.60

EBP will lead to increased reimbursement

3.60

3.60

Need to increase use of evidence in daily practice

1.40

1.80

Interested in learning and improving skills relating to EBP

1.40

1.80

Knowledge of online databases (knowledge item)

2.00

1.80

Formal training in search strategies (knowledge item)

2.40

1.60

Formal training in critical appraisal (knowledge item)

1.60

1.40

Confident in appraisal skills (knowledge item)

2.80

2.00

Confident in search skills (knowledge item)

2.80

1.80

cause of family obligations (participant K) and illness (participant A). Subsequently, both did participate in a detailed phone conference with the first author to discuss the material covered in the workshop. Specific comments from the participants reflected a general sense that the workshop was helpful but not sufficient to lead to changes in daily practice. Participant P: “I thought it was a great introduction, but you know there is just too much material to get it in one setting.” Participant R: “I agree that (the workshop) was helpful, but I still feel lost out there on my own, and more supervised practice is definitely needed.” Participant K: “I thought it was very helpful, especially for me, who hasn’t had any exposure to that formal training in 5 to 6 years. So that was much more helpful to me as a refresher, but then I, too, see that it was—it answered a lot of my questions, but, even still, when I went to do it myself with all the notes in front of me, it just appeared that I needed some more practice. And finding the time to do that is difficult. But I did find (the workshop) very helpful.”

5⫽strongly disagree, 4⫽disagree, 3⫽neutral, 2⫽agree, 1⫽strongly agree.

comitant analysis of the quantitative data from the other outcomes led to the emergence of several overarching themes for the project.

Results The themes that emerged at the conclusion of phase 3 included sustained positive attitudes and beliefs about evidence-based practice; variable implementation of the strategies developed during the initial collaboration phase; variable performance for individual goals; persistent barriers, including a lack of time and a lack of incentives for evidence-based practice activities; and a desire for user-friendly evidence-based clinical practice guidelines. Positive Attitudes and Beliefs About Evidence-Based Practice Table 3 shows the baseline and final mean scores for items relating to attitudes, beliefs, and knowledge about evidence-based practice on the questionnaire developed by Jette et al.20 The participants sustained very positive attitudes throughout September 2009

the project. All of the participants believed that research evidence is useful and that it aids in clinical decision making, as indicated by the following comments: Participant P: “I think (pediatric physical therapists) absolutely need to be (evidence-based practitioners) if they are going to be respected as a profession out there.” Participant A: “So that’s why I think (evidence-based practice) is very important, so that we see outcomes faster and our treatments are better, and that’s why I think that it should be important to always keep up on the research.”

Variable Implementation of Strategies Workshop. The first author provided a 4-hour evidence-based practice workshop during phase 1 of this project. This workshop was provided at no cost but occurred outside of regular work hours. Despite an effort to schedule the workshop at a convenient time, 2 of the 5 participants were unable to attend be-

Upgrade of Web site resources. The upgrade of the practice Web site to allow postings and online case discussions did not occur because of time constraints for the practice owner. Online practice exercise. The online practice exercise after the workshop did occur and was led by the first author. However, there was minimal interaction among the participants during this activity, and there were no subsequent practice exercises, as originally suggested. During the follow-up interviews, the participants attributed this result to several factors. A lack of time was a consistent issue. Also, several of the participants alluded to the fact that

Volume 89

Number 9

Physical Therapy f

925

Evidence-Based Practice in Pediatric Physical Therapy the clinical case scenario developed by the first author was not relevant to their practice needs at that time and therefore was not a worthwhile time investment. None of the participants expressed a willingness to take over and lead the online interaction process once the first author completed the first clinical case scenario.

Table 4. Baseline and Final Results for Participants’ Evidence-Based Practice Behaviors and Attention to the Literature (Jette et al20 Questionnaire) No. of Participants Item

Final

1

3

2

2–5

1

2

6–10

1

1

1

1

1

2–5

4

3

Read and review research literature (no. of articles/mo)

11–15

Participant L: “It’s still so varied with the presentation that it’s very difficult to take a blanket statement about cerebral palsy and apply it to any of the kids or take results from a piece of evidence that you might get and apply it.”

16 Use literature for decision making (no. of times/mo)

6–10

1

11–15

Participant P: “I guess what I find is that the desire is there to do it but the follow through time (was not).”

Variable Performance Relating to Evidence-Based Practice Knowledge and Behaviors The participants’ rankings and GAS scores are shown in Appendix 2. Overall, the participants reported no progress on 4 goals, minimal progress on 3 goals, and achievement of the remaining 6 goals. Selfreported ranking improved for each of the participants, including an improvement from 1 of 10 to 4.5 of 10 for participant R. In addition to rankings and GAS scores, mean baseline and final quantitative scores for all of the participants on the self-report evidence-based practice questionnaire (Jette et al20) and on the questionnaire about knowledge and behaviors relating to research (Connelly et al56) are shown in Tables 3, 4, and 5. The scores reflected some improvement in knowledge relating to research and evidencebased practice across all participants combined. However, there was minimal improvement in self-reported evidence-based practice behaviors. This result also was reflected in several comments from the participants.

Baseline

16 Use MEDLINE or other databases (no. of times/mo) 1

2

1

2–5

1

6–10

3

3

11–15 16

Table 5. Participants’ Self-Reported Baseline and Final Mean Scores for Knowledge and Behaviors Relating to Research (Connolly et al56 Questionnaire) Scorea Item

a

Baseline

Final

Regular reading of peer-reviewed journals (behavior item)

3.00

2.40

Necessary academic background for critical review and appraisal (knowledge item)

2.80

2.40

Level of knowledge (knowledge item)

3.40

2.40

Knowledge and behavior items (preceding 3 items) combined

9.20

7.20

Research is relevant to clinical practice

2.20

2.00

Clinical practice should be based on outcome measure research

2.00

1.60

Clinical practice should be based on what experts say works

2.60

2.20

Keeping current is a lifelong professional responsibility

1.40

1.40

Research is one of the responsibilities of clinicians

2.40

2.20

I personally hope to be involved in the research process

2.40

2.60

Other physical therapists place a high priority on professional research

3.80

3.40

5⫽strongly disagree, 4⫽disagree, 3⫽neutral, 2⫽agree, 1⫽strongly agree.

Participant K: “But, you know, I just wonder how long . . . how many

926

f

Physical Therapy

Volume 89

Number 9

September 2009

Evidence-Based Practice in Pediatric Physical Therapy searches do you have to do . . . how much time does this take . . . you know . . . how many times is it going to take me— 45 minutes or an hour— to find something when I just don’t have that time to give.” Participant R: “My lack of comfort with doing it just on my own, too. Like if I knew what I was doing and I thought, ‘OK, I have 20 minutes to sit down and do this,’ and I can do it, but I think [sigh] I have 20 minutes, but I don’t even hardly know where to begin.” Participant L: “When I sat down and really thought about this, I have looked up a lot of different things; it just doesn’t seem like I have. I mean I was surprised when I wrote down what I could remember of what I had gotten on them, so that was kind of nice to really think about it.”

Persistent Barriers Other comments reflected the numerous challenges faced by therapists during clinical decision making and clinical practice. In addition, there were general perceptions among the participants that many of their professional colleagues were not regularly using research evidence to guide practice and that there were few incentives from their clinical environment (mainly elementary and secondary schools) to carry out evidence-based practice activities.

the whole situation.”

complexity

of

the

Participant L: “You know there really isn’t any time when that’s part of our job. You know that it’s considered to be on our time ourselves—it’s just time you have to make, and I think that makes it difficult.” Participant A: “Are they evidencebased practitioners? I don’t think all of them are.” Participant K: “One of the issues I do see with pediatric therapists is the majority of them are part time . . . they are off on summers. So that’s an issue, too. Working full time versus part time—your whole mindset, your whole availability.”

Suggestions for Future Directions Finally, at the conclusion of this project, the participants identified several strategies that may be effective in supporting evidence-based practice by clinicians. These strategies included user-friendly evidencebased practice guidelines, perhaps generated and updated by the professional association. In addition, each of the participants felt strongly that continuing professional education should be mandatory to renew licensure. Participant P: “I have been an advocate of (mandatory continuing education) since 1981, when I became a therapist [laughter]. I could never understand why this wasn’t mandatory. And one of the things they said was, ‘Well, you are a professional, you should want to do it.’ Well, that’s unrealistic. People are only going to do what they have to do.”

Participant A: “Right now—it’s not realistic unless you get a ton of cancellations and you’re sitting there and you’re actually caught up with your paperwork, then there’s a chunk of time. Right now—where I am just in my family life—I just don’t have the time in the evening.”

Discussion

Participant P: “So I mean, so on one hand they may verbally encourage it, but there’s not that, when they’re looking at that financial—what they’re paying us—they’re not considering that piece into that, you know. They’re still, they want us to come [provide therapy] and go. So you know I think that perhaps adds to

Consistent with the results of several other studies, the participants in the present study reported positive attitudes about evidence-based practice throughout the 6-month time frame.12,16,20,39,46,56,73 The participants frequently referred to the benefits of research evidence as a means to provide support for clinical deci-

September 2009

sions. The participants believed that using research evidence was likely to increase confidence in decision making, improve effectiveness, and enhance the stature of the physical therapy profession. On the basis of previous research suggesting that an interactive, multifaceted, and targeted approach is more effective in eliciting behavior change, the first author and the participants collaborated to develop strategies and outcomes aimed at improving evidence-based practice knowledge and behaviors.48 –54 Despite this collaboration and despite the sustained positive attitudes of the participants toward evidencebased practice, the implementation of the strategies was variable. The participants indicated that the evidence-based practice workshop was helpful but not sufficient for sustaining behavior change. The strategy of updating the Web site was not implemented because of time constraints for the practice owner. The workshop follow-up activity was not sustained beyond the initial effort of the first author. With regard to outcomes, the results of the present study are similar to those of previous work; that is, knowledge may improve, but changes in clinicians’ behaviors are less likely to occur.46 – 48 The present project was modestly successful in improving the participants’ evidence-based practice knowledge and behaviors. Five of the 13 GAS goals established by the participants for behavior change were achieved. The participants’ self-reported rankings as evidence-based practitioners all improved as well. The items reflecting evidence-based practice behaviors on the questionnaire developed by Jette et al20 showed minimal improvement. According to the questionnaire developed by Connolly et al,56 the participants’ knowledge and behaviors were improved

Volume 89

Number 9

Physical Therapy f

927

Evidence-Based Practice in Pediatric Physical Therapy at the conclusion of the present project. The knowledge translation framework suggests that a user of knowledge is an active problem solver and a constructor of his or her own knowledge and that behavior change is rarely linear.34 –36 All of the participants indicated some satisfaction with their improvements as well as some frustration that moresubstantial progress did not occur and that they were unable to take advantage of all of the group strategies. Improvements were attributed to several factors. The evidencebased practice workshop provided baseline knowledge for some of the participants, whereas others described it as more of a refresher. The individual goals that emerged as a result of participation in the research project led to increased attention to and awareness of evidence-based practice issues and to a variety of individual strategies unique to each participant. For example, participant L began bringing research journals to work each day and used spare time to read articles. Participant A indicated that the project provided the impetus to more consistently use the skills that she had learned in her entry-level education. Participant K believed that the project—in particular, the workshop—provided her with some additional tools and an increased willingness to initiate evidence-based practice activities, such as database searches. The selfidentified goals and the regular interaction of the participants and the first author served as incentives for all of the participants to focus on and improve evidence-based practice. Previous research indicated that a credible change agent is a critical component of a successful knowledge translation process.36 The first author in this project may have fulfilled the role of a change agent for the participants.

928

f

Physical Therapy

Volume 89

Additional important considerations are the multiple influences on the daily clinical decisions made by the participants in the present study. Clinical decision making relates to the thought processes associated with a clinician’s examination and treatment of a patient or client. It is a process in which information is appraised, viable options are identified, and a choice is made. The goal is wise action or the best clinical judgment in a specific context.74 Throughout the present project, the participants reported that multiple influences and constraints on clinical decision making affected their ability to translate research evidence into practice. These constraints and influences, identified mainly through the individual and group interviews, are summarized in Appendix 3. Clinical decision making for practitioners is extremely challenging. Awareness of available research evidence and insight into the relevance of that research for a particular child are critical, but not sufficient. Skilled pediatric physical therapists must also be able to communicate information effectively to various constituencies, including families, other caregivers, teachers, and other health care providers, and to advocate for an optimal course of action. All of the influences on decision making must be taken into consideration as elements of evidence-based practice and of expert practice in pediatric physical therapy.75–79 Along with these multiple influences on clinical decision making, several barriers to evidence-based practice were identified. A lack of incentives for evidence-based practice was a significant issue for the participants in the present study. Although the lack of incentives was described in different ways, it was clear that this issue had a strong influence on evidence-based practice activities and on the use of research evidence

Number 9

to guide clinical decision making. Despite the effort of the physical therapy profession to move toward evidence-based practice,1,3,4,14,17–22 working in a school setting was not perceived as being supportive of evidence-based practice by the participants. A lack of reimbursement for time to complete evidence-based practice activities during the daily routine of physical therapists working part time in school settings was an important factor. In the present project, all of the strategies occurred outside of work hours. Also, as described by participant P, a lack of reimbursement for ongoing professional development and amassed expertise also contributed to this notion of a lack of incentives. Finally, several of the participants described a lack of evidence-based practice activities among their physical therapist colleagues. Most of the evidence to date indicates that this observation is consistent with the behavior of many physical therapist clinicians.12–14,20,38,39,46,56,80 – 82 A recommendation from all of the participants was the development of evidence-based clinical practice guidelines that are available and accessible within their daily routines. All of the participants identified lack of time as a consistent barrier and discussed the positive appeal of a condensed summary of evidence. In a recent review article relating to the practice of medicine, electronic guidelines, also described as decision support systems, were found to significantly improve physicians’ clinical practice in 68% of the research studies reviewed.83 Four features of the guidelines were identified as independent predictors of improved clinical practice: automatic provision of decision support as part of clinician work flow, provision of recommendations rather than just assessments, provision of decision support at the time and location

September 2009

Evidence-Based Practice in Pediatric Physical Therapy of decision making, and computerbased decision support.83 An additional recommendation from all of the participants was a requirement for mandatory continuing education credits for licensure. Currently, requirements for continuing education for physical therapists vary widely; most states have no mandatory requirements.84 The participants in the present project felt strongly that such a requirement is necessary to ensure all physical therapists are actively participating in ongoing professional development. In addition, several participants referred to the importance of continuing education conferences being interactive, clinically relevant, and evidence based. Limitations The nature of this formative evaluation pilot project does not permit generalization to a larger population. Instead, the focus was on describing, in detail, the phenomenon of evidence-based practice, the development and implementation of strategies aimed at improving evidencebased practice skills, and the outcomes of those strategies for a group of pediatric physical therapists. No effort was made to control for extraneous factors that may have affected the participants’ attitudes, beliefs, and behaviors relating to evidence-based practice during the course of this project. A thorough description of the data analysis and interpretation processes and the measures aimed at enhancing the trustworthiness of those processes in this project was provided. This information may or may not be relevant to other circumstances. Finally, the 6-month time frame may have been inadequate to permit substantial behavior change. Most of the work in this area has measured outcomes at between 3 and 6 months. However, a longer time period for September 2009

individual and group strategies to have had an effect may have led to more-substantial changes in the outcomes in this project. Future Directions Research with physical therapists from different practice areas and work settings is a necessary next step. Further investigations into the use of change agents to facilitate and support ongoing knowledge translation in all physical therapy settings are warranted. Investigations also should integrate the identification and use of incentives for physical therapists as an element of knowledge translation. The development and use of decision support systems and clinical practice guidelines that provide summaries of research evidence may hold great promise, especially in relation to the use of technology as an aspect of routine clinical practice. Evaluation of the effectiveness of continuing education and other professional development activities is needed for the physical therapy profession. Finally, investigating the effects of these various activities—including the use of change agents, incentives, clinical practice guidelines, and continuing professional education—on patient outcomes also is critical. Dr Schreiber, Dr Stern, and Dr Marchetti provided concept/idea/research design and writing. Dr Schreiber provided data collection. Dr Schreiber and Dr Provident provided project management and fund procurement. Dr Marchetti and Dr Provident provided consultation (including review of manuscript before submission). The authors acknowledge Gregory Frazer, PhD, and Paula Sammarone Turocy, EdD, ATC, for their assistance with this project. Institutional review board approval for this study was obtained through Duquesne University. This article was submitted August 27, 2008, and was accepted May 6, 2009. DOI: 10.2522/ptj.20080260

References 1 Evidence-based practice. Aust J Physiother. 1999;45:167–171. 2 Bohannon RW, LeVeau BF. Clinicians’ use of research findings: a review of literature with implications for physical therapists. Phys Ther. 1986;66:45–50. 3 Bury T. Evidence-based practice: survival of the fittest. Physiotherapy. 1996;82: 75–76. 4 Harris SR. How should treatments be critiqued for scientific merit? Phys Ther. 1996;76:175–181. 5 Herbert R, Sherrington C, Maher C, Moseley A. Evidence-based practice: imperfect but necessary. Physiother Theory Pract. 2001;17:201–211. 6 Jette AM. The peril of inadequate evidence. Phys Ther. 2005;85:302–303. 7 Mead J. Evidence based practice: how far have we come? Physiotherapy. 1996;82: 653– 654. 8 Rothstein JM. Caveat emptor [editorial]. Phys Ther. 1990;70:277–278. 9 Rothstein JM. Immelmann’s indignation [editorial]. Phys Ther. 1999;79:1024 – 1025. 10 Rothstein JM. Editor’s response to: Dewey D. What evidence [letter to the editor]? Phys Ther. 2000;80:112–115. 11 Rothstein JM. Autonomous practice or autonomous ignorance [editorial]? Phys Ther. 2001;81:1620 –1621. 12 Turner P. Evidence based practice and physiotherapy in the 1990’s. Physiother Theory Pract. 2001;17:107–121. 13 Turner P, Whitfield T. Physiotherapists’ use of evidence based practice: a crossnational study. Physiother Res Int. 1997; 2:17–29. 14 Turner P, Whitfield T. Physiotherapists’ reasons for selection of treatment techniques: a cross-national survey. Physiother Theory Pract. 1999;15:235–246. 15 Michels E. The 1969 Presidential Address. Phys Ther. 1969;49:1191–1200. 16 Barnard S, Wiles R. Evidence-based physiotherapy: physiotherapists’ attitudes and experiences in the Wessex area. Physiotherapy. 2001;87:115–124. 17 Bithell C. Evidence-based physiotherapy: some thoughts on “best evidence.” Physiotherapy. 2000;86:58 – 60. 18 Harrison M. Evidence-based practice: practice-based evidence. Physiother Theory Pract. 1996;12:129 –130. 19 Jette AM. Invited commentary on: “A quantitative analysis of research publications in physical therapy journals.” Phys Ther. 2003;83:131–132. 20 Jette DU, Bacon K, Batty C, et al. Evidencebased practice: beliefs, attitudes, knowledge, and behaviors of physical therapists. Phys Ther. 2003;83:786 – 805. 21 Morris J. Evidence based practice: the way forward. Physiotherapy. 2003;89: 330 –331.

Volume 89

Number 9

Physical Therapy f

929

Evidence-Based Practice in Pediatric Physical Therapy 22 Wakefield A. Evidence-based physiotherapy: the case for pragmatic randomized controlled trials. Physiotherapy. 2000;86: 394 –396. 23 Campbell E. The purpose of research. Physiotherapy. 1970;6:480 – 481. 24 Hislop HJ. Tenth Mary McMillan Lecture: The not-so-impossible dream. Phys Ther. 1975;55:1069 –1080. 25 Piper M. Physiotherapy and research: future visions. Physiother Can. 1991;43:7– 10. 26 Sherrington C, Moseley A, Herbert R, Maher C. Evidence-based practice. Physiother Theory Pract. 2001;17:125–126. 27 Basmajian JV. Research or retrench: the rehabilitation professions challenged. Phys Ther. 1975;55:607– 610. 28 APTA Vision 2020. Available at: http:// www.apta.org/AM/Template.cfm?Section⫽ Vision_20201&Template⫽/TaggedPage/ TaggedPageDisplay.cfm&TPLID⫽285& ContentID⫽32061. 29 O’Brien MA. Keeping up to date: continuing education improvement strategies and evidence-based physiotherapy practice. Physiother Theory Pract. 2001;17: 187–199. 30 Walker-Dilks C. Searching the physiotherapy evidence-based literature. Physiother Theory Pract. 2001;17:137–142. 31 Cormack J. Evidence-based practice: what is it and how do I do it? J Orthop Sports Phys Ther. 2002;32:484 – 487. 32 Haynes R, Devereaux P, Guyatt G. Physicians’ and patients’ choices in evidencebased practice [editorial]. Br Med J. 2002; 324:1350. 33 Davis D, Evans M, Jadad A, et al. The case for knowledge translation: shortening the journey from evidence to effect. Br Med J. 2003;327:33–35. 34 National Center for the Dissemination of Disability Research. A Review of the Literature on Dissemination and Knowledge Utilization. Austin, TX: Southwest Educational Development Laboratory; 1996:1– 37. 35 Hutchinson J, Huberman M. Knowledge Dissemination and Utilization in Science and Mathematics Education: A Literature Review. Arlington, VA: National Science Foundation; 1993. 36 Redfern S, Christian S. Achieving change in health care practice. J Eval Clin Pract. 2003;9:225–238. 37 Armstrong R, Waters E, Crockett B. The nature of evidence resources and knowledge translation for health promotion practitioners. Health Promotion International. 2007;22:254 –260. 38 Bohannon RW. Information accessing behaviour of physical therapists. Physiother Theory Pract. 1990;6:215–225. 39 Kamwendo K. What do Swedish physiotherapists feel about research? A survey of perceptions, attitudes, intentions, and engagement. Physiother Res Int. 2002;7:23– 34.

930

f

Physical Therapy

Volume 89

40 Parker-Taillon D. CPA initiatives put the spotlight on evidence-based practice in physiotherapy. Physiother Can. 2002; Winter:12–15. 41 Scherer S, Smith M. Teaching evidencebased practice in academic and clinical settings. Cardiopulmonary Physical Therapy. 2002;13:23–27. 42 Schreiber J, Stern P, Marchetti G, et al. School-based pediatric physical therapists’ perspectives on evidence-based practice. Pediatr Phys Ther. 2008;20:292–302. 43 Metcalfe C, Lewin R, Wisher S, et al. Barriers to implementing the evidence base in four NHS therapies: dietitians, occupational therapists, physiotherapists, speech and language therapists. Physiotherapy. 2001;87:433– 441. 44 Pomeroy V, Tallis R, Stitt E. Dismantling some barriers to evidence-based practice with hands-on clinical research secondments: initial development. Physiotherapy. 2003;89:266 –275. 45 Klassen T, Jadad A, Moher D. Guides for reading and interpreting systematic reviews. Arch Pediatr Adolesc Med. 1998; 152:700 –704. 46 Stevenson K, Lewis M, Hay E. Do physiotherapists’ attitudes towards evidencebased practice change as a result of an evidence-based educational program? J Eval Clin Pract. 2004;10:207–217. 47 Forsetlund L, Bradley P, Forsen L, et al. Randomised controlled trial of a theoretically grounded tailored intervention to diffuse evidence-based public health practice [ISRCTN23257060]. BMC Med Educ. 2003;3:2. 48 Taylor RS, Reeves BC, Ewings PE, Taylor RJ. Critical appraisal skills training for health care professionals: a randomized controlled trial [ISRCTN46272378]. BMC Med Educ. 2004;4:30. 49 Davis D, O’Brien M, Freemantle N, et al. Impact of formal continuing medical education: do conferences, workshops, rounds, and other traditional continuing education activities change physician behavior or health care outcomes? JAMA. 1999;282:867– 874. 50 Grimshaw J, Shirran L, Thomas R, et al. Changing provider behavior: an overview of systematic reviews of interventions. Med Care. 2001;39(suppl 2):II 2–II 45. 51 Coomarasamy A, Khan K. What is the evidence that postgraduate teaching in evidence-based medicine changes anything? A systematic review. Br Med J. 2004;329:1017–1022. 52 McCluskey A, Lovarini M. Providing education on evidence-based practice improved knowledge but did not change behaviour: a before and after study. BMC Med Educ. 2005;5:40. 53 Bero L, Grilli R, Grimshaw J, et al. Closing the gap between research and practice: an overview of systematic reviews of interventions to promote the implementation of research findings. Br Med J. 1998;317: 465– 468.

Number 9

54 Bekkering G, Hendriks H, van Tulder M, et al. Effect on the process of care of an active strategy to implement clinical guidelines on physiotherapy for low back pain: a cluster randomised controlled trial. Qual Saf Health Care. 2005;14:107–112. 55 Carr J, Mungovan S, Shepherd R, et al. Physiotherapy in stroke rehabilitation: bases for Australian physiotherapists’ choice of treatment. Physiother Theory Pract. 1994;10:201–209. 56 Connolly B, Lupinnaci M, Bush A. Changes in attitudes and perceptions about research in physical therapy among professional physical therapist students and new graduates. Phys Ther. 2001;81:1127–1134. 57 Rappolt S, Tassone M. How rehabilitation therapists gather, evaluate, and implement new knowledge. J Contin Educ Health Prof. 2002;22:170 –180. 58 Patton M. Qualitative Research and Evaluation Methods. 3rd ed. Thousand Oaks, CA: Sage Publications; 2002. 59 Hall B. Participatory research, popular knowledge, and power: a personal reflection. Convergence. 1981;6 –19. 60 Herr K, Anderson G. The Action Research Dissertation: A Guide for Students and Faculty. Thousand Oaks, CA: Sage Publications; 2005. 61 White G, Suchowierska M, Campbell M. Developing and systematically implementing participatory action research. Arch Phys Med Rehabil. 2004;85(suppl 2):S3– S12. 62 Kelly P. Practical suggestions for community interventions using participatory action research. Public Health Nurs. 2005; 22:65–73. 63 Atwal A. Getting the evidence into practice: the challenges and successes of action research. Br J Occup Ther. 2002;65: 335–341. 64 Foster N, Barlas P, Chesterton L, Wong J. Critically-appraised topics (CATs): one method of facilitating evidence-based practice in physiotherapy. Physiotherapy. 2001;87:179 –190. 65 Ottenbacher K, Cusick A. Goal attainment scaling as a method of clinical service evaluation. Am J Occup Ther. 1989;44:519 – 525. 66 Kiresuk T, Sherman R. Goal attainment scaling: a general method for evaluating comprehensive community mental health programs. Community Mental Health Journal. 1968;4:443– 453. 67 Boothroyd R, Banks S. Assessing outcomes in individually-tailored interventions. Lancet. 2006;367:801– 802. 68 Hurn J, Kneebone I, Cropley M. Goal setting as an outcome measure: a systematic review. Clin Rehabil. 2006;20:756 –772. 69 Ekstrom Ahl L, Johansson E, Granat T, Brogran Carlberg E. Functional therapy for children with cerebral palsy: an ecological approach. Dev Med Child Neurol. 2005; 47:615– 619. 70 Fisher K, Hardie R. Goal attainment scaling in evaluating a multidisciplinary pain management programme. Clin Rehabil. 2002; 16:871– 877.

September 2009

Evidence-Based Practice in Pediatric Physical Therapy 71 Tennant S, Field R. Continuing professional development: does it make a difference? Nurs Crit Care. 2004;9:167–172. 72 Strauss A, Corbin J. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. 2nd ed. Thousand Oaks, CA: Sage Publications; 1998. 73 Gosling AS, Westbrook JI. Allied health professionals’ use of online evidence: a survey of 790 staff working in the Australian public hospital system. Int J Med Inform. 2004;73:391– 401. 74 Higgs J, Jones M. Clinical Reasoning in the Health Professions. 2nd ed. Oxford, United Kingdom: Butterworth-Heinemann; 2000. 75 Embrey D, Guthrie M, White O, Dietz J. Clinical decision making by experienced and inexperienced pediatric physical therapists for children with diplegic cerebral palsy. Phys Ther. 1996;76:20 –33.

76 Jensen GM, Gwyer J, Hack LM, Shepard KF. Expertise in Physical Therapy. Oxford, United Kingdom: Butterworth-Heinemann; 2000. 77 Jensen GM, Gwyer J, Shepard KF, Hack LM. Expert practice in physical therapy. Phys Ther. 2000;80:28 –52. 78 Resnik L, Jensen GM. Using clinical outcomes to explore the theory of expert practice in physical therapy. Phys Ther. 2003;83:1090 –1106. 79 Palisano R. Evidence-based decision making [editorial]. Phys Occup Ther Pediatr. 2007;27:1–3. 80 Carter R, Stoecker J. Descriptors of American Physical Therapy Association physical therapist members’ reading of professional publications. Physiother Theory Pract. 2006;22:263–278. 81 Iles R, Davidson M. Evidence-based practice: a survey of physiotherapists’ current practice. Physiother Res Int. 2006;11:93– 103.

82 Palfreyman S, Tod A, Doyle J. Comparing evidence-based practice of nurses and physiotherapists. Br J Nurs. 2003;12:246 – 253. 83 Kawamoto K, Houlihan C, Balas E, Lobach D. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. Br Med J. 2005;330:765–772. 84 Landers M, McWhorter J, Krum L, Glovinsky D. Mandatory continuing education in physical therapy: survey of physical therapists in states with and without a mandate. Phys Ther. 2005;85:861– 871.

Appendix 1. Evidence-Based Practice Workshop Objectives

After participating in the workshop (including follow-up activities), attendees will be able to: 1. Define evidence-based practice 2. Discuss the relevance of “evidence” and evidence-based practice to pediatric physical therapy 3. Distinguish between a background question and a foreground question 4. Develop a clinical question in the patient/intervention/comparison/outcome format 5. Identify and access appropriate resources for obtaining research evidence relating to physical therapist practice 6. Use American Physical Therapy Association resources, Internet resources, or both to develop an evidence-based answer to a clinical question 7. Understand basic research and statistics terminology 8. Use understanding of research and statistics to analyze the strength of evidence a. Diagnosis, prognosis, and intervention evidence b. Levels of evidence and grades of recommendation c. American Academy of Cerebral Palsy and Developmental Medicine ranking system for group and single-subject designs 9. Formulate the answer to the clinical question into a critically appraised topic document or Matrix spreadsheet 10. Apply the results of clinical research to physical therapist practice

September 2009

Volume 89

Number 9

Physical Therapy f

931

Evidence-Based Practice in Pediatric Physical Therapy Appendix 2. Participants’ Evidence-Based Practice (EBP) Rankings and Goal Attainment Scaling (GAS) Scoresa EBP Ranking Participant K

Baseline 2

P

8

R

1

A

7

GAS Scores

Final 3

8.5

4.5

8

–2

–1

0

ⴙ1

ⴙ2

Read 1 research article every 2 months

Read 1 research article every month

Read 2 research articles every month

Read 3 research articles every month

Read more than 3 research articles every month

Rarely, if ever, incorporate ideas from research articles

Incorporate new idea from research article for 1 child on caseload

Incorporate new idea from research article for 2 children on caseload

Incorporate new idea from research article for 3 children on caseload

Incorporate new idea from research article for more than 3 children on caseload

Staff will use EBM in 0% of caseload evaluations and treatments





EBM will be used in 50% of my evaluations and ongoing treatment





Read an article occasionally

Read 1 article every 2 months

Read 1 article per month

Read 2 articles per month

Read 3 articles per month

Rarely use new information from articles

Use new information for 1 child on caseload

Use new information for 3 children on caseload

Use new information for 4 children on caseload

Use new information for more than 4 children on caseload

Getting none of my colleagues to participate more in using research articles for treatment skills

Getting 1 of my colleagues to use research articles 1 time by November 1 for treatment

Getting 1 of my colleagues to use 2 research articles 1 time by November 1 for treatment

Getting 2 of my colleagues to use 1 research article for treatment

Getting 2 of my colleagues to use 2 research articles for treatment

Not searching for a research article to find a new evaluation tool for school-based pediatrics

Finding only 1 research article

Finding 1 research article and putting it to use

Finding 2 research articles for the same evaluation tool to see which is more appropriate for school-based physical therapy

Sharing my research with 1 colleague to determine which evaluation tool would be more appropriate in the school system

Rarely searching for or using research articles for evaluation skills

Search for and obtain 1 new journal article to use for evaluation skills

Search for and obtain 2 new journal articles to use for evaluation skills

Search for and obtain 3 new journal articles to use for evaluation skills

Search for and obtain at least 3 new journal articles to use for evaluation skills

Rarely searching for or using research articles for treatment skills

Search for and obtain 1 new journal article to use for treatment skills

Search for and obtain 2 new journal articles to use for treatment skills

Search for and obtain 3 new journal articles to use for treatment skills

Search for and obtain at least 2 new journal articles to use for treatment skills (Continued)

932

f

Physical Therapy

Volume 89

Number 9

September 2009

Evidence-Based Practice in Pediatric Physical Therapy Appendix 2. Continued EBP Ranking Participant L

a

Baseline

Final

3

4

GAS Scores ⴙ1

ⴙ2

Have a minimal understanding of statistics and statistical analysis

Have a basic understanding of common statistical terms

Able to complete statistical analysis on an article

Analyze the statistics and quality of a research article in order to assign a “level of evidence” to the article

Regularly (at least once a week) apply the results of a research article to clinical practice based on an analysis of the quality of the research

Choose 1 common area of treatment in the school/ academic school year, research and implement based on EBP

Choose 1 common area of treatment in the school/ academic school year (half year), research and implement based on EBP

Choose 1 common area of treatment in the school/ academic school year (per month), research and implement based on EBP

Choose 1 common area of treatment in the school/ academic school year (every 2 weeks), research and implement based on EBP

Choose 1 common area of treatment in the school/ academic school year (weekly), research and implement based on EBP

Use evidence-based treatment on 0% of caseload





–2

–1

0

All baseline GAS scores are in the –2 column; shaded cells represent the final GAS score for each participant. EBM⫽evidence-based medicine.

Appendix 3. Constraints and Influences on Clinical Decisions in the School Setting

● Input and goals from the child and family ● Data collected from the child during the examination and the intervention ● Cognitive, behavioral, and motor skill levels of the child ● Response of the child to the intervention (trial and error); boredom and motivation (over the course of the entire school year) ● School environment (eg, amount of space, equipment, school schedule, and availability of adaptive physical education) ● Skills and knowledge of the teacher(s) and classroom staff ● Other professionals in the educational setting (eg, occupational therapists and adaptive physical education teachers) ● Individualized education plan and related service status

September 2009

Volume 89

Number 9

Physical Therapy f

933

Research Report Rehabilitation After Hallux Valgus Surgery: Importance of Physical Therapy to Restore Weight Bearing of the First Ray During the Stance Phase Reinhard Schuh, Stefan G. Hofstaetter, Samuel B. Adams Jr, Florian Pichler, Karl-Heinz Kristen, Hans-Joerg Trnka R. Schuh, CM, is Research Fellow, Gait Analysis Laboratory, Foot and Ankle Center Vienna, Alserstrasse 43/8D, 1080 Vienna, Austria. Address all correspondence to Mr Schuh at: [email protected]. S.G. Hofstaetter, MD, is Senior Resident, Department of Orthopaedic Surgery, Klinikum WelsGrieskirchen, Grieskirchnerstrasse 43, Wels, Austria. S.B. Adams Jr, MD, is Senior Resident, Division of Orthopaedic Surgery, Duke University Medical Center, Durham, North Carolina. F. Pichler, PT, is affiliated with Foot and Ankle Center Vienna. K.-H. Kristen, MD, is Senior Surgeon, Foot and Ankle Center Vienna. H.-J. Trnka, MD, PhD, is Associate Professor of Orthopaedic Surgery, Foot and Ankle Center Vienna. [Schuh R, Hofstaetter SG, Adams SB Jr, et al. Rehabilitation after hallux valgus surgery: importance of physical therapy to restore weight bearing of the first ray during the stance phase. Phys Ther. 2009;89: 934 –945.] © 2009 American Physical Therapy Association

Background. Operative treatment of people with hallux valgus can yield favorable clinical and radiographic results. However, plantar pressure analysis has demonstrated that physiologic gait patterns are not restored after hallux valgus surgery. Objective. The purpose of this study was to illustrate the changes of plantar pressure distribution during the stance phase of gait in patients who underwent hallux valgus surgery and received a multimodal rehabilitation program.

Design. This was a prospective descriptive study. Methods. Thirty patients who underwent Austin (n⫽20) and scarf (n⫽10) osteotomy for correction of mild to moderate hallux valgus deformity were included in this study. Four weeks postoperatively they received a multimodal rehabilitation program once per week for 4 to 6 weeks. Plantar pressure analysis was performed preoperatively and 4 weeks, 8 weeks, and 6 months postoperatively. In addition, range of motion of the first metatarsophalangeal joint was measured, and the American Orthopaedic Foot and Ankle Society (AOFAS) forefoot questionnaire was administered preoperatively and at 6 months after surgery.

Results. The mean AOFAS score significantly increased from 60.7 points (SD⫽ 11.9) preoperatively to 94.5 points (SD⫽4.5) 6 months after surgery. First metatarsophalangeal joint range of motion increased at 6 months postoperatively, with a significant increase in isolated dorsiflexion. In the first metatarsal head region, maximum force increased from 117.8 N to 126.4 N and the force-time integral increased from 37.9 N䡠s to 55.6 N䡠s between the preoperative and 6-month assessments. In the great toe region, maximum force increased from 66.1 N to 87.2 N and the force-time integral increased from 18.7 N䡠s to 24.2 N䡠s between the preoperative and 6-month assessments. Limitations. A limitation of the study was the absence of a control group due to the descriptive nature of the study. Conclusions. The results suggest that postoperative physical therapy and gait training may lead to improved function and weight bearing of the first ray after hallux valgus surgery.


f

Physical Therapy

Volume 89

Number 9

September 2009

Rehabilitation After Hallux Valgus Surgery

H

allux valgus deformity remains one of the most common and disabling pathologies of the foot. A myriad of potential therapeutic interventions have been described for treating people with symptomatic hallux valgus, including bracing, soft-tissue procedures, and a number of different osteotomies.1–3 The purpose of operative correction of the deformity by an osteotomy of the first metatarsal is to reduce the malalignment of the first ray, thereby restoring its function in weight bearing and ambulation.4 Operative correction has yielded good to excellent results.5–12 However, recent plantar pressure distribution analyses indicate that, despite improvement of clinical and radiographic parameters, restoration of function of the first ray and great toe does not occur.8,13–17 Kernozek and Sterikker17 found decreased 1-year peak pressures and force-time integrals (impulse) in the great toe region compared with the preoperative values. They concluded that physical therapy may help to restore great toe function after the Austin procedure. In a prospective pressure distribution study, Bryant et al13 found decreased load beneath the hallux 1 year after the Austin procedure compared with preoperative levels. They did not find any changes

Available With This Article at www.ptjournal.org • eAppendix: Rehabilitation Program After Hallux Valgus Surgery • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on July 16, 2009, at www.ptjournal.org.

September 2009

of plantar pressure parameters on the second, third, and fourth metatarsals after surgery. Guesgen et al18 reported that, at a mean of 3 years after chevron osteotomy, 56% of the patients did not use their great toe for push-off. Jones et al8 found decreased peak pressures 20 months after scarf osteotomy in the region of the first metatarsal head compared with the preoperative values. Dhukaram et al15 found decreased load under the hallux after scarf and Mitchell osteotomies compared with individuals with absence of any foot pathology. Because the first ray is the most heavily loaded structure of the foot during gait, proper weight bearing is essential for physiologic gait patterns.19,20 Lateral deviation of the great toe and subluxation of the sesamoids represent pathomorphologic characteristics of hallux valgus deformity.21 These changes alter kinematics of the first metatarsophalangeal (MTP) joint, leading to reduced strength (force-generating capacity) of the plantar flexors.22 Plantar pressure studies revealed that the great toe assumes a diminishing role in weight bearing of the forefoot. In addition to the lateral transfer of forces, the center of pressure shifts laterally.23–25 Therefore, several authors26 –28 have mentioned decreased weight bearing of the great toe during gait as the reason for lesser toe metatarsalgia. The results of plantar pressure distribution assessments performed after hallux valgus surgery suggest that structural correction of the pathobiomechanics alone is not sufficient to restore forefoot function.8,13,15,16 –18 Postoperative physical therapy is a well-established method to restore function after surgical intervention for disorders of the musculoskeletal system. The benefits of postoperative physical therapy have been reported for nearly all orthopedic surgery

subspecialties.29 –33 More applicable to this report, it has been shown that postoperative physical therapy for hindfoot surgical procedures improves postoperative function.34 However, there is a paucity of literature describing the effect of physical therapy on the functional outcome of forefoot surgery. Shamus et al35 reported good functional improvement in patients with hallux limitus when they underwent a special physical therapy program including sesamoid mobilization, flexor hallucis muscle strengthening, and gait training. These results indicate that physical therapy and gait training help to restore physiologic kinematics in the affected first MTP joint. Therefore, we hypothesized that physical therapy would improve function following surgical correction of symptomatic hallux valgus. The purpose of this prospective descriptive study was to illustrate the changes of plantar pressure distribution during the stance phase of gait in patients who underwent hallux valgus surgery and received a multimodal rehabilitation program.

Method Participants Prospective participants were referred to the study by a fellowshiptrained foot and ankle surgeon on the basis of mild to moderate hallux valgus deformity without radiographic signs of osteoarthritis of the first MTP joint. Between October 2006 and December 2007, 30 patients were included in this study. All patients complained of pain in the region of the first MTP joint. Demographics of the participants are shown in Table 1. None of the participants had evidence of lowerextremity malalignment (eg, genu valgum, genu varum) or any other pathologic conditions on the musculoskeletal system that might influence gait patterns (eg, low back pain; disk herniations; spondyloar-

Volume 89

Number 9

Physical Therapy f

935

Rehabilitation After Hallux Valgus Surgery Table 1.

sion at the medial aspect of the first MTP joint, as well as a dorsal skin incision at the first web space. The V-shaped osteotomy is performed with a sagittal oscillating saw, and afterward the distal fragment is shifted laterally to realign the first metatarsal. In the present study, fixation was performed by inserting an oblique compression screw (Charlotte Multi Use Compression Screw*) from dorsomedial to plantarlateral.

Demographic Characteristics of the Participants (N⫽30) Characteristic

Measurement

Sex Male

2

Female

28

Type of osteotomy Austin

20

Scarf

10

Age (y) X

58.4

SD

13.8

Range

22–79

The scarf osteotomy is a diaphyseal Z-shaped osteotomy of the first metatarsal shaft.7–9,37,38 The operative area is explored through the same incisions as described for the Austin osteotomy. The osteotomy is performed using the oscillating saw. Correction of the deformity is provided by pushing the distal fragment laterally. Fixation was performed with the same screw used for the Austin osteotomy. This screw was inserted in a dorsal to plantar direction.

Height (cm) 166.3

X SD

0.1

Range

152.0–178

Weight (kg) X

64.8

SD

8.9

Range

49–88

Body mass indexa X

23.4

SD

2.9

Range

17.8–31.6

Foot size (French) 38.5

X SD

1.3

Range

36–42

a

Body mass index calculated as weight in kilograms divided by the square of the height in meters.

thritis or osteoarthritis of the hip, knee, ankle, subtalar, transverse tarsal, or Lisfranc joints). The operations were performed by a single surgeon (H.J.T.), as previously described by Kristen et al9 and Trnka et al,12 in an ambulatory surgery center setting. Briefly, the Austin osteotomy is a distal V-shaped osteotomy of the first metatarsal combined with a release of the contractile aspects of the lateral joint capsule of the MTP joint.36 The operative area is explored through a median skin inci936

f

Physical Therapy

Volume 89

view Board. The rights of the participants were protected all the times. All measurements were taken by an independent observer who was neither the operating surgeon nor a physical therapist. The measurements included pedobarographic analysis and functional assessment using the metatarsophalangealinterphalangeal score of the American Orthopaedic Foot and Ankle Society (AOFAS), as well as measurements of range of motion (ROM) of the first MTP joint according to the criteria of the AOFAS.39,40 The AOFAS score and ROM of the first MTP joint were evaluated preoperatively and 6 months after surgery. Plantar pressure analyses were performed preoperatively and 4 weeks, 8 weeks, and 6 months after surgery.

Measurements Prior to collecting data, all participants signed an informed consent form approved by the Foot and Ankle Center Vienna Institutional Re-

Plantar Pressure Analysis The plantar loading parameters were assessed using a capacitive pressure measurement platform (emed-at platform†). The platform has a total area of 610 ⫻ 323 mm enclosing a 240- ⫻ 380-mm sensor area. It includes a total of 1,760 sensors, providing a resolution of 2 sensors per square centimeter. The sampling rate of the platform was fixed at 60 Hz and automatically triggered upon first contact. The pressure threshold is 10 kPa, with plantar pressures ranging up to 1,270 kPa. The platform has a maximum measurable force of 67,000 N, with a hysteresis of ⬍3%. Because of the 18-mm depth of the platform, the test arrangement enclosed the whole platform in the center of a polyethylene ramp with a length of 7 m. Participants were able to cross the platform in both directions. The validity, reliability, and repeatability of the EMED system† have been investigated previously.41– 43 According to Hughes et al,41 the coefficients of reliability (Pearson r)

* Wright Medical Technology Inc, 5677 Airline Rd, Arlington, TN 38002.

† Novel GmbH, Ismaniger Strasse 51, 81675 Munich, Germany.

Participants underwent the scarf osteotomy when their intermetatarsal angle was more than 16 degrees and underwent the Austin osteotomy when it was less than 16 degrees. The intermetatarsal angle is measured on weight-bearing anterior-posterior radiographs of the foot. The intermetatarsal angle was determined from the longitudinal axes of the first and second metatarsals. This angle is the main indicator of the degree of the deformity.3,21,39 To avoid the specific influence of a single surgical method, patients with both operations were included in this study.

Number 9

September 2009

Rehabilitation After Hallux Valgus Surgery range from .914 to .988 for the parameters that were evaluated in the present study if 5 steps are recorded. In order to provide valid and reliable results, the mid-gait method was chosen for this study. This method requires the individual to walk across a walkway while pressure data are collected from a single foot contact over the sensor platform. This method allows recording of measurements during free movement and thus ensures that the effect of acceleration and deceleration at the start and end of each walk is minimized. Putti et al42 investigated the repeatability of measurements of the EMED system by having patients walk at normal speed on 2 separate occasions, approximately 12 days apart. In the present study, the participants were told to walk at normal speed and to keep their speed constant. Data were collected and stored for analysis. Analysis of the records was performed with the emed/D software.†,44 An average of the 5 data sets was calculated by the software, and the foot was divided into geometric regions of interest according to the anatomical areas of the great toe, second toe, first metatarsal head, and second metatarsal head, as well as the total foot (Fig. 1). The following variables for each region were generated by the software: peak pressure (in kilopascals), maximum force (in newtons), contact area (in square centimeters), contact time (in milliseconds), and force-time integral (in newtons per second). Measurements of plantar pressure provide an indication of foot and ankle function during gait. Data obtained from plantar pressure assessment can be used for the evaluation and treatment of patients with foot disorders. In the present study, plantar pressure measurements were performed to investigate changes in gait before and in the postoperative peSeptember 2009

Figure 1. Plantar pressure image with regions of interest: total foot, first metatarsal head (MH1), second metatarsal head (MH2), big toe, and second toe.

Volume 89

Number 9

Physical Therapy f

937

Rehabilitation After Hallux Valgus Surgery riod after hallux valgus surgery with respect to the functional restoration of the operated area.45 Pressure (measured in pascals) is defined as force (measured in newtons)/ area (measured in square meters).46 Peak pressure in the assessment of dynamic plantar pressure distribution is defined as the greatest pressure that is applied to the ground during the stance phase of gait. Maximum force is defined as the greatest vertical force that acts on a certain area and indicates its load.46 In the present study, maximum force was measured to determine the load changes of certain regions of interest. The force-time integral (impulse) is the area under the curve of a force (ie, time curve).45 These parameters are appropriate for describing the overall loading effects of the foot during the stance phase of gait. Contact time reveals the time of ground contact of either the total foot or certain regions of interest during the stance phase. Contact area is the area of contact of the foot to the supporting surface during the stance phase. The data were not normalized to foot size and weight. The standard deviation reflects between-subject variations.

gion. Participants also received a special sock (Gilofamed㛳) that reduces swelling and the need for dressing changes. The first session of the physical therapy program started 4 weeks after surgery, with one session per week. Physical therapy treatment was performed by 3 licensed physical therapists following the same treatment protocol. In the first session, elevation of the leg, lymphatic drainage, activation of the muscle pump, and cryotherapy (cool packs) were used to reduce the swelling. Participants were told to perform these actions at home once a day for 20 minutes. During gait training, physiologic gait patterns were achieved. The stance phase was trained by performing a heel-strike in its physiological position at the lateral aspect of the 㛳

OFA Austria, Franz-Ofner Strasse, 6620 Salzburg, Austria.

heel,47 followed by weight bearing of the first metatarsal during midstance and terminal stance, with training of active push-off by the great toe flexors, the flexor digitorum longus and brevis muscles, and the lumbrical muscles. Selective strengthening of the peroneus longus muscle also was performed. The function of this muscle is to pronate the midfoot.20,48,49 Pronation is essential for ground contact of the first ray, the most heavily loaded structure of the foot during gait.19 If the peroneus longus muscle is too weak, people compensate by pushing the knee into a valgus position to achieve midfoot pronation. In addition, fascial release techniques for the peroneal muscles as well as to decrease of the tone (velocitydependent resistance to stretch) of the tibialis anterior muscle were performed to improve the interaction of those antagonists.

Rehabilitation Program An Aircast cryo-cuff‡ was applied for 8 hours starting immediately after surgery on the day of the operation and on the first postoperative day. This intervention was conducted as an inpatient treatment. Postoperatively, participants were placed in the Rathgeber postoperative shoe§ for 4 weeks. This shoe allows weight bearing of the operated limp while reducing stress in the forefoot re‡ DonJoy Orthopaedics, ORMED GmbH, Merzhauser Strasse, 112D-79100 Freiburg, Germany. § OFA Bamberg GmbH, Laubanger 20, Bamberg 96052, Germany.

938

f

Physical Therapy

Volume 89

Figure 2. Manual therapeutic intervention at the first metarsophalangeal joint.

Number 9

September 2009

Rehabilitation After Hallux Valgus Surgery Pedobarographic Analysis The results of the plantar pressure assessment are summarized in Table 2 and are illustrated in Figure 4.

Figure 3. Preoperative and postoperative means of the American Orthopaedic Foot and Ankle Society (AOFAS) score. The error bars indicate the standard deviation.

Manual therapeutic interventions were performed for all MTP joints. These manipulations focused on an improvement of flexion and included caudal sliding of the proximal phalanx to improve flexion and dorsal sliding of the proximal phalanx to improve extension (Fig. 2). In addition, oscillating traction was performed to activate the mechanoreceptors that inhibit the afferent pain sensors. The treatment protocol also included mobilization of the first MTP, Lisfranc, transverse tarsal, subtalar, and ankle joints. Concentric strengthening exercises of the great toe flexors and extensors were performed as well. The participants received a mean of 4.4 treatment sessions (range⫽3– 6) based on their individual findings. The sessions took place once a week for 3 to 6 weeks. The duration of the sessions ranged from 35 to 45 minutes. The participants also were instructed to do a marble pick-up exercise, apply cold packs, and do strengthening exercises and gait training at home. A more-detailed description of the rehabilitation program is included in the eAppendix (available at www.ptjournal.org).

September 2009

Data Analysis Student t tests were used to determine whether there was a significant difference between the preoperative and postoperative AOFAS scores and MTP ROM measurements. Repeatedmeasures analyses of variance and Tukey post hoc analyses were used to investigate the changes in plantar pressure parameters at the different time points. Statistical analysis was performed using SPSS version 11.3# as well as Excel for Macintosh.** The level of significance was defined as ␣⬍.05.

Results Twenty-eight patients were available for a complete follow-up. One patient was excluded from the 6-month follow-up examination because of a recent myocardial infarction. Another patient was not able to participate in the 6-month follow-up examination because of a work-related change of his living area. AOFAS Score The mean AOFAS score increased from 60.7 (SD⫽11.9) preoperatively to 94.5 (SD⫽4.5) 6 months after surgery (P⬍.001) (Fig. 3).

# SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606. ** Microsoft Corp, One Microsoft Way, Redmond, WA 98052-6399.

Total Foot The total foot area maximum force, contact time, and force-time integral did not show significant changes between the different examinations. Mean peak pressure decreased from 714.8 kPa (SD⫽195.8) preoperatively to 622.4 kPa (SD⫽228.0) 4 weeks postoperatively (P⫽.003). Six months postoperatively, it reached 687.8 kPa (SD⫽218.7), which was not statistically different from the preoperative value (P⫽.896). The contact area decreased from a preoperative mean value of 118.1 cm2 (SD⫽13.3) to 107.7 cm2 (SD⫽19.5) 4 weeks postoperatively (P⫽.023). Likewise, the contact area demonstrated a statistically significant increase to 118.0 cm2 (SD⫽14.8) 8 weeks after surgery (P⫽.048). By 6 months after surgery, the mean total foot contact area of 119.0 cm2 (SD⫽12.8) was not significantly different from the preoperative value (P⫽.960). First Metatarsal Head Contact time did not show any significant changes for the first metatarsal head. Mean maximum force decreased from 117.8 N (SD⫽48.0) preoperatively to 77.3 N (SD⫽41.9) 4 weeks postoperatively (P⫽.001) and increased to 123.7 N (SD⫽40.6) 8 weeks after surgery (P⬍.001). Mean peak pressure decreased in the same period from 288.9 kPa (SD⫽181.7) to 146.6 kPa (SD⫽73.5) (P⫽.001). Between the preoperative investigation and the assessment 6 months postoperatively, there was no statistically significant difference either for maximum force or for peak pressure (P⫽1.0). Mean contact area decreased between the preoperative assessment and the evaluation 4 weeks after surgery from 11.4 cm2 (SD⫽1.8) to 10.04

Volume 89

Number 9

Physical Therapy f

939

Rehabilitation After Hallux Valgus Surgery Table 2. Resultsa of Plantar Pressure Assessments for Maximum Force (MF), Peak Pressure (PP), Contact Time (CT), Contact Area (CA), and Force-Time Integral (FTI) Parameter

Preoperative

4 Weeks Postoperative

8 Weeks Postoperative

6 Months Postoperative

Total foot MF (N)

722.1⫾101.5 (690.3–766.1)

710.5⫾94.1 (670.7–750.2)

728.3⫾99.6 (694.1–767.5)

719.0⫾87.0 (686.0–753.7)

PP (kPa)

714.8⫾195.8b (649.9–805.7)

622.4⫾228.0 (429.7–600.0)

630.9⫾230.6 (534.0–710.8)

687.8⫾218.7 (603.0–772.5)

CT (ms)

818.4⫾181.7 (768.0–905.3)

934.1⫾132.5 (878.1–990.1)

894.7⫾131.0 (847.5–943.7)

891.1⫾137.7 (837.9–944.5)

CA (cm2)

118.1⫾13.3b (114.7–124.8)

107.7⫾19.5 (99.4–115.9)

118.00⫾14.77 (113.2–123.9)

119.0⫾12.8 (116.7–126.8)

FTI (N䡠s)

430.6⫾93.1 (404.6–480.8)

439.8⫾81.3 (405.5–474.1)

439.5⫾73.2 (415.2–473.8)

431.2⫾82.6 (408.5–480.3)

117.8⫾48.0b (105.6–142.2)

77.3⫾41.9c (59.6–95.0)

b

First metatarsal head MF (N)

123.7⫾40.6 (110.8–142.0)

126.4⫾40.2 (131.2–162.0)

PP (kPa)

288.9⫾181.7 (220.2–350.9)

146.6⫾73.5 (115.6–177.7)

207.2⫾60.8 (189.9–242.8)

287.4⫾153.0 (228.0–346.7)

CT (ms)

613.5⫾134.2 (574.6–675.4)

661.2⫾188.0 (581.8–740.6)

661.3⫾133.2 (612.5–709.9)

661.6⫾135.6 (609.1–714.2)

CA (cm2) FTI (N䡠s)

10.04⫾3.43c (8.6–11.5)

11.4⫾1.8 (10.9–12.2)

c

31.8⫾21.0 (22.9–40.6)

37.9⫾17.5 (34.2–49.5)

12.1⫾2.2 (11.4–13.0)

12.1⫾1.6 (11.4–12.7)

47.5⫾19.5 (40.8–55.1)

55.6⫾22.3 (46.9–64.3)

Second metatarsal head 118.1⫾51.0c (96.5–139.6)

173.1⫾54.0 (154.3–193.7)

185.8⫾41.9 (169.6–202.1)

PP (kPa)

b

614.2⫾217.1 (536.3–719.3)

325.8⫾212.7c (236.0–415.6)

519.0⫾255.2 (423.9–614.7)

584.4⫾246.2 (488.9–679.7)

CT (ms)

685.0⫾150.1 (638.6–751.6)

736.8⫾135.3 (670.7–793.9)

689.4⫾119.2 (647.0–736.0)

661.6⫾135.6 (578.1–1,019.1)

MF (N)

169.4⫾37.1b,d (157.4–188.9)


9.6⫾1.3 (9.3–10.2)

8.6⫾2.4 (7.6–9.7)

9.9⫾1.7 (9.3–10.5)

62.4⫾16.7 (58.0–73.5)

c

50.3⫾21.1 (41.4–59.2)

71.1⫾22.8 (62.2–79.7)

66.1⫾33.2b (57.0–83.2)

28.4⫾31.5 (15.1–51.7)

51.7⫾47.3e (33.2–67.6)

10.3⫾1.4 (9.8–10.7) 74.7⫾21.1 (66.5–82.9)

Big toe MF (N)

b

87.2⫾37.3 (72.8–101.7)

PP (kPa)

357.9⫾198.7 (301.4–451.2)

114.9⫾131.0 (59.6–170.2)

190.0⫾200.1 (117.9–265.4)

322.4⫾200.6 (244.6–400.0)

CT (ms)

548.8⫾138.3b (516.0–633.4)

363.7⫾262.3 (253.0–474.5)

437.7⫾201.0 (346.7–504.3)

533.6⫾161.8 (470.8–596.3)


5.09⫾3.1c (3.8–6.4)

7.3⫾2.1b,d (6.7–8.3) b

18.7⫾10.7 (16.0–25.6)

7.4⫾10.6 (2.9–11.9)

7.4⫾2.4e (6.5–8.2) e

16.6⫾11.3 (6.7–17.0)

9.2⫾1.5 (8.6–9.7) 24.2⫾13.7 (18.9–29.5)

Second toe MF (N)

23.6⫾15.4b (18.3–31.1)

10.4⫾11.2 (5.7–15.2)

15.5⫾12.1 (11.4–22.3)

20.8⫾16.6 (14.4–27.2)

PP (kPa)

150.6⫾83.2b (122.8–188.2)

68.9⫾56.8 (44.6–92.8)

103.5⫾66.5 (80.1–136.0)

135.7⫾90.0 (101.0–170.4)

CT (ms)

445.9⫾131.4 (417.4–522.9)

398.0⫾138.1 (361.2–466.0)

408.0⫾160.5 (345.8–470.3)


3.4⫾1.4b (3.0–4.0) 5.8⫾3.9 (4.6–7.7)

396.9⫾241.8 (294.9–499.0) 2.3⫾1.3 (1.7–2.8)

2.8⫾1.2 (2.4–3.3)

3.1⫾1.1 (2.7–3.5)

c

3.9⫾3.9 (2.7–5.7)

5.3⫾5.5 (3.0–7.3)

2.5⫾3.7 (1.1–5.3)

a

Results are expressed as mean⫾SD, with confidence interval (CI) in parentheses. b Statistically significant change at P⬍.05, preoperative assessment to 4-week postoperative assessment. c Statistically significant change at P⬍.05, 4-week assessment to 8-week postoperative assessment. d Statistically significant change at P⬍.05, preoperative assessment to 6-month postoperative assessment. e Statistically significant change at P⬍.05, 8-week assessment to 6-month postoperative assessment.

cm2 (SD⫽3.43) (P⫽.08) and increased to 12.1 cm2 8 weeks after surgery (P⫽.06). The force-time integral increased from a mean of 31.8 N䡠s 4 weeks postoperatively to 47.5 N䡠s 8 weeks postoperatively (P⫽.026). It increased from 37.9 N䡠s preoperatively to 55.6 N䡠s 6 months after surgery (P⫽.062). However, 940

f

Physical Therapy

Volume 89

this increase was not statistically significant. Second Metatarsal Head Maximum force, peak pressure, and force-time integral showed statistically significant decreases between the preoperative evaluation and the assessment 4 weeks after surgery

Number 9

(P⬍.001, P⬍.001, P⫽.047, respectively) and significant increases between the evaluation 4 weeks after surgery and the assessment 8 weeks after surgery (P⬍.001, P⫽.021, P⫽.003, respectively).

September 2009

Rehabilitation After Hallux Valgus Surgery Contact time did not show any statistically significant changes. Second Toe In the second toe, the maximum force, peak pressure, and contact area decreased significantly between the preoperative evaluation and the assessment 4 weeks after surgery (P⫽.005, P⫽.001, P⫽.003, respectively). There were no statistically significant changes for force-time integral or contact time.

Figure 4. Regional force changes in the treated feet: preoperative (gray), 4 weeks postoperative (green), 8 weeks postoperative (blue), and 6 months postoperative (orange).

Great Toe In the great toe, maximum force, peak pressure, contact area, and force-time integral decreased significantly between the preoperative evaluation and the assessment at 4 weeks following surgery (Pⱕ.001). The mean contact area showed a statistically significant increase from 5.09 cm2 (SD⫽3.1) 4 weeks after surgery (P⫽.001) to 7.4 cm2 (SD⫽2.4) 8 weeks after surgery (P⫽.003) and 9.2 cm2 (SD⫽1.5) 6 months after surgery (P⫽.017). The difference be-

tween the preoperative examination and the assessment 6 months after surgery was statistically significant (P⫽.034). Mean values for maximum force were 66.1 N (SD⫽33.2) preoperatively and 87.2 N (SD⫽37.3) 6 months after surgery (P⫽.320). Average force-time integral was 18.7 N䡠s (SD⫽10.7) before surgery and reached 24.2 N䡠s (SD⫽13.7) (P⫽.752) 6 months postoperatively.

First MTP Joint ROM Mean total ROM of the first MTP joint increased from 68.9 degrees (SD⫽ 11.9, range⫽40 –90) preoperatively to 73.3 degrees (SD⫽21.4, range⫽ 30 –150) 6 months after surgery. This improvement was not statistically significant (P⫽.31). However, mean dorsiflexion significantly increased from 40.4 degrees (SD⫽9.0, range⫽25– 60) preoperatively to 45.9 degrees (SD⫽14.0, range⫽ 20 – 80) 6 months after surgery (P⬍.05). Mean plantar flexion was 28.5 degrees (SD⫽6.9, range⫽15– 40) preoperatively and 27.4 degrees (SD⫽11.5, range⫽5– 45) 6 months after surgery. This difference was not statistically significant (P⫽.44) (Fig. 5).

Discussion

Figure 5. Range of motion (ROM) assessment: changes (in degrees) in plantar flexion, dorsiflexion, and overall ROM of the first metarsophalangeal joint.

September 2009

In our study, plantar pressure distribution was assessed in patients who underwent hallux valgus surgery and received postoperative physical therapy and gait training. In general, loading parameters in the great toe region and the region of the first metatarsal head did not decrease between the preoperative examination and the assessment at 6 months after surgery. Several authors8,13–17 have studied changes in plantar pressure distribution after hallux valgus surgery and found decreased loading parameters in the hallux and the first metatarsal head region after surgery. To the best of our knowledge, the postoperative regimens in those

Volume 89

Number 9

Physical Therapy f

941

Rehabilitation After Hallux Valgus Surgery studies did not include physical therapy and gait training, although Kernozek and Sterriker17 concluded that the inclusion of physical therapy and gait training would improve the functional outcome. Plantar pressure distribution measurements are a proper method to assess the functional outcome of hallux valgus surgery. This method was first recommended in 1956 by Barnett.50 Henry et al, in 1975, were the first authors to report the results of plantar pressure distribution analysis.26 They studied 170 feet retrospectively and found that 50% underwent resection arthroplasty according to Keller or arthrodesis of the first MTP joint for treatment of hallux valgus deformity. They showed that patients who underwent resection arthroplasty did not use their great toe for push-off. In addition, metatarsalgia showed a significantly higher incidence in the resectional arthroplasty group. Henry et al concluded that the higher incidence was attributable to the higher pressure distribution on the lateral aspects of the forefoot due to load shift. Even though both methods that were investigated in that study are joint-sacrificing methods rather than joint-preserving methods, which are able to restore physiological joint biomechanics as well as joint kinematics, the results indicate that the use of the great toe for push-off and weight bearing of the first ray is important to avoid metatarsalgia due to load shift after hallux valgus surgery. Therefore, a great deal of attention should be drawn to the restoration of physiologic gait patterns after such operations. In agreement with Henry and colleagues’ results,26 Stokes et al27 found no increase of plantar pressure patterns beneath the great toe region in 40 feet of patients who underwent a resectional arthroplasty or Wilson osteotomy. In addition, 942

f

Physical Therapy

Volume 89

they investigated the plantar pressure distribution of 64 individuals (128 feet) with absence of any foot pathology and compared the results with the results of the hallux valgus group. On the lateral aspects of the foot, the hallux valgus group showed higher load before as well as after surgery compared to the control group. Stokes et al also concluded that this load shift may cause metatarsalgia. This was the first study that revealed pathologic plantar pressure distribution after hallux valgus surgery with a joint-preserving method. Feet affected with hallux valgus deformity show a load shift to the lateral aspects of the foot and decreased weight bearing of the great toe.22,24,26 –28 In a kinematic study, Mitternacht and Lampe22 found that, due to the lateral shift of the tendons of the extrinsic muscles of the great toe, a decrease in plantar-flexion moment of the great toe can be identified. Recently, Putti et al42 performed a plantar pressure distribution assessment in 53 subjects who were healthy and used the force-time integral to describe the overall loading effect. The force-time integral is appropriate for describing the overall loading effect because it takes into account the amplitude and duration of load application.45 The study by Putti et al revealed mean force-time integrals of 26 N䡠s for the hallux region and 52 N䡠s for the first metatarsal head region. In our study, we found mean preoperative forcetime integrals of 37.9 N䡠s for the first metatarsal head region and 18.7 N䡠s for the first metatarsal head region. These measurements indicate a decreased load of the first ray in patients with hallux valgus deformity. Six months after surgery, the mean values for these regions reached 25.2 N䡠s for the big toe region and 55.6 N䡠s for the first metatarsal head region. These findings indicate increased weight bearing of the first ray and an almost physiological

Number 9

plantar pressure distribution. In addition, there were significantly decreased plantar pressure parameters in the region of the first and second metatarsal heads 4 weeks after surgery compared with the preoperative assessment. Considering the total foot region, no statistically significant changes for maximum force and force-time integral were observed. These results indicate the possibility of a load shift from the medial aspect of the forefoot to the lateral aspects of the forefoot. Our patients were placed in a postoperative shoe for 4 weeks after surgery. To ensure bone healing, the postoperative shoe should decrease the load in the traumatized region.2,3 The first ray is the most heavily loaded structure of the foot during gait.19 Therefore, the shoe is designed to shift the load from the medial aspect to the lateral aspect of the forefoot during propulsion. We believe that one reason for the decreased load in the great toe region and the region of the medial forefoot 4 weeks after surgery is the pathologic gait pattern that is necessary in the early postoperative period. However, a multimodal rehabilitation program seems to be important for the patient to eliminate these pathologic gait patterns and to restore the function of the operated structures. Recent plantar pressure distribution analysis with an intermediate-term follow-up revealed a decreased load in the region of the first MTP joint as well as in the great toe area after hallux valgus surgery. Kernozek and Sterricker17 found decreased peak pressure and force-time integral in the great toe region 1 year after surgery compared with the preoperative examination in a prospective study of 25 patients who underwent the Austin procedure for correction of hallux valgus deformity. They concluded that physical therapy may

September 2009

Rehabilitation After Hallux Valgus Surgery help to improve the functional outcome of this procedure. Bryant et al13 investigated 31 subjects (44 feet) before and after an Austin osteotomy. They also assessed the plantar pressure distribution in 36 control subjects. They found a decreased load beneath the hallux 1 year after the Austin procedure compared with preoperative levels. In a retrospective analysis, Guesgen et al18 measured plantar pressure distribution in 60 patients (66 feet) who underwent a chevron osteotomy, with a mean follow-up of 3 years. Thirty-four percent of the patients with a postoperative hallux valgus angle smaller than 20 degrees and 56% of the patients with a postoperative hallux valgus angle greater than 20 degrees did not use their great toe during propulsion. These results suggest that a total of 45% of the patients had pathologic gait patterns after surgery. Jones et al8 investigated 24 patients (35 feet) who underwent a scarf osteotomy prospectively. They found a decrease in the peak pressure of the first metatarsal after a mean follow-up of 20 months. Dhukaram et al15 investigated 28 patients who underwent a Mitchell or scarf osteotomy, with a mean follow-up of 3 years. They also measured plantar pressure distribution in 15 individuals who were healthy. They found deficient load bearing of the hallux for both groups. In this study, plantar pressure patterns in the great toe region decreased significantly 4 weeks after surgery compared with the preoperative assessment. Maximum force, peak pressure, contact area, and force-time integral showed statistically significant increases between the fourth and the eighth weeks postoperatively. For the great toe region and the region of the first metatarsal head, maximum force and force-time integral showed increases September 2009

compared with the preoperative values. This tendency was statistically nonsignificant. The changes concerning the plantar pressure distribution indicate that there is improved weight bearing of the first ray and the great toe. This finding indicates that there is a functional improvement after hallux valgus surgery, which does not correspond to the pedobarographic results reported by other authors.8,13–15,17,18 Based on those results, we believe that this functional improvement is based on the physical therapy interventions. In agreement with other authors, the AOFAS score improved significantly and reached 94.5 points at 6 months after surgery. Cancilleri et al51 investigated 30 patients after an Austin osteotomy and found a mean AOFAS score of 81.9 points at a mean of 37 months after surgery. Trnka et al,11 in 2- and 5-year follow-up assessments of 66 patients after a modified chevron (Austin) osteotomy, found a mean AOFAS score of 91 points. Aminian et al52 studied the clinical results of the scarf osteotomy in 27 patients and found that the mean AOFAS score increased from 54.5 points preoperatively to 86.5 points at an average follow-up of 16.1 months. Kristen et al,9 in 89 patients (111 feet) who underwent a scarf osteotomy, reported that the mean AOFAS score increased from 50.1 points preoperatively to 91 points postoperatively at a mean follow-up of 34 months. Perugia et al10 investigated 33 patients (45 feet) after a scarf osteotomy and reported a mean increase in AOFAS score from 35.7 points preoperatively to 89.8 points postoperatively. Jones et al,8 in 24 patients (35 feet) who underwent a scarf osteotomy, found the mean AOFAS score increased from 52 points preoperatively to 89 points at a mean of 22 months after surgery. Buchner et al,6 in 29 patients who underwent a scarf osteotomy, found an increase in mean AOFAS score

from 45 points preoperatively to 75 points at an average follow-up of 6 months. Crevoisier et al53 found in 84 feet an increase in mean AOFAS score from 43 points preoperatively to 82 points at a mean follow-up of 22 months. In the present study, patients had a relatively high AOFAS score in comparison with these other investigations, even though surgery was just 6 months prior. The total ROM improved from 68.8 degrees preoperatively to 73.3 degrees by 6 months after surgery. This improvement did not show statistical significance, but isolated dorsiflexion significantly improved from 40.4 to 45.9 degrees. It is difficult to compare the results of ROM measurements in our study with those of other studies because of the different methods used for the assessment of first MTP joint ROM. However, during propulsion, the first MTP joint has been reported to dorsiflex between 40 and 60 degrees during typical gait.54 Plantar flexion of only a few degrees is necessary to allow physiologic gait. The improvement of dorsiflexion also may help to restore physiological gait patterns. Weaknesses of this study include, due to its descriptive nature, the absence of a control group that did not receive physical therapy after hallux valgus surgery. A randomized controlled design would improve the level of evidence. Further research is necessary to determine whether there is a beneficial effect of a multimodal rehabilitation program on the restoration of physiological plantar pressure patterns. Further research should focus on performing a randomized controlled trial addressing this question. Gait speed seems to affect plantar pressure distribution.55 In the present study, plantar pressure assessment was performed using the mid-gait method because it is the most favorable way to represent normal gait patterns.42,45 Partic-

Volume 89

Number 9

Physical Therapy f

943

Rehabilitation After Hallux Valgus Surgery ipants were instructed to walk at a normal speed and to keep their speed constant. Putti et al42 showed that this method produces repeatable results. However, gait speed was not recorded. Therefore, it is impossible to analyze the influence of gait speed on the plantar pressure distribution in the patients in this study. The strengths of this study include its prospective nature and a systematic plantar pressure assessment. In addition, to the best of our knowledge, this is the first study determining plantar pressure changes after hallux valgus surgery and postoperative physical therapy.

Conclusion Numerous authors13,15–18,22,24,26 –28 have reported pathologic gait patterns after hallux valgus surgery. We found that there was an increase in plantar pressure parameters in the region of the great toe and the first ray after hallux valgus surgery in patients who received physical therapy as well as gait training in the postoperative period. Therefore, we believe that postoperative physical therapy helps to restore function in weight bearing and ambulation after hallux valgus surgery. Mr Schuh and Dr Trnka provided concept/ idea/research design. Mr Schuh and Dr Adams provided writing. Mr Schuh and Dr Hofstaetter provided data collection. Mr Schuh provided data analysis. Dr Hofstaetter and Mr Pichler provided project management. Mr Pichler and Dr Kristen provided participants. Dr Kristen and Dr Trnka provided facilities/equipment. Dr Hofstaetter, Dr Adams, Mr Pichler, and Dr Kristen provided consultation (including review of manuscript before submission). The authors acknowledge the help of Wolfgang Schuh, MSc, in preparation of the manuscript. This study was approved by the Foot and Ankle Center Vienna Institutional Review Board.

944

f

Physical Therapy

Volume 89

This article was received November 24, 2008, and was accepted May 28, 2009. DOI: 10.2522/ptj.20080375

References 1 Easley ME, Trnka HJ. Current concept review: hallux valgus, part II: operative treatment. Foot Ankle Int. 2007;29:748 –758. 2 Robinson AH, Limbers JP. Modern concepts in the treatment of hallux valgus. J Bone Joint Surg Br. 2005;87:1038 –1045. 3 Coughlin MJ. Instructional course lectures, the American Academy of Orthopaedic Surgeons: hallux valgus. J Bone Joint Surg Am. 1996;78:932–966. 4 Sammarco VAJ. Stability and fixation techniques in first metatarsal osteotomies. Foot Ankle Clin. 2001;6:409 – 432. 5 Barouk LS. Scarf osteotomy of the first metatarsal in the treatment of hallux valgus. Foot Disease. 1995;2:35– 48. 6 Buchner M, Schulze A, Zeitang F, Sabo D. Pressure distribution after scarf osteotomy for hallux valgus surgery [in German]. Z Orthop Ihre Grenzgeb. 2005;143:233–239. 7 Dereymaeker G. Scarf osteotomy for correction of hallux valgus: surgical technique and results as compared to distal chevron osteotomy. Foot Ankle Clin. 2000;5:513–524. 8 Jones S, Al Hussainy HA, Ali F, et al. Scarf osteotomy for hallux valgus: a prospective clinical and pedobarographic study. J Bone Joint Surg Br. 2004;86:830 – 836. 9 Kristen KH, Berger C, Stelzig S, et al. The SCARF osteotomy for the correction of hallux valgus deformities. Foot Ankle Int. 2002;23:221–219. 10 Perugia D, Basile A, Gensini A, et al. The scarf osteotomy for severe hallux valgus. Int Orthop. 2003;27:103–106. 11 Trnka HJ, Zembsch A, Easley ME, et al. The chevron osteotomy for correction of hallux valgus: comparison of findings after two and five years of follow-up. J Bone Joint Surg Am. 2000;82:1373–1378. 12 Trnka HJ, Zembsch A, Wiesauer H, et al. Modified Austin procedure for correction of hallux valgus. Foot Ankle Int. 1997;18: 119 –127. 13 Bryant AR, Tinley P, Cole JH. Plantar pressure and radiographic changes to the forefoot after the Austin bunionectomy. J Am Podiatr Med Assoc. 2005;95:357–365. 14 Dhanendran M, Pollard JP, Hutton WC. Mechanics of the hallux valgus foot and the effect of Keller’s operation. Acta Orthop Scand. 1980;51:1007–1012. 15 Dhukaram V, Hullin MG, Senthil Kumar C. The Mitchell and Scarf osteotomies for hallux valgus correction: a retrospective, comparative analysis using plantar pressures. J Foot Ankle Surg. 2006;45:400 – 409. 16 Kernozek TW, Roehrs T, McGarvey S. Analysis of plantar loading parameters pre and post surgical intervention for hallux vargus. Clin Biomech (Bristol, Avon). 1997;12:S18 –S19.

Number 9

17 Kernozek TW, Sterriker SA. Chevron (Austin) distal metatarsal osteotomy for hallux valgus: comparison of pre- and postsurgical characteristics. Foot Ankle Int. 2002;23:503–508. 18 G¨ usgen C, Walther M, W¨ olfel R, VispoSeara JL. The distal chevron osteotomy for hallux valgus: a medium-term retrospective clinical, radiographic and pedobarographic analysis [in German]. Fu␤Sprung. 2005;3:164 –171. 19 Jacob HAC. Forces acting in the forefoot during normal gait: an estimate. Clin Biomech (Bristol, Avon). 2001;16:783–792. 20 Rodgers MM. Dynamic biomechanics of the normal foot and ankle during walking and running. Phys Ther. 1988;68:1822–1830. 21 Myerson MS. The etiology and pathogenesis of hallux valgus. Foot Ankle Clin. 1997;2:583–598. 22 Mitternacht J, Lampe R. Calculation of functional kinetic parameters from the plantar pressure distribution measurement [in German]. Z Orthop Ihre Grenzgeb. 2006;144:410 – 418. 23 Grieve DW, Rashdi T. Pressures under normal feet in standing and walking as measured by foil pedobarography. Ann Rheum Dis. 1984;43:816 – 818. 24 Hutton WC, Dhanendran M. The mechanics of normal and hallux valgus feet: a quantitative study. Clin Orthop Relat Res. 1981;(157):7–13. 25 Sanders M. Conservative treatment and shoewear options for hallux valgus. Foot Ankle Clin. 1997;4:639 – 649. 26 Henry AP, Waugh W, Wood H. The use of footprints in assessing the results of operations for hallux valgus: a comparison of Keller’s operation and arthrodesis. J Bone Joint Surg Br. 1975;57:478 – 481. 27 Stokes IA, Hutton WC, Stott JR, Lowe LW. Forces under the hallux valgus foot before and after surgery. Clin Orthop Relat Res. 1979;(142):64 –72. 28 Waldecker U. Metatarsalgia in hallux valgus deformity: a pedographic analysis. J Foot Ankle Surg. 2002;41:300 –308. 29 Malone TB, Blackburn TA, Wallace LA. Knee rehabilitation. Phys Ther. 1980;60: 1602–1610. 30 Beynnon BD, Johnson RJ, Fleming BC. The science of anterior cruciate ligament rehabilitation. Clin Orthop Relat Res. 2002; (402):9 –20. 31 Chen B, Zimmerman JR, Soulen L, DeLisa JA. Continuous passive motion after total knee arthroplasty: a prospective study. Am J Phys Med Rehabil. 2000;79:421– 426. 32 Hodgson S. Proximal humerus fracture rehabilitation. Clin Orthop Relat Res. 2006; 442:131–138. 33 Theiler R, Schmid C, Risler R, Moser L. Postoperative physiotherapy in acute care: when, what and how much [in German]? Orthopade. 2007;36:552, 554 –559. 34 Shaffer MA, Okereke E, Esterhai JL Jr, et al. Effects of immobilization on plantarflexion torque, fatigue resistance, and functional ability following an ankle fracture. Phys Ther. 2000;80:769 –780.

September 2009

Rehabilitation After Hallux Valgus Surgery 35 Shamus J, Shamus E, Gugel RN, et al. The effects of sesamoid mobilization, flexor hallucis strengthening, and gait training on reducing pain and restoring function in individuals with hallux limitus: a clinical trial. J Orthop Sports Phys Ther. 2004;80: 769 –780. 36 Austin DW, Leventen EO. A new osteotomy for hallux valgus: a horizontally directed “V” displacement osteotomy of the metatarsal head for hallux valgus and primus varus. Clin Orthop Relat Res. 1981; (157):25–30. 37 Barouk LS. Scarf osteotomy for hallux valgus correction: local anatomy, surgical technique, and combination with other forefoot procedures. Foot Ankle Clin. 2000;5:525–558. 38 Jarde O, Trinquier-Lautard JL, Gabrion A, et al. Hallux valgus treated by Scarf osteotomy of the first metatarsus and the first phalanx associated with an adductor plasty: apropos of 50 cases with a 2-year follow up [in French]. Rev Chir Orthop Reparatrice Appar Mot. 1999;85:374 –380. 39 Smith RW, Reynolds JC, Stewart MJ. Hallux valgus assessment: report of research committee of American Orthopaedic Foot and Ankle Society. Foot Ankle. 1984;5: 92–103. 40 Kitaoka HB, Alexander IJ, Adelaar RS, et al. Clinical rating systems for the anklehindfoot, midfoot, hallux, and lesser toes. Foot Ankle Int. 1994;15:349 –353.

September 2009

41 Hughes J, Pratt L, Linge K, et al. Reliability of pressure measurements: the EMED F system. Clin Biomech (Bristol, Avon). 1991;6:14 –18. 42 Putti AB, Arnold GP, Cochrane LA, Abboud RJ. Normal pressure values and repeatability of the Emed ST4 system. Gait Posture. 2008;27:501–505. 43 van der Leeden M, Dekker JH, Siemonsma PC, et al. Reproducibility of plantar pressure measurements in patients with chronic arthritis: a comparison of onestep, two-step, and three-step protocols and an estimate of the number of measurements required. Foot Ankle Int. 2004;25: 739 –744. 44 Metaxiotis D, Accles W, Pappas A, Doederlein L. Dynamic pedobarography (DPB) in operative management of cavovarus foot deformity. Foot Ankle Int. 2000;21: 935–947. 45 Orlin MN, McPoil TG. Plantar pressure assessment. Phys Ther. 2000;80:399 – 409. 46 Barnes SZ, Berme N. Measurement of kinetic parameters technology. In: Craik RL, Oatis CA, eds. Gait Analysis: Theory and Application. St Louis, MO: Mosby-Year Book Inc; 1995:239 –251. 47 Cheung RTN, Gabriel YF. Influence of different footwear on force of landing during running. Phys Ther. 2008;88:620 – 628. 48 Perry J. Gait Analysis: Normal and Pathologic Function. Thorofare, NJ: Slack Inc; 1992.

49 Riegger CL. Anatomy of the ankle and foot. Phys Ther. 1988;68:1802–1814. 50 Barnett CH. Phases of human gait. Lancet. 1956;22:617– 621. 51 Cancilleri F, Marinozzi A, Martinelli N, et al. Comparison of plantar pressure, clinical, and radiological changes of the forefoot after biplanar Austin osteotomy and triplanar Boc osteotomy in patients with mild hallux valgus. Foot Ankle Int. 2008; 29:817– 824. 52 Aminian A, Kelikian A, Moen T. Scarf osteotomy for hallux valgus deformity: an intermediate follow-up of clinical and radiographic outcomes. Foot Ankle Int. 2006;27:883– 886. 53 Crevoisier X, Mouhsine E, Ortolano V, et al. The scarf osteotomy for the treatment of hallux valgus deformity: a review of 84 cases. Foot Ankle Int. 2001;22: 970 –976. 54 Hetherington VJ, Johnson RE, Albritton JS. Necessary dorsiflexion of the first metatarsophalangeal joint during gait. J Foot Surg. 1990;29:218 –222. 55 Rosenbaum D, Hautmann S, Gold M, Claes L. Effects of walking speed on pressure distribution patterns and hindfoot angular motion. Gait Posture. 1994;2:191–197.

Volume 89

Number 9

Physical Therapy f

945

Research Report

Job Strain in Physical Therapists Marc A. Campo, Sherri Weiser, Karen L. Koenig M.A. Campo, PT, PhD, OCS, is Associate Professor, Program in Physical Therapy, School of Health and Natural Sciences, Mercy College, 555 Broadway, Dobbs Ferry, NY 10522 (USA). Address all correspondence to Dr Campo at: [email protected]. S. Weiser, PhD, is Research Assistant Professor, Department of Ergonomics and Biomechanics, New York University, New York, New York. K.L. Koenig, PhD, is Assistant Professor, Department of Environmental Medicine, New York University School of Medicine, New York, New York. [Campo MA, Weiser S, Koenig KL. Job strain in physical therapists. Phys Ther. 2009;89:946 –956.] © 2009 American Physical Therapy Association

Background. Job stress has been associated with poor outcomes. In focus groups and small-sample surveys, physical therapists have reported high levels of job stress. Studies of job stress in physical therapy with larger samples are needed. Objective. The purposes of this study were: (1) to determine the levels of psychological job demands and job control reported by physical therapists in a national sample, (2) to compare those levels with national norms, and (3) to determine whether high demands, low control, or a combination of both (job strain) increases the risk for turnover or work-related pain.

Design. This was a prospective cohort study with a 1-year follow-up period. Methods. Participants were randomly selected members of the American Physical Therapy Association (n⫽882). Exposure assessments included the Job Content Questionnaire (JCQ), a commonly used instrument for evaluation of the psychosocial work environment. Outcomes included job turnover and work-related musculoskeletal disorders.

Results. Compared with national averages, the physical therapists reported moderate job demands and high levels of job control. About 16% of the therapists reported changing jobs during follow-up. Risk factors for turnover included high job demands, low job control, job strain, female sex, and younger age. More than one half of the therapists reported work-related pain. Risk factors for work-related pain included low job control and job strain.

Limitations. The JCQ measures only limited dimensions of the psychosocial work environment. All data were self-reported and subject to associated bias. Conclusions. Physical therapists’ views of their work environments were positive, including moderate levels of demands and high levels of control. Those therapists with high levels of demands and low levels of control, however, were at increased risk for both turnover and work-related pain. Physical therapists should consider the psychosocial work environment, along with other factors, when choosing a job.


f

Physical Therapy

Volume 89

Number 9

September 2009

Job Strain in Physical Therapists

J

ob stress increases the risk for a variety of adverse outcomes. These outcomes include burnout,1,2 turnover,3 sickness absence,4 and work-related musculoskeletal disorders (WMSDs).5 Job stress has been linked to medical and psychiatric conditions, including depression6,7 and cardiac disease.8,9 In health care workers, job stress has been linked to reduced quality of patient care.10 Studies have demonstrated that physical therapists may experience high levels of job stress,11–15 but the scope of the problem is difficult to determine. Research to date has consisted mostly of interview and focus group studies.11,12,15 Different dimensions of work stress have been studied in physical therapists, but common themes have emerged. Common sources of work stress have included excessive workloads (both clinical and administrative) and a lack of resources (equipment, staffing, and time).11–15 The professional culture in physical therapy may complicate the work environment. Physical therapists hold themselves to high professional standards and may experience a conflict between clinical realities and personal ideals.12,14 In the face of external pressures, including increasing workloads and job demands, job stress may be viewed as a personal failing. Job stress is a complex, multidimensional phenomenon with a variety of


September 2009

contributing factors.16 The psychosocial work environment is a major (but not the only) contributor. It is defined by workers’ perceptions of social, environmental, and organizational factors in their jobs.16 Studies to date on physical therapists provide evidence of potential issues in the psychosocial work environment that may cause job stress. These issues include perceptions of excessive work demands, a loss of control, a lack of support, frustration with clients, and difficulty with professional relationships.11–15,17 The findings from these studies, however, may not apply to typical physical therapists working in a variety of settings. Little research has explored the psychosocial work environment for physical therapists nationally; therefore, this is an area that is not well understood. No studies have compared the psychosocial work environment for physical therapists with the psychosocial environments in other occupations. New studies of the physical therapy work environment with larger samples are needed. Two aspects of the psychosocial work environment that are frequently studied in occupational health psychology are job demands and job control. The demand and control model of Karasek and colleagues18 proposes that job strain, a combination of high demands and low control, increases the risk for poor outcomes.19 The following is an analysis of job demands, job control, and job strain in physical therapists. It was based on a prospective cohort study of WMSDs in physical therapists.20 Increased demands, reduced control, and job strain have been associated with a wide variety of outcomes, including turnover3 and WMSDs.21 Both are important outcomes to consider in physical therapy. Some physical therapy settings

have turnover rates that are substantially higher than national averages,22,23 and turnover can result in substantial costs in health care settings.24 Work-related musculoskeletal disorders also are an important outcome to consider in physical therapy. Some authors have reported high rates of work-related pain in physical therapists,20,25 and WMSDs have consistently been associated with job strain in other populations.21,26 The purposes of this study were: (1) to determine the levels of job demands and control in physical therapists, (2) to compare levels of demands and control in physical therapists with levels of demands and control in other occupations, and (3) to explore whether increased demands, reduced control, or a combination of both (job strain) leads to an increased incidence of job turnover and increased incidence of WMSDs.

Method Study Design This was a prospective cohort study with 1-year follow-up. Data were collected via 2 validated postal questionnaires mailed 1 year apart. Exposure (ie, job strain) and demographic data were gathered at baseline. Outcomes (ie, musculoskeletal complaints and job turnover) were assessed at follow-up. Participants The sample consisted of randomly selected members of the American Physical Therapy Association (APTA). The APTA selected 1,500 members via random Microsoft Access* query. The number of therapists initially selected was limited by the project resources. Of the 1,500 members selected by APTA, 1,486 were determined to be eligible (some did not * Microsoft Corp, One Microsoft Way, Redmond, WA 98052-6399.

Volume 89

Number 9

Physical Therapy f

947

Job Strain in Physical Therapists reside in the United States or were students). The initial questionnaire was mailed to 1,486 potential participants. One year later, a follow-up questionnaire was mailed to every individual who met the inclusion criteria and who responded to the baseline questionnaire. Inclusion and Exclusion Criteria To be included in the study, a participant had to be working as a physical therapist with at least 1 hour per week of patient care. He or she had to be an APTA member and return the baseline questionnaire. There were no exclusion criteria. Exposure Assessment Job demands, job control, and job strain were evaluated using scales from the Job Content Questionnaire (JCQ), a commonly used occupational psychosocial assessment tool.18 The JCQ has been used to study a wide variety of outcomes in a broad range of occupations. The JCQ has yielded reliable and valid data across countries and occupational groups.18 The core of the job strain model focuses on the interaction between job demands and job control (Fig. 1).18 In this model, excessive work demands can be problematic but only when accompanied by a person’s lack of control over his or her work situation. High demands coupled with high control (active jobs) and low demands coupled with low control (passive jobs) are thought to be less problematic. Job demands were assessed with 5 questions that were combined to form one scale (psychological demands). Job control was assessed with 9 questions comprising 2 scales. These 2 scales were decision authority (a measure of the ability to make decisions) and skill discretion (how varied and skilled the position is). A combination of high demands and low control was classified as job 948

f

Physical Therapy

Volume 89

Figure 1. Demand and control model.

strain. Scores on the job demands scale range from 12 to 48, with higher scores representing higher demands. Scores on the job control scale range from 24 to 96, with higher scores representing higher control.27 Demands and control were dichotomized based on the median scores for each scale. Therapists with job demands above (but not including) the median score were classified as having high demands. Therapists with job control scores below (but not including) the median score were classified as having low control. Therapists with both high demands and low control were classified as having job strain. Medians are a common choice for classification thresholds,28,29 and sample medians have been used for dichotomization of demands and control in several recent prospective cohort studies with large samples.9,29,30 Outcome Assessment The follow-up questionnaire included items on job turnover, stopping work, and job rotation. Turn-

Number 9

over was defined as a situation where a therapist left one job and started work for another employer. Situations where therapists rotated within their facility or stopped working were not considered to be turnover. Therapists who rotated were retained for the turnover analysis. Therapists who retired or stopped working and did not return to work by the time the follow-up questionnaire was completed were not included in the turnover models. Questions on WMSDs were included in both the baseline and follow-up questionnaires. An incident WMSD was defined as one that was experienced during the follow-up year and was not present at any time during the year prior to the baseline survey. In a prior study of WMSDs from this cohort,20 the researchers found that many of the therapists with incident WMSDs had complaints of work-related pain in the year prior to the baseline survey that progressed in terms of severity, duration, or frequency. They also found that many therapists had moderate work-related pain that was not seSeptember 2009

Job Strain in Physical Therapists vere enough to reach a stringent case definition. The case definition for this analysis was modified so that it captured all new cases of workrelated pain. This modified case definition avoided missing therapists with moderate pain that did not reach the previous case threshold. It also avoided capturing therapists who had pain that did not reach the previous case threshold during the baseline year but progressed enough to qualify as cases during the follow-up year. Data Entry Data were entered twice into separate files using SPSS Data Entry Builder version 4.† Discrepancies were checked against the questionnaires and changed in the master data entry file if they were coding errors. Random samples of 20 questionnaires (at baseline and followup) then were selected and checked against the master data file. Data Analysis Data were analyzed with SPSS version 16† and Stata IC version 10.‡ The data were screened for missing or implausible values. Descriptive and frequency statistics were generated for all background, exposure, and outcome data. Demographic characteristics were compared with the APTA membership profile.31 The 3 scales (psychological demands, decision authority, and skill discretion) were totaled according to specific formulas.27 Decision authority and skill discretion were added together to form decision latitude (job control). Scale totals were compared with national averages from 2 studies with large samples: the Quality of Employment Surveys (QES) and another, more-recent † SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606. ‡ StataCorp LP, 4905 Lakeway Dr, College Station, TX 77845.

September 2009

national health survey, the New England Medical Center (NEMC) Study.18 Associations among job strain, turnover, and work-related musculoskeletal symptoms were evaluated using unconditional, multivariate logistic regression. Potential confounding factors, including sex, age, experience, hours worked per week at primary job, total hours worked per week, and holding a second job, were evaluated for association with job strain and with outcomes.32 When a confounder was at least moderately associated (P⬍.25) with both exposure and outcome, or if there was a theoretical justification for inclusion, it was retained for the multivariate model and retained throughout the modeling process. Job strain and confounding factors were entered simultaneously into a multivariate model. Plausible interactions among job strain and main effects predictors were generated and backward eliminated. Plausible interactions included age versus job strain and sex versus job strain. Odds ratios (ORs) and 95% confidence intervals (CIs) were reported. Goodness of fit was evaluated with the Hosmer-Lemeshow goodnessof-fit test.33 This process was repeated for the dichotomized job demands and job control scales (included in the same model), and separate models were developed for turnover and for work-related musculoskeletal symptoms. Ratio-level confounding factors retained for the models were dichotomized based on the median values. Pilot Testing The questionnaire was pilot tested with repeat mailings 1 month apart. Eighteen therapists responded to both questionnaires. Test-retest stability (intraclass correlation coeffi-

cient, 2-way mixed model for absolute agreement)34 of the JCQ scales was good for decision authority (.71) and psychological demands (.69) but poor for skill discretion (.35).35 Role of the Funding Source This project was supported by 2 National Institutes of Health Extramural Research Development Awards (grant HD 035965), a National Institute for Occupational Safety and Health Education and Research Center Pilot Project Award (T42 OH008422), and a Smart Family Foundation Grant. The grants were used to cover direct and indirect expenses related to the pilot studies and the full project. Dr. Koenig’s work was supported, in part, by a Center grant from the National Institute of Environmental Health Sciences (ES00260). None of the funding sources were involved with the design and methods of the project or had any influence on the way the study was conducted.

Results Response Figure 2 details the number and percentage of therapists who responded at each step of the study. Missing Values None of the questions had more than 5% missing values, with most questions having 5 or fewer total missing values. Thirteen therapists did not answer one of the questions related to demands. Missing values for these questions were not replaced. Seven therapists did not answer the question related to turnover. Most of those therapists, however, reported one of the other job outcomes (stopping work or rotating positions). Those therapists were assumed not to have changed jobs. One therapist did not specify his or her sex. Twenty-five therapists did not answer the question related to age, and 5 therapists did not answer the

Volume 89

Number 9

Physical Therapy f

949

Job Strain in Physical Therapists question related to work hours. Those values were replaced by the sample medians prior to logistic regression because they were considered to be confounding factors and not primary risk factors. One therapist did not answer the question about second jobs. That therapist was assumed not to have a second job. Demographics The demographic profile of respondents is shown in Table 1. The profile was generally similar to that of the APTA membership,31 although the therapists in our sample were younger (1.3 years) and less experienced (2 years) on average. Practice settings generally were similar. Job Demands and Job Control in Physical Therapists Scale means and standard deviations were compared with data from the QES and the NEMC Study (Tab. 2). Respondents reported a moderate level of demands and substantially higher levels of control than workers from the QES and NEMC Study surveys.18

Figure 2. Response rates and sample size.

Table 1. Demographic and Work Profiles of Respondents

According to norms from the QES, the therapists in our sample were in the “active” job category—a combination of high demands and high control. The mean of job demands, however, was only marginally higher than the national average from the QES for both men and women, and both male and female therapists reported slightly lower levels of demands than the NEMC Study averages. Turnover One hundred thirty-seven therapists (16%) changed jobs during the year prior to the follow-up survey. In addition, 21 therapists (2%) left their jobs and were not working or were retired at follow-up. Sixty-one therapists (7%) rotated positions within

950

f

Physical Therapy

Volume 89

Number 9

Factor

n

X

SD

Age (y)

857

40.3

10.4

Experience (y)

881

14.2

10.8

Hours per week (primary job)

877

36.8

10.2

Hours of patient care per week (primary job)

879

29.9

11.0

Total work hours per week (primary and secondary jobs)

868

38.1

10.9

n

%

Male

254

28.8

Female

627

71.1

No

702

79.6

Yes

179

20.3

Sex

Second job

Education (highest) Bachelor’s degree

353

40.0

Master’s degree

422

47.8

Doctor of Physical Therapy degree

94

10.7

Other doctorate

12

1.4

September 2009

Job Strain in Physical Therapists Table 2. Job Demands, Job Control, and National Norms

Scale Psychological demands

Decision latitude

Sample

Quality of Employment Surveys

New England Medical Center Study

X (SD)

X (SD)

X (SD)

Male

30.9 (4.7)

30.1 (7.2)

33.2 (7.5)

Female

31.1 (5.2)

30.9 (7.0)

34.8 (7.5)

Male

82.5 (8.2)

72.6 (15.4)

71.5 (14.6)

Female

80.9 (8.9)

65.7 (15.8)

65.9 (14.4)

Sex

Table 3. Work-Related Musculoskeletal Disorders Body Region

No. (%) of Physical Therapists With Incident Symptoms

Neck

63 (10.2)

Shoulder

51 (7.3)

Elbow

27 (3.7)

Wrist and hand

77 (13.0)

Upper back

48 (7.1)

Low back

81 (15.7)

Hip and thigh

25 (3.1)

Knee

33 (4.3)

Ankle

23 (2.8)

Total

295 (33.4)

their facility during the year prior to follow-up. Work-Related Musculoskeletal Disorders Fifty-eight percent of the therapists experienced a work-related ache or pain during the year prior to the follow-up survey. The most common region was the low back, followed by the wrist and hand. Two hundred ninety-five therapists (33.4%) experienced incident symptoms (ie, symptoms during the follow-up year that were not preceded by symptoms in the same body region in the year prior to the baseline survey) (Tab. 3). Potential Confounders Age and sex were included in all of the multivariate models. Older therapists were less likely than younger therapists to report changing jobs (OR⫽0.50, P⬍.01). Older therapists September 2009

also were less likely to report job strain (OR⫽0.59, P⬍.01) and low job control (OR⫽0.66, P⬍.01). Female therapists were more likely than male therapists to report changing jobs (OR⫽1.51, P⫽.06). Female therapists also were more likely to report low job control (OR⫽1.38, P⫽.03). Work hour measures and holding a second job were not associated with either outcome and were excluded. Experience was highly correlated with age (r⫽.89) and also was excluded. Job Strain and Job Turnover Associations between psychosocial factors and turnover are summarized in Table 4. High job demands increased the likelihood of turnover (OR⫽1.41, 95% CI⫽0.97–2.07). Low job control also increased the like-

lihood of turnover (OR⫽1.51, 95% C⫽1.03–2.22). Job strain, which combines these 2 variables, was more strongly associated with the risk of turnover (OR⫽1.62, 95% CI⫽1.06 –2.48) than either job demands or job control alone. No significant interactions were noted between age or sex and job strain, job demands, and job control. Job Strain and Work-Related Musculoskeletal Disorders Associations between psychosocial factors and WMSDs are listed in Tables 5 and 6. Both job strain and job control were associated with workrelated pain. Interactions between sex and job control (P⫽.01) and sex and job strain (P⫽.01) were noted. As shown in Table 6, low job control increased the likelihood of workrelated musculoskeletal symptoms in men (OR⫽2.46, 95% CI⫽1.41– 4.30) but not in women (OR⫽1.05, 95% CI⫽0.76 –1.47). Job strain also increased the likelihood of workrelated musculoskeletal symptoms in men (OR⫽3.32, 95% CI⫽1.70 – 6.45) but had little effect in women (OR⫽1.21, 95% CI⫽0.82–1.79). High job demands did not affect the likelihood of work-related musculoskeletal symptoms in men or women.

Discussion Job Demands and Job Control Physical therapists’ perceptions of their work environments generally were very positive. In comparison with other professions, physical therapy was seen as profession with moderate demands and high levels of control. In the demand/control model, physical therapy could have been considered an “active” job or a “low-strain” job, depending on the study used to establish a reference for job demands. In either formulation, the therapists in our sample, on average, felt that they had substantially higher levels of control over their work situations than the typical

Volume 89

Number 9

Physical Therapy f

951

Job Strain in Physical Therapists workers from prior studies.18 It should be noted that the decision authority and skill discretion subscales (added to form job control) had substantially higher levels of control than national averages, in both sexes.18 Thus, job control in this sample resulted from perceptions of control over workplace decisions (decision authority) as well as from feelings that therapy jobs were interesting, varied, and required high levels of skill (skill discretion). Prior studies of job stress in physical therapists highlighted issues associated with the work environment, including lack of resources and excessive workloads.11–14 Work environments were viewed more positively in our sample. Prior studies consisted of small-sample surveys or focus group studies and may have differed in terms of population characteristics or representativeness. It also is possible that different aspects of the psychosocial work environment were considered.

Table 4. Predictors of Job Turnovera

952

f

Physical Therapy

Volume 89

% With Turnover

Univariate Model OR (95% CI)

Multivariate Model OR (95% CI)

ⱕ39.8

429

19.8

1.00

1.00

⬎39.8

429

11.0

0.50 (0.34–0.73)

0.47 (0.32–0.70)

Male

253

11.9

1.00

1.00

Female

604

16.9

1.51 (0.98–2.34)

1.55 (0.99–2.42)

Low

463

13.0

1.00

1.00

High

383

18.0

1.48 (1.01–2.15)

1.41 (0.97–2.07)

High

470

12.3

1.00

1.00

Low

388

19.1

1.67 (1.15–2.43)

1.51 (1.03–2.22)

No

669

13.5

1.00

1.00

Yes

180

21.8

1.79 (1.18–2.71)

1.62 (1.06–2.48)

Age (y)b

Sexb

Job demandsc

Job controlc

Job strainb

a b c

OR⫽odds ratio, CI⫽confidence interval. Multivariate model with age, sex, and job strain. Multivariate model with age, sex, job demands, and job control.

Table 5. Predictors of Work-Related Musculoskeletal Disordersa

The JCQ has demonstrated consistent differences in scale averages by sex. Karasek et al18 have pointed to systematic sex differences in work authority and opportunities to use and develop skills. Unlike the QES and the NEMC surveys, where women have reported higher demands and lower control, the differences between men and women were negligible in this sample.18 Women reported slightly higher demands and slightly lower control. Job Strain and Job Turnover About 16% of the therapists in this sample changed jobs during the year prior to the follow-up survey. This rate was identical to the rate in acute care hospitals according to surveys by APTA.23 Other settings in physical therapy, such as nursing homes, have reported even higher rates (85%).22 These rates substantially exceeded monthly national averages

n

Risk Factor

n

% With Incident Work-Related Pain

Univariate Model OR (95% CI)

ⱕ39.8

441

34.9

1.00

⬎39.8

441

32.0

0.88 (0.66–1.16)

Male

254

30.3

1.00

Female

627

34.8

1.23 (0.90–1.68)

Low

475

32.6

1.00

High

394

34.8

1.09 (0.82–1.45)

Risk Factor Age (y)

Sex

Job demands

Job control High

478

30.3

1.00

Low

404

37.1

1.36 (1.02–1.80)

No

683

31.3

1.00

Yes

186

41.9

1.58 (1.13–2.21)

Job strain

a

OR⫽odds ratio, CI⫽confidence interval.

Number 9

September 2009

Job Strain in Physical Therapists Table 6.

analysis of this sample in which a more-stringent case definition was used (incidence⫽20.7%).20 In the prior analysis, the researchers found that many of the therapists with incident WMSDs had complaints of work-related pain in the year prior to the first survey that progressed in terms of severity, duration, or frequency and then qualified as incident cases. The rate was higher in this analysis because a less-restrictive definition was used. Using the current definition, minor cases were more likely to be included, but all new cases were captured. The issue of musculoskeletal disorders in physical therapists is discussed more fully elsewhere.20,25

Multivariate Predictors of Work-Related Musculoskeletal Disordersa n

% With Incident Work-Related Pain

ⱕ39.8

441

34.9

1.00

⬎39.8

441

32.0

0.90 (0.67–1.20)

High

152

22.4

1.00

Low

102

42.2

2.46 (1.41–4.30)

High

326

34.0

1.00

Low

301

35.5

1.05 (0.76–1.47)

ⱕ39.8

441

34.9

1.00

⬎39.8

441

32.0

0.91 (0.68–1.22)

No

204

25.5

1.00

Yes

45

53.3

3.32 (1.70–6.45)

No

479

33.8

1.00

Yes

140

38.6

1.21 (0.82–1.79)

Risk Factor

Multivariate Model OR (95% CI)

Model 1b Age (y)

Job control Male

Female

Model 2c Age (y)

Job strain Male

Female

a b c

OR⫽odds ratio, CI⫽confidence interval. Multivariate model with age, sex, job demands, and job control. Multivariate model with age, sex, and job strain.

for US workers in the same year (3.0%– 4.5%).36 The costs of turnover in this population could be substantial, but they are difficult to quantify. The costs can involve reduced productivity, overtime for current staff, training for new staff, and vacant periods between departures and hires. Jones37 calculated that turnover in nursing could result in costs that ranged from $62,100 to $67,100 per registered nurse. Waldman et al24 estimated that turnover costs at a major medical center exceeded 5% of the total annual operating budget. Job strain increased the risk of turnover substantially. This association September 2009

was consistent with prior studies.3,38 Turnover may have resulted from a variety of unexamined factors, including a relatively open job market,39 but psychosocial work conditions, including job strain, may have played an important role. Increased demands and reduced control, individually, also were associated with an increased likelihood of turnover. Mitigation of demands, increasing control, or both may reduce turnover among physical therapists. Job Strain and Work-Related Musculoskeletal Disorders About one third of the therapists in this sample reported an incident WMSD (incidence⫽33%). This incidence was higher than in a prior

Job strain has been associated with work-related musculoskeletal symptoms in a variety of populations,5,40 including nurses21,26 and physical therapists.20 In this sample, job strain led to work-related pain in men only. This finding stands in contrast to the study by Karlqvist et al,41 who found an association between job strain and musculoskeletal symptoms in women but not men. Vermeulen and Mustard42 found higher levels of distress related to job strain in men than in women. Blackmore et al6 found that job strain led to depression in men but not in women. Explanations offered by the authors included different distributions of men and women in particular jobs and shorter work hours by women on average. In this sample, men and women tended to work in different settings, but there was no evidence that this factor was responsible for the sex differences in the effects of job strain. A greater percentage of men than women worked in private practice settings. A greater percentage of women than men worked in skilled nursing facilities, home care, hospitals, and school systems. Men and women in private practice who re-

Volume 89

Number 9

Physical Therapy f

953

Job Strain in Physical Therapists ported job strain developed workrelated pain in substantially higher percentages (men⫽54%, women⫽ 51%) than in other settings. Adding setting (private practice versus non– private practice), however, had negligible effects on the multivariate model for work-related pain. Future studies with a focus on specific settings are needed. Implications Levels of psychological demands in physical therapy generally are similar to the levels of demands in other professions. Levels of self-reported job control appear to be higher in physical therapy than in other professions. Therapists with perceptions of job control that are lower than typical for physical therapists, however, are at risk for both turnover and WMSDs. High levels of decision latitude, therefore, may be needed to perform the job adequately. Additional research is needed to determine the specific aspects of physical therapy work that are associated with perceptions of control. Insights into specific factors that lead to perceptions of reduced control can be found in prior research. In a qualitative study, Blau et al15 examined the effects of hospital restructuring on physical therapy staff members at a large academic medical center. The therapists felt they had lost control over their work environment in the face of increasing work demands and constantly shifting policies. As a result, the therapists felt that they could not provide the best quality of care for their patients. They referred to stress, burnout, and frustration. Some of them actively considered quitting. In hospitals, perceptions of control, therefore, may be related to administrative policies and requirements, as well as the ability to care for patients adequately.

954

f

Physical Therapy

Volume 89

One of the tenets of the demand control model is that a combination of high demands and low control (job strain) results in greater risks than high demands or low control alone. This was true in this sample. The combination of both high demands and low control resulted in higher rates of both outcomes than either alone. It should be noted that the definition and coding of job strain in this analysis was relatively conservative (job strain/no job strain). A variety of job strain formulations, including a quadrant model using all 4 job classifications (high strain, low strain, active, and passive), have been proposed.28 In a quadrant model, low-strain situations are compared with high-strain situations. In this model, job strain was compared with all job situations without job strain. This was a more-conservative contrast. Recommendations The findings from this analysis highlight important considerations for therapists, both as they choose jobs for the first time and as they look for new positions after some degree of experience. Typical issues for consideration include salary and benefits, setting, educational and advancement opportunities, and workload. Other aspects of the work environment—the amount of control the therapist perceives, in particular—may be important factors in determining whether a physical therapist has a successful and rewarding tenure at a particular facility. A job with a positive psychosocial work environment may reduce the risk of injury and work-related pain, result in a better quality of patient care, and help to prevent turnover. Employers may be reluctant to take measures to improve the psychosocial work environment, particularly any measure that results in reduced patient loads. Such measures, however, may pay for themselves if turn-

Number 9

over or injuries can be avoided. Some of the ways in which employers may improve the psychosocial work environment include careful consideration of issues such as workload and administrative policies. Specifically, they should consider the number of patients seen each day, quality of patient care, professional development, time allotted for paperwork, consistency of organizational policies, and therapist input into organizational decisions. Limitations Only limited dimensions of the work environment were included in this study. One of the most commonly cited limitations of the JCQ is the multidimensional nature of work stress. The JCQ itself has several additional scales that are routinely used and recommended. These scales include coworker support, supervisor support, and job satisfaction.27 Additional studies with varied instruments are needed to explore other aspects of the psychosocial work environment of physical therapists. Another common criticism of the JCQ relates to the value of selfreports and associated potential recall bias. Prospective designs, however, help to mitigate recall bias, and the JCQ has proven to have validity across occupations and cultures.18 Demand and control survey averages from the QES represent data that were collected a relatively long time ago (throughout the 60s and 70s). Although the questions from the JCQ are valid for use in today’s workforce, caution should be exercised when comparing scale averages with a modern sample. In general, the JCQ has remained a practical and suitable tool for occupational health studies, and several recent studies have successfully used the JCQ with regard to a variety of outcomes.43– 47

September 2009

Job Strain in Physical Therapists Therapists with low control in this sample had low control compared with other therapists in the sample—not national norms. The effects of low job control can only be interpreted in relation to the levels of control typical for physical therapy. The low reliability of the skill discretion scale in this sample was another limitation. It is possible that ratings of skill discretion were either inaccurate or unstable over relatively short time periods. In that case, the null hypothesis of no effect due to job control would have been more likely than was demonstrated. It should be noted, however, that the sample size of the test-retest stability study was very low (n⫽18) and highly influenced by 2 cases. In other samples and over time, the JCQ has proven to be reliable and stable.18

Conclusions Physical therapists view their work situations very positively. Physical therapists have a moderately demanding work environment and very high levels of control compared with other professions, and they may require these high levels of control to perform their jobs adequately. Job strain, within this sample, was associated with turnover and workrelated musculoskeletal symptoms. The psychosocial work environment is an important consideration for both therapists and employers. Physical therapists should consider the psychosocial work environment before choosing a first position or a new position. More studies are needed to describe the characteristics of positive work environments in this population. Initiatives in specific facilities that improve the psychosocial work environment for physical therapists also should be developed and studied.

September 2009

All authors provided concept/idea/research design and writing. Dr Campo provided data collection, project management, fund procurement, participants, and facilities/equipment. Dr Campo and Dr Koenig provided data analysis. This work was conducted as part of Dr Campo’s doctoral dissertation in the Program in Ergonomics and Biomechanics at New York University. The materials and methods of this project were reviewed and approved by the University Committee on Activities Involving Human Subjects (UCAIS) at New York University. This research, in part, was presented at the Combined Section Meeting of the American Physical Therapy Association; February 9 –12, 2009; Las Vegas, Nevada, and at the Safe Patient Handling and Movement Conference; March 29-April 3, 2009; Lake Buena Vista, Florida. This project was supported by 2 National Institutes of Health Extramural Research Development Awards (grant HD 035965), a National Institute for Occupational Safety and Health Education and Research Center Pilot Project Award (T42 OH008422), and a Smart Family Foundation Grant. The grants were used to cover direct and indirect expenses related to the pilot studies and the full project. Dr. Koenig’s work was supported, in part, by a Center grant from the National Institute of Environmental Health Sciences (ES00260). None of the funding sources were involved with the design and methods of the project or had any influence on the way the study was conducted. This article was received October 7, 2008, and was accepted May 28, 2009. DOI: 10.2522/ptj.20080322

References 1 Escriba-Aguir V, Martin-Baena D, PerezHoyos S. Psychosocial work environment and burnout among emergency medical and nursing staff. Int Arch Occup Environ Health. 2006;80:127–133. 2 Ahola K, Hakanen J. Job strain, burnout, and depressive symptoms: a prospective study among dentists. J Affect Disord. 2007;104:103–110. 3 de Croon EM, Sluiter JK, Blonk RW, et al. Stressful work, psychological job strain, and turnover: a 2-year prospective cohort study of truck drivers. J Appl Psychol. 2004;89:442– 454. 4 Head J, Kivimaki M, Martikainen P, et al. Influence of change in psychosocial work characteristics on sickness absence: the Whitehall II Study. J Epidemiol Community Health. 2006;60:55– 61.

5 Krause N, Ragland DR, Fisher JM, Syme SL. Psychosocial job factors, physical workload, and incidence of work-related spinal injury: a 5-year prospective study of urban transit operators. Spine. 1998;23: 2507–2516. 6 Blackmore ER, Stansfeld SA, Weller I, et al. Major depressive episodes and work stress: results from a national population survey. Am J Public Health. 2007;97: 2088 –2093. 7 Clays E, De Bacquer D, Leynen F, et al. Job stress and depression symptoms in middleaged workers: prospective results from the Belstress study. Scand J Work Environ Health. 2007;33:252–259. 8 Aboa-Eboule C, Brisson C, Maunsell E, et al. Job strain and risk of acute recurrent coronary heart disease events. JAMA. 2007;298:1652–1660. 9 Kornitzer M, deSmet P, Sans S, et al. Job stress and major coronary events: results from the Job Stress, Absenteeism and Coronary Heart Disease in Europe Study. Eur J Cardiovasc Prev Rehabil. 2006;13: 695–704. 10 Williams ES, Manwell LB, Konrad TR, Linzer M. The relationship of organizational culture, stress, satisfaction, and burnout with physician-reported error and suboptimal patient care: results from the MEMO study. Health Care Manage Rev. 2007;32: 203–212. 11 Park JR, Coombs CR, Wilkinson AJ, et al. Attractiveness of physiotherapy in the National Health Service as a career choice: qualitative study. Physiotherapy. 2003;89: 575–583. 12 Broom JP, Williams J. Occupational stress and neurological rehabilitation physiotherapists. Physiotherapy. 1996;82:606 – 614. 13 Schuster ND, Nelson DL, Quisling C. Burnout among physical therapists. Phys Ther. 1984;64:299 –303. 14 Deckard GJ, Present RM. Impact of role stress on physical therapists’ emotional and physical well-being. Phys Ther. 1989; 69:713–718. 15 Blau R, Bolus S, Carolan T, et al. The experience of providing physical therapy in a changing health care environment. Phys Ther. 2002;82:648 – 657. 16 Weiser S. Psychosocial aspects of occupational musculoskeletal disorders. In: Hurley R, ed. Musculoskeletal Disorders in the Workplace: Principles and Practice. New York, NY: CV Mosby Co; 1997:51– 61. 17 Mottram E, Flin RH. Stress in newly qualifiedphysiotherapists.Physiotherapy.1988; 74:607– 612. 18 Karasek R, Brisson C, Kawakami N, et al. The Job Content Questionnaire (JCQ): an instrument for internationally comparative assessments of psychosocial job characteristics. J Occup Health Psychol. 1998;3: 322–355. 19 Karasek R, Theorell T. Healthy Work: Stress, Productivity and the Reconstruction of the Working Life. New York, NY: Basic Books; 1990.

Volume 89

Number 9

Physical Therapy f

955

Job Strain in Physical Therapists 20 Campo MA, Weiser S, Koenig KL, Nordin M. Work-related musculoskeletal disorders in physical therapists: a prospective cohort study with 1-year follow-up. Phys Ther. 2008;88:608 – 619. 21 Ahlberg-Hulten GK, Theorell T, Sigala F. Social support, job strain and musculoskeletal pain among female health care personnel. Scand J Work Environ Health. 1995;21:435– 439. 22 Physical Therapy Workforce Project: Physical Therapy Vacancy and Turnover Rates in Skilled Nursing Facilities. Alexandria, VA: American Physical Therapy Association; 2008. 23 Physical Therapy Workforce Project: Physical Therapy Vacancy and Turnover Rates in Acute Care Hospitals. Alexandria, VA: American Physical Therapy Association; 2008. 24 Waldman JD, Kelly F, Arora S, Smith HL. The shocking cost of turnover in health care. Health Care Manage Rev. 2004;29: 2–7. 25 Cromie JE, Robertson VJ, Best MO. Workrelated musculoskeletal disorders in physical therapists: prevalence, severity, risks, and responses. Phys Ther. 2000;80: 336 –351. 26 Josephson M, Lagerstrom M, Hagberg M, Wigaeus Hjelm E. Musculoskeletal symptoms and job strain among nursing personnel: a study over a three year period. Occup Environ Med. 1997;54:681– 685. 27 Karasek R. Job Content Questionnaire and User’s Guide. Lowell, MA: University of Massachusetts; March 1985. 28 Landsbergis PA, Schnall PL, Warren K, et al. Association between ambulatory blood pressure and alternative formulations of job strain. Scand J Work Environ Health. 1994;20:349 –363.

956

f

Physical Therapy

Volume 89

29 Clumeck N, Kempenaers C, Godin I, et al. Working conditions predict incidence of long-term spells of sick leave due to depression: results from the Belstress I prospective study. J Epidemiol Community Health. 2009;63:286 –292. 30 Achat H, Kawachi I, Byrne C, et al. A prospective study of job strain and risk of breast cancer. Int J Epidemiol. 2000;29: 622– 628. 31 APTA Membership and Demographic Profile. Alexandria, VA: American Physical Therapy Association; 2005. 32 Tabachnick B, Fidell L. Using Multivariate Statistics. 5th ed. New York, NY: Pearson; 2007. 33 Hosmer DW, Lemeshow S. Applied Logistic Regression. 2nd ed. New York, NY: John Wiley & Sons Inc; 2000. 34 McGraw KO, Wong SP. Forming inferences about some intraclass correlation coefficients. Psychol Meth. 1996;1:30 – 46. 35 Rosner B. Fundamentals of Biostatistics. 5th ed. Pacific Grove, CA: Duxbury; 2000. 36 Bureau of Labor Statistics. Job Openings and Labor Turnover Survey. 2008. Available at: http://www.bls.gov/jlt/. Accessed May 6, 2008. 37 Jones CB. The costs of nurse turnover, part 2: application of the Nursing Turnover Cost Calculation Methodology. J Nurs Adm. 2005;35:41– 49. 38 Hatton C, Emerson E, Rivers M, et al. Factors associated with intended staff turnover and job search behaviour in services for people with intellectual disability. J Intellect Disabil Res. 2001;45(pt 3): 258 –270. 39 The APTA Employment Survey. Alexandria, VA: American Physical Therapy Association; 2005.

Number 9

40 Hoogendoorn WE, Bongers PM, de Vet HC, et al. High physical work load and low job satisfaction increase the risk of sickness absence due to low back pain: results of a prospective cohort study. Occup Environ Med. 2002;59:323–328. 41 Karlqvist L, Tornqvist EW, Hagberg M, et al. Self-reported working conditions of VDU operators and associations with musculoskeletal symptoms: a cross-sectional study focussing on gender differences. Int J Indus Erg. 2002;30:277–294. 42 Vermeulen M, Mustard C. Gender differences in job strain, social support at work, and psychological distress. J Occup Health Psychol. 2000;5:428 – 440. 43 Tsuboi H, Takeuchi K, Watanabe M, et al. Psychosocial factors related to low back pain among school personnel in Nagoya, Japan. Indus Health. 2002;40:266 –271. 44 Ariens GA, Bongers PM, Hoogendoorn WE, et al. High physical and psychosocial load at work and sickness absence due to neck pain. Scand J Work Environ Health. 2002;28:222–231. 45 Andersen JH, Kaergaard A, Frost P, et al. Physical, psychosocial, and individual risk factors for neck/shoulder pain with pressure tenderness in the muscles among workers performing monotonous, repetitive work. Spine. 2002;27:660 – 667. 46 Salminen S, Kivimaki M, Elovainio M, Vahtera J. Stress factors predicting injuries of hospital personnel. Am J Indus Med. 2003;44:32–36. 47 Bonde JP, Mikkelsen S, Andersen JH, et al. Prognosis of shoulder tendonitis in repetitive work: a follow-up study in a cohort of Danish industrial and service workers. Occup Environ Med. 2003;60:E8.

September 2009

Research Report Clinical Interpretation of a Lower-Extremity Functional Scale–Derived Computerized Adaptive Test Ying-Chih Wang, Dennis L. Hart, Paul W. Stratford, Jerome E. Mioduski

Background. The increasing use of computerized adaptive tests (CATs) to generate outcome measures during rehabilitation has prompted questions concerning score interpretation. Objective. The purpose of this study was to describe meaningful interpretations of functional status (FS) outcome measures estimated with a body part–specific CAT developed from the Lower-Extremity Functional Scale (LEFS).

Design. This investigation was a prospective cohort study of 8,714 people who had hip impairments and were receiving physical therapy in 257 outpatient clinics in 31 states (United States) between January 2005 and June 2007.

Methods. Four approaches were used to clinically interpret outcome data. First, the standard error of the estimate was used to construct the 90% confidence interval for each CAT-generated score estimate. Second, percentile ranks were applied to FS scores. Third, 2 threshold approaches were used to define individual subject–level change: statistically reliable change and clinically important change. The fourth approach was a functional staging method.

Results. The precision of a single score was estimated from the FS score ⫾4. On the basis of the score distribution, 25th, 50th, and 75th percentile ranks corresponded to intake FS scores of 40, 48, and 59 and discharge FS scores of 50, 61, and 75, respectively. The reliable change index supported the conclusion that changes in FS scores of 7 or more units represented statistically reliable change, and receiver operating characteristic analyses supported the conclusion that changes in FS scores of 6 or more units represented minimal clinically important improvement. Participants were classified into 5 hierarchical levels of FS using a functional staging method. Limitations. Because this study was a secondary analysis of prospectively col-

Y.-C. Wang, OT, PhD, is Postdoctoral Research Fellow, Sensory Motor Performance Program, Rehabilitation Institute of Chicago, 345 E Superior St, Ste 1406, Chicago, IL 60611-2654 (USA), and Research Assistant and Consultant, Focus On Therapeutic Outcomes, Inc, Knoxville, Tennessee. Address all correspondence to Dr Wang at: [email protected]. D.L. Hart, PT, PhD, is Director of Consulting and Research, Focus On Therapeutic Outcomes, Inc, Knoxville, Tennessee. P.W. Stratford, PT, MS, is Professor, School of Rehabilitation Science and Department of Clinical Epidemiology and Biostatistics, McMaster University, Ontario, Quebec, Canada. J.E. Mioduski, MS, is Information Systems/Programmer, Focus On Therapeutic Outcomes, Inc, Knoxville, Tennessee. [Wang Y-C, Hart DL, Stratford PW, Mioduski JE. Clinical interpretation of a Lower-Extremity Functional Scale– derived computerized adaptive test. Phys Ther. 2009;89:957–968.] © 2009 American Physical Therapy Association

lected data via a proprietary database management company, generalizability of results may be limited to participating clinics.

Conclusions. The results demonstrated how outcome measures generated from the hip LEFS CAT can be interpreted to improve clinical meaning. This finding might facilitate the use of patient-reported outcomes by clinicians during rehabilitation services. Post a Rapid Response or find The Bottom Line: www.ptjournal.org September 2009

Volume 89

Number 9

Physical Therapy f

957

Interpretation of LEFS CAT

M

easures of health status that are based on patient-reported outcomes (PROs) are routinely used in clinical trials, observational studies, medical research, and clinical practice.1– 6 Measures from PROs represent patient-centered measures and are recommended by the Institute of Medicine7 and the US Food and Drug Administration8 because such measures provide patients’ perceptions of their health status without a third party’s interpretation and allow clinics to quantify the effectiveness of their treatments9 –11 and monitor patients’ progress.12 As a result, the number of initiatives designed to assess quality (ie, change in health status) or describe value-based purchasing (ie, payment based on quality or cost) is on the rise13; one such initiative has been simulated for outpatient rehabilitation with PROs.9 The use of PROs during rehabilitation is increasing, but one barrier to integrating PRO measures into clinical practice is that scores often do not have meaning for clinicians.5,14 Many PRO measures have strong reliability and validity and are sensitive to change, but relatively few have been shown to present clinically meaningful information.15 Therefore, one of the challenges facing PRO developers is describing the clinical meaning of PRO measures and any differences observed, that is, clinically meaningful or important

Available With This Article at www.ptjournal.org • The Bottom Line clinical summary • The Bottom Line Podcast

changes that can be used to determine whether score changes indicate true and meaningful changes in follow-up or outcome studies. Another challenge is communicating scores derived from standardized outcome measures to clinicians directly involved with patient care. The lack of clinical interpretation of derived outcome measures impedes clinicians’ use of the outcome measures during treatment of patients.16 The present study builds on previous work in which we developed, simulated, and applied body part– specific computerized adaptive tests (CATs)17–22 for people seeking rehabilitation for a variety of impairments in outpatient physical therapy clinics. Here, we examine the clinical interpretation of patient-reported measures of functional status (FS) estimated with a CAT for people with hip impairments18,20 managed in outpatient therapy clinics participating with Focus On Therapeutic Outcomes, Inc (an international medical rehabilitation outcome database management company).23–25 The use of CATs offers several advantages over standard computeradministered or paper-and-pencil outcome instruments. Instead of examinees being given the same fixed test, items are selected according to an examinee’s ability. After each response, the examinee’s ability estimate is updated, and a subsequent item that optimizes the psychometric properties of the new estimate is selected.26 Consequently, the number of items administered is minimized while measure precision is maintained. Functional status assessed with the hip CAT18,20 is operationally defined as a patient’s perception of his or her ability to perform functional tasks.

• Audio Abstracts Podcast This article was published ahead of print on July 23, 2009, at www.ptjournal.org.

958

f

Physical Therapy

Volume 89

The development,20 simulation,20 and use18 of the hip CAT were described previously. In brief, the item bank for the hip CAT20 was develNumber 9

oped with items from the LowerExtremity Functional Scale (LEFS),14 which has strong psychometrics14,27–29 and broad clinical and research acceptance.15 Previous results indicated that the LEFS CAT met the essential item response theory (IRT) assumptions of item unidimensionality and local independence.20 The LEFS items demonstrated differential item functioning30 for the lower extremity affected (hip, knee, or foot/ankle); that is, item difficulty parameter estimates varied across different body part impairment groups after a patient’s underlying ability was controlled for. For instance, people with knee or hip impairments perceived walking to be easier than people with foot/ankle impairments for walking between rooms, walking 2 blocks, walking 1.6 km (1 mile), and running.20 People with knee impairments perceived squatting to be more difficult compared with people with foot/ankle impairments.20 Therefore, the hip CAT was developed with items calibrated on the basis of data from people with hip impairments, making the hip CAT a body part–specific or condition-specific CAT. When administered, on average, the hip CAT used 7 items to produce precise estimates of FS that adequately covered the content range with negligible floor and ceiling effects and that discriminated people in known clinical groups well. People who were older, had more chronic symptoms, had more surgeries, had more comorbidities, and did not exercise before receiving rehabilitation reported poorer (ie, lower) discharge FS than other people when intake FS was controlled for.18 Nonparametric receiver operating characteristic (ROC)31 analyses indicated that changes in FS scores of 6 or more units represented minimal clinically important improvement. When people were grouped by September 2009

Interpretation of LEFS CAT baseline FS measures and 4 separate ROC analyses were conducted (1 per quartile of intake FS measures), the results suggested that changes in FS scores of 11 or more, 6 or more, 4 or more, and 2 or more units represented clinically meaningful improvement for people in the first (intake FS, 0 – 40), second (intake FS, 40 – 48), third (intake FS, 48 –59), and fourth (intake FS, 59 –100) quartiles of intake FS measures, respectively.18 Clinically meaningful interpretations of the hip CAT have not been studied. For example, if a patient with a hip sprain presented in therapy with an intake FS score of 30, the following questions might be asked. How confident can I be about a reported score? How does my patient’s FS score compare with the scores of other patients? How much change is likely to represent a true change? How much improvement is likely to represent improvement that is clinically important to the patient? What does a specific score mean? To answer these questions, we constructed the 90% confidence interval (CI) for each score point estimate; established percentile ranks for FS scores; assessed statistically reliable change; assessed clinically important improvement; and described a functional staging approach. The first 4 methods provided statistical indexes, and the fifth method provided a graphical presentation to guide the clinical interpretation of a patient’s improvement in FS.

Method Data Collection The data collection process and the sample were described previously.18 In brief, data were collected by use of Patient Inquiry computer software.*,23–25 People seeking rehabilitation entered demographic data by us* Focus On Therapeutic Outcomes, Inc, PO Box 11444, Knoxville, TN 37939-1444.

September 2009

ing a computer in the clinic before their initial evaluation and therapy. Clinical staff could administer the CAT during physical therapy visits as a follow-up evaluation to monitor an individual’s status. Data were labeled “intake” when the CAT was completed before the initial evaluation (ie, at admission); data were labeled “discharge” when the CAT was completed at the time of discharge. The FS score change was defined by subtracting the FS score at intake from the FS score at discharge. Data were selected from the CAT database if people were receiving treatment for a hip impairment (operationally defined as an orthopedic impairment of the pelvis, hip, or upper leg); if they were receiving outpatient physical therapy in clinics participating with Focus On Therapeutic Outcomes, Inc, in the United States between January 2005 and June 2007; and if they completed the LEFS CAT. Setting and Participants A convenience sample of 8,714 people who had hip impairments and were receiving outpatient physical therapy in 257 outpatient clinics in 31 states (United States) was analyzed. As described previously,18 the mean age of the participants was 56 years (SD⫽17, range⫽18 – 102). Most of the participants were women (63%). The participants were receiving treatment for hip (68%), upper-leg (25%), or pelvic (7%) impairments. Most of the participants reported that their symptoms were chronic (52%). The most common medical or surgical diagnoses were soft-tissue disorders of muscle, synovium, tendon, or bursa or enthesopathies (ICD-9 codes 725–729) (30%) and postsurgical conditions (CPT codes 20150 –29999, including total hip replacement and open treatment of greater trochanteric fracture) (6%). More-detailed characteristics of

the participants were described previously.18 Hip LEFS CAT During routine administration in the clinic, the CAT items were presented by asking the individual, “Today, do you or would you have any difficulty at all with:” followed by activities such as “performing heavy activities around your home.” The computer used the 5 original LEFS response categories. The LEFS rating scale categories are: (1) “extreme difficulty or unable to perform,” (2) “quite a bit of difficulty,” (3) “moderate difficulty,” (4) “a little bit of difficulty,” and (5) “no difficulty.” In addition, the participant could elect “not applicable” for any item; this response was recorded as missing data and was not used in the FS estimation. CAT Algorithm As described previously,18,20 the hip CAT used an item bank developed from the LEFS.14 In brief, the adaptive test started with the administration of the most informative32 item at a median level of difficulty (eg, going up or down 10 stairs, about one flight of stairs). A participant’s ability (FS) and associated standard errors (SE) were estimated.33 There were 2 stopping rules: (1) the SE for the provisional ability was less than 4 of 100 FS units (ability estimates were scaled from 0 to 100, with higher measures representing higher functioning), and (2) each change in provisional ability estimates for the last 3 administered items was less than 1 of 100.20 If a stopping rule was not met, the computer selected the most informative item given the current FS estimate. The computer continued to administer items until a stopping rule was satisfied, at which time a final estimate of ability and its SE were provided. The final FS score represented a point estimate of the lower-extremity FS of each participant on a scale from 0 to 100, with higher measures representing

Volume 89

Number 9

Physical Therapy f

959

Interpretation of LEFS CAT represented an estimate of the precision of the measure. If a participant had a discharge FS score overlapping the 90% CI range of the intake FS score, the score change might not represent improvement but instead might be attributable to measurement error.

Figure 1. Lower-Extremity Functional Scale– derived computerized adaptive test (CAT) algorithm. FS⫽functional status.

higher functioning. When this CAT algorithm is used, an individual can receive different set of items when taking CATs at different times, depending on changes in the person’s FS. Figure 1 summarizes the CAT algorithm.

960

f

Physical Therapy

Volume 89

Approaches to Deriving Meaningful Interpretations of Measurements Interpreting a single scale score: How confident can I be about a reported score? Because the final FS score represented a point estimate of the FS of each participant, the 90% CI associated with the FS score point estimate was constructed to provide an estimate of precision. The width of the CI band

Number 9

Establishing the percentile rank of an FS score: How does my patient compare with others? The percentile rank of a score represents the percentage of scores in a distribution to which a specific score is greater than or equal to in a defined population. The percentile rank provides additional information regarding the location of a patient’s condition along the functional continuum relative to the condition of a group of people with similar characteristics. Although the percentile rank could be based on a healthy population, we believed that people in such a population (a more general norm) would probably respond “no difficulty” to LEFS items or would obtain nearly maximum scores on the hip CAT (ie, FS scores close to 100). Therefore, we used the percentile rank to provide additional information regarding the location of a patient’s condition along the functional continuum relative to the condition of a group of people with similar hip impairments. To accommodate differences in FS scores at intake and at discharge, we generated 2 percentile ranks: a percentile rank for people at intake and a percentile rank for people at discharge. Using 2 threshold approaches to define individual patient-level change. To examine the sensitivity of change, we used 2 threshold approaches to define individual patient-level change: statistically reliable change and clinically important change.34

September 2009

Interpretation of LEFS CAT How much change is likely to represent a true change? Statistically reliable change reflects the statistical significance of individual change. We computed the reliable change index (RCI),17,35,36 a z test of a longitudinal change between intake and discharge, by using the following mathematical formula: RCI⫽(X2⫺X1)/(␴公2(1⫺r)), where X2 is the score at discharge, X1 is the score at intake, ␴ is the standard deviation of the score at intake, and r is the reliability coefficient. When the RCI is 1.65 or larger, change is considered statistically reliable or significant at P⬍.10.35 As computed, the minimal score change (ie, FS score change) required for a statistically reliable change (X2⫺X1⫽ 1.65⫻公2⫻␴公(1⫺r)) is equivalent to the upper limit of the 90% CI of the minimal detectable change (MDC90). The RCI and minimal detectable change statistics can be interpreted, as 90% of truly stable people will display random fluctuations when assessed on 2 occasions within the range of MDC90.37,38 Therefore, the MDC90 represents the smallest threshold for identifying statistically reliable change that is greater than random measurement error. A 90% CI was selected so that the results could be compared directly with the results of initial LEFS testing.14 How much improvement is likely to represent an improvement that is clinically important to a patient? To assess clinically important change,17,39 – 41 as recommended by Stratford and Riddle,42 we used an anchor-based longitudinal method43,44 and a 15-point Likerttype scale (⫺7 to ⫹7)† to provide a † Examples of “better” response options, as compared with no change or getting worse, are: 0 (“almost the same”), ⫹1 (“hardly any better at all”), ⫹2 (“a little better”), ⫹3 (“somewhat better”), ⫹4 (“moderately better”), ⫹5 (“a good deal better”), ⫹6 (“a great deal better”), and ⫹7 (“a very great deal better”).

September 2009

global rating of change.40 Minimal clinically important improvement was defined as a cut score of ⫹3 or greater (⫹3⫽somewhat better). The threshold was determined with nonparametric ROC31 analyses. The results were reported previously.18 Here, we used the results to assist in the clinical interpretation of the FS derived from the hip CAT. Using a functional staging approach: what does a specific score mean? Functional staging involves the classification of a patient into hierarchical outcome stages for the purpose of describing the patient’s expected FS in each stage.5 The development of a functional staging approach involves 3 steps: select a conceptual model or classification system that has hierarchical order and is in accordance with the underlying measurement construct, determine cut scores on the basis of the staging definitions established in the first step, and specify the expected performance in each stage. Select a conceptual model. To classify lower-extremity function, we used the classification of walking described by Perry et al45 as the framework to construct the stages. As defined by Perry et al,45 lowerextremity function can be classified into several hierarchical functional levels: physiological ambulator, limited household ambulator, independent household ambulator, limited community ambulator, and independent community ambulator. Because the original target population in the classification of Perry et al was people who had sustained a stroke, we established the functional staging approach for our hip CAT by combining 2 “household ambulator” levels (2 low functional levels) and then added a higher level, “active community ambulator” (a more challenging functional level), to further distinguish the functional per-

formance of subjects at the high end of functioning. By definition,45 a “physiological ambulator” is an individual who can walk only for the purpose of exercise (stage 1). A “household ambulator” is an individual who can walk continuously for distances that are considered reasonable for walking inside the home but limited for walking in the community because of endurance, strength, or safety concerns (stage 2). A “limited community ambulator” is an individual who can walk regularly in the home and occasionally in the community (stage 3). An “independent community ambulator” is an individual who can walk for distances of at least 400 m (0.25 mile) independently in the community without physical or safety concerns (stage 4). Finally, an “active community ambulator” was defined as a individual who not only can walk 1.6 km (1 mile) with no difficulty but also can run on even ground with little difficulty (stage 5). Determine the cut scores. Because our functional staging approach was based on the framework of the classification of walking ability, we selected specific walking items as our primary interest: walking between rooms, walking 2 blocks, walking 1 mile, and running on even ground. Four cut scores were needed to establish functional stages 1 to 5. To determine the cut scores for functional stages along the FS continuous scale from 0 to 100, we took advantage of the inherent feature of IRT mathematics.32 We first analyzed the original hip CAT item bank20 data by using the Andrich46 rating scale IRT model. This measurement model was selected because it is a latent structure model for polytomous responses to a set of test items and because it was the model used to develop the hip CAT. Within the

Volume 89

Number 9

Physical Therapy f

961

Interpretation of LEFS CAT Table 1. Hip Computerized Adaptive Test (CAT) Percentile Ranks Based on Intake and Discharge Functional Status (FS) Scoresa Score

PRi (%)

PRd (%)

Score

PRi (%)

PRd (%)

Score

PRi (%)

PRd (%)

20

1.9

0.3

46

45.8

17.7

66

89.0

61.6

25

3.3

0.5

48

51.4

21.8

68

91.1

65.4

30

7.2

1.1

50

56.1

26.5

70

92.6

68.5

32

9.7

1.7

52

60.8

31.0

72

93.9

71.6

34

12.9

2.8

54

66.4

36.3

75

95.4

76.1

36

17.3

4.0

56

70.0

39.7

85

97.7

84.1

38

22.2

5.7

58

74.7

44.9

90

98.6

89.8

40

27.7

8.2

60

78.9

48.5

95

98.9

91.6

42

32.6

10.7

62

82.0

52.7

97

99.0

93.0

44

40.6

14.6

64

85.6

56.5

98

100.0

100.0

a

The scale ranged from 0 to 100. Scores were estimated with the hip CAT at intake or discharge. The 25th, 50th, and 75th percentile ranks corresponded to intake FS scores of 40, 48, and 59 and discharge FS scores of 50, 61, and 75, respectively. PRi⫽percentile rank at intake, PRd⫽percentile rank at discharge.

Andrich46 rating scale IRT model, each item was characterized by its category structure measure information (ie, category probability curve), which illustrates the probability of endorsing the response to an item at a given level of ability. The cut scores between functional stages were determined by finding the “category boundaries” on the ability continuum at which the probability of endorsing one of the pair of contiguous responses was .5. Here, we use the term “category boundaries” to refer to the structure calibration (ie, Andrich threshold) or step calibration at which adjacent categories were equally probable. We performed an exploratory analysis on the basis of our initial defined hierarchical stages to identify item category thresholds for specific items for which patients at a given stage were very likely (ie, a probability of at least 50%) to achieve the performance described. As a result, the cut scores between a physiological ambulator and a household ambulator and between a household ambulator and a limited community ambulator were determined by finding the thresholds between the “1” and “2” responses and between the 962

f

Physical Therapy

Volume 89

“3” and “4” responses for the item “walking between rooms” (see original LEFS rating scale categories in earlier description of hip LEFS CAT). The cut score between a limited community ambulator and an independent community ambulator was determined by finding the threshold between the “2” and “3” responses for the item “walking 1.6 km (1 mile).” Finally, the cut score between an independent community ambulator and an active community ambulator was determined by finding the lower threshold between the “3” and “4” responses for the item “running on even ground.”

Results

Specify the expected performance. Once the initial conceptual functional staging approach was developed and the cut scores were determined by the structure calibration, we specified the expected performance in each stage on the basis of the Andrich46 rating scale IRT measurement model. Here, the expected performance represents the response categories that a subject most likely would report.

Establishing the Percentile Rank of an FS Score: How Does My Patient Compare With Others? The mean FS scores at intake and discharge were 49 (SD⫽15) and 63 (SD⫽18), respectively. On average, subjects improved by 13 FS score units. The 25th, 50th, and 75th percentile ranks corresponded to intake FS scores of 40, 48, and 59 and discharge FS scores of 50, 61, and 75, respectively. Table 1 lists detailed percentile ranks based on FS intake scores and FS discharge scores.

Number 9

Interpreting a Single Scale Score: How Confident Can I Be About a Reported Score? The SEs at discharge were similar to the SEs at intake, with differences of 0 to 0.25 score unit. Here, for brevity, we present only SEs associated with intake FS score estimates. On average, the SE for all levels of FS was 2.9, and the SE for 96% of subjects with FS intake scores between 20 and 80 was 2.4. For all levels of FS, the 90% CI was FS point estimate ⫾5, and the 90% CI for participants with FS scores between 20 and 80 was FS point estimate ⫾4.

September 2009

Interpretation of LEFS CAT

Figure 2. Functional staging of lower-extremity function with the hip computerized adaptive test.

Using Threshold Approaches to Define Meaningful Change How much change is likely to represent a true change? On the basis of our previous full-length LEFS data set of 444 subjects with hip impairments, the internal consistency reliability coefficient was .96.20 With a standard deviation at intake of 15, the minimal score

change (discharge FS ⫺ intake FS) needed for the RCI to be 1.65 or larger was 7 FS score units. Therefore, RCI analyses indicated that changes in FS scores of 7 or more units represented statistically reliable change.

How much improvement is likely to represent an improvement that is clinically important to the patient? As described previously,18 ROC31 analyses indicated that changes in FS scores of 11 or more, 6 or more, 4 or more, and 2 or more units represented clinically meaningful improvement for subjects in the first (intake FS, 0 – 40), second (intake FS,

Table 2. Performance Expected in Each Functional Stage

Stage

Functional Status Score Range

1

0–20

2 3

Performance Classification

Running on Even Ground

Walking 1.6 km (1 Mile)

Walking 2 Blocks

Walking Between Rooms

Physiological ambulator

Unable

Unable

Unable

Unable

21–35

Household ambulator

Unable

Unable

A lot of difficulty

Moderate difficulty

36–48

Limited community ambulator

Unable

A lot of difficulty

Moderate difficulty

A little difficulty

4

49–61

Independent community ambulator

Moderate difficulty

A little difficulty

A little difficulty

No difficulty

5

62–100

Active community ambulator

A little difficulty

No difficulty

No difficulty

No difficulty

September 2009

Volume 89

Number 9

Physical Therapy f

963

Interpretation of LEFS CAT Table 3. Frequency Distribution of the Functional Stage Classificationa Intake Functional Stage

1

1

8

8

21

8

9

54 (1.3)

2

4

81

179

142

85

491 (12.2)

3

1

33

435

540

480

1,489 (36.9)

4

0

7

90

383

732

1,212 (30.1)

Discharge Functional Stage 2

5

0

2

Total no. (%)

13 (0.3)

131 (3.3)

3

9 734 (18.2)

4

5

74

701

1,147 (28.4)

2,007 (49.8)

Total no. (%)

786 (19.5) 4,032 (100)

a Participants were classified into functional stages on the basis of their intake and discharge functional status scores. Data are reported as number (percentage) of participants.

40 – 48), third (intake FS, 48 –59), and fourth (intake FS, 59 –100) quartiles of FS intake measures, respectively. Using a Functional Staging Approach: What Does a Specific Score Mean? Figure 2 displays the functional staging of lower-extremity function. The expected response (the gray scale horizontal bars) to a given item is shown as a function of the underlying lower-extremity ability (ie, FS) estimated with the hip CAT. All of the hip CAT items are listed in descending order of difficulty at the left side of Figure 2; more-challenging items are listed at the top. Figure 2 also displays the FS score continuum ranging from 0 to 100 (higher values represent higher functioning toward the right) and separated by different levels of functional staging from stage 1 (left or lower functioning) to stage 5 (right or higher functioning). Lower stages (eg, stages 1 and 2) described a participant’s lowerextremity function as limited (walking between rooms), and higher stages (eg, stages 4 and 5) indicated that a participant was more independent (walking in the community). The threshold probability results identified 20 as the cut score between functional stages 1 and stage 2, 35 as the cut score between functional stages 2 and stage 3, and so forth. 964

f

Physical Therapy

Volume 89

The expected performance at a particular FS score could be easily inspected by drawing a vertical line over the measure (x-axis) on Figure 2. For example, if a subject had an FS measure of 40 at intake, then the expected performance of this subject would be a little bit of difficulty walking between rooms; moderate difficulty getting into or out of a bath and walking 2 blocks; quite a bit of difficulty squatting, standing for 1 hour, and performing hobbies; and extreme difficulty hopping, running on even ground, and making sharp turns. Using the functional staging method, we could compare a participant’s FS score with the functional stages to better interpret the participant’s FS score. For example, participants classified in functional stage 3 (scores⫽36 – 48) reported being limited community ambulators, having moderate difficulty walking 2 blocks and having quite a bit of difficulty to extreme difficulty walking 1.6 km (1 mile). Participants classified in functional stage 4 (scores⫽49 – 61) reported being independent community ambulators, having a little bit of difficulty to moderate difficulty walking 1.6 km (1 mile) and having moderate difficulty to quite a bit of difficulty running on even ground. A guideline for interpreting FS stages is provided in Table 2, in which the expected performance of walking

Number 9

items in each stage is specified and simplified for easy use. We also simplified the original LEFS rating scale categories and replaced them with “unable” (if the expected response was “extreme difficulty”), “a lot of difficulty” (for “quite a bit of difficulty”), “moderate difficulty,” “a little difficulty” (for “a little bit of difficulty”), and “no difficulty.” We then classified participants with hip impairments by using our functional staging method. For our sample of 8,714 participants receiving therapy for hip impairments, both intake and discharge data were available for 4,032 participants (ie, 46% completion rate). Of these 4,032 participants, 2,204 (55%) improved to the next (ie, higher) functional stage from intake to discharge, and 220 (5%) dropped to a lower functional stage. Table 3 shows the frequency distribution of the functional stage classification on the basis of intake and discharge FS scores. The percentages of participants in each functional stage at intake were 1.3% (stage 1), 12.2% (stage 2), 36.9% (stage 3), 30.1% (stage 4), and 19.5% (stage 5). At discharge, the percentages of participants in each functional stage at intake were 0.3% (stage 1), 3.2% (stage 2), 18.2% (stage 3), 28.4% (stage 4), and 49.8% (stage 5). For each functional stage, the percentages of participants who September 2009

Interpretation of LEFS CAT improved to a higher functional stage from intake to discharge were 85% (stage 1), 82% (stage 2), 68% (stage 3), and 60% (stage 4). A Clinical Example To illustrate how to use these strategies to enhance clinically meaningful interpretations, we will answer the questions posed earlier. A patient (referred to here as “Jack”) sustained an unspecified sprain of hip and thigh (ICD-9 code 843.90). Jack, an 18-year-old man, sought treatment at a clinic because of limited function related to his sprain. His intake FS score was 30, and his discharge FS score, after 7 outpatient therapy visits, was 77 (FS score change⫽47). He considered his overall condition to be “a great deal better” and reported a global rating of change of ⫹6. To visualize Jack’s responses to our hip CAT, we plotted all of his responses in Figure 3. The structure of Figure 3 is equivalent to that of Figure 2, except that Jack’s responses are circled: light gray circles identify the responses at intake, and dark gray circles identify the responses at discharge. The 90% CI estimate of Jack’s intake FS score location was 26 to 34. Compared with the percentile ranks for other patients with a variety of hip impairments, Jack’s percentile rank at intake was 7, indicating that his lower-extremity function (estimated by FS) exceeded that of 7% of the patients who also had hip impairments at intake. The functional staging algorithm classified Jack as a household ambulator (stage 2). At discharge, the 90% CI estimate of Jack’s FS score location was 73 to 81. Compared with the percentile ranks for other patients, Jack’s percentile rank at discharge was 76. The functional staging classification suggested that Jack improved to being classified as an active community ambulator (stage 5). Jack’s improveSeptember 2009

Figure 3. Clinical example. The patient’s (Jack’s) responses are circled on the figure: light gray circles identify the responses at intake, and dark gray circles identify the responses at discharge. Responses were as follows: 1⫽“extreme difficulty or unable to perform activity,” 2⫽“quite a bit of difficulty,” 3⫽“moderate difficulty,” 4⫽“a little bit of difficulty,” 5⫽“no difficulty.” Colons mark the threshold cut scores between contiguous responses for each item. The broken vertical line represents Jack’s intake score of 30. The solid vertical line represents Jack’s discharge score of 77. FS⫽functional status, FSCH⫽functional status at discharge ⫺ functional status at intake, RUNUNEV⫽running on uneven ground, TURNS⫽making sharp turns, HOP⫽hopping, HEAVY⫽performing heavy activities, WALKMILE⫽walking a mile, HOBBY⫽performing hobbies, STAND⫽standing for 1 hour, SQUAT⫽squatting, WORK⫽doing work, STAIRS⫽up/ down 1 flight of stairs, LIFT⫽lifting an object, WALK2BLK⫽walking 2 blocks, CAR⫽getting into/out of a car, LIGHT⫽performing light activities, BATH⫽getting into/ out of bath, SHOE⫽putting on your shoes/socks, WALKRM⫽walking between rooms.

ment, indicated by an FS score change of 47, was considered to be statistically reliable (RCI⫽11.08 [⬎1.65]; FS score change, ⬎7) and clinically meaningful (FS score change by quartile, ⬎11); in addition, the improvement was supported by Jack’s perspective that his condition was “a great deal better.”

Discussion Computerized adaptive tests are commonly used as standardized tests for licensure, certification, and admission47,48 but have only recently begun to be used to collect routine clinical data in busy outpatient rehabilitation clinics.6,9,17–19,49 –51 In the present study, we followed the ap-

Volume 89

Number 9

Physical Therapy f

965

Interpretation of LEFS CAT proaches recommended by Jette et al,5 Stratford et al,15 Schmitt and Di Fabio,34 and Hays et al35 to derive more clinically meaningful interpretations of outcome measures, which might facilitate the use of these measures by clinicians. Several methods have been proposed to enhance clinical interpretation; they have focused on responsiveness or have used a single numeric index to define the minimal detectable change.52,53 In the present study, clinical interpretation was provided by several different approaches, including traditional score distribution (eg, standard error, percentile), responsiveness indexes, and functional staging. Given that these approaches offer different perspectives, we used them to generate a more comprehensive and clinically relevant interpretation of the FS scores estimated with the hip CAT, so that clinicians may select an approach depending on need. As described by Liang,16 providing information on function to clinicians has not led to changes in the process of care or to improved patient health. We believe that it is the responsibility of instrument developers to identify meaningful intraindividual change and to report the clinical interpretation of the measures. If these steps are taken, clinicians, managers of outpatient rehabilitation clinics, and researchers can use the measures in their clinical practices for the purpose of improving outcomes. The item bank for the hip CAT was developed from items in the LEFS.14 On the basis of the original LEFS development and validation results, Binkley et al14 suggested that the potential error associated with a score on the LEFS (original LEFS score range⫽0 – 80) at a given point in time was 5.3 (or 6.6%) scale points (90% CI), the MDC90 was 9 (or 11.3%) scale points, and the minimal 966

f

Physical Therapy

Volume 89

clinically important difference was 9 (or 11.3%) scale points. In the present study, a 90% CI was selected so that the results could be compared directly with the results of the initial LEFS testing by Binkley et al.14 With the hip CAT (hip CAT score range⫽0 –100), the 90% CI was FS point estimate ⫾4 (or 4%), the minimal change in FS scores required for a statistically reliable change was 7 units (or 7%, equivalent to the MDC90), and minimal clinically important improvement was indicated by changes in FS scores of at least 6 units (or 6%) overall and 11, 6, 4, and 2 units by quartile. The overall better performance of the hip CAT scores may have been attributable to the use of IRT methods, which improve the linearity of categorically scored scales,54 or the CAT administrative algorithm, which uses the most informative items given a patient’s current FS estimate. The use of items whose difficulty may not be matched to a patient’s functional ability may introduce error in FS measures.55 Additionally, we focused only on hip impairments and did not include other lower-extremity musculoskeletal impairments, and our sample size was relatively large (N⫽8,714) compared with that in the study of Binkley et al14 (N⫽107). One of the strengths of the present study was the functional staging approach, which allowed clinical interpretation through a visual display of scales with strong, clinically logical, hierarchically structured item banks developed by use of IRT methods. Without such a mathematical structure, functional staging would be dependent on clinical intuition. The display transforms IRT results into a format that can be applied directly by clinicians without a background in IRT methods. The basic idea for functional staging was derived from bookmark56 and key form57 methods. The bookmark

Number 9

method provides guidelines for setting a standard by following a prescribed, rational system of procedures that result in the assignment of a number to differentiate between 2 or more degrees of performance. A key form is a unique product of IRT methods that provides a visual display of the expected response patterns for the underlying measures. By combining features from both methods, functional staging provides a classification system and a visual display measurement tool. With functional staging, a rating instrument can be presented as a simple classification form.58 – 61 Clinicians can use the visual display to inspect the expected performance of a patient on the basis of the FS estimates derived from the hip CAT. Additionally, clinicians can derive an approximation of an individual FS score or examine unexpected ratings without a computerized analysis, as described by Linacre57 and Kielhofner et al.61 In this regard, improving the interpretation of FS measures may assist in a clinician’s understanding of a patient’s abilities.58 One concern about using functional staging is whether such a specific classification system should be tailored to groups of people with distinct diagnoses, such as people with total hip replacement and people with arthritis, because the discharge functional goals of these groups may be different. If a particular patient’s responses do not clearly fit into a particular stage, then differential item functioning analysis should be performed to inspect the item hierarchical order of that patient’s specific diagnostic group. The other concern is the need to validate the functional staging classification system because the thresholds were determined arbitrarily. Further studies should be done to validate the functional staging classification and to determine whether different functional staging systems should be estabSeptember 2009

Interpretation of LEFS CAT lished for groups of people with distinct diagnoses. There are several limitations of the present study. First, to estimate the RCI, we used single internal consistency reliability. Using internal consistency reliability instead of a testretest reliability coefficient may inflate the interpretation of the precision of a measure. Test-retest reliability has not yet been determined for CAT estimates of FS; thus, the impact magnitude is unknown. Investigations of the estimation of the RCI with a test-retest reliability coefficient are warranted. Second, we used score distributions from people with similar diagnoses to establish our percentile ranks based on the assumption that a more general norm from a healthy population would produce nearly maximum scores on the hip CAT, whereas scores from people with similar diagnoses would be more representative of people treated for hip impairments in outpatient rehabilitation. Nonetheless, the true score distribution of general or healthy populations is unknown, and establishing norms based on general or healthy populations would be valuable. Finally, 4,032 patients completed the hip CAT at rehabilitation discharge. These data represented a completion rate (ie, percentage of patients with both intake data and discharge data) of 46%.6 The missing values led to a concern about potentially biased estimates. Compared with patients with just intake data in this sample,18 patients with both intake and discharge data in this sample were older (t⫽7.8; df⫽8,197; P⬍.001), exercised more (␹2⫽7.1; df⫽2; P⫽.029), were more likely to have had a surgical procedure on a hip (␹2⫽11.1; df⫽4; P⫽.025), and had lower FS intake scores (t⫽2.6; df⫽8,957; P⫽.009). The groups did not differ in sex (␹2⫽0.2; df⫽1; September 2009

P⫽.686), acuity of symptoms (␹2⫽3.5; df⫽2; P⫽.172), number of comorbidities (␹2⫽2.0; df⫽3; P⫽.579), or medication use for their conditions (␹2⫽2.2; df⫽1; P⫽.136) at intake. However, based on the fact that the hip CAT was administered in 257 outpatient physical therapy clinics in 31 states (United States) and that the data set was large, we believe that the potential impact of subject selection bias was reduced, although the true impact is unknown.

Conclusion We demonstrated clinically meaningful interpretations of patientreported FS outcome measures estimated with a body part–specific CAT for use in routine clinical practice. The hip CAT currently is used routinely in many outpatient rehabilitation clinics across the United States and is integrated with an electronic health records system in Israel, attesting to its efficiency and utility. The results of the present study should improve the clinical interpretation of outcome measures and encourage future studies. Dr Wang, Dr Hart, and Mr Stratford provided concept/idea/research design. Dr Wang and Dr Hart provided writing and data analysis. Dr Hart and Mr Mioduski provided data collection and project management. Mr Mioduski provided facilities/equipment and clerical support. Mr Stratford provided consultation (including review of manuscript before submission). Dr Wang, Dr Hart, and Mr Mioduski are employees of Focus On Therapeutic Outcomes, Inc, the database management company that manages the data analyzed in this study. Dr Hart guided many of the analyses in this study and edited the manuscript. Mr Mioduski programmed the software that was used to develop the computerized adaptive test (CAT) and the software that was used to collect the data, and he managed the data collected from the CAT. Mr Stratford is one of the developers of the Lower-Extremity Functional Scale (LEFS), from which the LEFS CAT was developed, and was involved in the design of the project, review of the analyses, and review of the manuscript.

This project was approved by the Institutional Review Board for the Protection of Human Subjects of Focus On Therapeutic Outcomes, Inc. This article was received November 8, 2008, and was accepted May 6, 2009. DOI: 10.2522/ptj.20080359

References 1 Fliege H, Becker J, Walter OB, et al. Development of a computer-adaptive test for depression (D-CAT). Qual Life Res. 2005; 14:2277–2291. 2 Kosinski M, Bjorner JB, Ware JE Jr, et al. An evaluation of a patient-reported outcomes found computerized adaptive testing was efficient in assessing osteoarthritis impact. J Clin Epidemiol. 2006;59:715–723. 3 Ware JE Jr, Bjorner JB, Kosinski M. Practical implications of item response theory and computerized adaptive testing: a brief summary of ongoing studies of widely used headache impact scales. Med Care. 2000;38(9 suppl):II73–II82. 4 de Vet HC, Terwee CB, Ostelo RW, et al. Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change. Health Qual Life Outcomes. 2006; 4:54 –58. 5 Jette AM, Tao W, Norweg A, Haley S. Interpreting rehabilitation outcome measurements. J Rehabil Med. 2007;39:585–590. 6 Deutscher D, Hart DL, Horn SD, et al. Implementing an integrated electronic outcomes and electronic health record process to create a foundation for clinical practice improvement. Phys Ther. 2008; 88:270 –285. 7 Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academy Press; 2001. 8 US Department of Health and Human Services FDA Center for Drug Evaluation and Research. Guidance for industry: patientreported outcome measures: use in medical product development to support labeling claims: draft guidance. Health Qual Life Outcomes. 2006;4:79 –98. 9 Hart DL, Connolly JB. Pay-for-performance for physical therapy and occupational therapy: Medicare Part B services. Centers for Medicare & Medicaid Services. Available at: http://www.cms.hhs.gov/Therapy Services/downloads/P4PFinalReport06-0106.pdf. 2006. Accessed June 5, 2009. 10 Resnik L, Liu D, Hart DL, Mor V. Benchmarking physical therapy clinic performance: statistical methods to enhance internal validity when using observational data. Phys Ther. 2008;88:1078 –1087. 11 Resnik L, Hart DL. Using clinical outcomes to identify expert physical therapists. Phys Ther. 2003;83:990 –1002. 12 Guide to Physical Therapist Practice. 2nd ed. Phys Ther. 2001;81:9 –746.

Volume 89

Number 9

Physical Therapy f

967

Interpretation of LEFS CAT 13 Johnson DA. Pay for performance: ACG guide for physicians. Am J Gastroenterol. 2007;102:2119 –2122. 14 Binkley JM, Stratford PW, Lott SA, Riddle DL. The Lower-Extremity Functional Scale (LEFS): scale development, measurement properties, and clinical application. Phys Ther. 1999;79:371–383. 15 Stratford PW, Hart DL, Binkley JM, et al. Interpreting lower extremity functional status scores. Physiother Can. 2005;57: 154 –162. 16 Liang MH. Longitudinal construct validity: establishment of clinical meaning in patient evaluative instruments. Med Care. 2000;38(9 suppl):II84 –II90. 17 Hart DL, Wang YC, Stratford PW, Mioduski JE. Computerized adaptive test for patients with foot or ankle impairments produced valid and responsive measures of function. Qual Life Res. 2008;17:1081–1091. 18 Hart DL, Wang YC, Stratford PW, Mioduski JE. Computerized adaptive test for patients with hip impairments produced valid and responsive measures of function. Arch Phys Med Rehabil. 2008;89:2129 –2139. 19 Hart DL, Wang YC, Stratford PW, Mioduski JE. Computerized adaptive test for patients with knee impairments produced valid and responsive measures of function. J Clin Epidemiol. 2008;61:1113–1124. 20 Hart DL, Mioduski JE, Stratford PW. Simulated computerized adaptive tests for measuring functional status were efficient with good discriminant validity in patients with hip, knee, or foot/ankle impairments. J Clin Epidemiol. 2005 Jun;58:629 – 638. 21 Hart DL, Cook KF, Mioduski JE, et al. Simulated computerized adaptive test for patients with shoulder impairments was efficient and produced valid measures of function. J Clin Epidemiol. 2006;59:290 –298. 22 Hart DL, Mioduski JE, Werneke MW, Stratford PW. Simulated computerized adaptive test for patients with lumbar spine impairments was efficient and produced valid measures of function. J Clin Epidemiol. 2006;59:947–956. 23 Dobrzykowski EA, Nance T. The Focus On Therapeutic Outcomes (FOTO) outpatient orthopedic rehabilitation database: results of 1994 –1996. J Rehabil Outcomes Meas. 1997;1:56 – 60. 24 Swinkels IC, van den Ende CHM, de Bakker DH, et al. Clinical databases in physical therapy. Physiother Theory Pract. 2007; 23:153–167. 25 Swinkels IC, Hart DL, Deutscher D, et al. Comparing patient characteristics and treatment processes in patients receiving physical therapy in the United States, Israel and the Netherlands: cross sectional analyses of data from three clinical databases. BMC Health Serv Res. 2008;8:163–174. 26 van der Linden WJ, Glas CAW, eds. Computerized Adaptive Testing: Theory and Practice. Norwell, MA: Kluwer Academic Publishers; 2000. 27 Alcock GK, Stratford PW. Validation of the Lower-Extremity Functional Scale on athletic subjects with ankle sprains. Physiother Can. 2002;54:233–240.

968

f

Physical Therapy

Volume 89

28 Stratford PW. Getting more from the literature: estimating the standard error of measurement from reliability studies. Physiother Can. 2004;56:27–30. 29 Stratford PW, Binkley JM, Watson J, HeathJones T. Validation of the LEFS on patients with total joint arthroplasty. Physiother Can. 2000;52:97–105. 30 Millsap RE, Everson HT. Methodology review: statistical approaches for assessing measurement bias. Appl Psych Meas. 1993; 17:287–334. 31 Deyo RA, Centor RM. Assessing the responsiveness of functional scales to clinical change: an analogy to diagnostic test performance. J Chronic Dis. 1986;39:897–906. 32 Lord FM. Applications of Item Response Theory to Practical Testing Problems. Hillsdale, NJ: Lawrence Erlbaum Associates; 1980. 33 Linacre JM. Estimating measures with known polytomous item difficulties. Rasch Measurement Transactions. 1998;12:638. 34 Schmitt JS, Di Fabio RP. Reliable change and minimum important difference (MID) proportions facilitated group responsiveness comparisons using individual threshold criteria. J Clin Epidemiol. 2004;57: 1008 –1018. 35 Hays RD, Brodsky M, Johnston MF, et al. Evaluating the statistical significance of health-related quality-of-life change in individual patients. Eval Health Prof. 2005;28: 160 –171. 36 Jacobson NS, Truax P. Clinical significance: a statistical approach to defining meaningful change in psychotherapy research. J Consult Clin Psychol. 1991;59:12–19. 37 Beaton DE, Bombardier C, Katz JN, Wright JG. A taxonomy for responsiveness. J Clin Epidemiol. 2001;54:1204 –1217. 38 Barreca SR, Stratford PW, Lambert CL, et al. Test-retest reliability, validity, and sensitivity of the Chedoke arm and hand activity inventory: a new measure of upperlimb function for survivors of stroke. Arch Phys Med Rehabil. 2005;86:1616 –1622. 39 Deyo RA, Patrick DL. The significance of treatment effects: the clinical perspective. Med Care. 1995;33(4 suppl):AS286 –AS291. 40 Jaeschke R, Singer J, Guyatt GH. Measurement of health status: ascertaining the minimal clinically important difference. Control Clin Trials. 1989;10:407– 415. 41 Kazis LE, Anderson JJ, Meenan RF. Effect sizes for interpreting changes in health status. Med Care. 1989;27(3 suppl): S178 –S189. 42 Stratford PW, Riddle DL. Assessing sensitivity to change: choosing the appropriate change coefficient. Health Qual Life Outcomes. 2005;3:23–29. 43 Crosby RD, Kolotkin RL, Williams GR. Defining clinically meaningful change in health-related quality of life. J Clin Epidemiol. 2003;56:395– 407. 44 Hsieh YW, Wang CH, Wu SC, et al. Establishing the minimal clinically important difference of the Barthel Index in stroke patients. Neurorehabil Neural Repair. 2007;21:233–238.

Number 9

45 Perry J, Garrett M, Gronley JK, Mulroy SJ. Classification of walking handicap in the stroke population. Stroke. 1995;26:982–989. 46 Andrich DA. A rating formulation for ordered response categories. Psychometrika. 1978;43:561–573. 47 Mills CN, Potenza MT, Fremer JJ, Ward WC, eds. Computer-Based Testing: Building the Foundation for Future Assessments. Mahwah, NJ: Lawrence Erlbaum Associates; 2002. 48 Wainer H, ed. Computerized Adaptive Testing: A Primer. 2nd ed. Mahwah, NJ: Lawrence Erlbaum Associates; 2000. 49 Jette AM, Haley SM, Tao W, et al. Prospective evaluation of the AM-PAC-CAT in outpatient rehabilitation settings. Phys Ther. 2007;87:385–398. 50 Gandek B, Sinclair SJ, Jette AM, Ware JEJ. Development and initial psychometric evaluation of the participation measure for post-acute care (PM-PAC). Am J Phys Med Rehabil. 2007;86:57–71. 51 Kopec JA, Badii M, McKenna M, et al. Computerized adaptive testing in back pain: validation of the CAT-5D-QOL. Spine. 2008;33:1384 –1390. 52 Watson CJ, Propps M, Ratner J, et al. Reliability and responsiveness of the lower extremity functional scale and the anterior knee pain scale in patients with anterior knee pain. J Orthop Sports Phys Ther. 2005;35:136 –146. 53 Beninato M, Gill-Body KM, Salles S, et al. Determination of the minimal clinically important difference in the FIM instrument in patients with stroke. Arch Phys Med Rehabil. 2006;87:32–39. 54 McHorney CA, Haley SM, Ware JEJ. Evaluation of the MOS SF-36 Physical Functioning Scale (PF-10), II: comparison of relative precision using Likert and Rasch scoring methods. J Clin Epidemiol. 1997;50:451– 461. 55 Thissen D. Reliability and measurement precision. In: Wainer H, ed. Computerized Adaptive Testing: A Primer. 2nd ed. Mahwah, NJ: Lawrence Erlbaum Associates; 2000:159 –184. 56 Cizek GJ, Bunch MB, Koons H. Setting performance standards: contemporary methods. Educational Measurement: Issues and Practice. 2004;23:31–51. 57 Linacre JM. Instantaneous measurement and diagnosis. Phys Med Rehabil. 1997; 11:315–324. 58 Woodbury ML, Velozo CA. Potential for outcomes to influence practice and support clinical competency. OT Practice. 2005;10:7– 8. 59 Hart DL, Wright BD. Development of an index of physical functional health status in rehabilitation. Arch Phys Med Rehabil. 2002;83:655– 665. 60 Arnould C, Penta M, Renders A, Thonnard JL. ABILHAND-Kids: a measure of manual ability in children with cerebral palsy. Neurology. 2004;63:1045–1052. 61 Kielhofner G, Dobria L, Forsyth K, Basu S. The construction of keyforms for obtaining instantaneous measures from the occupational performance history interview rating scales. Occup Ther J Res. 2005;25:1–10.

September 2009

Research Report Development of a Self-Report Measure of Fearful Activities for Patients With Low Back Pain: The Fear of Daily Activities Questionnaire Steven Z. George, Carolina Valencia, Giorgio Zeppieri Jr, Michael E. Robinson

Background. Self-report measures for assessing specific fear of activities have not been reported in the peer-reviewed literature, but are necessary to adequately test treatment hypotheses related to fear-avoidance models. Objective. This study described psychomotor properties of a novel self-report measure, the Fear of Daily Activities Questionnaire (FDAQ).

Design. A prospective cohort design was used. Methods. Reliability and validity cohorts were recruited from outpatient physical therapy clinics. Analyses for the reliability cohort included internal consistency and 48-hour test-retest coefficients, as well as standard error of measurement and minimal detectable change estimates. Analyses for the validity cohort included factor analysis for construct validity and correlation and multiple regression analyses for concurrent and predictive validity. Four-week responsiveness was assessed by paired t test, effect size calculation, and percentage of patients meeting or achieving MDC criterion.

Results. The FDAQ demonstrated adequate internal consistency (Cronbach alpha⫽.91, 95% confidence interval⫽.87–.95) and 48-hour test-retest properties (intraclass correlation coefficient⫽.90, 95% confidence interval⫽.82–.94). The standard error of measurement for the FDAQ was 6.6, resulting in a minimal detectable change of 12.9. Factor analysis suggested a 2- or 3-factor solution consisting of loaded spine, postural, and spinal movement factors. The FDAQ demonstrated concurrent validity by contributing variance to disability (baseline and 4 weeks) and physical impairment (baseline) scores. In predictive validity analyses, baseline FDAQ scores did not contribute variance to 4-week disability and physical impairment scores, but changes in FDAQ scores were associated with changes in disability. The FDAQ scores significantly decreased over a 4-week treatment period, with an effect size of .86 and 55% of participants meeting the minimal detectable change criterion.

S.Z. George, PT, PhD, is Associate Professor, Department of Physical Therapy, Center for Pain Research and Behavioral Health, Brooks Center for Rehabilitation Studies, University of Florida, PO Box 100154, Gainesville, FL 32615 (USA). Address all correspondence to Dr George at: szgeorge@phhp. ufl.edu. C. Valencia, BS, is a student in the Rehabilitation Science Doctoral Program, Department of Physical Therapy, University of Florida. G. Zeppieri Jr, PT, MPT, is Staff Physical Therapist, Shands Rehab Center, UF Orthopaedics and Sports Medicine Institute, Gainesville, Florida. M.E. Robinson, PhD, is Professor, Department of Clinical and Health Physiology and Center for Pain Research and Behavioral Health, University of Florida. [George SZ, Valencia C, Zeppieri G Jr, Robinson ME. Development of a self-report measure of fearful activities for patients with low back pain: the Fear of Daily Activities Questionnaire. Phys Ther. 2009;89:969 –979.] © 2009 American Physical Therapy Association

Limitations. The validity cohort was a secondary analysis of a clinical trial, and additional research is needed to confirm these findings in other samples.

Conclusions. The FDAQ is a potentially viable measure for fear of specific activities in physical therapy settings. These analyses suggest the FDAQ may be appropriate for determining graded exposure treatment plans and monitoring changes in fear levels, but is not appropriate as a screening tool. Post a Rapid Response or find The Bottom Line: www.ptjournal.org September 2009

Volume 89

Number 9

Physical Therapy f

969

Self-Report Measure of Fearful Activities for Patients With LBP

T

he fear-avoidance model of musculoskeletal pain (FAM) is a current model used to explain the development and maintenance of chronic low back pain (LBP).1 The FAM proposes that pain perception is primarily influenced by pain-related fear and pain catastrophizing.1–3 These psychological factors interact to determine an individual’s initial behavioral response to acute pain. Low levels of pain-related fear and pain catastrophizing are associated with a confrontation behavioral response, which is believed to be a precursor to resuming normal activities.1–3 In contrast, high levels of pain-related fear and pain catastrophizing are associated with an avoidance behavioral response, which is believed to be a precursor to experiencing chronic disability.1–3 Evidence supporting the FAM can be found in prospective clinical studies of pain-related fear. Several longitudinal studies4 –9 suggested that elevated measures of pain-related fear were predictive of poor LBP outcomes. Evidence supporting the FAM also can be found in studies incorporating treatment strategies to reduce pain-related fear. Effective LBP treatment strategies consistent with the FAM have been reported in the literature, and these interventions include patient education,10,11 graded exercise,12,13 and graded exposure.14 –17 Collectively, the previously cited studies provide an empir-


970

f

Physical Therapy

Volume 89

ical foundation for the FAM and suggest that the model may have clinical relevance for patients with LBP.1 Whether measurement of painrelated fear needs to be general or specific to an activity is an unresolved issue related to the FAM.1 Validated questionnaires assess beliefs related to the perceived harm and threat of experiencing LBP or performing physical activity while in pain.18,19 Examples of specific activities are not provided when patients respond to these questionnaires,18,19 limiting their use in developing treatment programs that incorporate graded, hierarchical exposure to specific fearful activities (ie, graded exposure). It has been hypothesized that graded exposure is more effective than quota-driven approaches to increasing general activity levels (ie, graded activity or exercise).1,14,20,21 Measurement limitations may hamper future clinical investigation of the FAM because testing graded exposure hypotheses in physical therapy settings require reliable and valid instruments to assess fear of specific activities. Therefore, the purpose of this study was to describe the psychometric properties of a novel self-report measure for fear of activities for patients with LBP. The Fear of Daily Activities Questionnaire (FDAQ) recently was developed to guide physical therapy supplemented with graded exposure in a clinical trial.20 In the current study, we investigated test-retest reliability, internal consistency, construct validity, concurrent validity, predictive validity, and responsiveness for the FDAQ. We hypothesized that the FDAQ would demonstrate adequate psychometric properties, suggesting potential utility for patients with LBP.

Number 9

Method Overview All participants provided informed consent before study participation was confirmed. Psychometric properties of the FDAQ have not been reported previously, and 2 cohorts were recruited for this study. The first cohort consisted of patients with chronic LBP. These participants were used primarily for analyses to investigate the reliability of FDAQ scores because they would be clinically stable during the 48-hour testretest period. The second cohort consisted of participants with acute or subacute LBP participating in a clinical trial.20 These participants were expected to have changes in their clinical status during the 4-week follow-up and were used in analyses to investigate the validity of FDAQ scores. The clinical trial utilized the FDAQ to measure specific fear of activities for implementing graded exposure, but the FDAQ was not used as an outcome measure. Participants The inclusion and exclusion criteria for the reliability and validity cohorts were based on guidelines from the Quebec Task Force on Spinal Disorders.22 For the purposes of this study, acute and subacute LBP were operationally defined as reporting current symptoms for 1 to 24 weeks and chronic LBP was defined as reporting current symptoms for greater than 24 weeks. Reliability cohort. A sample of convenience was recruited from patients seeking treatment for LBP at University of Florida–affiliated outpatient clinics. Inclusion criteria were being between 15 and 60 years of age and having chronic LBP with or without radiating symptoms. Patients had to have the ability to read and speak English because questionnaires were used. Exclusion criteria were having acute or subacute LBP, signs of nerve root compression, September 2009

Self-Report Measure of Fearful Activities for Patients With LBP lumbar spinal stenosis, or postoperative lumbar spine surgery. Patients also were excluded for pregnancy, osteoporosis, and spinal disorders related to metastatic disease, visceral disease, or fracture.

tings, and providing patients with options for open-ended responses. This modified version of the FDAQ was used in the previously described cohorts for formal psychometric analyses.

item scale that assesses the degree of catastrophic cognitions a patient reports due to LBP. The PCS has a total range of scores of 0 to 52, and higher scores are associated with higher amounts of pain catastrophizing.

Validity cohort. Consecutive patients seeking treatment for LBP at University of Florida–affiliated clinics were recruited. Inclusion criteria were being between 15 and 60 years of age and having acute or subacute LBP with or without radiating symptoms. Patients had to have the ability to read and speak English because questionnaires were used. Exclusion criteria were having chronic LBP, signs of nerve root compression, lumbar spinal stenosis, or postoperative lumbar spine surgery. Patients also were excluded for pregnancy, osteoporosis, and spinal disorders related to metastatic disease, visceral disease, or fracture.

The FDAQ lists 10 activities that patients with LBP commonly report as being fearful of performing due to LBP (Appendix). The FDAQ has 2 options for open-ended responses so that patients with LBP can provide additional examples and ratings of activities that they fear performing due to pain. Patients rate each FDAQ item using a numerical rating scale (NRS) ranging from 0 (“no fear”) to 100 (“maximal fear”). The FDAQ is scored by totaling the NRS ratings for the 10 standard activities and dividing by 10. Higher FDAQ scores indicate higher fear of activities. The open-ended responses were not included in the current analyses because responses varied in the appropriateness for rehabilitation, were not always associated with the highest fear ratings, and were not always provided by the participants. These issues made incorporation of the open-ended responses difficult for ranking and scoring purposes. Therefore, the decision was made to exclude the open-ended responses from these analyses, but we still believe they are potentially useful for clinical decision-making purposes.

Physical impairment. The previously described Physical Impairment Scale (PIS)23 was used to quantify physical impairment due to LBP. The PIS consists of 7 different examination procedures performed by the patient, and performance for each procedure is scored as a negative (0) or positive (1) for presence of impairment. The PIS has a total range of scores of 0 to 7, and higher scores indicate higher levels of physical impairment due to LBP.

Measures FDAQ. The FDAQ was developed by a group of health care professionals involved in rehabilitation of chronic musculoskeletal pain from clinics in Gainesville, Florida, and Jacksonville, Florida. The group’s goal was to create a self-report measure that is easy to administer, appropriate for use in determining graded exposure activity prescription, and acceptable for tracking changes in fear of activities. A physician, 2 physical therapists, and 2 psychologists generated potential items for the FDAQ over 2 separate meetings. A preliminary form of the FDAQ was created and pilot tested in the Jacksonville clinic for 6 months. The FDAQ then was further modified based on input from psychologists, physical therapists, and patients, as well as preliminary analyses. Modifications to the FDAQ included shortening of the total number of items, eliminating redundant items, removing items that could not be incorporated in standard rehabilitation setSeptember 2009

Previously validated measures consistent with the FAM. The Fear-Avoidance Beliefs Questionnaire (FABQ) was used to quantify fear-avoidance beliefs.19 The FABQ contains 2 scales: a 7-item FABQ work scale (FABQ-W, range of scores⫽0 – 42) and a 4-item FABQ physical activity scale (FABQ-PA, range of scores⫽0 –24). Higher scores indicate higher levels of fearavoidance beliefs for both FABQ scales. The Pain Catastrophizing Scale (PCS) was used to quantify pain catastrophizing.18 The PCS is a 13-

Pain and disability. Participants rated their pain intensity using an NRS ranging from 0 (“no pain”) to 10 (“worst pain imaginable”).24 They rated pain intensity over 3 conditions: the present pain intensity, the worst pain intensity over the past 24 hours, and the best pain intensity over the past 24 hours. These 3 ratings were summed and divided by 3 (arithmetic mean) for use in data analyses.25 Disability was assessed with the Oswestry Disability Questionnaire (ODQ), which has been recommended as an appropriate outcome measure for self-report of disability.26,27 The ODQ has 10 items that assess how LBP affects common daily activities (eg, sitting, standing, lifting). The ODQ has a range of scores of 0 (“no disability due to back pain”) to 100 (“completely disabled due to back pain”), so higher scores indicate higher disability from LBP. Procedure Reliability cohort. Participants who met the eligibility criteria for the reliability cohort provided informed consent and completed the FDAQ, NRS for pain intensity, and ODQ during a routine appointment

Volume 89

Number 9

Physical Therapy f

971

Self-Report Measure of Fearful Activities for Patients With LBP for outpatient physical therapy. They then were given a self-addressed, stamped envelope with instructions to complete the FDAQ again 48 hours later. They were instructed to complete the FDAQ, provide the date of completion on the form, and mail it to the authors. Validity cohort. Participants who met the eligibility criteria for the validity cohort provided informed consent and completed the FDAQ, along with the FABQ, PCS, NRS for pain intensity, and ODQ. A physical therapist who was masked to group assignment administered the PIS at baseline. The participants then were treated for 4 weeks by licensed physical therapists according to their random assignment of physical therapy alone, physical therapy supplemented with graded exercise, or physical therapy supplemented with graded exposure. The participants were reassessed on the same measures by a blinded evaluator 4 weeks after randomization. The primary analysis of the trial indicated no differences in 4-week outcomes for any of the previously validated measures used in this study. Therefore, participants were analyzed as a single cohort for the purpose of this study, instead of in randomly assigned treatment groups. Data Analysis Reliability cohort. Descriptive analyses were generated and reported in the appropriate metric for continuous and categorical variables. Reliability analyses included analysis of internal consistency (Cronbach alpha) for individual FDAQ items and analysis of test-retest reliability (intraclass correlation coefficient [ICC] [2,1]) for the total FDAQ score. These results were reported with appropriate coefficient and 95% confidence interval (CI). From these data, the standard error of measurement (SEM) was calculated using a previously described method (standard 972

f

Physical Therapy

Volume 89

deviation ⫻ 公(1 – test-retest reliability coefficient).28 –30 The minimal detectable change (MDC) also was calculated using a previously described method (1.96⫻SEM).31 Validity cohort. Descriptive analyses were generated and reported in the appropriate metric for continuous and categorical variables. Construct validity was assessed with factor analysis (principal component analysis, varimax rotation with Kaiser normalization) at baseline and 4 weeks. Concurrent validity was assessed by reporting correlations (Pearson r) of the FDAQ with the FABQ, PCS, PIS, NRS for pain intensity, and ODQ at baseline and 4 weeks. Concurrent validity was assessed further by separate multiple regression models for baseline and 4-week measures. These models tested FDAQ contributions to disability or physical impairment after controlling for pain intensity and commonly implemented measures of FAM variables. The independent variables for these regression analyses were the FDAQ, NRS for pain intensity, FABQ-PA, FABQ-W, and PCS. The ODQ and PIS were the dependent variables for these models. These analyses would provide information on the FDAQ in relation to previously established measures, as well as whether the assessment of the FAM should include general and specific measures. Predictive validity was assessed by investigating whether baseline FDAQ scores contributed additional variance to 4-week outcomes for disability and physical impairment. In these models, the baseline scores for the ODQ and PIS first were entered into the model to predict the respective 4-week outcomes. In the second step of the models, the NRS for pain intensity, FABQ-PA, FABQ-W, PCS, and FDAQ were considered in a stepwise manner. These analyses pro-

Number 9

vided information on whether the FDAQ could potentially be used as a screening tool to predict outcomes compared with the previously validated measures related to the FAM. Predictive validity was assessed further by determining whether 4-week changes in the FDAQ scores contributed additional variance to 4-week changes for disability and physical impairment. In these models, change scores for the NRS for pain intensity, FABQ-PA, FABQ-W, PCS, and FDAQ were considered as predictors in a stepwise manner for 4-week changes in scores for the ODQ and PIS (separate models). These analyses provided information on whether changes in the FDAQ scores were associated with changes in accepted outcome measures for LBP.26,27 Responsiveness was assessed by paired t test and calculation of effect size (Cohen d) for those participants who completed the 4-week followup. The percentage of participants from the reliability cohort who met the MDC criterion was calculated to provide a categorical estimate of responsiveness. Role of the Funding Source Dr George (principal investigator), Ms Valencia, and Dr Robinson received support from the National Institutes of Health/National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant AR051128) while preparing the manuscript.

Results Descriptive statistics for baseline measures of the reliability and validity cohorts are reported in Table 1. Ninety-two percent (46/50) of the participants in the reliability cohort completed the 48-hour assessment, with no differences in key variables for those who completed and those who did not complete the reliability follow-up. The validity cohort was followed for 4 weeks, with 85% (92/ 108) of the participants providing September 2009

Self-Report Measure of Fearful Activities for Patients With LBP Table 1. Baseline Characteristics for Reliability and Validity Cohortsa Variable

Reliability Cohort (nⴝ50)

Age (y)

Validity Cohort (nⴝ108)

44.28 (18.47)

37.2 (14.5)

Female

43 (86.0%)

69 (63.9%)

Male

17 (14.0%)

39 (36.1%)

Currently employed

30 (60.0%)

62 (57.4%)

Work-related LBP

13 (26.0%)

22 (20.4%)

39 (78.0%)

66 (61.1%)

Fear of Daily Activities Questionnaire (potential range of scores⫽0–100)

24.9 (20.7)

37.3 (26.7)

Oswestry Disability Questionnaire (potential range of scores⫽0–100)

27.4 (17.8)

29.5 (16.2)

4.2 (2.2)

4.7 (2.1)

Sex

Duration of LBP (no. of weeks of present episode) Prior history of LBP

7.5 (6.2)

Sudden onset of LBP

73 (67.6%)

Numerical rating scale for pain intensity (potential range of scores⫽0–10)

a

Fear-avoidance beliefs about physical activity (potential range of scores⫽0⫺24)

14.9 (5.5)

Fear-avoidance beliefs about work (potential range of scores⫽0⫺42)

13.4 (11.4)

Pain Catastrophizing Scale (potential range of scores⫽0–52)

16.3 (11.3)

Physical Impairment Scale (potential range of scores⫽0⫺7)

3.2 (1.9)

All values reported as mean (SD) or number (percentage). LBP⫽low back pain.

follow-up. For the validity cohort, baseline age, sex, disability, pain intensity, fear-avoidance beliefs, pain catastrophizing, and physical impairment scores were compared between those who completed and those who did not complete the 4-week assessments. None of the variables showed statistically significant (P⬎.05) differences for these comparisons. Reliability At baseline, Cronbach alpha was .91 (95% CI⫽87–.95) for the FDAQ, suggesting high levels of internal consistency among FDAQ items. The 48hour test-retest reliability coefficient for the FDAQ was .90 (95% CI⫽.82– .94). Based on baseline data and these reliability data, the SEM was 6.6, resulting in an MDC of 12.9. Construct Validity The baseline factor analysis identified a 2-factor solution, with eigenvalues of 6.3 (62.8% variance) and 1.1 (10.8% variance), respectively. Factor loadings ranged from .59 to September 2009

.92, with all 10 items loaded onto these 2 factors (Tab. 2). The factors created represented a loaded spine/ upright posture factor and a spinal motion/seated posture factor. The 4-week factor analysis identified a 3-factor solution, with eigenvalues of 4.3 (49.3% variance), 1.4 (13.5% variance), and 1.1 (10.2% variance), respectively. Factor loadings ranged from .51 to .87, with all factors loaded onto these 3 factors (Tab. 2). The factors created were similar to those of the baseline solution by including loaded spine and spinal motion factors. At 4 weeks, a postural factor also was observed, as the seated and upright posture items were no longer split on the factor solution. The item assessing fear of performing back exercises was cross-loaded on the postural and spinal motion factors. This item remained in the FDAQ for the remaining analyses because of its potential for clinical utility.

Concurrent Validity The correlation results for concurrent validity are summarized in Table 3. At baseline and 4 weeks, the FDAQ scores were moderately correlated with scores on the FABQ-PA, FABQ-W, PCS, NRS for pain intensity, and PIS (Pearson r⫽.24 –.52, P⬍.05). There were stronger correlations for the ODQ at baseline and 4 weeks (Pearson r ⫽ 0.70 and 0.49, P⬍ 0.01). The separate multiple regression models predicting ODQ scores accounted for 57% of the variance at baseline and for 51% of the variance at 4 weeks (Tab. 4). At baseline, the FDAQ was the strongest contributor to variance in ODQ scores (␤⫽.52, P⬍.01), and the FABQ-W also contributed to the model (␤⫽.20, P⫽.01). At 4 weeks, the FDAQ contributed to disability (␤⫽.24, P⫽.01), but in this case, pain intensity was the strongest contributor to the model (␤⫽.49, P⬍.01).

Volume 89

Number 9

Physical Therapy f

973

Self-Report Measure of Fearful Activities for Patients With LBP Table 2. Factor Loadings for Fear of Daily Activities Questionnairea Loaded Spine/ Upright Posture

Baseline Analysis

Seated Posture/ Spinal Motion

1. Sitting for longer than 1 hour

.59

2. Standing for longer than 30 minutes

.64

3. Walking for longer than 30 minutes

.70

4. Lifting less than 20 pounds

.82

5. Lifting 20 pounds or more

.91

6. Carrying less than 20 pounds

.78

7. Carrying 20 pounds or more

.92

8. Twisting

.66

9. Reaching to the floor

.78

10. Performing back exercises

.89

4-Week Analysis

Loaded Spine

Upright and Seated Postures

1. Sitting for longer than 1 hour

.75

2. Standing for longer than 30 minutes

.83

3. Walking for longer than 30 minutes

.59

4. Lifting less than 20 pounds

.82

5. Lifting 20 pounds or more

.84

6. Carrying less than 20 pounds

.87

7. Carrying 20 pounds or more

.79

8. Twisting

.81

9. Reaching to the floor

.77

10. Performing back exercises a

Spinal Motion

.51

.54

Only loading factors greater than .50 reported in table.

The separate multiple regression models predicting PIS scores accounted for 28% of the variance at baseline and for 21% of the variance at 4 weeks (Tab. 4). At baseline, the FDAQ contributed to variance in PIS scores (␤⫽.21, P⫽.05), as did pain intensity (␤⫽.39, P⬍.01) and the FABQ-W (␤⫽.20, P⫽.04). At 4 weeks, only pain intensity uniquely contributed to the variance in PIS scores (␤⫽.35, P⬍.01). Predictive Validity Baseline ODQ scores accounted for 11.4% of the variance in 4-week ODQ scores (F1,90⫽11.6, P⬍.01). Only the FABQ-W was added to this model, and it accounted for an additional 4.1% of variance in 4-week ODQ scores (F1,89⫽4.3, P⫽.04). 974

f

Physical Therapy

Volume 89

Table 3. Correlations (Pearson r) Between Fear of Daily Activities Questionnaire (FDAQ) Scores and Scores on Previously Validated Measures: Concurrent Validitya Correlation

Baseline

4 Weeks

FDAQ and FABQ-PA

.45*

.31*

FDAQ and FABQ-W

.34*

.24**

FDAQ and PCS

.52*

.35*

FDAQ and ODQ

.70*

.49*

FDAQ and NRS

.34*

.36*

FDAQ and PIS

.31*

.26**

a

FABQ-PA⫽Fear-Avoidance Beliefs Questionnaire physical activity scale, FABQ-W⫽Fear-Avoidance Beliefs Questionnaire work scale, PCS⫽Pain Catastrophizing Scale, ODQ⫽Oswestry Disability Questionnaire, NRS⫽numerical rating scale for pain intensity, PIS⫽Physical Impairment Scale. * P⬍.01, ** P⬍.05.

Baseline PIS scores accounted for 20.5% of the variance in 4-week PIS scores (F1,78⫽20.2, P⬍.01). No other variables were entered into the model for the PIS. In the predictive

Number 9

analyses that incorporated change scores, change in NRS scores accounted for 27.8% of the variance in ODQ change scores (F1,90⫽34.7, P⬍.01). Change in FDAQ scores was September 2009

Self-Report Measure of Fearful Activities for Patients With LBP Table 4. Hierarchical Regression Analysis for Fear of Daily Activities Questionnaire (FDAQ) and Disability and Physical Impairment: Concurrent Validitya Baseline Model for Disability (R2ⴝ.57, P

Physical Therapy- Journal of the APTA- September 2009, Volume 89, Issue 9

Physical Therapy- Journal of the APTA- June 2009, Volume 89, Issue 6

Physical Therapy- Journal of the APTA- July 2009, Volume 89, Issue 7

Physical Therapy- Journal of the APTA- August 2009, Volume 89, Issue 8

Physical Therapy- Journal of the APTA- Feburary 2009, Volume 89, Issue 2

Physical Therapy- Journal of the APTA- March 2009, Volume 89, Issue 3

Physical Therapy- Journal of the APTA- January 2009, Volume 89, Issue 1

Physical Therapy- Journal of the APTA- October 2009, Volume 89, Issue 10

Physical Therapy- Journal of the APTA- November 2009, Volume 89, Issue 11

Physical Therapy- Journal of the APTA- May 2009, Volume 89, Issue 5

Physical Therapy- Journal of the APTA- December 2009, Volume 89, Issue 12

Physical Therapy- Journal of the APTA- April 2009, Volume 89, Issue 4

Physical Therapy- Journal of the APTA, Volume 90, Issue 2 (February 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 3 (March 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 7 (July 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 1 (January 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 6 (June 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 4 (April 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 5 (May 2010)

sports medicine Volume 39 Issue 9 September 2009

MyJalah, Edisi 9 - September 2009

Journal of Chiropractic Humanities: Volume 16, Issue 1, (December 2009)

Journal of Neurologic Physical Therapy (March 2010, Volume 34, Issue 1)

sports medicine Volume 40 Issue 9 September 2010

sports medicine Volume 41 Issue 9 September 2011

Radical Philosophy Issue: 89

Spektrum der Wissenschaft September 2009 issue 09

Manual Therapy Journal - Volume 14, Supplement (October 2009)

Manual Therapy Journal - Volume 14, Issue 3, Pages 241-352 (June 2009)

Manual Therapy Journal - Volume 14, Issue 2, Pages 117-240 (April 2009)

Physical Therapy- Journal of the APTA- September 2009, Volume 89, Issue 9

Physical Therapy- Journal of the APTA- June 2009, Volume 89, Issue 6

Physical Therapy- Journal of the APTA- July 2009, Volume 89, Issue 7

Physical Therapy- Journal of the APTA- August 2009, Volume 89, Issue 8

Physical Therapy- Journal of the APTA- Feburary 2009, Volume 89, Issue 2

Physical Therapy- Journal of the APTA- March 2009, Volume 89, Issue 3

Physical Therapy- Journal of the APTA- January 2009, Volume 89, Issue 1

Physical Therapy- Journal of the APTA- October 2009, Volume 89, Issue 10

Physical Therapy- Journal of the APTA- November 2009, Volume 89, Issue 11

Physical Therapy- Journal of the APTA- May 2009, Volume 89, Issue 5

Physical Therapy- Journal of the APTA- December 2009, Volume 89, Issue 12

Physical Therapy- Journal of the APTA- April 2009, Volume 89, Issue 4

Physical Therapy- Journal of the APTA, Volume 90, Issue 2 (February 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 3 (March 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 7 (July 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 1 (January 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 6 (June 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 4 (April 2010)

Physical Therapy- Journal of the APTA, Volume 90, Issue 5 (May 2010)

sports medicine Volume 39 Issue 9 September 2009

MyJalah, Edisi 9 - September 2009

Journal of Chiropractic Humanities: Volume 16, Issue 1, (December 2009)

Journal of Neurologic Physical Therapy (March 2010, Volume 34, Issue 1)

sports medicine Volume 40 Issue 9 September 2010

sports medicine Volume 41 Issue 9 September 2011

Radical Philosophy Issue: 89

Spektrum der Wissenschaft September 2009 issue 09

Manual Therapy Journal - Volume 14, Supplement (October 2009)

Manual Therapy Journal - Volume 14, Issue 3, Pages 241-352 (June 2009)

Manual Therapy Journal - Volume 14, Issue 2, Pages 117-240 (April 2009)

Recommend Documents