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

June 2009

Volume 89

Number 6

Research Reports 526

Effects of Forced Use on Arm Function After Stroke

580

Clinimetric Properties of the Lower Extremity Functional Scale

546

Validity and Reliability of the Continuing Care Activity Measure

589

Computerized Adaptive Testing of Activity in Children With Cerebral Palsy

556

Updating Clinical Practice for Patients With Stroke

Case Report

569

Reliability and Validity of Outcome Measures for Alzheimer Disease

601

Training of Walking Skills in Incomplete Spinal Cord Injury

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PTJ1208

at PT 2009 Reserve These Dates and Times for PTJ Sessions at PT 2009 PTJ Symposium: Nonpharmacologic CARE for Patients With Arthritis Thursday, June 11

2:00–5:00 pm

0.30 CEUs

This year, Physical Therapy (PTJ) will publish papers adapted from presentations at the CARE V Conference held in Oslo, Norway. In this session, a panel of authors and editors will help clinicians and researchers deal with issues ranging from ethics, to the multidisciplinary team approach, to patient perspectives. Upon completion of this course, you’ll be able to: (1) explain the primary care provider approach to arthritis management, (2) discuss recent data from European and Canadian patient advocates and the implications of the findings for US patient populations, and (3) identify challenges related to the use of the ICF in developing a core set of measurements in the rehabilitation management of rheumatoid arthritis. Speakers: G Kelley Fitzgerald, PT, PhD, OCS—Philadelphia, PA; Emalie Hurkmans, PT—The Netherlands; James J Irrgang, PT, PhD, ATC—Pittsburgh, PA; Anne Townsend, PhD—Vancouver, British Columbia

The 2009 Rothstein Debate: “When Does Regulation Become Over-Regulation, and When Does Under-Regulation Invite Abuse?” Friday, June 12

9:30–11:00 am

0.15 CEUs

Medicare regulation—some say “over-regulation”—and reimbursement cuts by all payers affect the business of physical therapy. But what are the effects on clinical practice and professionalism? Payment is different for hospitalbased versus outpatient-based practice; what might be the impact of continued payment under the Medicare Fee Schedule versus a bundled, episodic, or per-diem payment system in the outpatient setting? Under Medicare rules, and as an APTA position, the only extender of physical therapy services is the physical therapist assistant; what would be the benefits of utilizing other extenders based on patient type? The annual Rothstein Debate was established in memory of Jules Rothstein, PT, PhD, FAPTA, Editor in Chief Emeritus of PTJ. Upon completion of this course, you’ll be able to: (1) describe some of the ways in which current and potential Medicare rules and regulations might affect the health of the business enterprise across various settings, (2) explain the implications of a modification of the Medicare payment system and Medicare regulations on the practice of physical therapy, and (3) discuss the issues related to physical therapy extenders. Speakers: Anthony Delitto, PT, PhD, FAPTA—Pittsburgh, PA; Larry N Benz, PT, DPT, MBA, ECS, OCS—Louisville, KY; Stephen M Levine, PT, DPT, MSHA—Wilton Manors, FL

PTJ Breakfast—Essentials of Writing and Reviewing: Focus on Case Reports Saturday, June 13

8:00–11:00 am

0.30 CEUs

Are you an author looking to avoid common pitfalls, reduce review and revision time, and increase your chances for high-impact publication? Are you a reviewer who wants to enhance your skills? This is the session for you— regardless of which journals you write or review for! When you develop your skills as a reviewer, you also sharpen your skills as an author, and vice versa. This interactive session will discuss all manuscript types but also will include a special focus on case reports. The 3rd edition of Writing Case Reports: A How-to Manual for Clinicians will be released in June—get a sneak peek! Upon completion of this course, you’ll be able to: (1) list the top 5 essentials of high-quality research papers, (2) identify manuscript weaknesses that can bog down the review process and reduce chances of success, (3) review a manuscript using a systematic approach, and (4) describe the role of case reports and the critical elements that allow case reports to contribute to the physical therapy body of knowledge. Speakers: Rebecca L Craik, PT, PhD, FAPTA—Philadelphia, PA; Irene McEwen, PT, PhD, FAPTA—Oklahoma City, OK; G Kelley Fitzgerald, PT, PhD, OCS, FAPTA—Pittsburgh, PA; Patricia J Ohtake, PT, PhD—Buffalo, NY; Daniel Riddle, PT, PhD, FAPTA—Richmond, VA

NATIONAL PHYSICAL THERAPY MONTH 2009 A BRAND NEW EVENT! National Physical Therapy Month (NPTM) occurs each October. This year’s event will focus on APTA’s new brand for the physical therapy profession: Move Forward.TM Physical Therapy Brings Motion to Life. NPTM is your opportunity to show pride in your profession. It’s a chance to inform your communities that you are the expert they can depend on to improve motion and help achieve long- term quality of life. We’ve assembled the tools and resources you need to kick off your NPTM celebration. Look for them on the National Physical Therapy Month Web page at www.apta.org/nptm. From that page, follow the link to www.apta.org/brandbeat, the members-only resource for learning and living your new brand. Watch our Web site and publications for our brand new, exclusive Move Forward.TM collection of clothing and specialty items that will be introduced at PT ’09 in Baltimore and available for purchase in June. It’s your brand. Learn it, live it, wear it, share it—not only for National Physical Therapy Month 2009, but for all the months to come!

The Bottom Line On “Effects of Forced Use on Arm Function in the Subacute Phase After Stroke: A Randomized, Clinical Pilot Study” What problems did the researchers set out to study, and why? The researchers wanted to study the effectiveness of 2 weeks of forced use training on arm function. Learned non-use of the upper limb is a problem frequently encountered after stroke, and constraint-induced movement therapy (CIMT) has been suggested to improve the patient’s ability to use the involved extremity in daily tasks. CIMT includes both intensive training for several hours daily and the forced use of the involved arm by restraint of the unaffected upper limb. The contribution of constraint versus intensive training to the benefit of CIMT remains unclear. Thus, this study examined the effect of providing only the constraint component of the therapy, and not the intensive training component, in an effort to model real-world clinical application of this training modality. Who participated in this study? A convenience sample of 30 participants who had experienced stroke between 1 and 6 months prior to the study. Participants were required to be independent ambulators and have some movement in the paretic arm. They were excluded if there was complete sensory loss and/or the presence of severe perceptual impairments. What new information does this study offer? Although improvements were observed in both groups, changes in the forced-use group did not differ from the changes in the standard training group for any outcome measure. What new information does this study offer for patients? Training that includes forcing a patient to use the involved arm after stroke has been shown to be effective as part of an intensive training program in helping patients to use their involved arm. The results of this study suggest that adding only the forced-use component and not the intensive training component may not be of any additional benefit beyond standard training alone. Further research is needed to confirm this due to limitations of this trial. How did the researchers go about the study? Participants were randomized into 2 groups (15 each): over a period of 2 weeks, one group received standard rehabilitation, and the other group received forced use. Training was done 5 days per week as inpatient or outpatient therapy and included a variety of motor- and task-oriented exercises designed to promote use of the paretic upper limb. The forced-use group, in addition to the standard training, wore a sling that held the unaffected arm against the body. This sling was to be worn for up to 6 hours per day. Six outcome measures representing different constructs of the International Classification of Functioning, Disability and Health (ICF) were used to track changes from baseline at 2 weeks, 1 month, and 3 months. How might these results be applied to physical therapist practice? The results of this trial suggest that the addition of forced use to standard training after stroke may offer no additional benefit and should not be part of standard rehabilitation training. This information will be useful in the design of future trials investigating CIMT.

June 2009

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

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The Bottom Line What are the limitations of the study, and what further research is needed? This study had several limitations, including an extended study time due to the strict inclusion criteria for CIMT and the resulting difficulty in recruiting eligible individuals. In addition, the assessor was nonblinded, the sample size was small. Future research should consider the limitations of this trial as studies are conducted to best determine the optimal timing after stroke, as well as the interplay of training, restraint, and dosage as part of CIMT. Eric K Robertson E.K. Robertson, PT, DPT, OCS, is Assistant Professor, Department of Physical Therapy, Medical College of Georgia. This is the Bottom Line for: “Hammer AM, Lindmark B. Effects of Forced Use on Arm Function in the Subacute Phase After Stroke: A Randomized, Clinical Pilot Study. Phys Ther. 2009;89:529–541. 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 “Physical Therapists’ Experiences Updating the Clinical Management of Walking Rehabilitation After Stroke: A Qualitative Study” What problems did the researchers set out to study, and why? Using research literature as part of evidence-based physical therapist practice is not ubiquitous among physical therapists despite a high value placed on using evidence in practice. No published studies have examined how physical therapists attempt to use research literature to address clinical questions related to walking rehabilitation after stroke. The researchers in this study set out to examine physical therapists’ clinical questions related to walking rehabilitation after stroke, identify sources of information that physical therapists seek out to answer these questions, and identify factors that enable or challenge physical therapists’ ability to incorporate research evidence into clinical practice. Who participated in this study? Two researchers conducted telephone interviews with 23 physical therapists who were registered with the College of Physiotherapists of Ontario and who practiced at least 30 hours a week and provided care to a minimum of 10 adults with stroke per year. Participants were recruited from a sample that had previously participated in a mail survey on evidence-based practice in stroke management. What new information does this study offer? Physical therapists commonly raise questions about selection of interventions and about outcomes. For information, therapists relied most often on peers, followed by research literature. Barriers to the use of research literature included insufficient computer skills by older clinicians and difficulty with critical appraisal and application of research findings to practice. Insufficient time and peer isolation were identified as institutional barriers to the use of research evidence.

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The Bottom Line What new information does this study offer for patients? Patient outcomes for walking rehabilitation after stroke were found to be improved when intervention was delivered based on current research evidence and clinical guidelines. This study looked at how physical therapists get information to answer questions about walking rehabilitation for patients after stroke. Time constraints dictated many decisions, including utlizing peers most often as a source of information. Barriers to incorporating research literature into practice were noted, and this may help therapists to develop ways to improve the use of research in clinical practice and ultimately improve patient outcomes. How did the researchers go about the study? Two researchers conducted telephone interviews with study participants using a semistructured interview guide. Interviews were recorded, and a constant comparative method of inquiry using open coding methods was used for data analysis. How might these results be applied to physical therapist practice? The information from this study can be used to guide the development of information resources, research reporting, organization systems, and continuing education to support evidence-based physical therapist practice after stroke. What are the limitations of the study, and what further research is needed? The participants had already participated in a survey about evidence-based practice and were likely interested in the topic. The majority of the participants held a bachelor’s degree, were over the age of 50 years, and were from nonrural settings, which may limit the ability to generalize these findings to other groups. Future research should examine the best methods to reduce barriers to the application of research literature to evidence-based practice. Eric K Robertson E.K. Robertson, PT, DPT, OCS, is Assistant Professor, Department of Physical Therapy, Medical College of Georgia. This is the Bottom Line for: “Salbach NM, Veinot P, Rappolt S, Bayley M, Burnett D, Judd M, Jaglal SB. Physical Therapists’ Experiences Updating the Clinical Management of Walking Rehabilitation After Stroke: A Qualitative Study. Phys Ther. 2009;89:556–568. 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.

June 2009

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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: Randy Roesch, PT, MBA, DPT 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: William D. Bandy, PT, PhD, SCS, ATC; 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, MS, OCS; Stephen C.F. McDavitt, PT, DPT, MS, FAAOMPT; Paul A. Rockar Jr, PT, DPT, MS; Lisa K. Saladin, PT, PhD; John G. Wallace Jr, PT, MS, OCS

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 Andrea Behrman, PT, PhD, Melrose, FL; Rachelle Buchbinder, MBBS(Hons), MSc, PhD, FRACP, Malvern, Victoria, Australia; W. Todd Cade, PT, PhD, St Louis, MO; John Childs, PT, PhD, Schertz, TX; Charles Ciccone, PT, PhD, FAPTA (Continuing Education), Ithaca, NY; Joshua Cleland, PT, DPT, PhD, OCS, FAAOMPT (The Bottom Line), Concord, NH; Janice J. Eng, PT/OT, PhD, Vancouver, BC, Canada; G. Kelley Fitzgerald, PT, PhD, OCS, Pittsburgh, PA; James C. (Cole) Galloway, PT, PhD, Newark, DE; Kathleen Gill-Body, PT, DPT, NCS, Boston, MA; Paul J.M. Helders, PT, PhD, PCS, Utrecht, The Netherlands; Maura D. Iversen, PT, MPH, ScD, 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 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; Eric Robertson, PT, DPT, OCS; Kathleen Rockefeller, PT, MPH, ScD; Michael Ross, PT, DHS, OCS; Patty Scheets, PT, DPT, NCS; 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

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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.

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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.

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Research Report

Effects of Forced Use on Arm Function in the Subacute Phase After Stroke: A Randomized, Clinical Pilot Study Ann M. Hammer, Birgitta Lindmark A.M. Hammer, PT, MSc, is Doctoral Student, Department of Re¨ rebro Unihabilitation Medicine, O versity Hospital, and School of ¨ reHealth and Medical Sciences, O ¨ rebro, bro University, S-701 85 O Sweden. Address all correspondence to Ms Hammer at: ann. [email protected]. B. Lindmark, PhD, is Professor Emeritus, Section of Physiotherapy, Department of Neuroscience, Uppsala University, Uppsala, Sweden. [Hammer AM, Lindmark B. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Phys Ther. 2009;89:526 –539.] © 2009 American Physical Therapy Association

Background and Objective. Following stroke, it is common to exhibit motor impairments and decreased use of the upper limb. The objective of the present study was to evaluate forced use on arm function during the subacute phase after stroke. Design. A comparison of standard rehabilitation only and standard rehabilitation together with a restraining sling was made through a randomized, nonblinded, clinical pilot trial with assessments before intervention, after intervention, and at 1and 3-month follow-ups. Setting. The present study took place at the departments of rehabilitation medicine, geriatrics, and neurology at a university hospital. Participants. A convenience sample of 30 people 1 to 6 months (mean, 2.4 mo) after stroke was randomized into 2 groups (forced-use group and standard training group) of 15 people each. Twenty-six participants completed the 3-month follow-up.

Intervention. All participants received their standard rehabilitation program with training 5 days per week for 2 weeks as inpatients or outpatients. The forced-use group also wore a restraining sling on the nonparetic arm with a target of 6 hours per day.

Measurements. The Fugl-Meyer (FM) test, the Action Research Arm Test, the Motor Assessment Scale (MAS) (sum of scores for the upper limb), a 16-hole peg test (16HPT), a grip strength ratio (paretic hand to nonparetic hand), and the Modified Ashworth Scale were used to obtain measurements.

Results. The changes in the forced-use group did not differ from the changes in the standard training group for any of the outcome measures. Both groups improved over time, with statistically significant changes in the FM test (mean score changed from 52 to 57), MAS (mean score changed from 10.1 to 12.4), 16HPT (mean time changed from ⬎92 seconds to 60 seconds), and grip strength ratio (mean changed from 0.40 to 0.55). Limitations. The limitations of this pilot study include an extended study time, a nonblinded assessor, a lack of control of treatment content, and a small sample size. Conclusions. The results of the present pilot study did not support forced use as

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a reinforcement of standard rehabilitation in the subacute phase after stroke. Forced use did not generate greater improvements with regard to motor impairment and capacity than standard rehabilitation alone. The findings of this effectiveness study will be used to help design future clinical trials with the aim of revealing a definitive conclusion regarding the clinical implementation of forced use for upper-limb rehabilitation.

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Effects of Forced Use on Arm Function After Stroke

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troke is the leading cause of disability in many countries.1 Because motor deficits and decreased use of the upper limb are frequent problems after stroke, it is important to develop cost-effective rehabilitation approaches designed to address these problems.

Many patients with arm paresis after stroke initially activate mostly their nonparetic side to be as independent as possible.2,3 There is usually some restoration of motor capacity in the paretic upper limb, but the patient often fails to complete daily tasks with that limb.2,3 This behavioral development of not using the recovering upper limb is known as “learned nonuse.”3 Both the theory of learned nonuse and the notion of bringing the paretic side into more use by restraining the nonparetic side with a sling were introduced in primate research. Restraint alone induced the use of the forelimb in these experiments when restriction was used for a week or more.2 On the basis of these primate experiments, pioneer studies in patients with stroke involved the application of a restraining sling, termed “forced use,” without any training.4,5 Both studies indicated a positive effect in

Available With This Article at www.ptjournal.org • Invited Commentary from James H. Cauraugh and Jeffery J. Summers, Invited Commentary from Jeanne Charles, and the Author Responses • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on April 16, 2009, at www.ptjournal.org.

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the chronic stage after stroke for upper-limb motor function. In an initial randomized controlled trial (RCT), forced use was combined with training for 2 weeks in 4 patients at least 1 year after stroke. Promising results for motor function and the use of the upper limb were seen immediately after the intervention and at a 2-year follow-up relative to the results seen for 5 patients in a control group.3 The short-term effect was explained by the neurophysiologic effects of unmasking, that is, bringing latent neural pathways into use.3 The concept of overcoming learned nonuse was further developed and described6 as a combination of immobilization of the unaffected arm and intensive training of the affected arm. The classic design of constraintinduced movement therapy (CIMT) involves massed practice (intense, concentrated, repetitive exercises with increasing speed or difficulty following improvements of performance) 6 hours per day for 2 weeks and the use of a restraining device for 90% of waking time.6 Further promising results were seen in the chronic stage after stroke, mostly in studies in which training was conducted in research laboratories.7 From a clinical perspective, training patients individually for 6 hours per day is rarely feasible. Several attempts at modifying CIMT have been made since concerns were raised regarding patient and therapist devotion to CIMT8 and available resources in clinical settings.9 There also is an ongoing discussion regarding the actual effect of CIMT and the importance of the various components.2,10 –14 The restraining aspect initially was presented as the essential factor,3,15 but intense training frequently has been referred to as the crucial treatment factor.2,7 The most recent descriptions of the concept of CIMT emphasize not only the com-

ponents of immobilization and intense training but also a behavioral approach to facilitating the transfer of motor behavior during exercise to daily use in the home environment.16 –18 This shift of emphasis in CIMT places the focus on learning strategies to accomplish transfer to daily use by means of an agreement regarding behavior and strategies. Identification of the critical elements of the CIMT paradigm has been and continues to be elusive. Because learned nonuse was proposed to develop in the acute and subacute phases after stroke, questions were posed about whether overcoming or even preventing its occurrence would be more efficient in early rehabilitation because of greater brain plasticity.4,5,19 The present RCT was based on knowledge from initial studies in this area.3–5 We transferred the idea of overcoming learned nonuse by applying forced use in our context of clinical rehabilitation. The present study was intended to test whether providing only the constraint component of CIMT could reinforce standard rehabilitation during the subacute stage. Thus, at the start of our study, there were no reports on forced use or CIMT during the subacute stage after stroke. Testing of health care interventions is frequently classified as efficacy, effectiveness, and efficiency studies.20 Seemingly similar in meaning, these terms express distinctly different concepts. Efficacy represents evaluation of an effect during ideal circumstances; effectiveness represents whether an intervention works in usual circumstances, such as routine clinical care; and efficiency represents effect in relation to cost. The present study tested effectiveness because the environment was standard rehabilitation in clinical health care.

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Effects of Forced Use on Arm Function After Stroke The purpose of this study was to evaluate the effectiveness of 2 weeks of forced use on arm function after stroke. The specific aim was to investigate any differences in changes in motor impairment and capacity between a group of patients wearing a restraining sling in addition to receiving rehabilitation training and a group of patients receiving rehabilitation training only.

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Method Design This study was a prospective, randomized, nonblinded clinical pilot trial. Participants and Recruitment Participants were recruited by convenience sampling from the departments of rehabilitation medicine, geriatrics, and neurology at a university hospital in central Sweden. The physical therapist, occupational therapist, or physician caring for the patients recommended potential participants to the researcher (AMH), who then presented the project to each patient. If the patient was interested, the researcher assessed the potential participant for eligibility according to the inclusion criteria (see below). If these criteria were met, the patient was invited to participate. Upon voluntary consent, the patient was included in the study. The inclusion criteria were based mainly on previous research on forced use6 and were as follows: • 1 to 6 months after stroke • Daily training for 5 days per week at the hospital (ongoing or possible to arrange) • Ability to perform independent transfers to and from chair, bed, and toilet • Ability to move the shoulder and elbow voluntarily and extend 20 degrees in the wrist and 10 degrees in the fingers of the paretic arm and hand3,5,6,15 (but participants should

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not have achieved prestroke use of the arm and hand) Score of ⱕ2 of 5 on the Modified Ashworth Scale for muscle spasticity (hypertonicity)21 No complete sensory loss in the arm or hand Freedom from severe perceptual impairments, such as neglect, which was assessed by drawing a clock and a human figure22–24 Score of ⱖ20 of 30 on the MiniMental State Examination25 Ability to understand and follow instructions

A sample size of 30 participants was chosen as possible and convenient to achieve. No power analysis was performed. Participants provided voluntary, written informed consent. Randomization After participant inclusion, a restricted block randomization was used. Thirty pieces of paper had been prepared with the letter E (experimental group, later called forced-use group [FU group]) on 15 of them and the letter K (conventional group, later called standard training group [ST group]) on the other 15. A block size of 10 was used (5 “E” plus 5 “K”). The pieces of paper were folded twice, and the first block of 10 was placed in a metal box, while the rest were stored in 2 sealed envelopes with 1 block in each. For each participant in the study, the metal box was shaken, and an arbitrarily chosen staff member drew a piece of paper to determine the group allocation. No stratification was used. The researcher (A.M.H.) retained the list of consecutive participants included in the study. After randomization, participants were scheduled for preintervention testing as soon as possible. Intervention The difference between the intervention conditions was the presence or absence of forced use. During the

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intervention period of 2 weeks, all participants in the study received their usual interdisciplinary rehabilitation program. Training was done 5 days per week on an inpatient or outpatient basis. In addition, participants in the FU group wore a sling* holding the nonparetic arm against the body with a target of 6 hours on each training day. Physical therapy and occupational therapy were individualized with a task-oriented approach. For the paretic upper limb, basic motor exercises and task-oriented activities were performed. Exercises included facilitation of proximal and distal motor control and improvement of strength (force-generating capacity) and endurance by use of apparatus or hands-on techniques; skilled task training, such as moving objects (gripping and releasing), putting pegs in a board, putting puzzles together, and writing or typing; and daily tasks. Exercises for range of motion and stretching of the paretic limb, particularly the shoulder, also were used when appropriate. Lower-limb training included weightbearing activities, balance and gait training on even or uneven surfaces, and exercises for improving strength and endurance. Generally, all participants were encouraged to be active and to try to use their affected side. Assistant therapy staff members were involved with both one-on-one treatment and supervision of self-training. The researcher (A.M.H.) was not responsible for the training of any of the participants in the present study. The therapy staff members kept a study log for each participant during the intervention. The daily amount of therapy time, which included all scheduled sessions in the therapy ar* CAMP Scandinavia AB, Karbingatan 38, S-254 67 Helsingborg, Sweden.

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Effects of Forced Use on Arm Function After Stroke eas, was recorded. Practice sessions were 30 or 45 minutes, and each participant had several practice sessions daily. The sum of therapy time for each participant was used for analysis. For participants in the FU group, adherence to wearing the sling also was recorded (in minutes). In addition, activities interrupting sling wear were recorded to assess the feasibility of the restraint. Outcome Measures For outcome evaluation, 6 measures representing different constructs in the International Classification of Functioning, Disability and Health (ICF)26 were used. These tests were chosen because they are commonly used clinically and in research and have been described in the literature as being valid and reliable after stroke. The upper-extremity section of the Fugl-Meyer (FM) test27 grades motor function on the ICF level of body functions (muscle and movement functions). A 3-point ordinal scale is used to score 33 items, with a maximum score of 66. Good reliability and validity have been reported.27–29 The Modified Ashworth Scale21 grades spasticity on the ICF level of body functions (muscle tone functions). The elbow flexor and extensor muscles and the wrist and finger flexor muscles were evaluated in the sitting position. The sum of the 3 muscle scores (0 –15) was used for analysis. Good reliability has been reported for the elbow flexor muscles.21 The Action Research Arm Test (ARAT)30 grades the capacity of arm and hand function on the ICF level of mobility in activities and participation. All 19 items are combined movements; 16 of them require handling an object. The items are scored on a 4-point ordinal scale, with a maximum score of 57. Good reliability and validity have been reported.29 –31

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The Motor Assessment Scale (MAS)32 rates motor capacity on the ICF level of mobility in activities and participation. Upper-arm function, hand movements, and advanced hand activities were used in the present study. The sum of the scores for the upper-limb items (0 –18) was used for analysis.33 Good reliability and validity have been reported.32,34 A 16-hole peg test (16HPT)35 was used to measure dexterity on the ICF level of body functions (movement functions). The time needed to place 16 pegs (2.1⫻5.9 cm) in a pegboard with 16 holes was determined with a stopwatch. The best value from 3 trials was used for effect analysis of the paretic hand. Isometric grip strength on the ICF level of body functions (muscle power functions) was measured with the electronic instrument Grippit.†,36 Each hand was tested in three 10-second trials. The ratio of the strength (the best peak values) of the paretic hand to that of the nonparetic hand was used for analysis. This ratio was chosen because the strength of the nonparetic hand varied considerably among participants. Good reliability has been reported.37 These assessments were conducted on 4 occasions: just before the intervention (preintervention), immediately after the 2-week intervention (postintervention), at a 1-month follow-up, and at a 3-month follow-up (counting from the end of the 2week intervention). The researcher (AMH), who was a physical therapist experienced in neurology and the outcome measures, performed all of the tests. The assessments were done in a separate room at the physical therapy department and were performed according to the test manuals. A new score sheet was † AB Detektor, Box 17124, S-402 61 Gothenburg, Sweden.

used on every occasion to minimize bias from awareness of data from previous assessments. The tests were performed in the order shown above, and the order was fixed for all participants and test occasions. This format was chosen so that participants would have about the same degree of weariness from the measures over the study period. Three follow-up assessments were done in the homes of participants who were not able to come to the hospital for testing. Between postintervention testing and follow-up testing, no control was applied to the rehabilitation services, and participants continued their overall rehabilitation plan as needed. This schedule often included lessfrequent therapy. At the follow-up visits, participants self-reported their therapy since intervention. Data Analysis Descriptive statistics were used to summarize baseline data. Category variables (sex, paretic side, and department) were compared between groups by use of the Fisher exact test. Between-group comparisons of baseline characteristics (age, months after stroke, and Mini-Mental State Examination score) and outcome measures before the intervention were made using both the t test for independent groups and the MannWhitney U test. Therapy times for the 2 groups were compared in the same way. Analyses of effects were performed on the basis of both intention to treat (ITT) and the data actually collected. For the ITT analysis, any missing value was imputed from the last value, a conservative assumption. For the effect analyses, both parametric and nonparametric methods were used for each of the outcome measures. This solution was chosen for 2 reasons. First, with the current

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Effects of Forced Use on Arm Function After Stroke sample size, there is no feasible nonparametric method that can handle a 2-group design where measures are repeated more than twice, a situation that forces the use of analysis of variance (ANOVA). On the other hand, not all assumptions required for ANOVAs were met, because not all of the data fulfilled tests for normality and rating scales are seen as ordinal. The change score for each of the measures was calculated for the intervals from preintervention to postintervention, 1-month followup, and 3-month follow-up. Nonparametrically, the change scores were compared between groups by use of the Mann-Whitney U test. Parametrically, a repeated-measures 2-way ANOVA (within factor, time; between factor, group) was performed on the change scores. The significance level was set at P⬍.05, but, to reduce the probability of type I errors from multiple comparisons, a Bonferroni correction was applied in case of significance. Effect sizes (Cohen d) were calculated to further elucidate the sizes of the between-group differences. The calculations were performed on change scores as the mean result for the FU group minus the mean result for the ST group divided by the standard deviation for the ST group.38 An effect size of .2 to .5 was considered small, an effect size .5 to .8 was considered medium, and an effect size above .8 was considered large. Data were registered in Statistica 5.0‡ and analyzed with SPSS 14.0.§ Role of the Funding Source The Folksam Research Foundation, ¨ rebro the Research Funds of O ¨ rebro University, County Council, O and the Swedish Stroke Association supported this study. The supporting sources had no involvement in ‡

StatSoft Scandinavia AB, Sportfa¨ltsva¨gen 3, S-754 19 Uppsala, Sweden. SPSS AB, Box 1262, S-164 29 Kista, Sweden.

§

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the design, conduct, or reporting of the study.

2 and in more detail below. Effect sizes were mainly small (Tab. 4).

Results

The FM test mean score improved by approximately 5 points up to the 3-month follow-up in both groups (Fig. 2a). Improvements were steady and occurred continuously, with very few declines in score. The time⫻group interaction effect was not significant, regardless of the analytical method (ANOVA P⫽.74 for analysis based on actual data collected [n⫽26] and P⫽.53 for analysis based on ITT; Mann-Whitney P⫽.07– .80 [n⫽26] and P⫽.17–.85 [ITT]). (The format shown here for ANOVA and Mann-Whitney U test results is used throughout the “Results” section.)

Potential participants were recruited from November 1998 to October 2006 (Fig. 1). Thirty participants were enrolled in the study and underwent random assignment to 2 groups. There were a total of 4 dropouts during the study. Two participants in the FU group discontinued the 2-week intervention period; one dropped out on the first day of intervention because of refusal to continue, and the other was discharged on day 5 of the intervention. The other 2 participants dropped out before follow-up because of illness (FU group) and because of refusal to continue (ST group). The groups did not significantly differ in any of the baseline characteristics (Tab. 1). The groups also were comparable in outcome measures before the intervention (Tab. 2). The intervention sessions were conducted as inpatient rehabilitation (n⫽ 6), outpatient rehabilitation in day care units (n⫽22), or both (n⫽2) (Tab. 3). Total therapy times were similar for the groups (X⫽ 30.7 and 27.0 hours), that is, approximately 3 hours daily (Tab. 3). Participants in the FU group wore the restricting sling for 21.2 to 58.0 hours (X⫽37.4 hours) (Tab. 3). Activities interrupting sling wear were 2-hand daily tasks or training tasks (Tab. 3). The details of the rehabilitation during follow-up were similar in the 2 groups. There were no differences in changes between the groups at any time for any of the outcome measures, regardless of the analytical method (ANOVA P⫽.092–.911; MannWhitney U test P⫽.070 –.982). Data collected for the outcome measures before and after the intervention and at follow-up are presented in Figure

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The Modified Ashworth Scale sum score was low and steady throughout the study (Fig. 2b). Changes were mainly the same in both groups (ANOVA P⫽.43 [n⫽26] and P⫽.40 [ITT]; Mann-Whitney U test P⫽.27– .98 [n⫽26] and P⫽.29 –.98 [ITT]). The ARAT mean score for motor capacity improved in both groups (Fig. 2c), although the score was more scattered than that on the FM test. The interaction effect (time⫻ group) did not reach significance, regardless of the analytical method (ANOVA P⫽.09 [n⫽26] and P⫽.12 [ITT]; Mann-Whitney U test P⫽.16 – .68 [n⫽26] and P⫽.22–.68 [ITT]). The other scale of motor capacity, the MAS sum score for the upper limb, improved slightly and steadily up to the 3-month follow-up (Fig. 2d) in both groups (ANOVA P⫽.10 [n⫽26] and P⫽.16 [ITT]; MannWhitney U test P⫽.19 –.94 [n⫽26] and P⫽.15–.83 [ITT]). Time on the 16HPT improved up to the 3-month follow-up in both groups (Fig. 2e). The time⫻group interaction effect was not significant, regardless of analytical method June 2009

Effects of Forced Use on Arm Function After Stroke

Figure 1. Flow chart for study participants. PT⫽physical therapist, OT⫽occupational therapist.

(ANOVA P⫽.33 [n⫽26] and P⫽.23 [ITT]; Mann-Whitney U test P⫽.17– .88 [n⫽26] and P⫽.44 –.76 [ITT]). All participants initially needed more time for placing the pegs with the paretic hand than with the nonparetic hand (Tab. 2). All participants managed to perform the test, June 2009

but there was wide variability in the groups. The Grippit ratios (paretic/nonparetic hand) improved up to the 3-month follow-up in both groups (Fig. 2f). However, the differences in changes between the groups were

not significant (ANOVA P⫽.86 [n⫽26] and P⫽.91 [ITT]; MannWhitney U test P⫽.19 –.33 [n⫽26] and P⫽.27–.49 [ITT]). The initial ratios exposed impaired function for all participants but one; 29 people had ratios of less than 1.0, and only 9 had ratios of greater than 0.50. Only

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Effects of Forced Use on Arm Function After Stroke Table 1. Baseline Characteristics of the Participants Forced-Use Group (nⴝ15)

Variable

Standard Training Group (nⴝ15)

Pa

.14

Age (y) X (SD)

66.3 (10.3)

60.4 (11.1)

Range

51–83

31–80

Sex: men/women (n)

14/1

9/6

.08

Paretic side (n) Right/left

11/4

8/7

.45

Dominant side/nondominant side

12/3

7/8

.13

Mini-Mental State Examination score, X (SD)

28.6 (1.3)

27.7 (2.5)

.25

Time, mo, between stroke and intervention, X (SD)

2.6 (1.5)

2.3 (1.2)

.64

Rehabilitation medicine departments/ geriatric departments (n)

7/8

11/4

.26

a

As determined with the Fisher exact test for proportions and with the t test for independent groups for continuous variables.

3 additional participants achieved a ratio of greater than 0.50 by the end of the study. A simple correlation analysis revealed no significant correlations between sling time or therapy time and changes in outcome. Correlations were low and not significant; Spearman correlation coefficients were ⫺.36 to .43 for sling time and ⫺.32 to .44 for therapy time. These findings are congruent with the results presented above. We found that all participants improved over time (pooled data) on 4 of the 6 measures, as shown by statistically significant changes. The score on the FM test improved from 52 to 57 (ANOVA P⫽.000), the score on the MAS improved from 10.1 to 12.4 (ANOVA P⫽.009 –.014), the mean time on the 16HPT improved from greater than 92 seconds to 60 seconds (ANOVA P⫽.008 –.011), and the Grippit ratio improved from 0.40 to 0.55 (ANOVA P⫽.000).

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Discussion This pilot study demonstrated no additional benefit of the use of a restraining sling during upper-limb rehabilitation. In the context of CIMT,7 we applied forced use in a standard clinical environment. This real-world application was explored in an effort to identify a resource-efficient method for improving rehabilitation outcomes in the subacute phase after stroke. However, improvements were similar in both groups in our study. Since the inception of our study, a few other studies have reported on forced-use therapy and CIMT in the subacute phase after stroke. Our results are in concordance with those of Brogårdh et al39; in that study, participants in both groups also achieved similar improvements after arm and hand training for 3 hour per weekday, with the experimental group also wearing a mitt for 90% of waking time for 2 weeks. The authors concluded that the mitt could be omitted even though the restraint

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was much more extensive than that in our study. Ploughman and Corbett40 also compared conventional therapy alone with forced-use therapy combined with conventional therapy in the subacute phase. They reported ⱕ20% greater recovery with the forced-use therapy, although no arm measure met a statistically significant group difference. A comparison with these results is difficult because the duration of the intervention in that study was not controlled; patients received intervention until they were discharged from rehabilitation, at a mean of 2 months. Other research groups also have failed to demonstrate differences in results between CIMT and an equal amount of an alternate intervention, both in the chronic phase41 and in the acute phase.42,43 However, the most impressive RCT in the area of CIMT and stroke in the subacute stage was recently reported.44 This EXCITE study included 222 patients and was conducted with meticulous methodology.18 A classic time period of 2 intervention weeks was evaluated with the use of a mitt 90% of waking time, together with intense exercises and task training of the hand and arm in a clinical research laboratory for 6 hours per day. This regimen was found to be beneficial; however, it is important to note that the control group received no or much less training and attention. A comparison of the present study with the EXCITE study must be made with caution, because the amount of time wearing the sling and the intensity, amount, and type of training differed extensively. Moreover, the EXCITE study was an example of an efficacy study, whereas the present study concerned effectiveness. Our rehabilitation program achieved a mean recorded training time of 3 hours per day for both the FU group and the ST group. Interestingly, the average amount of active time in therapy in the EXCITE study June 2009

Effects of Forced Use on Arm Function After Stroke was 40 to 44 hours, instead of the 60 hours that was described in their protocol, because participants rarely were able to sustain the preplanned amount of training.45 In agreement with our results, no explicit doseresponse correlation was revealed.45 Training not only involved upperextremity function but also was individually planned, depending on the total rehabilitation needs of each patient. Our participants also wore the restraint less than 90% of waking time. Other study features were similar, including participant age, time after stroke, and the intervention period of 2 weeks. In an effort to create a fair comparison condition,46 we aimed for similar intensities of training in the experimental and control groups. The amount of training time in our study may be more representative of clinical practice in rehabilitation settings. Effectiveness of Sling Use An obvious explanation for the lack of benefit is the treatment dose and content, both the actual interventions performed, and the lack of control of training factors between groups. The first possibility is that the sling was not worn long enough. The mean sling use adherence was ⬃62% of the targeted 6 hours per day. This value is much lower than the 90% of waking time used in classic CIMT. In the present “real-world” application of forced use, there were several reasons for not choosing 90% of waking time as well as difficulties in implementing the targeted 6 daily hours. To begin with, we made the ethical decision to allow participants to not be “forced” to use the sling at home because of safety considerations. Secondly, all but one of the participants in the FU group who completed the intervention were outpatients, and a day at the outpatient unit was rarely as long as 6 hours. Clinical resources could not be extended that far for most study participants. This is the main explaJune 2009

Table 2. Outcome Measures at the Preintervention Test Occasion Measurea

Forced-Use Group (nⴝ15)

Standard Training Group (nⴝ15)

Pb

.89

Fugl-Meyer test (0–66) X (SD)

51.7 (6.2)

52.0 (7.2)

Median (IQR)

52 (47–58)

51 (48–58)

X (SD)

1.1 (1.0)

1.5 (1.7)

Median (IQR)

1 (0–2)

1 (0–3)

Modified Ashworth Scale (0–15), sum score, upper limb .52

Action Research Arm Test (0–57) X (SD)

43.7 (12.2)

47.3 (9.2)

Median (IQR)

40 (32–57)

49 (40–56)

X (SD)

10.1 (2.9)

10.1 (3.4)

Median (IQR)

11 (9–13)

11 (7–13)

.36

Motor Assessment Scale (0–18), sum score, upper limb .95

16-hole peg test (s), paretic hand X (SD) Median (IQR)

101.6 (74.5)

92.6 (68.6)

70.8 (46.0–190.0)

60.2 (37.6–138.9)

X (SD)

27.7 (5.5)

26.2 (8.1)

Median (IQR)

27.9 (23.1–30.2)

25.2 (22.2–26.4)

.73

16-hole peg test (s), nonparetic hand .56

Grippit maximum value (N), paretic hand X (SD)

130.1 (102.1)

Median (IQR)

124 (64–172)

100.3 (70.0)

.36

88 (52–128)

Grippit maximum value (N), nonparetic hand X (SD)

298.4 (113.4)

291.5 (106.6)

Median (IQR)

268 (216–420)

264 (200–420)

.86

Grippit ratio, maximum value, paretic hand/nonparetic hand

a b

X (SD)

0.44 (0.29)

0.36 (0.22)

Median (IQR)

0.38 (0.17–0.67)

0.29 (0.17–0.57)

.41

IQR⫽interquartile range. As determined with the t test for independent groups.

nation for why the targeted 6 hours per day was not reached. Another explanation was the interruption of sling wear by 2-hand activities. Reports have suggested that patients in an early phase of recovery after stroke might not be able to tolerate the strain of an all-day constraint.8,40,47 This was another consideration that made us decide not to extend hours at the outpatient units

for participants. Ploughman and Corbett40 reported problems with constraint adherence, with a mean of 2.7 hours per day instead of the targeted 6 hours. Three of our 4 participants who dropped out were in the FU group, a fact that might imply strain from sling wear. All 4 participants who dropped out were from the department of geriatrics, that is, among the older study participants. This

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Effects of Forced Use on Arm Function After Stroke Table 3. Details of the 2-Week Intervention Parametera

Forced-Use Group (nⴝ13)

Standard Training Group (nⴝ15)

Pb

30.7 (7.9)

27.0 (9.4)

.28

28.5 (27.5–32.7)

29.2 (24.1–30.0)

17.5–51.0

9.2–45.0

Total therapy time (h) X (SD) Median (IQR) Range Time wearing sling (h) X (SD)

37.4 (11.5)

Median (IQR)

NA

40.2 (26.7–44.2)

Range

21.2–58.0

Clinical setting during intervention (n) Inpatient rehabilitation Outpatient rehabilitation

2 (1 discontinued intervention)

4

13 (1 discontinued intervention)

9

Both inpatient and outpatient Activities interrupting sling wear

2 Motor or task exercises involving both hands (n⫽5) Bathroom visit (n⫽4)

missed in the constructs of motor impairment and capacity. However, there were several problems with the measures chosen. The ARAT showed a ceiling effect, and the MAS did so to some degree as well, because scores for advanced hand activities for most participants stopped at 2. Spasticity might be viewed more as an index of adverse events and not as an expected outcome of improvement, because the inclusion criteria claimed a low level of spasticity and the study participants showed no tendency for increased spasticity during the study period. However, there was room for improvement for all participants in the Grippit ratio and in timed dexterity as measured by the 16HPT. The selection of measures is a very challenging and interesting issue in both research and clinical routine.

Pool exercising (n⫽3) Walking with aid between therapy areas (n⫽2) Cycling with a manuped (n⫽2) Kitchen training (n⫽1) Balance test (n⫽1) Walking in parallel bars (n⫽1) a b

IQR⫽interquartile range. As determined with the t test for independent groups. NA⫽not applicable.

fact might indicate that some older participants with stroke had a diminished amount of energy for accomplishing this demanding intervention. Also, the testing procedure was extensive for participants. Some follow-up assessments were done in the homes of 2 participants to ensure completeness of the data. The critical level of restraint use remains unknown, and if there had been even an emerging effect of forced use, then it should have been evident in the data at some point, even if the differences were not statistically significant. However, no between-group differences were revealed for change scores, as indicated by the failure of the between534

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group difference on the ARAT to reach 5.7 points, which has been proposed as the threshold for clinically important change.41 Assessment Across Levels of the ICF Several measures of motor function representing different constructs in the ICF26 were used. This report covers outcomes on the level of body functions (grip strength, spasticity, FM test, and 16HPT) and the construct of capacity for activities and participation (MAS and ARAT). Measuring capacity means evaluating the execution of tasks in a standard environment. Because all of these measures were used, it is highly unlikely that an effect would have been

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The general trend was that participants improved over time, a result that was expected, but forced use made no difference in motor improvements. Our results may not be generally applicable to other patients with stroke. Although the improvements were similar in the 2 groups, there might have been a difference in the daily use of the hand and arm that was not addressed in this study. A discrepancy between the results of motor function tests and the results of measures of arm use in daily activities was previously reported for patients in the chronic stage after stroke participating in CIMT.16,48 Measures of daily use address an outcome on the ICF level of performance of activities and participation and will be presented elsewhere. Study Limitations As is the case with all pilot studies, the present study had certain limitations. These included the extended study time, the lack of control of treatment dose and content, the small sample size, and the lack of June 2009

Effects of Forced Use on Arm Function After Stroke Table 4. Effect Sizesa Effect Size Postintervention Measure

a

nⴝ26

ITT

1-mo Follow-up nⴝ26

ITT

3-mo Follow-up nⴝ26

ITT

Fugl-Meyer test

.68

.50

.21

.21

.12

.11

Modified Ashworth Scale, sum score, upper limb

.20

.13

.49

.44

.01

.00

Action Research Arm Test

⫺.04

⫺.13

.12

.25

.50

.56

Motor Assessment Scale, sum score, upper limb

⫺.10

⫺.22

⫺.54

⫺.46

.13

.00

16-hole peg test, paretic hand

.72

.57

.48

.42

.32

.28

Grippit ratio, paretic hand/nonparetic hand

.57

.31

.80

.69

.44

.23

Analysis was carried out on the basis of data actually collected (n⫽26) and on the basis of intention to treat (ITT).

blinding and the nonrandomized test order in the assessment procedure.

ment problems also have been experienced in other CIMT studies.43,49,50

A major difficulty in the present study was recruiting patients with stroke who met the specific inclusion criteria. The accrual rate was extremely low. It took almost 8 years to recruit 30 suitable patients. Most of the patients in the departments had additional disabilities, such as more paresis, poor balance, cognitive deficits, or a combination of these. Many other patients had already recovered beyond our inclusion criteria during the first month after stroke. We did not attempt to determine learned nonuse because there is no validated screening procedure for detecting this behavior or the risk of developing this behavior. Nevertheless, the inclusion criteria were concordant with those in previous forced-use and CIMT studies and likely were appropriate for finding patients suitable for the type of intervention used in the present study, both functionally and ethically. Another problem was “catching” patients before they were discharged from rehabilitation facilities, because the length of stay after stroke has declined. A few patients were part of other RCTs and, therefore, could not be included in this one. Block randomization was used to guard against the threat of treatment changes over years. Recruit-

As discussed earlier, training was not focused solely on the upper limb. The protocol did not specify the training in detail, and our hope was to achieve parity between groups. Although the 2 groups achieved similar total therapy times, we cannot rule out the possibility that the groups received different amounts of upper-limb training and ambulation training, because the amount of time devoted to upper-extremity training was not specifically recorded. Neither did we gather data regarding the amount of unilateral or bilateral upper-limb training. With regard to dose, for the abovementioned reasons, it was not possible to extend the total therapy time to 6 hours per day in the real clinical setting in which our study took place. We also did not use the recently described approach of transfer within the concept of CIMT, which would have included behavioral techniques to facilitate the transfer of motor behavior during exercise to daily use in the home environment.16 –18

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Finally, neither patients nor therapists could be blinded. The assessor was not blinded due to resources available, but this situation did not seem to have favored the results for the FU group. The duration of the

study certainly could have caused problems in maintaining the same external assessor for all participants. The nonrandomized test order could also have introduced bias with practice or fatigue effects. However, 2 possible modes of the Hawthorne effect need to be mentioned. As indicated by Taub et al,16 rehabilitation therapists nowadays are aware of the problem of learned nonuse. As part of their clinical routine, the therapists in our study encouraged all of the participants to be active and to try to use their affected side as much as possible. Moreover, the number of publications on CIMT17 recently has brought a great deal of attention to this concept. Many patients knew about the CIMT approach, and participants appropriate for and consenting to take part in the present study were presumably the most interested and motivated (in both the FU group and the ST group). As in most CIMT studies, participants were highly selected and only moderately impaired. Recommendations for Future Study The design of a future study must take into consideration the limitations of the present study. Design features need to accomplish as much experimental control as possible in a clinical context. Control of treatment dose and content, or at least

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Figure 2. Outcome measures at preintervention, postintervention, and follow-up tests. Graphs show means per group and error bars of 95% confidence intervals plotted with connecting lines. Symbols: ●, forced-use group; Œ, standard training group. (A) Fugl-Meyer test, upper-extremity score. (B) Modified Ashworth Scale, upper limb. (C) Action Research Arm Test. (D) Motor Assessment Scale, upper-limb score. (E) 16-hole peg test, paretic hand. (F) Grip strength ratio (paretic hand to nonparetic hand). (Continued)

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Effects of Forced Use on Arm Function After Stroke

Figure 2. Continued

tracking of these data, is important. Furthermore, a blinded tester should perform the outcome assessments, and the measures should be tested in a randomized order. The choice of outcome measures must cover different but important ICF categories. A full-size study requires a power calculation to calculate a proper sample size, a factor that might not be achievable in a single center. More resources for selecting study participants could shorten study time. A retrospective power analysis was performed to determine the required sample size. For an 80% power to find the minimum clinical difference of 5.7 points for the ARAT41 between the study groups, we would have had to include at least 58 people in each group. This power calculation was based on the use of a t test and a 2-tailed significance level of 5%. The preintervention values calculated in our study were used (standard deviations of 12.2 in the FU group and 9.2 in the ST group) June 2009

(Tab. 2). Accordingly, our study sample was too small to detect an effect. However, as discussed earlier, the lack of differences in outcomes between the groups might be explained by insufficient contrast between the treatments.

Conclusion The results of the present pilot study did not support forced use as a reinforcement for standard rehabilitation in the subacute phase after stroke. It was ineffective in generating greater improvements in motor impairment and capacity than standard rehabilitation only. Both study groups seemed to accomplish certain motor improvements, and little deterioration was noted during follow-up. However, certain design problems made absolute conclusions uncertain. The important questions of optimal timing after stroke and the duration, intensity, and amount of both the use of restraints and training are still to be resolved in future research on CIMT and forced use.

Both authors provided concept/idea/research design, writing, data analysis, and fund procurement. Ms Hammer provided data collection, project management, subjects, facilities/equipment, and institutional liaisons. Dr Lindmark provided consultation (including review of manuscript before submission). The authors thank all of the patients who participated in the study. They also thank the physical therapists and other staff members from the departments involved for their assistance with recruitment of participants and implementation of the study. Statistical advice from Anders Magnuson, Statistical and Epidemiology Unit, ¨ rebro University Clinical Research Centre, O ¨ rebro, Sweden, is greatly appreciated. Hospital, O ¨ rebro The research ethics committee at O County Council approved the study protocol. The Folksam Research Foundation, the Re¨ rebro County Council, search Funds of O ¨ rebro University, and the Swedish Stroke O Association supported this study. The supporting sources had no involvement in the design, conduct, or reporting of the study. This article was received January 15, 2008, and was accepted February 9, 2009. DOI: 10.2522/ptj.20080017

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Effects of Forced Use on Arm Function After Stroke References 1 Zorowitz RD, Gross E, Polinski DM. The stroke survivor. Disabil Rehabil. 2002; 24:666 – 679. 2 Taub E, Uswatte G. Constraint-induced movement therapy: bridging from the primate laboratory to the stroke rehabilitation laboratory. J Rehabil Med. 2003; 41(suppl):34 – 40. 3 Taub E, Miller NE, Novack TA, et al. Technique to improve chronic motor deficit after stroke. Arch Phys Med Rehabil. 1993;74:347–354. 4 Ostendorf CG, Wolf SL. Effect of forced use of the upper extremity of a hemiplegic patient on changes in function: a singlecase design. Phys Ther. 1981;61: 1022–1028. 5 Wolf SL, Lecraw DE, Barton LA, et al. Forced use of hemiplegic upper extremities to reverse the effect of learned nonuse among chronic stroke and head-injured patients. Exp Neurol. 1989;104:125–132. 6 Morris DM, Crago JE, DeLuca SC, et al. Constraint-induced movement therapy for motor recovery after stroke. Neurorehabilitation. 1997;9:29 – 43. 7 Taub E, Uswatte G, Pidikiti R. Constraintinduced movement therapy: a new family of techniques with broad application to physical rehabilitation—a clinical review. J Rehabil Res Dev. 1999;36:237–251. 8 Page SJ, Levine P, Sisto S, et al. Stroke patients’ and therapists’ opinions of constraintinduced movement therapy. Clin Rehabil. 2002;16:55– 60. 9 Page SJ, Sisto SA, Levine P. Modified constraint-induced therapy in chronic stroke. Am J Phys Med Rehabil. 2002; 81:870 – 875. 10 van der Lee JH. Constraint-induced movement therapy: some thoughts about theories and evidence. J Rehabil Med. 2003; 41(suppl):41– 45. 11 Siegert RJ, Lord S, Porter K. Constraintinduced movement therapy: time for a little restraint? Clin Rehabil. 2004;18: 110 –114. 12 Hakkennes S, Keating JL. Constraint-induced movement therapy following stroke: a systematic review of randomised controlled trials. Aust J Physiother. 2005; 51:221–231. 13 Bonaiuti D, Rebasti L, Sioli P. The constraint induced movement therapy: a systematic review of randomised controlled trials on the adult stroke patients. Eura Medicophys. 2007;43:139 –146. 14 Wolf SL. Revisiting constraint-induced movement therapy: are we too smitten with the mitten? Is all nonuse “learned”? and other quandaries. Phys Ther. 2007; 87:1212–1223. 15 Taub E, Wolf SL. Constraint induced movement techniques to facilitate upper extremity use in stroke patients. Top Stroke Rehabil. 1997;3:38 – 61. 16 Taub E, Uswatte G, Mark VW, et al. The learned nonuse phenomenon: implications for rehabilitation. Eura Medicophys. 2006;42:241–256.

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17 Morris DM, Taub E, Mark VW. Constraintinduced movement therapy: characterizing the intervention protocol. Eura Medicophys. 2006;42:257–268. 18 Winstein CJ, Miller JP, Blanton S, et al. Methods for a multisite randomized trial to investigate the effect of constraintinduced movement therapy in improving upper extremity function among adults recovering from a cerebrovascular stroke. Neurorehabil Neural Repair. 2003;17: 137–152. 19 Russo SG. Hemiplegic upper extremity rehabilitation: a review of the forced-use paradigm. Neurol Rep. 1995;19:17–22. 20 Haynes B. Can it work? Does it work? Is it worth it? The testing of health care interventions is evolving. BMJ. 1999;319: 652– 653. 21 Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther. 1987;67: 206 –207. 22 Bailey MJ, Riddoch MJ. Hemineglect. Part 1. The nature of hemineglect and its clinical assessment in stroke patients: an overview. Phys Ther Rev. 1999;4:67–75. 23 Shulman KI, Gold DP, Cohen CA, et al. Clock-drawing and dementia in the community: a longitudinal study. Int J Geriatr Psychiatry. 1993;8:487– 496. 24 Chen-Sea MJ. Validating the Draw-A-Man Test as a personal neglect test. Am J Occup Ther. 2000;54:391–397. 25 Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975; 12:189 –198. 26 International Classification of Functioning, Disability and Health (ICF). Geneva, Switzerland: World Health Organization; 2001. 27 Fugl-Meyer AR, Jaasko L, Leyman I, et al. The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Scand J Rehabil Med. 1975;7: 13–31. 28 Duncan PW, Propst M, Nelson SG. Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident. Phys Ther. 1983;63: 1606 –1610. 29 De Weerdt WJG, Harrison MA. Measuring recovery of arm-hand function in stroke patients: a comparison of the BrunnstromFugl-Meyer test and the Action Research Arm test. Physiother Can. 1985;37:65–70. 30 Lyle RC. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int J Rehabil Res. 1981;4:483– 492. 31 van der Lee JH, De Groot V, Beckerman H, et al. The intra- and interrater reliability of the Action Research Arm test: a practical test of upper extremity function in patients with stroke. Arch Phys Med Rehabil. 2001;82:14 –19. 32 Carr JH, Shepherd RB, Nordholm L, et al. Investigation of a new motor assessment scale for stroke patients. Phys Ther. 1985;65:175–180.

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33 Lannin NA. Reliability, validity and factor structure of the upper limb subscale of the Motor Assessment Scale (UL-MAS) in adults following stroke. Disabil Rehabil. 2004;26:109 –115. 34 Poole JL, Whitney SL. Motor assessment scale for stroke patients: concurrent validity and interrater reliability. Arch Phys Med Rehabil. 1988;69:195–197. 35 Heller A, Wade DT, Wood VA, et al. Arm function after stroke: measurement and recovery over the first three months. J Neurol Neurosurg Psychiatry. 1987;50:714 –719. 36 Nordenskiold UM, Grimby G. Grip force in patients with rheumatoid arthritis and fibromyalgia and in healthy subjects: a study with the Grippit instrument. Scand J Rheumatol. 1993;22:14 –19. 37 Hammer AM, Lindmark B. Test-retest intrarater reliability of grip force in patients with stroke. J Rehabil Med. 2003;35: 189 –194. 38 Peat J, Barton B. Medical Statistics: A Guide to Data Analysis and Critical Appraisal. Malden, MA: Blackwell Publications; 2005. 39 Brogårdh C, Vestling M, Sjo ¨ lund BH. Shortened constraint-induced movement therapy in subacute stroke—no effect of using a restraint: a randomized controlled study with independent observers. J Rehabil Med. 2009;41:231–236. 40 Ploughman M, Corbett D. Can forced-use therapy be clinically applied after stroke? An exploratory randomized controlled trial. Arch Phys Med Rehabil. 2004;85: 1417–1423. 41 van der Lee JH, Wagenaar RC, Lankhorst GJ, et al. Forced use of the upper extremity in chronic stroke patients: results from a single-blind randomized clinical trial. Stroke. 1999;30:2369 –2375. 42 Edwards DF, Lang CE, Birkenmeier R, et al. VECTORS (Very Early Constraint Therapy for Recovery from Stroke) phase II RCT: results of secondary analyses [abstract]. International Stroke Conference 2008. Stroke. 2008;39:abstract 144. 43 Boake C, Noser EA, Ro T, et al. Constraintinduced movement therapy during early stroke rehabilitation. Neurorehabil Neural Repair. 2007;21:14 –24. 44 Wolf SL, Winstein CJ, Miller JP, et al. Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA. 2006;296:2095–2104. 45 Wolf SL, Newton H, Maddy D, et al. The EXCITE Trial: relationship of intensity of constraint-induced movement therapy to improvement in the Wolf Motor Function Test. Restor Neurol Neurosci. 2007;25: 549 –562. 46 Dobkin BH. Confounders in rehabilitation trials of task-oriented training: lessons from the designs of the EXCITE and SCILT multicenter trials. Neurorehabil Neural Repair. 2007;21:3–13. 47 Blanton S, Wolf SL. An application of upper-extremity constraint-induced movement therapy in a patient with subacute stroke. Phys Ther. 1999;79:847– 853.

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Effects of Forced Use on Arm Function After Stroke 48 Uswatte G, Taub E. Implications of the learned nonuse formulation for measuring rehabilitation outcomes: lessons from constraint-induced movement therapy. Rehabil Psychol. 2005;50:34 – 42.

Invited Commentary Hammer and Lindmark’s elegant study on forced use in people with subacute stroke did not differentiate arm functions of the experimental treatment group in comparison with a standard rehabilitation group.1 They elaborated on the clinical implications of the equivalent subacute stroke findings. We agree with their detailed explanations. In this commentary, we propose an alternative theoretical perspective for consideration: bilateral coordination theory. Moreover, we postulate that the neurophysiological evidence that supports bilateral coordination protocols is a compelling explanation for equivalent forced-use findings. Finally, we advocate new approaches to stroke recovery that include intensive motor problem solving as well as cortical stimulation during rehabilitation. For the past 20 years, bilateral coordination studies have shown distinct characteristics of 2 hands performing symmetrical movements, demonstrating strong temporal and spatial interactions between the hands such as frequency and phase locking as well as amplitude coupling. Indeed, Bernstein2 stated that 2 centrally linked arms form a coordinative structure when the upper extremities execute homologous coupling of muscle groups on both sides of the body. Furthermore, Latash3 eloquently and logically discussed 2 arms functioning together as a synergy. Concerning bilateral stroke rehabilitation protocols, Cauraugh and

June 2009

49 Blanton S, Morris DM, Prettyman MG, et al. Lessons learned in participant recruitment and retention: the EXCITE trial. Phys Ther. 2006;86:1520 –1533.

50 Ro T, Noser E, Boake C, et al. Functional reorganization and recovery after constraint-induced movement therapy in subacute stroke: case reports. Neurocase. 2006;12:50 – 60.

James H. Cauraugh and Jeffery J. Summers

Summers4 discussed an integral component: symmetrical, homologous movements with both arms and hands activate similar neural networks in both hemispheres.5–10 Arguments favoring balanced interhemispheric interactions for normal voluntary movements support practicing bilateral stroke protocols and, consequently, facilitating the motor output from the damaged hemisphere.4,9 –15 Furthermore, recent imaging evidence indicates widespread activation within a large distributed neural network associated with bilateral movements. The distributed bilateral neural basis includes the supplementary motor area, sensorimotor cortex, cingulate motor cortex, lateral premotor cortex, superior parietal cortex, and cerebellum.16 –21 Additional neural evidence indicates that bilateral coordination is robustly associated with corpus callosum white matter integrity and that such integrity may generate interhemispheric pathways to 2 motor areas: the caudal cingulate motor area and the supplementary motor area.22,23 On the contrary, unilateral movements activate interhemispheric inhibition in the ipsilateral hemisphere that serves to prevent mirror movements in the opposite upper limb.24 Typically, forced-use protocols, such as the treatment provided to Hammer and Lindmark’s experimental rehabilitation group, only perform motor actions on the impaired limb, denying bilateral movement practice. Forced-use unilateral movements may cause interhemispheric inhibition by increasing hyperexcitability of the unaffected motor cor-

tex,25–29 thus, not differentiating motor improvements from standard treatment protocols. Moreover, stroke recovery findings that counter unilateral forced use are plentiful.30,31 Evidence that favors bilateral movement training abound.12,23,32– 45 These stroke bilateral coordination findings take on a more persuasive nature, given Hammer and Lindmark’s equivalent forced-use results. Additional indications that forceduse alternatives are becoming ubiquitous are the recent studies arguing in favor of the task-oriented or motor problem-solving approach. This motor learning and control-based approach promises to vastly improve motor capabilities.46 In fact, the approach is a central component of an in-progress cortical stimulation randomized clinical trial named the Everest Trial. In discussing the Everest Trial, Harvey and Winstein47 provide specific details on rehabilitating arm functions after a stroke. Clinically meaningful changes in both the impairment and function of the impaired arm and hand will be determined. The intensive rehabilitation sessions will be standardized by certifying the treating therapists on the principles of motor problem solving. Taken together, the new stroke therapies emphasizing motor learning principles and the comprehensive discussion on current stroke recovery and rehabilitation48 –50 clearly show that research is moving away from forced use, as implemented in

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Effects of Forced Use on Arm Function After Stroke 48 Uswatte G, Taub E. Implications of the learned nonuse formulation for measuring rehabilitation outcomes: lessons from constraint-induced movement therapy. Rehabil Psychol. 2005;50:34 – 42.

Invited Commentary Hammer and Lindmark’s elegant study on forced use in people with subacute stroke did not differentiate arm functions of the experimental treatment group in comparison with a standard rehabilitation group.1 They elaborated on the clinical implications of the equivalent subacute stroke findings. We agree with their detailed explanations. In this commentary, we propose an alternative theoretical perspective for consideration: bilateral coordination theory. Moreover, we postulate that the neurophysiological evidence that supports bilateral coordination protocols is a compelling explanation for equivalent forced-use findings. Finally, we advocate new approaches to stroke recovery that include intensive motor problem solving as well as cortical stimulation during rehabilitation. For the past 20 years, bilateral coordination studies have shown distinct characteristics of 2 hands performing symmetrical movements, demonstrating strong temporal and spatial interactions between the hands such as frequency and phase locking as well as amplitude coupling. Indeed, Bernstein2 stated that 2 centrally linked arms form a coordinative structure when the upper extremities execute homologous coupling of muscle groups on both sides of the body. Furthermore, Latash3 eloquently and logically discussed 2 arms functioning together as a synergy. Concerning bilateral stroke rehabilitation protocols, Cauraugh and

June 2009

49 Blanton S, Morris DM, Prettyman MG, et al. Lessons learned in participant recruitment and retention: the EXCITE trial. Phys Ther. 2006;86:1520 –1533.

50 Ro T, Noser E, Boake C, et al. Functional reorganization and recovery after constraint-induced movement therapy in subacute stroke: case reports. Neurocase. 2006;12:50 – 60.

James H. Cauraugh and Jeffery J. Summers

Summers4 discussed an integral component: symmetrical, homologous movements with both arms and hands activate similar neural networks in both hemispheres.5–10 Arguments favoring balanced interhemispheric interactions for normal voluntary movements support practicing bilateral stroke protocols and, consequently, facilitating the motor output from the damaged hemisphere.4,9 –15 Furthermore, recent imaging evidence indicates widespread activation within a large distributed neural network associated with bilateral movements. The distributed bilateral neural basis includes the supplementary motor area, sensorimotor cortex, cingulate motor cortex, lateral premotor cortex, superior parietal cortex, and cerebellum.16 –21 Additional neural evidence indicates that bilateral coordination is robustly associated with corpus callosum white matter integrity and that such integrity may generate interhemispheric pathways to 2 motor areas: the caudal cingulate motor area and the supplementary motor area.22,23 On the contrary, unilateral movements activate interhemispheric inhibition in the ipsilateral hemisphere that serves to prevent mirror movements in the opposite upper limb.24 Typically, forced-use protocols, such as the treatment provided to Hammer and Lindmark’s experimental rehabilitation group, only perform motor actions on the impaired limb, denying bilateral movement practice. Forced-use unilateral movements may cause interhemispheric inhibition by increasing hyperexcitability of the unaffected motor cor-

tex,25–29 thus, not differentiating motor improvements from standard treatment protocols. Moreover, stroke recovery findings that counter unilateral forced use are plentiful.30,31 Evidence that favors bilateral movement training abound.12,23,32– 45 These stroke bilateral coordination findings take on a more persuasive nature, given Hammer and Lindmark’s equivalent forced-use results. Additional indications that forceduse alternatives are becoming ubiquitous are the recent studies arguing in favor of the task-oriented or motor problem-solving approach. This motor learning and control-based approach promises to vastly improve motor capabilities.46 In fact, the approach is a central component of an in-progress cortical stimulation randomized clinical trial named the Everest Trial. In discussing the Everest Trial, Harvey and Winstein47 provide specific details on rehabilitating arm functions after a stroke. Clinically meaningful changes in both the impairment and function of the impaired arm and hand will be determined. The intensive rehabilitation sessions will be standardized by certifying the treating therapists on the principles of motor problem solving. Taken together, the new stroke therapies emphasizing motor learning principles and the comprehensive discussion on current stroke recovery and rehabilitation48 –50 clearly show that research is moving away from forced use, as implemented in

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Effects of Forced Use on Arm Function After Stroke the laboratory. Indeed, Hammer and Lindmark’s methodologically sound study may take on the significance of the tolling bell in Hemingway’s classic book titled For Whom the Bell Tolls. The bell tolls for thee, forced use. J.H. Cauraugh, PhD, is Professor and Associate Dean of Research, Department of Applied Physiology and Kinesiology, Motor Behavior Laboratory, Center for Exercise Science, University of Florida, Gainesville, FL 32611 (USA). Address all correspondence to Dr Cauraugh at: [email protected]. J.J. Summers, PhD, is Professor, Psychology Department, University of Tasmania, Hobart, Tasmania, Australia. DOI: 10.2522/ptj. 20080017.ic1

References 1 Hammer AM, Lindmark B. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Phys Ther. 2009;89:526 –539. 2 Bernstein N. The Co-ordination and Regulation of Movements. Oxford, United Kingdom: Pergamon Press; 1967. 3 Latash ML. Synergy. New York, NY: Oxford University Press; 2008. 4 Cauraugh JH, Summers JJ. Neural plasticity and bilateral movements: a rehabilitation approach for chronic stroke. Prog Neurobiol. 2005;75:309 –320. 5 Wenderoth N, Debaere F, Sunaert S, et al. Parieto-premotor areas mediate directional interference during bimanual movements. Cereb Cortex. 2004;14: 1153–1163. 6 Hallett M. Functional reorganization after lesions of the human brain: studies with transcranial magnetic stimulation. Rev Neurol (Paris). 2001;157:822– 826. 7 Lacroix S, Havton LA, McKay H, Yang H, et al. Bilateral corticospinal projections arise from each motor cortex in the macaque monkey: a quantitative study. J Comp Neurol. 2004;473:147–161. 8 Rossini PM, Calautti C, Pauri F, Baron J-C. Post-stroke plastic reorganisation in the adult brain. Lancet Neurol. 2003;2: 493–502. 9 Wenderoth N, Debaere F, Sunaert S, Swinnen SP. The role of anterior cingulate cortex and precuneus in the coordination of motor behaviour. Eur J Neurosci. 2005;22:235–246. 10 Heuer H, Klein W. The modulation of intermanual interactions during the specification of the directions of bimanual movements. Exp Brain Res. 2006;169:162–181. 11 Carson RG. Neural pathways mediating bilateral interactions between the upper limbs. Brain Res Rev. 2005;49:641– 662.

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12 Cauraugh JH, Coombes SA, Lodha N, et al. Upper extremity improvements in chronic stroke: coupled bilateral load training. Restor Neurol Neurosci. 2009; 27:17–25. 13 Ferbert A, Vielhaber S, Meincke U, Buchner H. Transcranial magnetic stimulation in pontine infarction: correlation to degree of paresis. J Neurol Neurosurg Psychiatry. 1992;55:294 –299. 14 Hummel F, Celnik P, Giraux P, et al. Effects of non-invasive cortical stimulation on skilled motor function in chronic stroke. Brain. 2005;128:490 – 499. 15 Cincotta M, Ziemann U. Neurophysiology of unimanual motor control and mirror movements. Clin Neurophysiol. 2008; 119:744 –762. 16 Nachev P, Kennard C, Husain M. Functional role of the supplementary and presupplementary motor areas. Nat Rev Neurosci. 2008;9:856 – 869. 17 Goldberg G. Supplementary motor area structure and function: review and hypotheses. Behav Brain Sci. 1985;8: 567– 616. 18 Debaere F, Wenderoth N, Sunaert S, et al. Cerebellar and premotor function in bimanual coordination: parametric neural responses to spatiotemporal complexity and cycling frequency. Neuroimage. 2004;21:1416 –1427. 19 Jancke L, Peters M, Himmelbach M, et al. FMRI study of bimanual coordination. Neuropsychologia. 2000;38:164 –174. 20 Swinnen SP. Intermanual coordination: from behavioural principles to neuralnetwork interactions. Nat Rev Neurosci. 2002;3:348 –359. 21 Swinnen SP, Wenderoth N. Two hands, one brain: cognitive neuroscience of bimanual skill. Trends Cogn Sci. 2004;8: 18 –25. 22 Johansen-Berg H, Della-Maggiore V, Behrens TE, et al. Integrity of white matter in the corpus callosum correlates with bimanual co-ordination skills. Neuroimage. 2007;36(suppl 2):T16 –T21. 23 Stinear CM, Barber PA, Coxon JP, et al. Priming the motor system enhances the effects of upper limb therapy in chronic stroke. Brain. 2008;131:1381–1390. 24 Duque J, Hummel F, Celnik P, et al. Transcallosal inhibition in chronic subcortical stroke. Neuroimage. 2005;28:940 –946. 25 Liepert J, Storch P, Fritsch A, Weiller C. Motor cortex disinhibition in acute stroke. Clin Neurophysiol. 2000;111:671– 676. 26 Murase N, Duque J, Mazzocchio R, Cohen LG. Influence of interhemispheric interactions on motor function in chronic stroke. Ann Neurol. 2004;55:400 – 409. 27 Shimizu T, Hosaki A, Hino T, et al. Motor cortical disinhibition in the unaffected hemisphere after unilateral cortical stroke. Brain. 2002;125:1896 –1907. 28 Floel A, Nagorsen U, Werhahn KJ, et al. Influence of somatosensory input on motor function in patients with chronic stroke. Ann Neurol. 2004;56:206 –212.

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29 Duque J, Murase N, Celnik P, et al. Intermanual differences in movement-related interhemispheric inhibition. J Cogn Neurosci. 2007;19:204 –213. 30 van der Lee JH. Constraint-induced movement therapy: some thoughts about theories and evidence. J Rehabil Med. 2003:41– 45. 31 McCombe Waller S, Whitall J. Bilateral arm training: why and who benefits? NeuroRehabilitation. 2008;23:29 – 41. 32 Lewis GN, Byblow WD. Bimanual coordination dynamics in poststroke hemiparetics. J Mot Behav. 2004;36:174 –188. 33 Celnik P, Hummel F, Harris-Love M, et al. Somatosensory stimulation enhances the effects of training functional hand tasks in patients with chronic stroke. Arch Phys Med Rehabil. 2007;88:1369 –1376. 34 Luft AR, McCombe-Waller S, Whitall J, et al. Repetitive bilateral arm training and motor cortex activation in chronic stroke: a randomized controlled trial. JAMA. 2004;292:1853–1861. 35 Summers JJ, Kagerer FA, Garry MI, et al. Bilateral and unilateral movement training on upper limb function in chronic stroke patients: a TMS study. J Neurol Sci. 2007;252:76 – 82. 36 Cauraugh JH, Kim SB. Two coupled motor recovery protocols are better than one: electromyogram-triggered neuromuscular stimulation and bilateral movements. Stroke. 2002;33:1589 –1594. 37 Cauraugh JH, Kim SB, Summers JJ. Chronic stroke longitudinal motor improvements: cumulative learning evidence found in the upper extremity. Cerebrovasc Dis. 2008;25:115–121. 38 Kreisel SH, Hennerici MG, Bazner H. Pathophysiology of stroke rehabilitation: the natural course of clinical recovery, use-dependent plasticity and rehabilitative outcome. Cerebrovasc Dis. 2007;23: 243–255. 39 Harris-Love ML, McCombe Waller S, Whitall J. Exploiting interlimb coupling to improve paretic arm reaching performance in people with chronic stroke. Arch Phys Med Rehabil. 2005;86:2131–2137. 40 McCombe Waller S, Whitall J. Fine motor control in adults with and without chronic hemiparesis: baseline comparison to nondisabled adults and effects of bilateral arm training. Arch Phys Med Rehabil. 2004; 85:1076 –1083. 41 Whitall J, McCombe Waller S, Silver KH, Macko RF. Repetitive bilateral arm training with rhythmic auditory cueing improves motor function in chronic hemiparetic stroke. Stroke. 2000;31:2390 –2395. 42 Stinear JW, Byblow WD. Rhythmic bilateral movement training modulates corticomotor excitability and enhances upper limb motricity poststroke: a pilot study. J Clin Neurophysiol. 2004;21:124 –131. 43 Lewis GN, Byblow WD. Neurophysiological and behavioural adaptations to a bilateral training intervention in individuals following stroke. Clin Rehabil. 2004;18: 48 –59.

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Effects of Forced Use on Arm Function After Stroke 44 Harris-Love ML, Perez MA, Chen R, Cohen LG. Interhemispheric inhibition in distal and proximal arm representations in the primary motor cortex. J Neurophysiol. 2007;97:2511–2515. 45 Cauraugh JH, Kim SB, Duley A. Coupled bilateral movements and active neuromuscular stimulation: intralimb transfer evidence during bimanual aiming. Neurosci Lett. 2005;382:39 – 44.

46 Bass-Haugen J, Mathiowetz V, Flinn N. Optimizing motor behavior using the occupational therapy task-oriented approach. In: Radomski MV, Trombly CA, eds. Occupational Therapy for Physical Dysfunction. Baltimore, MD: Lippincott Williams & Wilkins; 2008:598 – 617. 47 Harvey RL, Winstein CJ. Design for the Everest randomized trial of cortical stimulation and rehabilitation for arm function following stroke. Neurorehabil Neural Repair. 2009;23:32– 44.

Author Response

Ann M. Hammer, Birgitta Lindmark

We thank Cauraugh and Summers1 for their interest in and commentary on our report.2 They provide some of the many considerations within the field of upper-extremity rehabilitation for people after stroke. However, we will attempt to discuss some of the evidence gained within the area.

of producing repetitive training is robot-assisted therapy. Two different reviews made similar conclusions. Kwakkel et al,5 in a meta-analysis of 10 studies involving 218 patients, found no overall effect, although the shoulder-elbow robotics showed a significant effect on motor function but not on function in activities of daily living (ADL). A recent Cochrane review6 investigating robotassisted arm training in 11 trials with 328 participants found that this type of training was not more efficient than other training or no training on ADL, but arm motor function and strength improved. Both author groups encountered difficulties with design variability among studies, making conclusions uncertain.

A scientific basis for physical therapy interventions is emerging, with a rapid increase of publications. Several important systematic reviews have been analyzing stroke motor rehabilitation. So far, however, there is scant evidence that any treatment is superior to another. Cauraugh and Summers3 contributed to a summary of knowledge concerning bilateral movement training in stroke rehabilitation, stating there is a favorable effect on motor recovery. The validity of this conclusion, however, seems uncertain as the results of control groups were not included in the comparisons. A Cochrane protocol focusing on simultaneous bilateral training for improving arm function after stroke has now been published.4 Intense, repetitive practice has been proposed to be advantageous for people after stroke based on learning principles within movement science. This can be accomplished by means of various training approaches that increase repetitions. One way

June 2009

Another extensive systematic review summarized studies of repetitive functional task practice without being able to synthesize a firm recommendation for upper-limb interventions.7 Augmented therapy was analyzed by Kwakkel et al,8 and although a positive association was found between added therapy time and outcome on ADL, the same could not be shown for upperextremity dexterity. Likewise, a summary explicitly on arm therapy concluded that more-intensive exercise therapy may be beneficial, but firm evidence was not found.9

48 Stein J, Harvey RL, Macko RF, et al. Stroke Recovery and Rehabilitation. New York, NY: Demos Medical Publishing; 2009. 49 Cramer SC, Riley JD. Neuroplasticity and brain repair after stroke. Curr Opin Neurol. 2008;21:76 – 82. 50 Cramer SC. Repairing the human brain after stroke, II: restorative therapies. Ann Neurol. 2008;63:549 –560.

The impact of physical therapy was scrutinized by van Peppen et al.10 Their presentation includes upperlimb functional outcome in several of their intervention categories. Regarding upper-extremity recovery, no evidence was found for applying one specific neurological treatment program or strengthening exercises to improve grip force. Study pooling posed difficulties, and exercises for the upper limb, bilateral arm training, mirror therapy, biofeedback therapy, and neuromuscular electrical stimulation all gave limited support for effectiveness. A significant effect was found for constraintinduced movement therapy (CIMT). Physical therapy treatment based on different principles also has been compared. Pollock et al11 reviewed conventional neurophysiologic, motor learning, and orthopedic approaches of physical therapy. This recently updated review of 20 trials involving 1,087 patients concluded that the only significant result was from using a “mix” of components from different approaches compared with no treatment. However, their focus was still the recovery of postural control and lower limb. Another systematic review12 investigated whether electrostimulation improved movement or functional ability, concluding there was no clear evidence of the benefit of electro-

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Effects of Forced Use on Arm Function After Stroke 44 Harris-Love ML, Perez MA, Chen R, Cohen LG. Interhemispheric inhibition in distal and proximal arm representations in the primary motor cortex. J Neurophysiol. 2007;97:2511–2515. 45 Cauraugh JH, Kim SB, Duley A. Coupled bilateral movements and active neuromuscular stimulation: intralimb transfer evidence during bimanual aiming. Neurosci Lett. 2005;382:39 – 44.

46 Bass-Haugen J, Mathiowetz V, Flinn N. Optimizing motor behavior using the occupational therapy task-oriented approach. In: Radomski MV, Trombly CA, eds. Occupational Therapy for Physical Dysfunction. Baltimore, MD: Lippincott Williams & Wilkins; 2008:598 – 617. 47 Harvey RL, Winstein CJ. Design for the Everest randomized trial of cortical stimulation and rehabilitation for arm function following stroke. Neurorehabil Neural Repair. 2009;23:32– 44.

Author Response

Ann M. Hammer, Birgitta Lindmark

We thank Cauraugh and Summers1 for their interest in and commentary on our report.2 They provide some of the many considerations within the field of upper-extremity rehabilitation for people after stroke. However, we will attempt to discuss some of the evidence gained within the area.

of producing repetitive training is robot-assisted therapy. Two different reviews made similar conclusions. Kwakkel et al,5 in a meta-analysis of 10 studies involving 218 patients, found no overall effect, although the shoulder-elbow robotics showed a significant effect on motor function but not on function in activities of daily living (ADL). A recent Cochrane review6 investigating robotassisted arm training in 11 trials with 328 participants found that this type of training was not more efficient than other training or no training on ADL, but arm motor function and strength improved. Both author groups encountered difficulties with design variability among studies, making conclusions uncertain.

A scientific basis for physical therapy interventions is emerging, with a rapid increase of publications. Several important systematic reviews have been analyzing stroke motor rehabilitation. So far, however, there is scant evidence that any treatment is superior to another. Cauraugh and Summers3 contributed to a summary of knowledge concerning bilateral movement training in stroke rehabilitation, stating there is a favorable effect on motor recovery. The validity of this conclusion, however, seems uncertain as the results of control groups were not included in the comparisons. A Cochrane protocol focusing on simultaneous bilateral training for improving arm function after stroke has now been published.4 Intense, repetitive practice has been proposed to be advantageous for people after stroke based on learning principles within movement science. This can be accomplished by means of various training approaches that increase repetitions. One way

June 2009

Another extensive systematic review summarized studies of repetitive functional task practice without being able to synthesize a firm recommendation for upper-limb interventions.7 Augmented therapy was analyzed by Kwakkel et al,8 and although a positive association was found between added therapy time and outcome on ADL, the same could not be shown for upperextremity dexterity. Likewise, a summary explicitly on arm therapy concluded that more-intensive exercise therapy may be beneficial, but firm evidence was not found.9

48 Stein J, Harvey RL, Macko RF, et al. Stroke Recovery and Rehabilitation. New York, NY: Demos Medical Publishing; 2009. 49 Cramer SC, Riley JD. Neuroplasticity and brain repair after stroke. Curr Opin Neurol. 2008;21:76 – 82. 50 Cramer SC. Repairing the human brain after stroke, II: restorative therapies. Ann Neurol. 2008;63:549 –560.

The impact of physical therapy was scrutinized by van Peppen et al.10 Their presentation includes upperlimb functional outcome in several of their intervention categories. Regarding upper-extremity recovery, no evidence was found for applying one specific neurological treatment program or strengthening exercises to improve grip force. Study pooling posed difficulties, and exercises for the upper limb, bilateral arm training, mirror therapy, biofeedback therapy, and neuromuscular electrical stimulation all gave limited support for effectiveness. A significant effect was found for constraintinduced movement therapy (CIMT). Physical therapy treatment based on different principles also has been compared. Pollock et al11 reviewed conventional neurophysiologic, motor learning, and orthopedic approaches of physical therapy. This recently updated review of 20 trials involving 1,087 patients concluded that the only significant result was from using a “mix” of components from different approaches compared with no treatment. However, their focus was still the recovery of postural control and lower limb. Another systematic review12 investigated whether electrostimulation improved movement or functional ability, concluding there was no clear evidence of the benefit of electro-

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Effects of Forced Use on Arm Function After Stroke stimulation on the upper extremities. Thus, several recent reviews have had continued problems of proving a clear-cut conclusion. Functional, patient-related outcomes on the International Classification of Functioning, Disability and Health levels of body function, activity, and participation13 should be the primary choice when generating evidence for rehabilitation interventions.14 A complementary source is the theoretical foundation or other support providing biological plausibility for an explanation of the mechanism of effect. Conversely, over the years, the theoretical neurophysiologic impact on therapy approaches probably has been too strong, as clinical evidence of effects in controlled studies of proprioceptive neuromuscular facilitation, Bobath treatment, and the Brunnstro ¨m model is meager. Considering learned nonuse/CIMT/ forced use and bilateral movement therapy, the theories behind the 2 techniques appear contradictory. Because the population of people with stroke is heterogeneous, there presumably are therapies that are appropriate for certain poststroke status or situations. In the case of motor neglect and extinction, Punt and Riddoch15 suggested that a bilateral training approach is inappropriate.

equipment or training approaches. On the other hand, benefits of rehabilitation efforts are mostly posed as advantageous. Maybe how therapy is accomplished is of less importance. The details of importance might be an active treatment principle—that motor capacity is targeted and challenged, yet individually adjusted. High-quality randomized controlled trials will generate an accumulating knowledge, but we currently have insufficient evidence for details of motor restoring therapies. DOI: 10.2522/ptj.20080017.ar1

References 1 Cauraugh JH, Summers JJ. Invited commentary on “Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study.” Phys Ther. 2009;89:539 –541. 2 Hammer AM, Lindmark B. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Phys Ther. 2009;89:526 –539. 3 Stewart KC, Cauraugh JH, Summers JJ. Bilateral movement training and stroke rehabilitation: a systematic review and metaanalysis. J Neurol Sci. 2006;244:89 –95. 4 Coupar F, Van Wijck F, Morris J, et al. Simultaneous bilateral training for improving arm function after stroke. Cochrane Database Syst Rev. 2007;2:CD006432. 5 Kwakkel G, Kollen BJ, Krebs HI. Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review. Neurorehabil Neural Repair. 2008;22: 111–121. 6 Mehrholz J, Platz T, Kugler J, Pohl M. Electromechanical and robot-assisted arm training for improving arm function and activities of daily living after stroke. Cochrane Database Syst Rev. 2008;4:CD006876.

7 French B, Leathley M, Sutton C, et al. A systematic review of repetitive functional task practice with modelling of resource use, costs and effectiveness. Health Technol Assess. 2008;12:iii. 8 Kwakkel G, van Peppen R, Wagenaar RC, et al. Effects of augmented exercise therapy time after stroke: a meta-analysis. Stroke. 2004;35:2529 –2539. 9 van der Lee JH, Snels IA, Beckerman H, et al. Exercise therapy for arm function in stroke patients: a systematic review of randomized controlled trials. Clin Rehabil. 2001;15:20 –31. 10 van Peppen RP, Kwakkel G, WoodDauphine´e S, et al. The impact of physical therapy on functional outcomes after stroke: what’s the evidence? Clin Rehabil. 2004;18:833– 862. 11 Pollock A, Baer G, Pomeroy VM, Langhorne P. Physiotherapy treatment approaches for the recovery of postural control and lower limb function following stroke. Cochrane Database Syst Rev. 2007;1:CD001920. 12 Pomeroy VM, King L, Pollock A, et al. Electrostimulation for promoting recovery of movement or functional ability after stroke. Cochrane Database Syst Rev. 2006;2:CD003241. 13 International Classification of Functioning, Disability and Health: ICF. Geneva, Switzerland: World Health Organization; 2001. 14 Bucher HC, Guyatt GH, Cook DJ, et al; Evidence-Based Medicine Working Group. Users’ guides to the medical literature, XIX: applying clinical trial results, A: how to use an article measuring the effect of an intervention on surrogate end points. JAMA. 1999;282:771–778. 15 Punt TD, Riddoch MJ. Motor neglect: implications for movement and rehabilitation following stroke. Disabil Rehabil. 2006;28:857– 864.

Thus, there is limited evidence supporting the use of specific technical

Invited Commentary

Jeanne Charles

Within stroke rehabilitation research, constraint-induced movement therapy (CIMT) is an intervention protocol designed to improve involved upper-extremity use that is based on principles of clinical research.1 Originating from seminal animal deafferentation studies2 and electromyo542

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graphic biofeedback studies,3 CIMT has been described as a “therapeutic package” that consists of several components.4 They include: (1) repetitive, task-oriented practice of the more-involved upper limb for several hours per day over a period of 10 or 15 days, (2) behavioral adherence to

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“at-home” practice that encourages practice in the patient’s home environment as a transfer from practice in the laboratory setting, and (3) constraining the patient to use the moreinvolved upper limb during waking hours through the use of a restraint on the less-involved upper limb.4 June 2009

Effects of Forced Use on Arm Function After Stroke stimulation on the upper extremities. Thus, several recent reviews have had continued problems of proving a clear-cut conclusion. Functional, patient-related outcomes on the International Classification of Functioning, Disability and Health levels of body function, activity, and participation13 should be the primary choice when generating evidence for rehabilitation interventions.14 A complementary source is the theoretical foundation or other support providing biological plausibility for an explanation of the mechanism of effect. Conversely, over the years, the theoretical neurophysiologic impact on therapy approaches probably has been too strong, as clinical evidence of effects in controlled studies of proprioceptive neuromuscular facilitation, Bobath treatment, and the Brunnstro ¨m model is meager. Considering learned nonuse/CIMT/ forced use and bilateral movement therapy, the theories behind the 2 techniques appear contradictory. Because the population of people with stroke is heterogeneous, there presumably are therapies that are appropriate for certain poststroke status or situations. In the case of motor neglect and extinction, Punt and Riddoch15 suggested that a bilateral training approach is inappropriate.

equipment or training approaches. On the other hand, benefits of rehabilitation efforts are mostly posed as advantageous. Maybe how therapy is accomplished is of less importance. The details of importance might be an active treatment principle—that motor capacity is targeted and challenged, yet individually adjusted. High-quality randomized controlled trials will generate an accumulating knowledge, but we currently have insufficient evidence for details of motor restoring therapies. DOI: 10.2522/ptj.20080017.ar1

References 1 Cauraugh JH, Summers JJ. Invited commentary on “Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study.” Phys Ther. 2009;89:539 –541. 2 Hammer AM, Lindmark B. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Phys Ther. 2009;89:526 –539. 3 Stewart KC, Cauraugh JH, Summers JJ. Bilateral movement training and stroke rehabilitation: a systematic review and metaanalysis. J Neurol Sci. 2006;244:89 –95. 4 Coupar F, Van Wijck F, Morris J, et al. Simultaneous bilateral training for improving arm function after stroke. Cochrane Database Syst Rev. 2007;2:CD006432. 5 Kwakkel G, Kollen BJ, Krebs HI. Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review. Neurorehabil Neural Repair. 2008;22: 111–121. 6 Mehrholz J, Platz T, Kugler J, Pohl M. Electromechanical and robot-assisted arm training for improving arm function and activities of daily living after stroke. Cochrane Database Syst Rev. 2008;4:CD006876.

7 French B, Leathley M, Sutton C, et al. A systematic review of repetitive functional task practice with modelling of resource use, costs and effectiveness. Health Technol Assess. 2008;12:iii. 8 Kwakkel G, van Peppen R, Wagenaar RC, et al. Effects of augmented exercise therapy time after stroke: a meta-analysis. Stroke. 2004;35:2529 –2539. 9 van der Lee JH, Snels IA, Beckerman H, et al. Exercise therapy for arm function in stroke patients: a systematic review of randomized controlled trials. Clin Rehabil. 2001;15:20 –31. 10 van Peppen RP, Kwakkel G, WoodDauphine´e S, et al. The impact of physical therapy on functional outcomes after stroke: what’s the evidence? Clin Rehabil. 2004;18:833– 862. 11 Pollock A, Baer G, Pomeroy VM, Langhorne P. Physiotherapy treatment approaches for the recovery of postural control and lower limb function following stroke. Cochrane Database Syst Rev. 2007;1:CD001920. 12 Pomeroy VM, King L, Pollock A, et al. Electrostimulation for promoting recovery of movement or functional ability after stroke. Cochrane Database Syst Rev. 2006;2:CD003241. 13 International Classification of Functioning, Disability and Health: ICF. Geneva, Switzerland: World Health Organization; 2001. 14 Bucher HC, Guyatt GH, Cook DJ, et al; Evidence-Based Medicine Working Group. Users’ guides to the medical literature, XIX: applying clinical trial results, A: how to use an article measuring the effect of an intervention on surrogate end points. JAMA. 1999;282:771–778. 15 Punt TD, Riddoch MJ. Motor neglect: implications for movement and rehabilitation following stroke. Disabil Rehabil. 2006;28:857– 864.

Thus, there is limited evidence supporting the use of specific technical

Invited Commentary

Jeanne Charles

Within stroke rehabilitation research, constraint-induced movement therapy (CIMT) is an intervention protocol designed to improve involved upper-extremity use that is based on principles of clinical research.1 Originating from seminal animal deafferentation studies2 and electromyo542

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graphic biofeedback studies,3 CIMT has been described as a “therapeutic package” that consists of several components.4 They include: (1) repetitive, task-oriented practice of the more-involved upper limb for several hours per day over a period of 10 or 15 days, (2) behavioral adherence to

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“at-home” practice that encourages practice in the patient’s home environment as a transfer from practice in the laboratory setting, and (3) constraining the patient to use the moreinvolved upper limb during waking hours through the use of a restraint on the less-involved upper limb.4 June 2009

Effects of Forced Use on Arm Function After Stroke The original CIMT protocol was associated with a behavioral paradigm that used operant conditioning as the form of practice. The goal of operant conditioning was to overcome learned nonuse of the more-involved upper extremity by obtaining efficient performance of practiced tasks through successive approximation. Specifically, forced use is defined as constraint of the less-involved upper extremity via a sling or a mitt during most of the waking hours, thus “forcing” use of the moreinvolved upper extremity.5 During this time, the patient engages in activities that are collaboratively determined by the patient and clinician and performed in the home setting.5 Studies that have examined the efficacy of CIMT in populations of people with acute, subacute, and chronic stroke have shown significant changes in outcome measures from before to after intervention, with these changes maintained on follow-up evaluation.6,7 It should be noted that intervention protocols as well as outcome measures were not consistent among studies. However, the recent results of the Extremity Constraint-Induced Therapy Evaluation (EXCITE) trial, a multicenter randomized clinical trial demonstrating that CIMT produced statistically significant and clinically relevant improvements in people who had a stroke in the previous 3 to 9 months,8 provide adequate evidence of the efficacy of this intervention. Given the ongoing interest in examining the effectiveness of CIMT, Hammer and Lindmark9 should be commended for undertaking an intervention study involving 30 people with a 3-month follow-up evaluation. Training studies involve a great deal of work over a long period of time. However, a close examination of this study raises some conceptual and methodological concerns. For instance, although the authors used a forced-use paradigm as a means to June 2009

enhance a traditional rehabilitation therapeutic program for this poststroke population, they did not define what is “enhanced” in the traditional rehabilitation program. Based on their definition of the differences in the interventions between the 2 groups (forced use versus non– forced use), one would assume that application of the restraint alone would result in increased use of the more-involved upper extremity during a treatment session. However, the fact that therapists in the non–forced use group may have used constraining strategies, such as encouraging a patient to use the more-involved limb during a task or constraining a task so that it necessitated involved upper-extremity use, raises the question of which group was truly constrained during therapy. That is, why would we expect greater constraint in the forced-use group when therapists in both groups could have been consistently promoting increased use of the involved upper limb? A clearer picture may have emerged if measures were used to capture the type and amount of practice that was completed by the more-involved limb throughout the therapy session in addition to the time that was spent in a restraint. For example, the authors list (Tab. 3) the type of bimanual activities that resulted in restraint removal. If the patient actively used both limbs during those activities, is that not active practice for the more-involved upper extremity? In addition, is not use of both limbs in a bimanual task a forced-use task? Finally, as defined above, forced use involves a collaborative process between the patient and the therapist to define goals or exercises that can be practiced in the home environment. This behavioral contract is an essential component of forced use,1,4 and it involves more than use of a restraint. It is the basis for the

transfer of practice from the rehabilitation setting to the home environment and to increased functional use of the more-involved limb. This process was not included as part of the force-use paradigm in this study. What is exciting about the contribution of the CIMT studies to rehabilitation research is that it has sparked more research initiatives to define the effectiveness of neurorehabilitation.10 The neurobiology of repair after stroke11 and the neuroplasticity in the adult brain poststroke10 offer new opportunities to refine current interventions and to define and test new effective interventions. Imaging studies have provided new information regarding the neurophysiology of the central nervous systems’ inhibitory and excitatory processes and their effects on contralateral hemisphere activity both before and after stroke. Functional magnetic resonance imaging studies have shown practice that involves active problem-solving promotes greater central nervous system neuroplasticity poststroke.12 Psychosocial factors and the relationship of the person to his or her significant other or caregiver may affect a patient’s behavior in regard to adherence to a practice regimen.10 The use of a constraint to promote increased upper-limb use may be a method to ensure adherence in involved upper-extremity use, but the type of practice that is used to promote increased use may be more critical, thus necessitating more complete measures of activity during practice. Constraint-induced movement therapy is evolving beyond the original forced use studies1 and is continuing to refine the fundamental learned nonuse model.5 J. Charles, PT, PhD, is Assistant Professor, Division of Physical Therapy, Emory University School of Medicine, 1441 Clifton Rd NE,

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Effects of Forced Use on Arm Function After Stroke Atlanta, GA 30322. Address all correspondence to Dr Charles at: [email protected]. DOI: 10.2522/ptj.20080017.ic2

References 1 Blanton S, Wilsey H, Wolf SL. Constraintinduced movement therapy in stroke rehabilitation: perspectives on future clinical applications. Neuro Rehabilitation. 2008;23:15–28. 2 Taub E. Somatosensory deafferentation research in monkeys: implications for rehabilitation medicine. In Ince L, ed. Behavioral Psychology in Rehabilitation Medicine: Clinical Applications. Baltimore, MD. Williams & Wilkins; 1980:371– 401. 3 Wolf SL. Electromyographic feedback applications to stroke patients: a critical review. Phys Ther. 1983;63:1448 –1459.

4 Morris DM, Taub E, Mark VW. Constraintinduced therapy: characterizing the intervention protocol. Euro Medicophys. 2006;42:257–268. 5 Wolf SL. Revisiting constraint-induced movement therapy: Are we too smitten with the mitten? Is all nonuse “learned”? and other quandaries. Phys Ther. 2007; 87:1212–1223. 6 Bonaiuti D, Rebasti L, Sioli P. The constraint-induced movement therapy: a systematic review of randomized control trials on the adult stroke patients. Euro Medicophys. 2007;43:139 –146. 7 Hakkennes S, Keating JL. Constraintinduced movement therapy following stroke: a systematic review of randomized controlled trials. Aust J Physiother. 2005; 51:221–231. 8 Wolf SL, Winstein CJ, Miller P. et al. Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA. 2006;296:2095–2104.

Author Response

Ann M. Hammer, Birgitta Lindmark

We appreciate the commentary provided by Charles1 and will respond to the questions posed, as several of the points were congruent with our presentation.

appropriate at the start of our study. The intention of enhanced outcomes focused the general goal of motor rehabilitation—improved motor function and capacity and performance of daily activities, with a focus on the paretic arm. This goal historically has been present9 –11 in training approaches preceding forced use and CIMT. Even though the critical elements of CIMT are inconclusively investigated, the really new component of the concept was, and is, the restraint. The protocol for CIMT6 points out the importance of a physical restraint as a reminder to limit the use of the unaffected limb. A sling or a mitt is evidently a more substantial marker than no physical restraint for facilitation of arm practice and use, probably having an influence not only on the patients, but also on therapists and others encountering the “forced” patient. The shorter situations of restraint removal in our study probably were because the patients could not manage the activity without the unaffected hand. Therefore, the suggestion of Charles was not probable, but

The original forced-use studies administered nothing but a restraint.2,3 The broadened definition stated in the commentary by Charles was not applied in our study.4 Details in our article specify that forced use was applied with a restraint in connection with the ongoing rehabilitation in the departments concerned. The behavior contract is rather a component of the classic constraintinduced movement therapy (CIMT) paradigm,5 although it recently has received more emphasis.6 Goal setting and treatment planning are core duties in interdisciplinary rehabilitation programs and not exclusively in CIMT. Some reviews7,8 emphasized that data on efficacy or effectiveness of CIMT are limited and that conclusions remain uncertain. The evaluation of sling use together with ongoing rehabilitation seemed

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9 Hammer AM, Lindmark B. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Phys Ther. 2009;89:526 –539. 10 Levin MF, Kleim JA, Wolf SL. What do motor recovery and “compensation” mean in patients following stroke. Neurorehabil Neural Rep. 2009;23:313–319. 11 Cramer SC, Riley JD. Neuroplasticity and brain repair after stroke. Curr Opin Neurol. 2008;21:76 – 82. 12 Gauthier LV, Taub E, Perkins C, et al. Remodeling the brain: plastic structural brain changes by different motor therapies after stroke. Stroke. 2008;39:1520 –1525.

rather these situations were not focused on enhanced use of the affected hand. As noted in our article, the details of the training performed unfortunately were not tracked in our study. As Morris et al6 pointed out, however, there are many facets of motor interventions that make this recording very challenging: the chosen activity or task, levels of difficulty progression, duration and intensity, feedback manners, movements emphasized, and interaction between the therapist and the patient such as coaching, encouragement, and modeling. The research of brain plasticity is exciting, promising, and important. Nevertheless, interventions need to be proven efficient for the patient’s capacity and performance in daily motor functions and activities. In addition, interventions need to be feasible in clinical contexts, which is not assured in classic CIMT. Along with feasibility, interventions need to be relevant and adjusted on an

June 2009

Effects of Forced Use on Arm Function After Stroke Atlanta, GA 30322. Address all correspondence to Dr Charles at: [email protected]. DOI: 10.2522/ptj.20080017.ic2

References 1 Blanton S, Wilsey H, Wolf SL. Constraintinduced movement therapy in stroke rehabilitation: perspectives on future clinical applications. Neuro Rehabilitation. 2008;23:15–28. 2 Taub E. Somatosensory deafferentation research in monkeys: implications for rehabilitation medicine. In Ince L, ed. Behavioral Psychology in Rehabilitation Medicine: Clinical Applications. Baltimore, MD. Williams & Wilkins; 1980:371– 401. 3 Wolf SL. Electromyographic feedback applications to stroke patients: a critical review. Phys Ther. 1983;63:1448 –1459.

4 Morris DM, Taub E, Mark VW. Constraintinduced therapy: characterizing the intervention protocol. Euro Medicophys. 2006;42:257–268. 5 Wolf SL. Revisiting constraint-induced movement therapy: Are we too smitten with the mitten? Is all nonuse “learned”? and other quandaries. Phys Ther. 2007; 87:1212–1223. 6 Bonaiuti D, Rebasti L, Sioli P. The constraint-induced movement therapy: a systematic review of randomized control trials on the adult stroke patients. Euro Medicophys. 2007;43:139 –146. 7 Hakkennes S, Keating JL. Constraintinduced movement therapy following stroke: a systematic review of randomized controlled trials. Aust J Physiother. 2005; 51:221–231. 8 Wolf SL, Winstein CJ, Miller P. et al. Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA. 2006;296:2095–2104.

Author Response

Ann M. Hammer, Birgitta Lindmark

We appreciate the commentary provided by Charles1 and will respond to the questions posed, as several of the points were congruent with our presentation.

appropriate at the start of our study. The intention of enhanced outcomes focused the general goal of motor rehabilitation—improved motor function and capacity and performance of daily activities, with a focus on the paretic arm. This goal historically has been present9 –11 in training approaches preceding forced use and CIMT. Even though the critical elements of CIMT are inconclusively investigated, the really new component of the concept was, and is, the restraint. The protocol for CIMT6 points out the importance of a physical restraint as a reminder to limit the use of the unaffected limb. A sling or a mitt is evidently a more substantial marker than no physical restraint for facilitation of arm practice and use, probably having an influence not only on the patients, but also on therapists and others encountering the “forced” patient. The shorter situations of restraint removal in our study probably were because the patients could not manage the activity without the unaffected hand. Therefore, the suggestion of Charles was not probable, but

The original forced-use studies administered nothing but a restraint.2,3 The broadened definition stated in the commentary by Charles was not applied in our study.4 Details in our article specify that forced use was applied with a restraint in connection with the ongoing rehabilitation in the departments concerned. The behavior contract is rather a component of the classic constraintinduced movement therapy (CIMT) paradigm,5 although it recently has received more emphasis.6 Goal setting and treatment planning are core duties in interdisciplinary rehabilitation programs and not exclusively in CIMT. Some reviews7,8 emphasized that data on efficacy or effectiveness of CIMT are limited and that conclusions remain uncertain. The evaluation of sling use together with ongoing rehabilitation seemed

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9 Hammer AM, Lindmark B. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Phys Ther. 2009;89:526 –539. 10 Levin MF, Kleim JA, Wolf SL. What do motor recovery and “compensation” mean in patients following stroke. Neurorehabil Neural Rep. 2009;23:313–319. 11 Cramer SC, Riley JD. Neuroplasticity and brain repair after stroke. Curr Opin Neurol. 2008;21:76 – 82. 12 Gauthier LV, Taub E, Perkins C, et al. Remodeling the brain: plastic structural brain changes by different motor therapies after stroke. Stroke. 2008;39:1520 –1525.

rather these situations were not focused on enhanced use of the affected hand. As noted in our article, the details of the training performed unfortunately were not tracked in our study. As Morris et al6 pointed out, however, there are many facets of motor interventions that make this recording very challenging: the chosen activity or task, levels of difficulty progression, duration and intensity, feedback manners, movements emphasized, and interaction between the therapist and the patient such as coaching, encouragement, and modeling. The research of brain plasticity is exciting, promising, and important. Nevertheless, interventions need to be proven efficient for the patient’s capacity and performance in daily motor functions and activities. In addition, interventions need to be feasible in clinical contexts, which is not assured in classic CIMT. Along with feasibility, interventions need to be relevant and adjusted on an

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Effects of Forced Use on Arm Function After Stroke individual basis to the poststroke condition of each patient in a clinical context. DOI: 10.2522/ptj.20080017.ar2

References 1 Charles J. Invited commentary on “Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study.” Phys Ther. 2009;89: 542–544. 2 Ostendorf CG, Wolf SL. Effect of forced use of the upper extremity of a hemiplegic patient on changes in function. A singlecase design. Phys Ther. 1981;61: 1022–1028.

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3 Wolf SL, Lecraw DE, Barton LA, et al. Forced use of hemiplegic upper extremities to reverse the effect of learned nonuse among chronic stroke and head-injured patients. Exp Neurol. 1989;104:125–132. 4 Hammer AM, Lindmark B. Effects of forced use on arm function in the subacute phase after stroke: a randomized, clinical pilot study. Phys Ther. 2009;89:526 –539. 5 Morris DM, Crago JE, DeLuca SC, et al. Constraint-induced movement therapy for motor recovery after stroke. Neurorehabilitation. 1997;9:29 – 43. 6 Morris DM, Taub E, Mark VW. Constraintinduced movement therapy: characterizing the intervention protocol. Eura Medicophys. 2006;42:257–268. 7 Hakkennes S, Keating JL. Constraintinduced movement therapy following stroke: a systematic review of randomised controlled trials. Aust J Physiother. 2005;51:221–231.

8 Bonaiuti D, Rebasti L, Sioli P. The constraint induced movement therapy: a systematic review of randomised controlled trials on the adult stroke patients. Eura Medicophys. 2007;43:139 –146. 9 Ernst E. A review of stroke rehabilitation and physiotherapy. Stroke. 1990;21: 1081–1085. 10 Shumway-Cook A, Woollacott MH. Motor Control: Theory and Practical Applications. Baltimore, MD: Williams & Wilkins; 1995. 11 Bobath B. Adult Hemiplegia: Evaluation and Treatment. 2nd rev ed. London: Heinemann; 1978.

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Research Report

M.P.J. Huijbregts, PT, PhD, is Director, Quality, Risk, & Patient Safety, Baycrest Centre for Geriatric Care, Poslun’s Building, Room 414B, 3560 Bathurst St, Toronto, Ontario, Canada M6A 2E1, and Assistant Professor, Department of Physical Therapy, University of Toronto, Toronto, Ontario, Canada. Address all correspondence to Dr Huijbregts at: mhuijbregts@ baycrest.org. G.F. Teare, DVM, PhD, is Director, Quality Measurement and Analysis, Health Quality Council, Saskatoon, Saskatchewan, Canada. C. McCullough, PT, MEd, is Senior Physiotherapist, Baycrest Centre for Geriatric Care. T.M. Kay, PT, MHSc, is Chief of Health Disciplines, Sunnybrook Health Sciences Centre, Toronto. D. Streiner, PhD, is Director, Kunin Lunenfeld Applied Research Unit, Baycrest Centre for Geriatric Care. S.K.C. Wong, PT, MHS, is Professional Practice Leader, Physiotherapy, Baycrest Centre for Geriatric Care. S.E. McEwen, PT, MSc, is Doctoral Candidate, Graduate Department of Rehabilitation Science, University of Toronto. I. Otten, PT, BSc, is Physiotherapist, Specialized Geriatric Services, Sunnybrook Health Sciences Centre. [Huijbregts MPJ, Teare GF, McCullough C, et al. Standardization of the Continuing Care Activity Measure: a multicenter study to assess reliability, validity, and ability to measure change. Phys Ther. 2009; 89:546 –555.] © 2009 American Physical Therapy Association

Standardization of the Continuing Care Activity Measure: A Multicenter Study to Assess Reliability, Validity, and Ability to Measure Change Maria P.J. Huijbregts, Gary F. Teare, Carolyn McCullough, Theresa M. Kay, David Streiner, Steve K.C. Wong, Sara E. McEwen, Ingrid Otten

Background. There is a lack of standardized mobility measures specific to the long-term care (LTC) population. Therefore, the Continuing Care Activity Measure (CCAM) was developed.

Objective. This study determined levels of reliability, validity for clinical utilization, and sensitivity to change of this measure.

Design. This was a prospective longitudinal cohort study among elderly people with primarily physical or medical impairments who were residing in LTC institutions that provide nursing home and more-complex care, with access to physical therapy services. Method. The CCAM, the Clinical Outcome Variables Scale (COVS), the Social Engagement Scale (SES) of the Resident Assessment Instrument—Minimum Data Set (RAI-MDS) 2.0 instrument, and the Resource Utilization Groups, version 3, (RUG-III) were administered by clinical and research physical therapists, with timing dictated by the study purpose. Results. The participants were 136 residents of LTC institutions and 21 physical therapists. The CCAM interrater reliability (intraclass correlation coefficient [ICC]) was .97 (95% confidence interval⫽.91–1.00), and test-retest reliability (ICC) over a period of 1 week was .99 (95% confidence interval⫽.93–1.00). Over 6 months, the absolute change in total score was 5.88 for the CCAM and 4.26 for the COVS; the CCAM was 28% more responsive across all participants (n⫽105) and 68% more responsive for those scoring in the lower half (n⫽49). The minimal detectable difference of the CCAM was 8.6 across all participants. The CCAM correlated with the COVS, nursing care hours inferred from the RUG-III, and the SES. Limitations. Some participants were lost to follow-up. Conclusions. The CCAM is a reliable and valid tool to measure gross motor function and physical mobility for elderly people in LTC institutions. It discriminates among functional levels, measures individual functional change, and can contribute to clinical decision making.

Post a Rapid Response or find The Bottom Line: www.ptjournal.org 546

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Validity and Reliability of the Continuing Care Activity Measure

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hysical functioning is an important component of quality of life for elderly people because it affects their sense of autonomy, social engagement, and overall sense of well-being.1 This finding was confirmed in a 1998 study by Fox and Gooding,2 who found that physical mobility made the largest contribution to physical and social wellbeing. A 1987 study by Thorne et al3 confirmed the assumption that mobility is a social resource allowing for increased reciprocity and balance in relationships. In addition, long-term care (LTC) financial costs are significantly affected by restrictions in physical mobility, with transferring and walking ability being important predictors of LTC nursing care hours.4,5 Therapeutic interventions to promote and maintain functioning may be important to quality of life for clients receiving LTC and may reduce nursing time requirements, which account for 80% of the costs of nursing care in this population.6 However, physical therapy services in LTC settings often are limited and may occur only in response to acute events. In order to assess the value of ongoing therapy, rigorous scientific intervention studies are needed. Even though there are a variety of existing and proposed therapeutic approaches in this population, the ability to scientifically evaluate them

Available With This Article at www.ptjournal.org • eAppendix Continuing Care Activity Measures (CCAM) Scoring Sheet and Short Key • Audio Abstracts Podcast This article was published ahead of print on April 9, 2009, at www.ptjournal.org.

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is hampered by the lack of appropriate standardized outcome measures.7 The Clinical Outcome Variables Scale (COVS)8 is used by some LTC organizations to assess physical functioning because the functional domains are relevant, but this measure has not been standardized for use in this population.9 The COVS is a measure of gross motor function and mobility and has items in 3 different domains: gross motor function (6 items), mobility (5 items), and upper-extremity function (2 items). In rehabilitation populations, the COVS has demonstrated good interrater reliability (IRR) and test-retest reliability (TRR), as well as sensitivity to change.8,9 In a recent review of the literature, we examined a number of commonly used mobility measurement instruments.8,10 –20 Only the Nursing Home Physical Performance Test (NHPPT)18 and the Continuing Care Activity Measure (CCAM) were specifically developed for elderly people residing in LTC institutions. All other measures have limited application for this population because the specific items tested and the grading of the performance assume a level of physical functioning and changes in physical functioning that are unattainable for most LTC residents. Even though the NHPPT appears relevant, applicability for the most-dependent clients in LTC and important psychometric properties have not been established. Therefore, the CCAM was developed at Baycrest Centre for Geriatric Care (Toronto, Ontario, Canada) as a measure of gross motor functioning and mobility that is able to measure change, discriminate among different levels of functioning, and assist in care planning and appropriate targeting of intervention in the LTC population. The Appendix provides the CCAM measure items (eAppendix showing the CCAM scoring sheet and short key is available at www.ptjournal.org).

Individual items on the CCAM were generated through discussions with clients and family members, physical therapists, occupational therapists, and nurses. These participants also contributed to item reduction. A feasibility trial utilizing physical therapists at different organizations was conducted. This process established content validity of the measure and resulted in a 17-item measure, comprised of 3 domains: gross motor function (12 items), mobility (3 items), and upper-extremity function (2 items). Item homogeneity testing revealed that 1 item (car transfers) did not provide additional information and, therefore, was removed from the measure. The final CCAM (Appendix) has 16 items.21 Initial pilot testing of the reliability, validity, and responsiveness of the measure was promising,10,21 leading to the current definitive study. We hypothesized that the CCAM would be a reliable and valid measure of gross motor function and physical mobility in the LTC population. This hypothesis was tested through 5 objectives: 1. To measure IRR; 2. To measure TRR; 3. To determine concurrent validity with the COVS; 4. To address construct validity by examining relationships between the CCAM and average daily nursing staff minutes and social engagement; and 5. To measure the responsiveness of the CCAM. To address the first and second objectives, and conclude that the measure is reliable, we were expecting high indicators of reliability,22 based on the findings from our earlier pilot study.10 The criterion was set so that

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Validity and Reliability of the Continuing Care Activity Measure Table 1. Study Designa Time 1

Time 2

Time 3

Clinical Therapist

Research Therapist

Staff

Research Therapist

Clinical Therapist

Research Therapist

Staff

CCAM

CCAM COVS

MDS

CCAM COVS

Treatment record

CCAM COVS

MDS

a Time 1⫽baseline assessment, time 2⫽time 1 ⫹ 1 week, time 3⫽time 1 ⫹ 6 months, CCAM⫽Continuing Care Activity Measure, COVS⫽Clinical Outcome Variables Scale, MDS⫽Minimum Data Set.

the point estimate of the intraclass correlation coefficient (ICC) would be at least .80, with a lower bound of ⱖ.70 for the confidence interval (CI) for the measure as a whole. The third objective was to determine concurrent validity with the COVS. The COVS was chosen as the measure to address concurrent validity because it is in general use by physical therapists in Canada, is reliable and sensitive to change in a general rehabilitation population, and has relevant functional mobility domains for LTC. We hypothesized that the CCAM would have a moderate correlation22 with the COVS.10,21 The fourth objective, construct validity, was verified by examining 2 relationships: (1) the relationship between CCAM total score and the average daily nursing staff minutes, as measured by the Resident Assessment Instrument— Minimum Data Set (RAI-MDS),5 and (2) the relationship between the CCAM total score and the RAI-MDS Social Engagement Scale (SES) score. The SES is a measure of the capacity to respond to social overtures from others and to initiate meaningful social involvement.23 We expected low22 Pearson correlations (r) between the CCAM score and staff time minutes, according to the Resource Utilization Groups, version 3, (RUG-III) resident classification system,4,5 and between the CCAM score and RAI-MDS SES score.2,3,23 To meet the final objective, measuring the responsiveness of the CCAM, the efficiency of the CCAM in measuring change over time and the relative efficiency of the CCAM compared with the COVS in measuring change were calculated. No a priori 548

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criterion for determined.

responsiveness

was

Method Study Design This was a cohort study with crosssectional and longitudinal components. Participants were recruited from 4 Toronto organizations providing LTC services corresponding to nursing home, complex continuing care (CCC), and low-tolerance, longduration (LTLD) rehabilitation levels of care. Residents in these organizations have a range of abilities and different potential for further functional improvements. Nursing home residents generally have higher levels of functioning, CCC residents are more dependent in functional ability, and the functioning of LTLD residents varies across a wide spectrum, but they are identified as having more potential for recovery and, therefore, are expected to have larger changes on functional ability measures such as the COVS and the CCAM. The study design is summarized in Table 1. To assess IRR, the CCAM was administered twice at time 1 (baseline assessment), with a maximum of 72 hours between the 2 assessments, once by a research therapist and once by the clinical therapist. The clinical therapist was the attending physical therapist at each organization responsible for the clinical care of the study participant. The research therapists were hired for the study. To examine TRR, the CCAM was administered a second time by the research therapist at time 2 (1 week after time 1). To

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determine concurrent validity with the COVS, the research therapist administered the COVS at time 1. To determine the relationship between the CCAM and the expected average daily nursing staff minutes and between the CCAM and social engagement, relevant Minimum Data Set (MDS) data were collected at time 1 by center staff following mandated, standardized processes in place in each organization. To determine the efficiency of the CCAM in measuring change and the relative efficiency of the CCAM compared with the COVS, both the CCAM and the COVS were administered at time 1, time 2, and time 3 (6 months after time 1). Approval for the study was obtained from the research ethics board at each participating organization, and all participants or their substitute decision maker provided informed consent. Study Participants Recruitment strategies attempted to ensure that the results of the study would be generalizable across this heterogeneous population for different levels of care. Newly admitted clients and existing clients at each of the 4 centers were invited to participate. Study clients were included if they were 19 years of age or older and admitted to LTC primarily for physical or medical reasons. Clients were excluded if they were deemed to be medically unstable by the attending physician or if the primary diagnosis was a cognitive or psychiatric disorder.

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Validity and Reliability of the Continuing Care Activity Measure Sample size calculation was based on the sample size requirement for the reliability component of the study. In this study, the power was set at .80, with ␣⫽.05. A sample size of 117 is required to estimate an ICC of .80 with precision of ⫾.10.24 Therefore, we planned to conduct the study on 130 clients to account for a potential loss to follow-up of approximately 10%. A sample size of 20 would allow for the detection of a correlation of .60 (objective 3), a sample size of 47 would allow for a correlation of ⫺.40 (for relationship between CCAM total score and average daily nursing staff minutes in objective 4), and a sample size of 85 would allow for a correlation of .30 (for relationship between CCAM total score and RAI-MDS SES score in objective 4). Sample size for the responsiveness component was 105. The planned sample size, therefore, was adequate to meet all study objectives. Approximately 45 subjects were recruited at each institution. As indicated, this study involved clinical and research physical therapists. The clinical therapists administered both the CCAM as per usual clinical practice; the research therapists administered both the CCAM and the COVS. Both clinical and research therapists were required to be licensed to practice in Ontario, Canada, and have a minimum of 1 year of experience working in LTC. All therapists attended a 4-hour CCAM training workshop that included the use of a training video, clinical application, and scoring. The research therapists received additional, similar training on the COVS. All therapist training sessions were carried out by the same instructor. Assessments The following demographic and clinical variables were assessed: age, sex, Minimum Data Set Activities of Daily Living (MDS-ADL) SelfPerformance Hierarchy, MDS CogJune 2009

nitive Performance Scale, MDS receptive communication, stability of health condition as measured with the MDS Changes in Health, EndStage Disease, and Signs and Symptoms Scale (MDS-CHESS), and weekly minutes of occupational therapy and physical therapy. In addition, the most common disease types of the study participants were noted. The MDS-ADL Self-Performance Hierarchy is based on 7 items pertaining to activities of daily living (ADL) from the RAI-MDS 2.0 instrument. These items (dressing, personal hygiene, toilet use, locomotion, transfers, bed mobility, and eating) cover a spectrum of early-, mid-, and lateloss ADL, and taken together they are able to accurately predict the functional level on other ADL items. The MDS-ADL Self-Performance Hierarchy is a 7-level scale, ranging from 0 (independent) to 6 (total dependence). Scores of 3 and 4 indicate extensive assistance is required to perform ADL.25 The MDS Cognitive Performance Scale is a widely used measure of cognitive impairment. It has 7 levels, ranging from 0 (no impairment) to 6 (very severe impairment). The measure correlates strongly with the Mini-Mental State Examination.26 Minimum Data Set receptive communication is measured using a single item on the MDS, “Able to understand others,” which measures a person’s ability to receive, process, and understand written or spoken language. It is rated from 0 (always) to 3 (rarely or never). The MDS-CHESS is an index of health instability that is strongly predictive of time to death and is highly correlated with other measures of health instability (eg, frequency of physician visits; oxygen use).27 The index ranges from 0 (stable) to 5 (highly unstable). Scores higher than 3 generally indicate considerable instability of the patient’s condition, and scores at this level are frequent among patients receiving

palliative care and other patients in short-stay, end-of-life CCC settings. To develop the RUG-III resident classification system, the US Centers for Medicaid and Medicare Services (CMS) conducted studies in 1990, 1995, and 1997. More than 350 nursing homes in 12 states participated to measure the staff time involved in provision of care for more than 10,000 nursing home residents.4,28 The version of RUG-III used in Ontario, Canada, classifies nursing home residents into 44 groupings of functional, clinical, and service characteristics, according to the average amount of cost-weighted staff time used to provide care for the CMSstudied residents in each of the groupings. The MDS data were used to classify study participants into RUG-III groups, and data from the CMS RUG-III studies were used to assign nursing staff times to each participant based on his or her RUG-III group.29 Data Analysis To determine IRR and TRR, analysis of variance (ANOVA) tables were generated. For both IRR and TRR, ICCs (2,1)30 and their respective 95% CIs were calculated. To further determine reliability of the CCAM total score, the minimal detectable difference (MDD) was calculated using the standard error of the difference.31,32 To measure concurrent validity with the COVS, the Pearson correlation (r) between scores on the CCAM and COVS was calculated for subscale scores and total scores. To examine construct validity, the Pearson correlation was calculated between the CCAM score and the average daily nursing staff minutes associated with participants’ RUGIII case-mix categories and between the CCAM score and the RAI-MDS SES score. To determine sensitivity to change, the efficiency of the CCAM in measuring change over time and the rel-

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Validity and Reliability of the Continuing Care Activity Measure ative efficiency of the CCAM compared with the COVS in measuring change were calculated. Because there was no a priori construct of change in response to therapy for this population, the responsiveness of the CCAM was measured based on the reasonable assumption (construct of change) that the physical function of the participants receiving LTC services, regardless of therapy status, would change more in the 6 months between time 2 and time 3 than during the 1-week interval between time 1 and time 2. The Guyatt Responsiveness Index33 was used to measure the ratio of observed change between time 2 and time 3 to the standard deviation of the change scores between time 1 and time 2.34 Role of the Funding Source This study was financially supported by the Drummond Foundation, Montreal, Quebec, Canada. The funding source did not in any way influence the design, results, or reporting of this study.

Results Four Toronto-based organizations providing LTC services participated: (1) Baycrest Centre for Geriatric Care, with 201 CCC beds and approximately 35 new admissions per year; (2) the Toronto Rehabilitation Institute, with 266 CCC beds and approximately 58 new admissions per year; (3) Providence Healthcare, with 286 CCC beds, 30 LTLD beds, and approximately 60 new admissions per year; and (4) Sunnybrook Health Sciences Centre, with 190 nursing home beds and approximately 110 new admissions per year, 256 CCC beds and about 190 new admissions per year, and 24 LTLD beds and approximately 40 new admissions per year. Long-term care services in other jurisdictions may provide similar levels of care as described above but in varying settings such as skilled nursing facilities. 550

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In total, 21 physical therapists participated in the study. Four physical therapists functioned as research therapists and 19 as clinical therapists; 2 of the therapists had both a clinical role and a research role. The therapists’ level of physical therapy education ranged from diploma to master’s degree. The therapists’ number of years since graduation ranged from 1 to 41 years, and most of the therapists had worked in a variety of clinical areas. Initially, 141 study participants were recruited. Eight of these participants had incomplete data at time 1, resulting in 136 participants in the IRR component of the study and in 133 participants for the level of care subanalysis for the MDD. Of the 141 study participants, 6 had missing CCAM data either at time 1 (3 subjects) or at time 2 (3 subjects) for the TRR component of the study, resulting in 135 participants for this component. Of the 138 participants with valid time 1 data, 33 were lost to follow-up due to death or discharge, resulting in 105 participants for the calculation of the responsiveness index. The Figure provides an explanation of the different study analysis samples. Table 2 provides a summary demographic description of the study participants in the IRR component of the study at time 1 (n⫽136) and shows that the participants typically had mild to moderate levels of cognitive impairment and moderate to moderate-severe limitations in ADL. Only about 10% had severe receptive communication impairment, and a similar percentage had more than mild-moderate instability of their health condition. On average, the study participants received nearly 50 minutes of occupational therapy and nearly 80 minutes of physical therapy in the 7 days of observations covered by the MDS assessment. Table 3 provides the most common di-

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agnoses among the study participants. There were no significant differences between the total study sample and the group participating at time 3. The time 3 group appeared to be a “longer stay” group, but this was not statistically significant. Reliability Interrater reliability (IRR) for CCAM total score was .97 (95% CI⫽.91– 1.00). The average IRR coefficient for the 16 items in the CCAM was .93; only one item had an IRR coefficient less than .83 (95% CI⫽.76 – .89). Test-retest reliability over a period of 1 week for CCAM total score was .99 (95% CI⫽.93–1.00); all but one of the items on the CCAM had TRR coefficients greater than .91. Very similar TRR results were seen for the COVS. The MDD for the CCAM total score was 8.6 points, when considering the entire, heterogeneous study sample (n⫽136). However, when measured within more homogeneous subsamples (nursing home, CCC, and LTLD), the MDD was much smaller. The least homogenous subsample was the CCC group, among which the standard deviation in CCAM total score at time 1 (treating therapist assessment) was 27.1 points. This group had an MDD of 7.5 points. Both the nursing home and LTLD groups were more homogenous than the CCC group (standard deviations of the time 1 score of 12.1 and 18.5 points, respectively); the MDD was 3.3 points for the nursing home group and 5.1 points for the LTLD group. Validity The Pearson correlation coefficient between the CCAM total score and the COVS total score was very high22 (r⫽.96, 95% CI⫽.91–1.00, P⬍.001) for the measure as a whole. The Pearson correlation coefficient between the CCAM total score and RUG-III grouping associated with total daily June 2009

Validity and Reliability of the Continuing Care Activity Measure

Figure. Study analysis samples (boldfaced blue numbers indicate sample used in analyses). CCAM⫽Continuing Care Activity Measure, COVS⫽Clinical Outcomes Variables Scale, IRR⫽interrater reliability, TRR⫽test-retest reliability, CT⫽clinical therapist, RT⫽research therapist, LOC⫽level of care, T1⫽time 1 (baseline assessment), T2⫽time 2 (time 1⫹1 week).

nursing minutes was high22 (r⫽ ⫺.71, 95% CI⫽.59 –.83, P⬍.01), indicating that required nursing time decreased with higher client scores on the CCAM, representing higher function. The Pearson correlation coefficient between the CCAM total score and RAI-MDS SES score was low22 (r⫽.30, 95% CI⫽.14 –.46, P⬍.01). The study hypotheses for both concurrent and construct validity were higher than expected for the relationship between the CCAM June 2009

and the COVS and between the CCAM and the RUG-III grouping and accepted for the relationship between the CCAM and the RAI-MDS SES. Responsiveness Average absolute change on the CCAM total score over 6 months was 5.88 units (out of a possible range of 96 units) compared with 4.26 units on the COVS (out of a possible range of 78 units). Among all clients with

complete CCAM and COVS information at times 2 and 3 (n⫽105), the CCAM was 28% more responsive. The Guyatt Responsiveness Index33 was 2.03 for the CCAM versus 1.61 for the COVS. The CCAM was 68% more responsive than the COVS for participants who scored in the lower half on both tools at their first assessment (n⫽49), representing lower physical functioning.

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Validity and Reliability of the Continuing Care Activity Measure Table 2. Demographics of Continuing Care Activity Measure (CCAM) Study Sample at Time 1 (n⫽136)a Demographics

Mean

SD

Median

77.5

12.8

80.0

Age (y)

Percentage

Sex Male

40

Female

60

MDS-ADL Self-Performance Hierarchy (range⫽0–6, where 0⫽intact, 6⫽severe impairment)

3.8

1.9

4.0

MDS-Cognitive Performance Scale (range⫽0–6, where 0⫽intact, 6⫽severe impairment)

2.6

2.1

2.0

MDS-receptive communication (able to understand others: sometimes, usually, or always)

89

Health condition relatively stable; MDS-CHESS score ⬍3 (range⫽0–5, where 0⫽stable, 5⫽highly unstable)

90

Occupational therapy (minutes per week)

47.0

58.0

30.0

Physical therapy (minutes per week)

77.2

56.0

60.0

CCAM total score (range⫽16–112, where 16⫽lowest functional level, 112⫽highest functional level)

68.2

31.3

74.0

47.9

27.2

36.5

101.1

12.3

105.0

84.9

18.5

86.5

CCC group (n⫽69) Nusing home group (n⫽17) LTLD group (n⫽47) a

MDS⫽Minimum Data Set; MDS-ADL⫽Minimum Data Set Activities of Daily Living; MDS-CHESS⫽Minimum Data Set Changes in Health, End-Stage Disease, and Signs and Symptoms Scale; CCC⫽complex continuing care; LTLD⫽low-tolerance, long-duration rehabilitation.

Table 3. Common Diagnoses (%) Among Participants by Level of Carea Cardiovascularb

Dementiac

Stroke

COPD

TBI

All

37

29

47

8

4

CCC

32

36

42

7

7

LTC

47

29

47

24

0

LTLD

40

19

53

4

0

Level of Care

a

CCC⫽complex continuing care group; LTC⫽long-term care group; LTLD⫽low-tolerance, long-duration rehabilitation group; COPD⫽chronic obstructive pulmonary disease; TBI⫽traumatic brain injury. b Includes atherosclerotic disease, congestive heart failure, and other cardiovascular diseases. c Includes Alzheimer disease and non-Alzheimer dementias.

Discussion The CCAM is a measure of gross motor function and mobility in the LTC population. The population-specific items and grading scale were developed to ensure that the items were meaningful in this population and able to capture clients at different levels of physical functioning. The results indicate that the CCAM has high levels of IRR and TRR. This means it can be used with confidence in the clinical setting: different therapists will provide similar 552

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scoring on individuals, and scoring on the measure will be stable during a period of no change. Moreover, the measure’s ability to capture change over time is highly relevant in the clinical setting. It is important to demonstrate benefits when they occur, but for individuals with progressive neurological conditions, it also is important to be able to demonstrate when their level of functioning is maintained or when there is a slowdown in expected levels of deterioration. Moreland and colleagues7

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contended that a mobility measure that is sensitive to change in the LTC population would be helpful to guide clinical intervention, but also to demonstrate relative benefits of different physical therapy approaches in this population. The current study indicates that the CCAM may be able to support such studies from an outcome measurement perspective and provides estimates from which sample sizes can be calculated by researchers.

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Validity and Reliability of the Continuing Care Activity Measure From a clinical perspective, the availability of the MDD will be helpful in determining when meaningful change occurs. For clinicians, it is important to realize that changes of less than 8.7 points (the MDD) cannot be relied on as true changes— they may be just measurement error. In organizations using the CCAM, physical therapist practice typically has been to administer the measure on an annual basis for individuals receiving physical therapy. This may not provide a good understanding of the patterns of change occurring in this population. However, morefrequent assessments with the CCAM may lead to a better understanding of the patterns of change for individuals in more-advanced stages of different degenerative conditions and for those who initially have complex or subacute conditions and go on to make significant mobility improvements. Being able to target these changes will allow for greater understanding of when the frequency or intensity of interventions should be altered. In addition, the study has shown that there is a strong relationship between mobility as measured by the CCAM and required nursing care time. Moreover, there is a modest, but significant, relationship between scoring on the CCAM and an individual’s social engagement as measured by the MDS. These findings provide an additional incentive to focus on gross motor functioning and mobility in this population, as optimizing function may reduce costs associated with nursing time and contribute to well-being. It also may provide further incentives to develop physical therapy interventions and management approaches that will optimize clients’ physical functioning. Ideally, the findings of this study could be compared with those of similar studies for consistency. HowJune 2009

ever, no other studies could be found for comparison.

This article was received September 18, 2008, and was accepted February 4, 2009. DOI: 10.2522/ptj.20080287

Conclusions The CCAM has been found to be a reliable and valid measure in the LTC population, both from a clinical perspective and from a research perspective. Clinicians also can use this measure to determine mobility changes in LTC residents. The next step will be to administer the CCAM as an outcome measure in effectiveness studies. This will further enhance the body of knowledge pertaining to mobility interventions and their impact on burden of care and resource allocation in the increasingly frail and dependent LTC population. Dr Huijbregts, Dr Teare, Ms Kay, Dr Streiner, Mr Wong, and Ms Otten provided concept/ idea/research design. Dr Huijbregts, Dr Teare, Ms McCullough, and Dr Streiner provided writing. Dr Huijbregts, Dr Teare, Ms McCullough, Mr Wong, Ms McEwen, and Ms Otten provided data collection. Dr Huijbregts and Dr Teare provided data analysis and fund procurement. Dr Huijbregts, Dr Teare, and Ms McCullough provided project management. Ms McCullough and Ms Otten provided subjects. Dr Huijbregts, Dr Teare, Ms Kay, and Ms Otten provided facilities/ equipment. Dr Huijbregts, Dr Teare, Mr Wong, and Ms McEwen provided institutional liaisons. Ms Otten provided clerical support. Dr Teare, Ms McCullough, Ms Kay, Dr Streiner, Mr Wong, and Ms McEwen provided consultation (including review of manuscript before submission). The authors thank Rebecca Gruber, Anne Levin, and Julie Moreland for their constructive feedback and support during the preparation of the manuscript. This research, in part, was presented at the 14th International Congress of the World Confederation for Physical Therapy; June 7– 12, 2003; Barcelona, Spain. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are affiliated. This study was supported by the Drummond Foundation, Montreal, Quebec, Canada.

References 1 Arnold BS. The measurement of quality of life in the frail elderly. In: Birren JE, Lubben JE, Rowe JC, Deutchman DE, eds. The Concept and Measurement of Quality of Life in the Frail Elderly. Toronto, Ontario, Canada: Academic Press Inc; 1991:50 –73. 2 Fox M, Gooding B. Physical mobility and social integration: their relationship to the well-being of older Canadians. Can J Aging. 1998;17:372–383. 3 Thorne S, Griffin C, Adlersberg M. How is your health? Gerontion. 1987;1(5):14 –18. 4 Fries BE, Cooney L. Resource utilisation groups: a patient classification system for long-term care. Med Care. 1985;23: 110 –122. 5 Fries BE, Schneider DP, Foley WJ, et al. Refining a case-mix measure for nursing homes: Resource Utilisation Groups (RUG: III). Med Care. 1994;32:668 – 685. 6 Mulrow CD, Gerety MB, Kanten D, et al. A randomised trial of physical rehabilitation to very frail nursing home residents. JAMA. 1994;271:519 –524. 7 Moreland J, DePaul V, Fournel D. Practice patterns for the physiotherapy management of clients with maintenance goals: a Canadian survey. Physiother Can. 1997; 49:222–229. 8 Seaby L, Torrance G. Reliability of a physiotherapy functional assessment used in a rehabilitation setting. Physiother Can. 1989;41:264 –271. 9 Finch E, Brooks D, Stratford PW, Mayo N. Physical Rehabilitation Outcome Measures. 2nd ed. Hamilton, Ontario, Canada: BC Decker Inc; 2002. 10 Huijbregts M. The CCAM: a gross motor function and mobility outcome measure for the long-term care client. Can J Rehabil. 1997;40:18 –19. 11 Smith R. Validation and reliability of the elderly mobility scale. Physiotherapy. 1994;80:74 –77. 12 Gowland C, Stratford PW, Ward M, et al. Measuring physical impairment and disability with the Chedoke-McMaster Stroke Assessment. Stroke. 1993;24:58 – 63. 13 Berg K, Wood-Dauphine´e SL, Williams J. Measuring balance in the elderly: preliminary development of an instrument. Physiother Can. 1989. 14 Duncan PW, Weiner DK, Chandler J, Studenski S. Functional Reach: a new clinical measure of balance. J Gerontol. 1990; 45:M192–M197. 15 Butland RJA, Pang J, Gross ER, et al. Two-, six-, and 12-minute walking tests in respiratory disease. Br Med J. 1982;284:607– 608. 16 MacKnight C, Rockwood K. Hierarchical assessment of balance and mobility. Age Ageing. 1995;24:126 –130.

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Validity and Reliability of the Continuing Care Activity Measure 17 Podsiadlo D, Richardson S. The timed “Up and Go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39:142–145. 18 Binder EF, Miller JP, Ball LJ. Development of a test of physical performance for the nursing home setting. Gerontologist. 2001; 41:671– 679. 19 Creel GL, Light KE, Thigpen MT. Concurrent and construct validity of scores on the Timed Movement Battery. Phys Ther. 2001;81:789 –798. 20 Winograd CH, Lemsky CM, Nevitt MC, et al. Development of a physical performance and mobility examination. J Am Geriatr Soc. 1994;42:743–749. 21 Huijbregts MPJ, Kay TM. The Continuing Care Disability Measure (CCDM): a gross motor function and mobility outcome measure for continuing care clients. In: Proceedings of the 12th International Congress of the World Confederation for Physical Therapy; June 25–30, 1995; Washington, DC. 1995:654.

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22 Munro H. Statistical Methods for Health Care Research. Philadelphia, PA: JB Lippincott Co; 2001. 23 Mor V, Branco K, Fleishman J, et al. The structure of social engagement among nursing home residents. J Gerontol B Psychol Sci Soc Sci. 1995;50:P1–P8. 24 Walter SD, Eliasziw M, Donner A. Sample size and optimal design for reliability studies. Stat Med. 1998;17:101–110. 25 Morris JN, Fries BE, Morris SA. Scaling ADLs within the MDS. J Gerontol A Biol Sci Med Sci. 1999;54:M546 –M553. 26 Morris JN, Fries BE, Mehr DR, et al. MDS Cognitive Performance Scale. J Gerontol. 1994;49:M174 –M182. 27 Hirdes JP, Frijters DH, Teare G. The MDSCHESS scale: a new measure to predict mortality in the institutionalised elderly. J Am Geriatr Soc. 2003;51:96 –100. 28 Medicare program: prospective payment system and consolidated billing for skilled nursing facilities, final rule. Federal Register. 1998;63FR(91):26251–26316.

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29 Centers for Medicare and Medicaid Services. RUG Refinement. 2007. Available at: http://www.cms.hhs.gov/ SNFPPS/ 09_RUG Refinement.asp. 30 Shrout PE, Fleiss JL. Intra class correlation coefficients: uses in assessing rater reliability. Psychol Bull. 1979;88:420 – 428. 31 Ottenbacher KJ, Johnson MB, Hojem M. The significance of clinical change and clinical change of significance: issues and methods. Am J Occup Ther. 1988;42:156 –163. 32 Haley SM, Fragala-Pinkham MA. Interpreting change scores of tests and measures used in physical therapy. Phys Ther. 2006; 86:735–743. 33 Guyatt G, Walter S, Norman G. Measuring change over time: assessing the usefulness of evaluative instruments. J Chronic Dis. 1987;40:171–178. 34 Stratford PW, Binkley JM, Riddle DL. Health status measures: strategies and analytic methods for assessing change scores. Phys Ther. 1996;76:1109 –1123.

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Validity and Reliability of the Continuing Care Activity Measure Appendix. Continuing Care Activity Measure (CCAM) Items

1. Rolling from supine to side lying (right) 2. Rolling from supine to side lying (left) 3. Moving up in bed (reposition) 4. Lying to sitting 5. Sitting to lying 6. Sitting at the bedside (feet supported) 7. Sitting ability (seating needs) 8. Reposition in wheelchair/lounge chair 9. Supported sitting duration 10. Sitting to standing 11. Transfer (bed/wheelchair) 12. Ambulation 13. Ambulation distance (indoors) 14. Wheelchair mobility (indoors) 15. Upper-extremity function (right) 16. Upper-extremity function (left) Total score: 16–112

Operational Definitions Independent: The client does not require assistance or the presence of another person. Supervision: The client requires another person in the room for safety or for verbal cueing. Assistance: One or more people are providing physical help to the client. • Minimal assistance: Intermittent guidance, guiding throughout, or initiating a movement or finalizing a position. Client provides ⱖ75% of the effort. • Moderate assistance: The client provides ⱖ50% of the effort. • Maximal assistance: The client provides ⬍50% of the effort. • Total assistance: The client does not contribute to the movement or requires 2 people to complete the movement.

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Research Report

N.M. Salbach, PT, PhD, is Assistant Professor and Heart and Stroke Foundation of Ontario Clinician Scientist, Department of Physical Therapy, Faculty of Medicine, University of Toronto, 160-500 University Ave, Toronto, Ontario, M5G 1V7 Canada. Address all correspondence to Dr Salbach at: [email protected]. P. Veinot, MHSc, is Research Consultant, Toronto, Ontario, Canada. S. Rappolt, OT, PhD, is Associate Professor, Department of Occupational Science and Occupational Therapy, Faculty of Medicine, University of Toronto. M. Bayley, MD, FRCPC, is Associate Professor, Division of Psychiatry, Toronto Rehabilitation Institute, and Department of Medicine, Faculty of Medicine, University of Toronto. D. Burnett, PT, PhD, is Research Coordinator, Interprofessional Rehabilitation University Clinic in Primary Health Care, University of Ottawa, Ottawa, Ontario, Canada. M. Judd, PT, MSc, is Senior Program Officer, Canadian Health Services Research Foundation, Ottawa, Ontario, Canada. S.B. Jaglal, PhD, is Associate Professor, Department of Physical Therapy, Faculty of Medicine, University of Toronto. [Salbach NM, Veinot P, Rappolt S, et al. Physical therapists’ experiences updating the clinical management of walking rehabilitation after stroke: a qualitative study. Phys Ther. 2009;89:556 –568.]

Physical Therapists’ Experiences Updating the Clinical Management of Walking Rehabilitation After Stroke: A Qualitative Study Nancy M. Salbach, Paula Veinot, Susan Rappolt, Mark Bayley, Dawn Burnett, Maria Judd, Susan B. Jaglal

Background. Little is known about physical therapists’ experiences using research evidence to improve the delivery of stroke rehabilitation.

Objectives. The purpose of this study was to explore how physical therapists use research evidence to update the clinical management of walking rehabilitation after stroke. Specific objectives were to identify physical therapists’ clinical questions related to walking rehabilitation, sources of information sought to address these questions, and factors influencing the incorporation of research evidence into practice. Design and Methods. Two authors conducted in-depth telephone interviews with 23 physical therapists who treat people with stroke and who had participated in a previous survey on evidence-based practice. Data were analyzed with a constant comparative approach to identify emerging themes.

Results. Therapists commonly raised questions about the selection of treatments or outcome measures. Therapists relied foremost on peers for information because of their availability, ease of access, and minimal cost. Participants sought information from research literature themselves or with the help of librarians or students. Research syntheses (eg, systematic reviews) enabled access to a body of research. Older therapists described insufficient computer and search skills. Most participants considered appraisal and application of research findings challenging and identified insufficient time and peer isolation as organizational barriers to the use of research. Conclusions. Physical therapists require efficient access to research syntheses primarily to inform the measurement and treatment of walking limitation after stroke. Continuing education is needed to enhance skills in appraising research findings and applying them to practice. Older therapists require additional training to develop computer and search skills. Peer networks and student internships may optimize the exchange of new knowledge for therapists working in isolation.

© 2009 American Physical Therapy Association Post a Rapid Response or find The Bottom Line: www.ptjournal.org 556

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Updating Clinical Practice for Patients With Stroke

E

vidence-based practice (EBP) is defined as a culture in which clinicians naturally and consistently consider evidence in every aspect of practice.1 To implement EBP, practitioners find the best available evidence to address clinical questions; critically appraise the evidence for validity, impact, and applicability; integrate clinical expertise and the patient’s needs and preferences; decide on an appropriate course of action; and evaluate the effect of practice.2– 6 Although physical therapists indicate that the application of EBP is necessary and improves the quality of patient care,7,8 many do not identify research evidence as a primary source of information for use in clinical practice.8 –13 Numerous studies have been conducted to enhance understanding of the challenges that physical therapists face when attempting to access research findings and integrate those findings into clinical practice.7,8,11,14 –16 Berwick17 broadly classified these challenges as characteristics of the practitioner, the organization, and the research (ie, the innovation). At the practitioner level, inadequate education in the principles of EBP and insufficient skill and self-efficacy in searching research literature, appraising research findings, and applying those findings to clinical practice represent substantial barriers to EBP.7,8,14,15 Obser-

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 April 16, 2009, at www.ptjournal.org.

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vations that physical therapists with low self-efficacy for implementing EBP report lower levels of use of research in clinical decision making than physical therapists with high self-efficacy indicate that perceptions of ability may represent a factor driving engagement in EBP activities.18 Factors that are related to the health care organization and that may restrict physical therapists’ engagement in EBP include lack of a mandate (ie, a written requirement) supporting EBP7 and failure to provide protected time to pursue EBP activities.7,8,14 Limited acceptance of new practices by peers and isolation from peers also may be important barriers to implementing new knowledge.12 In terms of perceptions of the available research, the second most prevalent barrier to EBP after lack of time, identified by one third of physical therapists in large surveys, is the lack of generalizability of research findings to their patient populations.7,8 Negative perceptions of research appear to dissuade its use in clinical practice.19 Research to date has been fundamental in providing estimates of the prevalence and, thus, the relative importance of specific barriers to EBP of physical therapy. It is difficult to address these barriers in the development of interventions designed to facilitate EBP, however, without an indepth understanding of physical therapists’ experiences and approaches to using research literature to address questions arising from clinical practice. Qualitative methods of data collection that are based on direct consultation with physical therapists, such as the conduct of focus groups or interviews, are well suited to achieving such understanding.20 Moreover, findings from research conducted among physicians indicate that interventions targeting specific aspects of care may be more

effective in improving EBP of physical therapy than interventions directed toward improvement in all aspects of service delivery.21 Physical therapy service delivery for people with stroke provides an ideal context for the study of EBP for several reasons. First, there is an extensive body of research literature to inform physical therapist practice. Comprehensive clinical practice guidelines22–24 and systematic reviews of stroke rehabilitation interventions and standardized assessment tools25,26 are available through electronic bibliographic databases and Web sites. Second, adherence to clinical practice recommendations in the postacute phase of rehabilitation has been associated with physical recovery and patient satisfaction after stroke,27,28 strengthening the rationale for promoting research use among physical therapists in this area of practice. Finally, stroke continues to be an important cause of death and disability in Canada,29 the United States, and across the world.30 The ability to walk is commonly affected, with as many as 60% to 80% of people losing the ability to walk independently immediately after stroke.31–35 Walking deficits often persist, limiting participation in community life36,37 and negatively affecting perceptions of health.38 Across the continuum of care, the physical therapist is the health care professional primarily responsible for the delivery of evidence-based walking rehabilitation to optimize the quality of physical therapy services and mobility outcomes in stroke rehabilitation.15,39 Although physical therapists’ methods of gathering information to inform the management of low back pain have been examined,12 approaches may vary, depending on the resources available for a particular area of practice specialization and clinical approach, particularly in neurological rehabili-

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Updating Clinical Practice for Patients With Stroke tation.19 No studies to date have investigated how physical therapists attempt to use research literature to address clinical questions related to walking rehabilitation after stroke. This research is essential to guide the development of clinically relevant interventions designed to facilitate the implementation of evidence-based walking rehabilitation and ultimately optimize the mobility outcomes of people with stroke. Thus, the purpose of this study was to explore how physical therapists use research evidence to update the clinical management of walking rehabilitation after stroke. Specific objectives were: (1) to identify physical therapists’ clinical questions related to walking rehabilitation after stroke, (2) to identify sources of information that physical therapists seek to address these clinical questions, and (3) to identify factors that enable or challenge physical therapists in incorporating research evidence into practice.

Method A qualitative descriptive approach20 was used to address the study objectives. We used 2 frameworks for design of the study and interpretation of the findings: the stepwise process of EBP2–5 and self-efficacy theory.40 The tenet from self-efficacy theory of primary interest was that perceptions of ability (ie, self-efficacy) to organize and execute a task, such as conducting a literature review, are expected to influence decisions to perform that task.40 Participants Physical therapists were considered eligible if they were registered with the College of Physiotherapists of Ontario (the provincial regulatory body), practicing clinically a minimum of 30 hours per week, and providing services to a minimum of 10 adults with stroke per year. These criteria were designed to capture

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therapists who would likely seek information about stroke management. Sampling and Recruitment A list of 109 physical therapists who had participated in a mailed survey on EBP in stroke management (conducted by the authors7) and who had provided signed permission to be contacted for future research was generated for recruitment. In the previous study, these therapists had rated their self-efficacy for implementing EBP (EBP self-efficacy) by using a new scale; this scale required the therapists to rate their level of confidence in performing 12 EBP activities, such as formulating a question to guide a literature search and conducting a search. The average of the item-level scores yielded a total score ranging from 0% to 100%. For the present study, we used a 2-step sampling approach. First, we randomly selected therapists from 3 subgroups, defined by low, moderate, and high summary ratings of EBP self-efficacy7 (low, 0%–50%; moderate, ⬍50%– 80%; high, ⬍80%–100%). Sampling in this manner was expected to yield a group of participants with diverse approaches to accessing research evidence to address clinical questions, given the observed associations between selfefficacy and research use among physical therapists.18 After 14 physical therapists had consented to participate, a purposive sampling approach was adopted to optimize diversity in EBP self-efficacy as well as practice setting because EBP resources (eg, Internet access) vary by practice setting.7 To recruit therapists, we mailed them an information letter and a consent form and attempted to contact them by telephone to screen them for eligibility. Eligible therapists who were interested in participating returned a completed consent form before participating in a telephone interview.

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Data Collection Two authors (N.M.S. and P.V.) conducted in-depth telephone interviews from July to October 2006. Interviewers were unfamiliar with participants. Participants were aware that the findings of this study would be used to develop resources or educational initiatives to facilitate appropriate integration of research findings into interventions for walking rehabilitation after stroke because this intention was described in the information letter and consent form. In an attempt to secure confidentiality of responses, some participants completed the telephone interview at home. Others completed the interview at work, either after hours or during a lunch break. We developed a semistructured interview guide that was pilot tested and revised on the basis of 2 practice interviews. Interviewers asked participants to describe a time when they had a question about a person’s walking deficit after stroke. If participants could not think of a question related to walking, then they were prompted to think about a question related to any aspect of stroke management that had previously arisen. Next, interviewers asked participants about their experiences accessing research literature and about the factors that either enabled or challenged them in accessing evidence (eg, “What did you find easy about that experience?” or “What did you find difficult about that experience?”). Interviewers posed clarifying questions to obtain sufficient details about approaches that participants described. Interviewers also sought participants’ feedback on ideas that study participants had described in earlier interviews in the present study. Finally, interviewers verified sociodemographic and practice information that had been collected in the previous survey7 with participants.

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Updating Clinical Practice for Patients With Stroke Interviews were audiotaped with the permission of participants and transcribed verbatim. Interviewers reviewed and edited the transcripts to ensure accuracy. Data collection continued until saturation of themes was achieved. Data Analysis Transcripts and field notes were entered into NVivo 7.* A constant comparative method of inquiry41 was used for data analysis with opencoding methods. Two authors (N.M.S. and P.V.) independently reviewed the transcripts, identified and named emerging concepts, and developed a coding scheme. The authors compared the coding of the first 10 transcripts and reached a consensus on how to code a particular unit of text. Subsequently, one author (P.V.) coded the remaining transcripts. The coding scheme evolved as data analysis progressed. Themes derived through synthesis and cross tabulations of open codes (axial coding) then were pieced together to identify common themes and issues across groups. Strategies for Ensuring Trustworthiness We used different strategies throughout the study to ensure methodological rigor. Interviewers asked probing and iterative questions to clarify responses and to examine inconsistencies and possible contradictions in self-reported descriptions of practice. Interviewers recorded field notes describing general impressions, a participant’s emotional state, or analytic reflections during and immediately after interviews. Field notes were included in the analysis. Interviewers compared transcripts of the first several interviews with audiotapes to verify the accuracy of transcription and reviewed and edited the transcripts to ensure accu* QSR International Pty Ltd, 651 Doncaster Rd, Doncaster, Victoria 3108, Australia.

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racy. Dual coding of the first 10 transcripts, peer debriefing with colleagues or experts knowledgeable about the topic, and the use of verbatim quotations support the quality of the data.42 Finally, we identified the conceptual frameworks, including the stepwise process of EBP2–5 and self-efficacy theory,40 which served as a basis for reflection in the analysis. Role of the Funding Source This research was funded through a Canadian Stroke Network grant and a Continuing Education Research and Development Award from the Office of Continuing Education, Faculty of Medicine, University of Toronto. Dr Salbach was supported by an Ontario March of Dimes–Canadian Institutes of Health Research postdoctoral fellowship while conducting this study. Dr Jaglal is supported by the Toronto Rehabilitation Chair at the University of Toronto.

Results We mailed an information package and consent form to a total of 61 physical therapists and were able to contact 55 therapists by telephone to screen them for eligibility. Of the 32 therapists who were eligible, 9 refused to participate, primarily for the reason of insufficient time. A total of 23 therapists consented to participate and completed a telephone interview. Table 1 shows participant and practice characteristics. There were 18 women and 5 men, ranging in age from 27 to 59 years. The practice settings most frequently indicated included a general hospital (n⫽9), a rehabilitation hospital (n⫽5), and private practice (n⫽3). Interviews lasted 45 to 60 minutes. One interview had field notes but not a transcript because of technical difficulty with audiotaping. The findings were organized under the following domains: clinical questions related to

stroke management, sources of information used to address clinical questions and factors enabling incorporation of evidence into practice, and challenges in implementing EBP. Verbatim quotes were used to support study findings. Numbers provided in brackets following quotations uniquely identify the study participant being quoted. Clinical Questions Related to Stroke Management Participants identified gaps in their clinical knowledge that covered the continuum of patient care (Tab. 2). Information needs were related to medical history, assessment, prognosis, treatment, education, and discharge planning. Some questions reflected a need for general or factual information about a condition or topic that could be found in textbooks. For example, participants asked questions about neuroanatomy, sought to review the body functions controlled by the area of the brain affected by the stroke, and reported consulting neuroanatomy textbooks. Other factual informationtype questions related to the existence of standardized assessment tools and educational or community resources. Participants working in a home care setting expressed a particular need for materials to educate clients and caregivers about the effects of stroke and the benefits of continuing to exercise in the home environment. Selected participants described distributing to patients or caregivers educational materials that they had downloaded from Web sites of stroke associations. Therapists also desired information about community programs or resources to which they could refer their clients in readiness for discharge. Other questions reflected a need for specialized knowledge related to a patient encounter for the purpose of guiding clinical decisions or actions. For example, participants asked

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Updating Clinical Practice for Patients With Stroke Table 1. Participant (n⫽23) and Practice Characteristics Characteristic

No.

%

20–29

1

4

30–39

5

22

40–49

4

17

13

57

18

78

5

22

15

65

Age (y)

50⫹ Sex Women Men Highest degree Bachelor’s Master’s

2

9

Othera

4

17

Missing

2

9

Years practicing ⬍5

2

9

5–10

3

13

11–15

1

4

17

74

Low

8

35

Moderate

9

39

High

6

26

⬎15 Self-efficacy for implementing evidence-based practice

Practice approach Mixedb

11

48

Neurodevelopmental treatment

7

30

Bobath

2

9

Proprioceptive neuromuscular facilitation

1

4

Missing

2

9

General hospital

9

39

Rehabilitation hospital

5

22

Private practice clinic

3

13

Home care agency

2

9

Long-term care facility

2

9

Community health center

1

4

Complex continuing care

1

4

17

74

Suburban

3

13

Rural

3

13

Practice setting

Practice location Urban

a b

Including diploma, European college degree. Motor relearning and neurodevelopmental treatment approaches were most commonly cited.

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questions about prognosis or the efficacy of a specific treatment for a particular patient and sought answers to these questions from research literature. Factual information was sometimes needed to inform a review of research literature. For example, one participant described consulting the handbook Physical Rehabilitation Outcome Measures43 (PROM), from the Canadian Physiotherapy Association (CPA), to identify an outcome measure before consulting research literature for more specific information: The CPA’s red [PROM] book that would be my first reference, . . . but then being able to go to the literature and either validate what I felt about . . . I do tend to go to maybe a more specific article, but I do certainly start with that. [ID1118]

Although few participants used the term prognosis, they spoke of needing to evaluate the risk of falling, particularly in the context of determining readiness for discharge. Sources of Information Used to Address Clinical Questions and Factors Enabling Incorporation of Evidence Into Practice To address their clinical questions, interviewees sought information from diverse sources, including individual people or groups of people, textbooks, gray literature, research reports in printed journals, electronic bibliographic databases or Web sites, and informal or formal continuing education. Individual people. Participants reported consulting foremost with peers, including coworkers, colleagues at other facilities, and peers from courses, to obtain articles and discuss research findings. Participants also spoke of consulting with colleagues whom they considered to be clinical experts (eg, senior therapists and course mentors) for feedback on treatment approaches for June 2009

Updating Clinical Practice for Patients With Stroke particular clients. Peers were a preferred source because of their availability, ease of access, and minimal cost: It’s easy and it’s available . . . if it’s a question that I have that maybe I haven’t come across, somebody else may have, or may have already looked it up themselves, so I might actually be able to get the information quick and dirty. [ID1151]

It was noted that peers are not always available when a question arises or may not be knowledgeable about a particular topic. Several participants identified students as sources of new knowledge. Participants with low or moderate levels of EBP self-efficacy, in particular, asked students to do online literature searches. A relationship of mutual benefit was described in which the physical therapist shared clinical expertise with the student and the student provided knowledge of the most recent research: I have a back and forth . . . reciprocal relationship with my students. I find that an excellent way to keep up to date. [ID613]

Most participants spoke of having access to resource people, including librarians, research therapists, or managers, who made it easier to stay current by facilitating access to research evidence in an efficient manner: Just by virtue of my time available . . . I don’t do many of the searches myself online. I . . . give them key words and have the librarian here search out topics and titles and give me . . . the abstracts, and I’ll go through them and see whether I want to pursue the papers and if any of them are relevant to the question that I have. [ID909]

Regardless of self-efficacy score, librarians were often used to help refine a search strategy. Librarians June 2009

provided one-on-one help with conducting searches, retrieving articles, and sending e-mail alerts, and they provided in-service training. Research therapists facilitated access to articles and participation in research studies; encouraged discussions of research; summarized and presented research findings; organized educational events, journal clubs, and teleconferences; and provided in-service training on how to search and critically appraise research literature. Groups of people. Discussion groups were perceived as an important information source, particularly by older therapists and by home care therapists who work in isolation from peers. Discussion groups were described as regular meetings to discuss clinical cases, research articles, and application of clinical strategies (eg, assessment tools and treatment techniques). Attendance by people from different institutions was perceived to lend validity to group decisions regarding outcome measures and treatment interventions and to support the continuity of care. Interprofessional discussion groups were perceived as being less relevant to practice than groups comprising solely physical therapists because of different information needs across professions. Participation in journal clubs was perceived as providing opportunities to practice critical appraisal skills and to learn how to apply evidence to clinical practice, particularly when someone with research expertise (such as a resource person or employer) facilitated meetings. Research. After peers, research literature was the second mostpreferred source of information, regardless of self-efficacy score: I probably use people first and . . . from the stroke perspective anyway, I probably use literature second. [ID1151]

Several participants described searching research literature in electronic bibliographic databases (eg, MEDLINE, CINAHL, PEDro, Cochrane, and EMBASE) or using the PubMed search tool. Physical therapists with high EBP self-efficacy, therapists who had recently graduated, and young therapists appeared to be confident in searching for and retrieving articles on their own and generally preferred detailed research information. Physical therapists with low EBP self-efficacy appeared to be more likely than those with high selfefficacy to seek help with online searching and preferred summarized research information. Having a connection with a university facilitated online access to journal articles. Participants did not frequently report using e-mail alerts to access research articles but recognized them as a time-saving strategy for facilitating EBP. Consulting research syntheses, including clinical practice guidelines and systematic reviews, was a preferred and efficient way for accessing research, and participants perceived the findings of such sources as being dependable and of high quality: If somebody else would review the work . . . that would be the first thing I would be looking at. I know the quality that is behind [it], and . . . how much [it] is reliable. [ID667]

Participants described using Internet search engines, such as Google, and visiting Web sites presenting systematic reviews of stroke rehabilitation (eg, Evidence-Based Reviews in Stroke Rehabilitation26 [www.ebrsr.com] and StrokEngine [www.medicine. mcgill.ca/Strokengine]). The availability of reviews online facilitated access to information, saved time, and increased exposure to evidence. Participants described how systems for organizing research articles enabled easy access. Systems included storing journals in boxes and transforming Webbased resources into a printed re-

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Updating Clinical Practice for Patients With Stroke Table 2. Clinical Questions Related to Stroke Management Type Medical history

Examples Etiology of stroke Neuroanatomy Comorbid conditions

Assessmenta

Outcome measures to assess walking, movement control, safety, function, home environment

Prognosis

Predictors of walking recovery

Norms for outcome measures

Risk of falling Treatmenta

Enhancement of weight bearing, standing balance, walking, movement control

Education

Educational materials on effects of stroke and benefits of continuing exercise at home for patient, caregiver, or both

Discharge planning

Community programs or resources

Prescription of assistive or orthotic device

a

Questions related to selection of standardized assessment tools (n⫽19) and treatment (n⫽22) were most frequently asked.

Table 3. Summary of Challenges in Implementing Evidence-Based Practice (EBP) Type Practitioner

Challenges Insufficient computer skills Difficulty searching electronic bibliographic databases Insufficient critical appraisal skills Insufficient understanding of statistical procedures Difficulty applying research evidence to practice Difficulty organizing collections of research articles Insufficient awareness of Web-based EBP resources

Organization

Lack of time Limited number of client visits Peer isolation

Informal or formal continuing education. Continuing education opportunities included conferences or teleconferences, workshops, seminars, in-service training, rounds, clinical courses, and graduate degree programs. Attendees at workshops outside of their workplaces shared their learning with coworkers. Mainly recent graduates and participants continuing their education in a master’s degree program reported that they had learned a great deal about finding and evaluating evidence through their university education. Therapists working independently or in remote practice settings, in particular, valued teleconferences, such as those provided by the CPA. The CPA organizes teleconferences on a range of professionally relevant topics, including new roles for physical therapists and advances in evaluation and treatment techniques.44 Challenges in Implementing EBP Participants described a variety of challenges related to accessing information, applying information to clinical practice, and participating in educational events. Table 3 presents these challenges classified as relating to the practitioner, the organization, or the research literature on stroke management.

Limited EBP resources (eg, Internet access, librarian) Inadequate financial support for continuing education Research

Gaps in research Insufficient application to a wide range of clients Lack of detailed reporting Clinical practice guidelines not available or vague

source for colleagues and students in a department: So if we find a good article, we just label them evidence-based practice and then we put them [in the binder], so we have 2 big binders now. [ID969]

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One participant organized research articles downloaded in PDF format into an extensive tree of folders labeled according to subject area (eg, anatomy, outcome measures, and treatment) on a personal digital assistant.

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Practitioner. There was overwhelming agreement among participants that maintaining skills and participating in the steps of EBP on an ongoing basis are challenging. Participants recognized that the onus is on the individual clinician to seek information to stay current in practice. Using a computer was perceived as being difficult, mainly by older therapists, because of a lack of training in basic computer use and fear of or apprehension about technology. Participants noted that comfort level and efficiency with technologyrelated tasks improve with practice. Many therapists also perceived conJune 2009

Updating Clinical Practice for Patients With Stroke ducting searches of electronic bibliographic databases or of the Internet to be challenging. Difficulties were related to defining key words, refining searches, or obtaining research articles from online journals:

their personal characteristics. Some older participants were never taught about statistics, and others had not applied the knowledge gained from their statistics courses and had since forgotten what they had learned:

Sometimes it’s hard; you don’t know what key words to type in. [ID551]

We didn’t have statistics; . . . I don’t really understand statistics. . . . I have a global . . . , but if you ask me what the exact number means in terms of, “Is it statistically significant?”, I won’t know. [ID468]

I’ve found sometimes I’ll go round in circles. [ID909]

Many participants, particularly older therapists, reported difficulty in critically appraising research articles: Critical appraisal of research was not a priority in the programs back then. . . . I have attended a few inservices on critical appraisal research, but . . . it’s not something that is a strength of mine. [ID909]

Even younger therapists who had graduated more recently and who had received this type of training admitted that skill diminishes over time and that evidence is constantly changing:

Participants completing a master’s degree program, in addition to practitioners holding a bachelor’s degree or a diploma, perceived the application of research in clinical practice as challenging: Making that bridge . . . is always a difficult thing . . . you get a lot of theoretical knowledge, but then how does that really translate to the clinical context? [ID551]

Several participants acknowledged that changing practice is difficult:

I graduated 5 years ago. . . . I don’t do as much review of the literature as I should, and part of that is that I don’t feel confident anymore, in how to critically review an article. [ID551]

To change practice takes a lot, takes effort; it doesn’t come by itself. It has to be voluntary, definitely, and before you change something, you really need a good reason to do it. [ID667]

Participants with high self-efficacy seemed to be more confident than those with low self-efficacy in their critical appraisal skills. However, even this group acknowledged that, although their search and appraisal skills were adequate, there was not always an “easy” answer. A young therapist commented on the value of refresher or booster sessions:

Many participants did not seem to be aware of Web-based resources. Few interviewees mentioned clinical practice guidelines available online or Web sites presenting results of systematic reviews of rehabilitation research. Despite the challenges raised, there was a willingness to learn and apply new EBP strategies regardless of age, setting, or selfefficacy level.

I think it would be really beneficial to have refresher courses . . . for research design and . . . how to evaluate the literature. [ID613]

The majority of participants identified interpreting statistical procedures used to evaluate the quality of research as a challenge, regardless of June 2009

to keep on top of things like [EBP activities]. [ID1141]

There was a perception that taking time to review research literature was done at the expense of patient care: I’d basically be sacrificing patient care if I was doing it at work hours. [ID551]

Some therapists experienced settingspecific challenges. Practitioners in private, home care, or rural settings described the disadvantage of isolation from peers as it relates to applying new knowledge to clients: It’s very difficult to talk to somebody when you have a problem . . . you feel alone, you don’t have that dialogue . . . there’s nobody else around, and it becomes fairly subjective. [ID1141]

Participants in home care settings reported that limitations in the number of visits permitted with clients prevented the implementation of evidence-based treatments requiring more sessions. Internet access was less readily available in home care settings than in acute care or rehabilitation facilities. A resource person to facilitate EBP was not available to everyone: No, I don’t have anybody. . . . This is what you call luxury. [ID371]

Organization. Lack of time (eg, to conduct literature searches, to read, and to implement changes) was the barrier most commonly mentioned by interviewees:

Lack of management and organizational support to attend courses, to pay for conferences, to provide vacation coverage, educational leave, on-site research coordinators, and library access, and to purchase or provide new technology and equipment on-site were problems for several participants. An additional concern in rural settings was difficulty traveling to educational sessions because traveling involved additional time away from work.

By the time you put your 12-hour day in, to be quite frank, it’s not that easy

Participants described advocacy strategies for increasing organiza-

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Updating Clinical Practice for Patients With Stroke tional support, such as banding together and developing a case for change:

I have yet to find a measure of any sort of validity that actually looks at the qualitative aspects of walking . . . if you’re looking at true quality of movement, that’s difficult. [ID696]

I was one of the new grads along with a couple others that started to . . . demand some more support for education and . . . to say, “Listen, if you want to deliver a quality base care, you have to provide . . . more time and more money for education.” [ID613]

Physical therapists also indicated that some studies were conducted with subgroups of people with stroke who represented a limited proportion of clients seen in practice:

One participant described using research to help advocate for change (eg, to buy new equipment):

My patients don’t look like that, or only a small percentage of them would fit into this category. [ID1151]

I think it’s getting more information . . . and trying to use that to encourage management to go for it . . . you got to have some facts to give them . . . showing that something . . . productive is coming out of it. [ID940]

Participants reported that clinical interventions frequently were not described in books or in research literature in sufficient detail to determine their relevance or to reproduce them in the clinic:

Research. Participants described many challenges related to the availability and applicability of stroke research and the quality of reporting. Gaps in research conducted in acutecare and outpatient hospital settings or for patients with specific characteristics (eg, a high level of mobility) made it difficult for practitioners to know how best to assess relevance and adapt research findings to their practice: I think that stroke rehab is . . . there isn’t a lot of . . . definitive research about it; you have to use bits and pieces of research and come up with sort of an approach yourself. [ID1151]

Participants perceived a need to encourage stroke research and highlighted a need for setting-specific research as well as information on gait, treatment strategies, and outcome measures. Several participants acknowledged the availability of standardized assessment tools that measure quantitative aspects of walking after stroke but desired assessment tools that capture the quality of walking: 564

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They’ll [report], we tried trunk control exercises with A and just general rehab with B and compared the 2, but they’re not specific enough in their exercise protocol. [ID539]

One participant stated that although the PROM handbook43 describes the validity and reliability of outcome measures, it lacks information on how to administer tools. Perceptions of challenges related to individual studies also applied to clinical practice guidelines that therapists described as being either vague or limited in number: I have difficulty with guidelines because the guidelines are so general, and we don’t have a lot of guidelines. [ID835]

Discussion The present study is one of the first to investigate how physical therapists use research evidence to inform physical rehabilitation after stroke, and the findings have implications for the development of interventions and resources. Study find-

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ings were related to clinical questions that physical therapists have about stroke management, sources of information used to address clinical questions and factors enabling the incorporation of evidence into practice, and challenges in implementing EBP. We described these 3 main findings in relation to existing literature on EBP and indicated how the findings may inform the future development of interventions and resources to facilitate EBP among physical therapists. Clinical Questions Physical therapists most frequently required information on treatment and standardized assessment tools, a finding similar to that of a study conducted among nurse practitioners.45 Of note was the infrequent mention of the use of research literature to evaluate prognosis, despite the fact that there is extensive literature describing walking outcomes and predictors of physical recovery after stroke.32,46 – 48 A related and important finding was the need for educational materials and community resources, particularly among physical therapists providing services in the home care setting. Education is an integral part of home care services.49 Patients and caregivers previously indicated that they require individualized information on recovery, treatment, prognosis, practical caring tasks, and community resources,50 and therapists in the present study perceived similar educational needs. In identifying a need for information related to stroke management, participants completed the first step of EBP (ie, they identified a knowledge gap4). To subsequently formulate a question to guide a search of research literature and to conduct the search, physical therapists commonly enlisted the assistance of an-

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Updating Clinical Practice for Patients With Stroke other individual. Consultation with peers, students, or resource people was, by and large, described as an indirect method for obtaining research evidence. In all cases, this approach saved therapists time. In some cases, participants selected this strategy because they did not feel confident in their ability to successfully conduct an online literature search, a finding that was previously reported.7,8,14 Perceptions of physical therapists’ role in EBP may also have been a factor. In our previous study,7 only one half of the participants surveyed about EBP agreed that physical therapists should be responsible for conducting their own literature reviews to answer their clinical questions. Sources of Information Peers were, by far, the most common source of information for physical therapists, a finding confirming observations made in previous studies involving physical therapists and occupational therapists,9,12,51 nurses,45 and physicians.52 In a survey of 206 Canadian physical therapists,10 respondents ranked input from colleagues as the third most-important factor influencing their treatment of people with stroke, after experience working with patients and continuing education. In a qualitative study,9 most physical therapist participants formed discharge recommendations on the basis of clinical experience and opinion sharing with colleagues and health care team members. These combined results highlight the important role of peer networks in physical therapist practice. Students also were a mechanism for accessing research evidence, a finding that confirms the results of previous studies involving physical therapists and occupational therapists12,53 and nurses.54 Educationally influential occupational therapists working in adult stroke rehabilitation have described how mentoring June 2009

students contributed to their capacity to translate research evidence into practice and how answering students’ questions stimulated reflective learning.53 Student placements may be an important strategy for promoting EBP. Experience as a student supervisor has been associated with having a positive attitude toward EBP.7 Physical therapists described seeking out research directly as the second most-preferred source of information (after peers) for addressing their clinical questions. In contrast, previous studies showed that although clinicians believed that research was important, it was not a preferred source.12,19,51,55 A qualitative research study19 conducted to examine the information sources that physical therapists weighed in clinical decision making showed that they preferred informal sources of information (eg, clinical observation, peer consultation, and information from clients) and that, when their experience conflicted with research findings, they relied on their experience to make decisions. In the present study, physical therapists who appeared to be most comfortable with using electronic bibliographic databases to search research literature perceived their EBP selfefficacy to be high, were recent graduates, or were in the process of completing a graduate degree. Therapists with a master’s degree, young therapists, or therapists with a few years of clinical experience are more likely to report higher levels of EBP selfefficacy and to have received education in EBP than their counterparts.7 When considered together, these findings indicate that new graduates of master’s degree-level professional programs, the highest level offered in Canada, are poised to serve as role models for the implementation of EBP. Resources and continuing education may be necessary to promote

EBP among therapists who have not graduated from a professional program based on EBP. Challenges in Implementing EBP After locating research articles, most physical therapists appeared to find critical appraisal a challenge, as reported in previous studies.7,8 Some therapists perceived that consulting systematic reviews enabled them to bypass this step of EBP. By providing a comprehensive summary of available studies addressing a specific research question, systematic reviews enable faster consumption of research literature; in addition, they produce a larger sample size—larger than that in individual studies that are homogeneous in design—from which to synthesize an estimate of effect in meta-analyses. As with other research designs, however, the methodological quality of a systematic review can vary. For this reason, tools have been developed for use by researchers and practitioners alike to evaluate the quality of systematic reviews and clinical practice guidelines.56 –58 Therapists will continue to require fundamental skills to appraise published reports of individual studies in new areas of research or areas for which systematic reviews are unavailable. Given that, in the present study, even interviewees who were new graduates expressed difficulty with search and appraisal skills, continuing education opportunities for enhancing EBP skills may benefit junior as well as senior clinicians. Following appraisal in the process of EBP, physical therapists described a number of limitations of the stroke rehabilitation research that made the application of findings to clinical practice difficult. Therapists practicing in stroke rehabilitation7,14 and in other areas8 have made similar comments, indicating that these perceptions appear to be common to diverse domains of physical therapist

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Updating Clinical Practice for Patients With Stroke practice. These findings correspond to the field of knowledge translation, in which the perceptions of an innovation by potential users are expected to influence the adoption of the innovation.17,59 The role of the organization in EBP is clear. Without a doubt, EBP cannot occur without access to electronic bibliographic databases or Webbased resources. The lack of support for continuing education is a key barrier to professional development. Education about EBP is associated with EBP self-efficacy,7 and physical therapists have attributed their lack of use of outcome measures, for example, to a lack of education and organizational support.19 The observation of insufficient time as the predominant barrier to implementing EBP in the present study and in previous studies7,8,12,14 deserves note. A clinical culture that does not value time spent identifying and implementing EBP will fall short of achieving high-quality physical therapy services and optimal patient outcomes. Organizational resources and a supportive culture are necessary to uphold EBP, a principle guiding Canada’s approach to health care for people with stroke.60 Limitations Participants had responded to a previous survey on EBP and likely were interested in EBP. This fact might have limited the heterogeneity of the sample and may partially explain participants’ frequent use of research evidence as an information source. The majority of therapists held a bachelor’s degree, were over the age of 50 years, had more than 15 years of clinical experience, and practiced in a hospital or in an urban area. Although participants described a range of experiences with EBP, the inclusion of more therapists practicing in rural regions might have yielded different experiences with

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EBP, given the limited availability of resources to support EBP in these areas.7 Moreover, physical therapists who are recent graduates and are just entering the work force may experience barriers to implementing EBP that differ from the barriers identified by study participants who had practiced for more than 15 years.

Conclusion The present study yielded valuable insights about how physical therapists use research evidence to update the clinical management of walking rehabilitation after stroke. The results can be used to guide the development of information resources, research reporting, organizational systems, and continuing education to support the delivery of EBP of physical therapy after stroke. The findings showed that physical therapists require efficient access at the workplace to summaries of research evidence primarily to inform treatment, selection of outcome measures, and prognosis for walking rehabilitation after stroke. Therapists also need easy access to educational materials on the effects of stroke and the benefits of regular exercise, as well as information on community programs for clients and caregivers. Detailed reporting on procedures for delivering treatment interventions or administering outcome measures will likely facilitate their clinical use. From the organizational perspective, managers of home care, rural, and private-practice settings may consider fostering peer networks and providing physical therapy internships as strategies for facilitating the exchange of new research findings among clinicians. Older therapists may benefit from opportunities to develop basic computer skills and competence in conducting online literature searches. Finally, continuing education opportunities that increase awareness of information resources and help therapists develop

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skills in appraising research evidence and applying it to clinical practice are needed to build capacity among physical therapists to engage in EBP for the ultimate benefit of people with stroke. Dr Salbach, Dr Rappolt, Dr Bayley, Dr Burnett, Ms Judd, and Dr Jaglal provided concept/idea/project design. Dr Salbach, Ms Veinot, and Dr Jaglal provided writing. Dr Salbach, Ms Veinot, and Dr Rappolt provided data collection. Dr Salbach, Ms Veinot, Dr Rappolt, and Dr Burnett provided data analysis. Dr Salbach and Ms Veinot provided project management and clerical support. Dr Salbach and Dr Jaglal provided fund procurement and facilities/equipment. Dr Salbach provided participants. All authors provided consultation (including review of manuscript before submission). The authors thank the 23 physical therapists who generously gave their time to participate in the study. They also thank Dr Kelly O’Brien for providing insightful feedback on the manuscript. The Research Ethics Board of the University of Toronto approved this study. This research was funded through a Canadian Stroke Network grant and a Continuing Education Research and Development Award from the Office of Continuing Education, Faculty of Medicine, University of Toronto. Dr Salbach was supported by an Ontario March of Dimes–Canadian Institutes of Health Research postdoctoral fellowship while conducting this study. Dr Jaglal is supported by the Toronto Rehabilitation Chair at the University of Toronto. This article was received August 13, 2008, and was accepted February 18, 2009. DOI: 10.2522/ptj.20080249

References 1 Dopson S, Locock L, Gabbay J, et al. Evidence-based medicine and the implementation gap. Health. 2003;7:311–330. 2 Sackett DL, Rosenberg WM, Gray JA, et al. Evidence based medicine: what it is and what it isn’t. BMJ. 1996;312:71–72. 3 Straus SE, Richardson WS, Glasziou P, Haynes RB. Evidence-Based Medicine: How to Practice and Teach EBM. 3rd ed. Edinburgh, Scotland: Elsevier Churchill Livingstone; 2005. 4 Guyatt GH, Haynes RB, Jaeschke RZ, et al. Users’ guides to the medical literature. XXV. Evidence-based medicine: principles for applying the users’ guides to patient care. JAMA. 2000;284:1290 –1296.

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Updating Clinical Practice for Patients With Stroke 5 Rappolt S. The role of professional expertise in evidence-based occupational therapy. Am J Occup Ther. 2003;57:589 –593. 6 Davidoff F, Haynes B, Sackett D, Smith R. Evidence-based medicine. BMJ. 1995;310: 1085–1086. 7 Salbach NM, Jaglal SB, Korner-Bitensky N, et al. Practitioner and organizational barriers to evidence-based practice of physical therapists for people with stroke. Phys Ther. 2007;87:1284 –1303. 8 Jette DU, Bacon K, Batty C, et al. Evidencebased practice: beliefs, attitudes, knowledge, and behaviors of physical therapists. Phys Ther. 2003;83:786 – 805. 9 Jette DU, Grover L, Keck CP. A qualitative study of clinical decision making in recommending discharge placement from the acute-care setting. Phys Ther. 2003;83: 224 –236. 10 Stevenson TJ, Barclay-Goddard R, Ripat J. Influences on treatment choices in stroke rehabilitation: survey of Canadian physical therapists. Physiother Can. 2005;57:135–144.

22 van Peppen RP, Hendriks HJ, van Meeteren NL, et al. The development of a clinical practice stroke guideline for physiotherapists in The Netherlands: a systematic review of available evidence. Disabil Rehabil. 2007;29:767–783. 23 Canadian Stroke Network and Heart & Stroke Foundation of Canada. The Canadian stroke strategy. Canadian best practice recommendations for stroke care: 2006. Available at: http://www.strokecen ter.org/prof/CSSManualENG_WEB_Sept07. pdf. Accessed February 26, 2009. 24 Duncan PW, Zorowitz R, Bates B, et al. Management of adult stroke rehabilitation care: a clinical practice guideline. Stroke. 2005;36:e100 – e143. 25 Korner-Bitensky N, Roy MA, Teasell R, et al. Creation and pilot testing of StrokEngine: a stroke rehabilitation intervention Web site for clinicians and families. J Rehabil Med. 2008;40:329 –333. 26 Teasell RW, Foley NC, Bhogal SK, Speechley MR. An evidence-based review of stroke rehabilitation. Top Stroke Rehabil. 2003;10:29 –58.

11 Huijbregts MPJ, Myers AM, Kay TM, Gavin TS. Systematic outcome measurement in clinical practice: challenges experienced by physiotherapists. Physiother Can. 2002;54:25–31, 36.

27 Duncan PW, Horner RD, Reker DM, et al. Adherence to postacute rehabilitation guidelines is associated with functional recovery in stroke. Stroke. 2002;33: 167–177.

12 Rappolt S, Tassone M. How rehabilitation therapists gather, evaluate, and implement new knowledge. J Contin Educ Health Prof. 2002;22:170 –180.

28 Reker DM, Duncan PW, Horner RD, et al. Postacute stroke guideline compliance is associated with greater patient satisfaction. Arch Phys Med Rehabil. 2002; 83:750 –756.

13 Turner P, Whitfield TW. Physiotherapists’ use of evidence-based practice: a crossnational study. Physiother Res Int. 1997;2:17–29. 14 Pollock AS, Legg L, Langhorne P, Sellars C. Barriers to achieving evidence-based stroke rehabilitation. Clin Rehabil. 2000; 14:611– 617. 15 Langhorne P, Legg L, Pollock A, Sellars C. Evidence-based stroke rehabilitation. Age Ageing. 2002;31(suppl 3):17–20. 16 Maher CG, Sherrington C, Elkins M, et al. Challenges for evidence-based physical therapy: accessing and interpreting highquality evidence on therapy. Phys Ther. 2004;84:644 – 654. 17 Berwick DM. Disseminating innovations in health care. JAMA. 2003;289:1969 –1975. 18 Salbach NM, Jaglal S, Rappolt S, et al. Factors associated with physiotherapists’ use of research findings in stroke rehabilitation. Paper presented at: 15th International Congress of WCPT; June 2– 6, 2007; Vancouver, British Columbia, Canada. 19 McGlynn M, Cott CA. Weighing the evidence: clinical decision making in neurological physical therapy. Physiother Can. 2007;59:241–254. 20 Sandelowski M. Whatever happened to qualitative description? Res Nurs Health. 2000;23:334 –340. 21 Borgiel AE, Williams JI, Davis DA, et al. Evaluating the effectiveness of 2 educational interventions in family practice. CMAJ. 1999;161:965–970.

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29 Heart & Stroke Foundation. Available at: http://www.heartandstroke.com/site/c.ikI QLcMWJtE / b.3483991 / k.34A8 /Statistics. htm. Accessed February 26, 2009. 30 Rosamond W, Flegal K, Furie K, et al. Heart disease and stroke statistics: 2008 update—a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2008;117:e25– e146. 31 Friedman PJ. Gait recovery after hemiplegic stroke. Int Disabil Studies. 1990;12: 119 –122. 32 Jorgensen HS, Nakayama H, Raaschou HO, Olsen TS. Recovery of walking function in stroke patients: the Copenhagen Stroke Study. Arch Phys Med Rehabil. 1995;76:27–32.

37 Perry J, Garrett M, Gronley JK, Mulroy SJ. Classification of walking handicap in the stroke population. Stroke. 1995;26: 982–989. 38 Mayo NE, Wood-Dauphine´e S, Cote R, et al. Activity, participation, and quality of life 6 months poststroke. Arch Phys Med Rehabil. 2002;83:1035–1042. 39 Swinkels A, Albarran JW, Means RI, et al. Evidence-based practice in health and social care: where are we now? J Interprof Care. 2002;16:335–347. 40 Bandura A. Self-Efficacy: The Exercise of Control. New York, NY: WH Freeman; 1997. 41 Strauss A, Corbin J. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. 2nd ed. Thousand Oaks, CA: Sage Publications; 1998. 42 Lincoln YS, Guba EG. Naturalistic Inquiry. Newbury Park, CA: Sage; 1985. 43 Finch E, Brooks D, Stratford PW, Mayo NE. Physical Rehabilitation Outcome Measures. 2nd ed. Baltimore, MD: Lippincott Williams & Wilkins; 2002. 44 Canadian Physiotherapy Association Web site. http://www.physiotherapy.ca/. Accessed February 26, 2009. 45 Cogdill KW. Information needs and information seeking in primary care: a study of nurse practitioners. J Med Libr Assoc. 2003;91:203–215. 46 Kwakkel G, Wagenaar RC, Kollen BJ, Lankhorst GJ. Predicting disability in stroke: a critical review of the literature. Age Ageing. 1996;25:479 – 489. 47 Hendricks HT, Van LJ, Geurts AC, Zwarts MJ. Motor recovery after stroke: a systematic review of the literature. Arch Phys Med Rehabil. 2002;83:1629 –1637. 48 Meijer R, Ihnenfeldt DS, de Groot IJM, et al. Prognostic factors for ambulation and activities of daily living in the subacute phase after stroke: a systematic review of the literature. Clin Rehabil. 2003;17:119 –129. 49 Cooper J, Urquhart C. The information needs and information-seeking behaviours of home-care workers and clients receiving home care. Health Info Libr J. 2005;22:107–116.

33 Skilbeck CE, Wade DT, Langton Hewer R, Wood VA. Recovery after stroke. J Neurol Neurosurg Psychiatry. 1983;46:5– 8.

50 Wiles R, Pain H, Buckland S, McLellan L. Providing appropriate information to patients and careers following a stroke. J Adv Nurs. 1998;28:794 – 801.

34 Wade DT, Langton Hewer R. Functional abilities after stroke: measurement, natural history and prognosis. J Neurol Neurosurg Psychiatry. 1987;50:177–182.

51 Sweetland J, Craik C. The use of evidencebased practice by occupational therapists who treat adult stroke patients. Br J Occup Ther. 2001;64:256 –260.

35 Wade DT, Wood VA, Heller A, et al. Walking after stroke: measurement and recovery over the first 3 months. Scand J Rehabil Med. 1987;19:25–30.

52 Rappolt S. Family physicians’ selection of informal peer consultants: implications for continuing education. J Contin Educ Health Prof. 2002;22:113–120.

36 Lindmark B, Hamrin E. A five-year follow-up of stroke survivors: motor function and activities of daily living. Clin Rehabil. 2000;9:1–9.

53 Craik J, Rappolt S. Enhancing research utilization capacity through multifaceted professional development. Am J Occup Ther. 2006;60:155–164.

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Updating Clinical Practice for Patients With Stroke 54 Estabrooks CA, Rutakumwa W, O’Leary KA, et al. Sources of practice knowledge among nurses. Qual Health Res. 2005;15:460 – 476. 55 Turner P, Whitfield A. Journal readership amongst Australian physiotherapists: a cross-national replication. Aust J Physiother. 1997;43:197–202. 56 Oxman AD, Guyatt GH. Validation of an index of the quality of review articles. J Clin Epidemiol. 1991;44:1271–1278.

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57 Oxman AD, Guyatt GH, Singer J, et al. Agreement among reviewers of review articles. J Clin Epidemiol. 1991;44:91–98. 58 AGREE Collaboration. Development and validation of an international appraisal instrument for assessing the quality of clinical practice guidelines: the AGREE project. Qual Saf Health Care. 2003; 12:18 –23.

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59 Grol R, Wensing M. What drives change? Barriers to and incentives for achieving evidence-based practice. Med J Aust. 2004;180:S57–S60. 60 The Canadian Stroke Strategy Web site. Available at: http: // www.canadianstroke strategy.ca /eng/aboutus/aboutus.html. Accessed February 26, 2009.

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Research Report Test-Retest Reliability and Minimal Detectable Change Scores for the Timed “Up & Go” Test, the Six-Minute Walk Test, and Gait Speed in People With Alzheimer Disease Julie D. Ries, John L. Echternach, Leah Nof, Michelle Gagnon Blodgett

Background. With the increasing incidence of Alzheimer disease (AD), determining the validity and reliability of outcome measures for people with this disease is necessary.

Objective. The goals of this study were to assess test-retest reliability of data for the Timed “Up & Go” Test (TUG), the Six-Minute Walk Test (6MWT), and gait speed and to calculate minimal detectable change (MDC) scores for each outcome measure. Performance differences between groups with mild to moderate AD and moderately severe to severe AD (as determined by the Functional Assessment Staging [FAST] scale) were studied.

Design. This was a prospective, nonexperimental, descriptive methodological study.

Methods. Background data collected for 51 people with AD included: use of an assistive device, Mini-Mental Status Examination scores, and FAST scale scores. Each participant engaged in 2 test sessions, separated by a 30- to 60-minute rest period, which included 2 TUG trials, 1 6MWT trial, and 2 gait speed trials using a computerized gait assessment system. A specific cuing protocol was followed to achieve optimal performance during test sessions.

Results. Test-retest reliability values for the TUG, the 6MWT, and gait speed were high for all participants together and for the mild to moderate AD and moderately severe to severe AD groups separately (intraclass correlation coefficients ⱖ.973); however, individual variability of performance also was high. Calculated MDC scores at the 90% confidence interval were: TUG⫽4.09 seconds, 6MWT⫽33.5 m (110 ft), and gait speed⫽9.4 cm/s. The 2 groups were significantly different in performance of clinical tests, with the participants who were more cognitively impaired being more physically and functionally impaired.

J.D. Ries, PT, PhD, GCS, is Assistant Professor, Program in Physical Therapy, Marymount University, 2807 N Glebe Rd, Arlington, VA 22207 (USA). Address all correspondence to Dr Ries at: julie. [email protected]. J.L. Echternach, PT, DPT, EdD, ECS, FAPTA, is Professor and Eminent Scholar Emeritus, School of Physical Therapy, Old Dominion University, Norfolk, Virginia, and Adjunct Professor, Department of Physical Therapy, Nova Southeastern University, Fort Lauderdale, Florida. L. Nof, PT, PhD, is Professor, Department of Physical Therapy, Nova Southeastern University. M. Gagnon Blodgett, PsyD, is Clinical Assistant Professor, Department of Geriatrics, Nova Southeastern University. [Ries JD, Echternach JL, Nof L, Gagnon Blodgett M. Test-Retest reliability and minimal detectable change scores for the Timed “Up & Go” Test, the Six-Minute Walk Test, and gait speed in people with Alzheimer disease. Phys Ther. 2009;89:569 –579.] © 2009 American Physical Therapy Association

Limitations. A single researcher for data collection limited sample numbers and prohibited blinding to dementia level.

Conclusions. The TUG, the 6MWT, and gait speed are reliable outcome measures for use with people with AD, recognizing that individual variability of performance is high. Minimal detectable change scores at the 90% confidence interval can be used to assess change in performance over time and the impact of treatment. Post a Rapid Response or find The Bottom Line: www.ptjournal.org June 2009

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Reliability and Validity of Outcome Measures for Alzheimer Disease

A

lzheimer disease (AD) is the most common form of dementia in elderly people and affects an estimated 5.2 million individuals in the United States.1 It is estimated that 13% of people aged 65 years and older are diagnosed with AD, and the incidence and prevalence increase considerably with age.1 With the aging of the population, physical therapists in geriatrics will be treating an increasing number of people with AD. Given the need to measure outcomes to assess progress or decline in function, specific clinical tools should be tested for reliability and validity with individuals with AD. There are recent publications supporting the physical and functional benefits of exercise in the management of AD.2,3 Identification of appropriate and useful outcome measures for people with AD would enhance the ability to assess the effectiveness of interventions in clinical and research environments. Our current understanding of the psychometric properties of specific clinical tests with this population is limited. Methodological studies assessing the reliability of clinical tools for people with AD or dementia are scarce, but not nonexistent.4 – 8 Given the extremely limited research available exclusively with people with a diagnosis of AD, information gleaned from research with individuals with other types of dementia was included in

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 April 23 2009, at www.ptjournal.org.

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our review of the literature. Mixed results from studies make it difficult to know which outcome measures will best serve physical therapists’ needs in monitoring change in performance in individuals with AD. Outcome measures that have been studied for reliability with individuals with AD or dementia include: the Timed “Up & Go” Test (TUG),4,5,8,9 the Six-Minute Walk Test (6MWT),4,6 and gait speed.4,5,10 Reliability measurements indicate the degree to which scores of a clinical test are free from measurement errors,11 and although conceptually straightforward, the application of this notion can be complex.11,12 Reliability can be expressed as relative reliability or as absolute reliability. If a measurement has high relative reliability, this indicates that repeated measurements will reveal consistent positioning or ranking of individuals’ scores within a group.11 If a measurement has high absolute reliability, this indicates that, upon repeated measurement, scores show little variability.11 Relative reliability is measured with correlation coefficients. The intraclass correlation coefficient (ICC) evaluates correlation based upon variance estimates from analysis of variance13; the more common the variance between sets of measurements, the higher the ICC.12 The ICC is an appropriate statistic for examining test-retest reliability.13 As a general guideline, an ICC above .75 is considered to demonstrate good reliability; for clinical measures, it is suggested that reliability should exceed .90 to ensure reasonable validity.13 Excellent test-retest reliability does not necessarily ensure that individuals’ repeated performance will be consistent from test to test. Scores may vary, given expected variability of individual performance and measurement error. A measure of absolute variability provides useful infor-

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mation to delineate the “expected” changes from “true” changes in performance. Statistically, absolute reliability is determined by the standard error of measurement (SEM), or the standard deviation of the measurement errors,11,13 and a clinically useful mechanism for looking at absolute reliability is the minimal detectable change (MDC) score.14 Recent literature presenting TUG8,10 and gait speed10 data for individuals with dementia highlights the importance of understanding relative versus absolute reliability. Even though test-retest reliability coefficients for clinical tests are high, individual variability and measurement error make it very difficult to identify a “true” change in performance over time. Minimal detectable change scores provide researchers and clinicians with the opportunity to determine whether a change in performance is a meaningful change (ie, beyond expected measurement error and individual variability). Clinical observation in people with AD reveals increasing variability of performance with increasing levels of dementia. The existing literature supports this observation. Although Thomas and Hageman5 found the TUG to have reasonable test-retest reliability in subjects in day care settings who were considered to have mild to moderate dementia (MiniMental Status Examination [MMSE] [SD]⫽16.9 [7.3]), Tappen et al4 found the TUG to be impracticable for use in subjects with moderate to severe AD (MMSE⫽9.3 [6.0]). Miller et al,6 in a post hoc assessment of performance on the 6MWT (as a component of assessing test-retest reliability of the Senior Fitness Test), found that subjects who were cognitively impaired showed greater variability than subjects who were cognitively intact; they suggested that the 6MWT is not reliable for use with elderly people who are cognitively June 2009

Reliability and Validity of Outcome Measures for Alzheimer Disease impaired. The combined findings of these studies4 – 6 and the previously noted clinical observation suggest that test-retest reliability of physical and functional performance measures with individuals with AD may be influenced by level of dementia. The purposes of this research were: (1) to determine test-retest reliability of data for the TUG, the 6MWT, and gait speed with individuals with AD; (2) to determine MDC scores for each of the outcome measures; and (3) to identify performance differences between participant groups stratified by level of dementia. The existing literature guided the choice of outcome measures for the present study. We hypothesized that the test-retest reliability of the clinical tools would decrease with increased level of dementia, such that the measures would be reliable for use with individuals with mild to moderate AD, but not for use with individuals with moderately severe to severe AD. We also hypothesized that, when stratified by level of dementia, the participants who were less cognitively impaired would perform better on the clinical tests compared with the participants who were more cognitively impaired.

Method Participants and Procedure This methodological study used a prospective, nonexperimental, descriptive research design. Guardian informed consent was obtained for all participants, with the exception of one participant who signed her own informed consent statement with her family’s approval. When possible, assent forms were signed by participants in conjunction with guardian informed consent. Four sites providing care to individuals with AD (2 inpatient programs and 2 day care programs) participated in the study. The administrative contact at each site aided in the recruitment June 2009

of participants. Inclusion criteria were: probable diagnosis of AD, medical stability, and ambulation with or without an assistive device or with handheld guiding assistance of one person. Exclusion criteria were: overt neuromuscular or musculoskeletal problems, acute cardiac or pulmonary conditions, and surgery within the previous 6 months. Background data were collected primarily from the facility chart and included: age, sex, living environment, and use of an assistive device (classified as “none,” “use of a cane,” or “use of a walker or rolling walker”) or handheld guiding assistance for ambulation. Personal information (eg, vocation, avocations, family members’ names, likes and dislikes) was collected from the facility record and staff. This information proved useful in establishing rapport with the participants. The primary researcher (J.D.R.) administered the MMSE to all participants. The primary researcher scored the Functional Assessment Staging (FAST) scale15–18 using a caregiver or staff informant. The FAST scale has been established as a reliable and valid assessment tool for people with AD.19 The FAST instrument identifies 16 levels of functioning, separated into 7 stages (Tab. 1), and provided the operational definitions for level of AD in this study. The FAST scale was used to stratify the participants into 2 groups based on level of dementia: a mild to moderate AD group (FAST scale score⫽4 or 5) and a moderately severe to severe AD group (FAST scale score⫽6 or 7). Practical tips on interaction and communication with individuals with AD have been reported in the literature. Every effort was made to integrate these concepts into the protocol for the present study to maximize success of interactions, including: creating a personal connection with the patient using personal

historical information; creating a low-stress environment; using friendly facial expressions, eye contact, and a pleasant, but firm, voice; one-step commands; and stating meaningful goals.20 –29 The progression of cuing for all tests also was specific and based on the published literature.30,31 Cuing began with verbal instruction with a concurrent visual cue or gesture, followed by modeling or demonstration, followed by tactile guidance, and finally, if necessary, physical assistance. Participants were given 10 seconds to respond to a cue before the tester defaulted to a higher level of cuing. A 7-level scale of assistance developed by Beck et al31 for elderly people with cognitive impairments was used to classify the type of cuing or assistance required for each participant. If a participant required handheld guiding assistance, every effort was made to allow the participant to drive the movement; however, if the participant stopped or veered from the intended path of movement, the researcher guided the participant’s motion back on task. Two testing sessions for each participant were performed on the same day with a 30- to 60-minute rest period separating testing sessions. Every effort was made to keep all factors associated with the testing sessions consistent (eg, general time of day, staff member assisting with testing, room or area in which testing was performed). Participants performed the TUG, the 6MWT, and the test of gait speed. The TUG32 is a test of the time required for an individual to stand up from a chair with armrests, walk 3 m, turn, walk back to the chair, and sit down. In the present study, participants circled a small orange cone placed at the 3-m mark. Participants were instructed to “go as fast as you safely can.” The stopwatch timing

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Reliability and Validity of Outcome Measures for Alzheimer Disease Table 1. Functional Assessment Staging (FAST) Scale for People With Alzheimer Disease (AD)15,18 Stage

Level of Functioning

1

No decrement

“Normal” adult

2

Subjective deficit in word finding

Normal-aged adult

3

Deficit in demanding employment settings

Compatible with incipient AD

4

Assistance required in complex tasks (eg, handling finances, marketing, planning dinner for guests)

Mild AD

5

Assistance required in choosing proper clothing

Moderate AD

6a

Assistance required in putting on clothing

Moderately severe AD

6b

Assistance required in bathing properly

6c

Assistance required with the mechanics of toileting (eg, flushing, wiping)

6d

Urinary incontinence

6e

Fecal incontinence

7a

Speech ability limited to approximately a half-dozen intelligible words

7b

Intelligible vocabulary limited to a single word

7c

Ambulatory ability lost

7d

Ability to sit up lost

7e

Ability to smile lost

7f

Ability to hold up head lost

started when the participant’s bottom left the chair and ended when the bottom made contact with the chair after the walk. The 6MWT is the distance walked in a period of 6 minutes. This test was initially considered an endurance measure33 but more recently has been considered a broader measure of mobility and function.34,35 The 6MWT was performed in long hallways of the participating facilities. Participants walked at a “comfortable pace,” were discouraged from talking during the test, and were notified of each passing minute. If participants were distracted or stopped walking, they were prompted to “keep walking” and were advised of the time remaining. Self-selected gait speed was assessed using the GAITRite walkway.* This portable mat with embedded sensors and companion software creates a * CIR Systems Inc, 60 Garlor Dr, Havertown, PA 19083.

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profile of temporal and spatial parameters of gait and is considered a valid and reliable quantitative gait assessment tool.36,37 Participants were instructed to walk at a “comfortable” pace for the length of the mat (4.57 m [15 ft]), and the walking path was established such that acceleration and deceleration did not occur on the mat. Testing took place at the participating facilities. Patients performed one practice run of the TUG and one practice pass on the GAITRite walkway. They did not perform a practice run of the 6MWT, but were oriented to the walking course. Each testing session included 2 trials of the TUG, 2 passes at a comfortable pace on the GAITRite mat, and 1 trial of the 6MWT. Tests were performed in variable order to control for variability of performance from first to last test as a confounding factor. The order of test administration was randomized, determined by blind drawing of test order from all possible

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Severe AD

combinations for each participant. The test order administration remained constant from test session 1 to test session 2 for each participant. Data Management and Analysis We used SPSS 15.0 for Windows† for data management and analysis. Level of significance was predetermined to be P⬍.05 for all statistical analyses. Descriptive statistics for comparisons of groups included independentsamples t tests for parametric data and chi square and Mann-Whitney U tests for nonparametric data. All descriptive comparisons between groups were 2-tailed, as no assumptions of directionality were made. Test-retest reliability of data for all tests was assessed using the ICC (model 2), which is appropriate for methodological research.11,13 Reliability of data obtained for the TUG and gait speed was assessed using the ICC (2,2), as mean scores from 2 † SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606-6412.

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Reliability and Validity of Outcome Measures for Alzheimer Disease trials from each test session were used in the calculations. Mean scores are considered better estimates of true scores and can increase reliability estimates.13 For calculation of test-retest reliability for the 6MWT, the ICC (2,1) was used, as there was only one test score from each session. For each clinical test, the reliability coefficient was calculated for the entire sample and then separately for the mild to moderate AD group and the moderately severe to severe AD group. Independent-samples t tests were used to determine differences in performance on the clinical tests between the 2 groups. Comparisons were made using the mean score of all trials for each participant on the given test (ie, mean of 4 TUG scores, mean of 2 6MWT scores, and mean of 4 gait speed measurements). Onetailed tests were used to assess these data, as there is evidence to suggest that a decrease in speed occurs in patients with dementia38 – 45; therefore, an assumption of directionality was thought to be reasonable. Standard errors of measurement and MDC scores were calculated for the TUG, the 6MWT, and gait speed. Standard errors of measurement11 were calculated using the following equation: (1)

SEM ⫽ sd ⫻ 冑共1 ⫺ r兲

In this equation, sd is the standard deviation of the measure, and r is the reliability coefficient (test-retest reliability in the form of ICC for the subject group). For repeated measures, the SEM was multiplied by the square root of the number of measurements.11 Minimal detectable change scores were calculated for the TUG, 6MWT, and gait speed data at the 90% confidence interval. The formula used for calculating MDC9014,46 was: June 2009

(2)

MDC90 ⫽ SEM ⫻ 1.65 ⫻

冑2

In this equation, SEM was calculated as described previously. The 1.65 in the MDC90 equation represents the z-score at the 90% confidence level. The product of SEM multiplied by 1.65 is multiplied by the square root of 2 to account for errors associated with repeated measurements.

Results Data were collected on a total of 53 participants. Two participants’ data were eliminated from analysis because their dementia was later determined to be caused by factors other than AD. One setting was not conducive to the performance of the 6MWT, so that test was not performed with participants in that setting. On 2 occasions, individuals at other settings declined to perform the 6MWT. The Figure diagrams a flowchart of participants, explaining any differences between numbers of participants tested and data used in analysis of the results. The remaining 51 participants were stratified into the mild to moderate AD group (n⫽20) and the moderately severe to severe AD group (n⫽31). Descriptive statistics for the 51 subjects are shown in Table 2. The 2 groups were similar in age, as determined by the independent-samples t test, and similar in sex and living environment (ie, home versus inpatient), as determined by analysis of frequencies using the chi-square test. Mini-Mental Status Examination scores also are presented in Table 2. The MMSE scores of the 2 groups were compared using the MannWhitney U test, a nonparametric statistical analysis, given the ordinal nature of the MMSE data. Given the desire to compare the participants in the present study with those in many published studies that reported MMSE findings using parametric statistics, mean scores and standard deviations are presented for both

groups as well. All participants were consistent in their level of cuing needs from test session 1 to test session 2. The 2 groups were significantly different in their level of cuing needs, as evidenced by MannWhitney U test analysis, with the participants who were more cognitively impaired requiring higher levels of cuing than those who were less cognitively impaired (Tab. 2). The use of assistive devices (classified as “none,” “use of a cane,” or “use of a walker or rolling walker”) was similar between groups. More than 50% of the participants of both groups were ambulatory without assistive devices. Six participants, all in the moderately severe to severe AD group, required handheld guiding assistance for ambulation. Intraclass correlation coefficients for test-retest reliability were very high for all outcome measures and for the entire sample and each group (for the TUG, ICC⫽.985–.988, P⬍.001; for the 6MWT, ICC⫽.982–.987, P⬍.001; and for gait speed, ICC⫽.973–.977, P⬍.001). There were statistically significant differences between the mild to moderate AD group and the moderately severe to severe AD group on TUG, 6MWT, and gait speed performance. The participants who were more cognitively impaired were slower on the TUG and the test of gait speed and walked shorter distances in the 6MWT compared with the participants who were less cognitively impaired (Tab. 3). Repeated-measures SEMs were calculated for the TUG, the 6MWT, and gait speed to provide a comparison of individual variability of performance across groups (Tab. 4). Although there was little difference in SEMs for the mild to moderate AD group compared with the moderately severe to severe AD group for the 6MWT and gait speed (⬃10% dif-

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Figure. Flowchart of study participants. AD⫽Alzheimer disease, MMSE⫽Mini-Mental Status Examination, 6MWT⫽Six-Minute Walk Test, TUG⫽Timed “Up & Go” Test, GAITRite⫽computerized walkway test of gait parameters.

ference), there was a substantial difference in SEMs for TUG scores between the 2 groups (⬃100% difference), with the participants who were more cognitively impaired showing greater variability of performance compared with the participants who were less cognitively impaired. Table 4 also presents the MDC90 values for the TUG, the 6MWT, and gait speed for all participants.

Discussion Our initial purpose was to determine test-retest reliability of data for the 574

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TUG, the 6MWT, and gait speed for individuals with AD. All 3 outcome measures were found to have excellent test-retest reliability, well exceeding the r⫽.90 threshold13 for minimal acceptable reliability for a clinical test and indicating that these tests can be used clinically with good confidence in their test-retest reliability (ie, relative reliability). Testretest reliability was not influenced by level of dementia, as was hypothesized. Existing literature shows mixed results for relative reliability of these tools in people with AD and dementia.

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The TUG appears to be the most widely studied of the tools. We calculated an ICC of .987 for test-retest reliability of TUG scores for all participants. Tappen et al4 had such difficulty getting their subjects with moderately severe to severe AD (MMSE⫽9.3 [6.0]) to perform the TUG, that they had to modify the test beyond recognition. Our participants in the moderately severe to severe AD group had comparable MMSE scores (10.2 [8.8]) and were able to perform the test with excellent relative reliability results. Rockwood et al7 reported an ICC of .56 June 2009

Reliability and Validity of Outcome Measures for Alzheimer Disease Table 2. Descriptive Statistics for Participants (N⫽51)a All Participants (Nⴝ51)

Mild to Moderate AD Group (nⴝ20)

Moderately Severe to Severe AD Group (nⴝ31)

Age (y), X⫾SD

80.71⫾8.77

81.05⫾9.48

80.48⫾8.43

t⫽.223 df⫽49 P⫽.824

Sex (no. female [%])

34 (66.7)

12 (60.0)

22 (70.7)

␹2⫽.658 df⫽1 P⫽.417

Living environment (no. living at home [%])

39 (76.5)

16 (80.0)

23 (74.2)

␹2⫽.228 df⫽1 P⫽.633

MMSE X⫾SD Range Median

13.1⫾8.2 0–30 14

Variable

Levels of assistance for elderly people with cognitive impairment (level of cuing)

17.40⫾4.50 10–26 16.5 Mean rank: 33.78 Sum of ranks: 675.50

10.20⫾8.83 0–30 7.5 Mean rank: 19.98 Sum of ranks: 599.50

Mean rank: 19.05 Sum of ranks: 381.00

Mean rank: 30.48 Sum of ranks: 945.00

Statistical Comparison Between Groups

M-W U⫽134.5 P⫽.001*

M-W U⫽171.00 P⫽.004*

AD⫽Alzheimer disease, MMSE⫽Mini-Mental Status Examination, t⫽independent-samples t test, df⫽degrees of freedom, ␹2⫽chi-square test of independence, M-W U⫽Mann-Whitney U test of independent samples. Asterisk indicates statistically significant difference between dementia groups.

a

for test-retest reliability of TUG scores in elderly individuals with cognitive impairment, but their methodology was fraught with difficulties of working within the limitations of retrospective data. A study by Thomas and Hageman5 with a small sample of individuals with mild to moderate dementia (MMSE⫽ 16.9 [7.3]) revealed an ICC of .87 for test-retest reliability of TUG scores, and van Iersel et al10 examined testretest reliability in people with dementia (MMSE⫽19.1 [5.2]) and found an ICC of .97 for the TUG. These findings were more consistent

with the higher relative reliability found in our study. The 6MWT has not been widely used in people with AD or dementia; however, Tappen et al4 reported that their participants with AD who were unable to perform the TUG were able to perform the 6MWT. They did not report test-retest reliability of the 6MWT scores, although the research design was such that their ICCs of .76 to .90 for intrarater reliability (one rater observing 2 different sessions) could potentially be interpreted as test-retest reliability. The

authors suggested that the 6MWT may be the preferred test of physical performance for people with AD. We calculated an ICC of .987 for testretest reliability of 6MWT scores in our study. Thomas and Hageman5 and van Iersel et al10 reported ICCs of .92 and .77, respectively, for testretest reliability of measurements of self-selected gait speed in people with dementia. We calculated an ICC of .977 for test-retest reliability of gait speed measurements. Our findings consistently showed higher testretest reliability on all 3 outcome

Table 3. Performance Differences on Timed “Up & Go” Test, Six-Minute Walk Test, and Gait Speed Between Dementia Groups Outcome Measure Timed “Up & Go” Test (s)

Six-Minute Walk Test (ft)

Gait speed (cm/s)

a

Dementia Group (n)

XⴞSD

Independent-Samples t Test, t (df)

P

Mild to moderate AD (20)

19.95⫾9.81

⫺1.876 (49)

.0335*

Moderately severe to severe AD (31)

28.01⫾17.49

Mild to moderate AD (16)

938.78⫾428.62

Moderately severe to severe AD (17)

615.71⫾338.34

Mild to moderate AD (20)

66.07⫾29.63

Moderately severe to severe AD (31)

52.43⫾23.58

2.411 (31)

.011*

1.823 (49)

.037*

AD⫽Alzheimer disease. Asterisk indicates statistically significant at P⬍.05.

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Reliability and Validity of Outcome Measures for Alzheimer Disease Table 4. Standard Error of Measurement (SEM) for Repeated Measures and Minimal Detectable Change Scores at the 90% Confidence Interval (MDC90) for the Timed “Up & Go” Test, the Six-Minute Walk Test, and Gait Speed SEM

Outcome Measure

All Participants (Nⴝ51)

Mild to Moderate AD Group (nⴝ20)

Moderately Severe to Severe AD Group (nⴝ31)

MDC90, All Participants

Timed “Up & Go” Test (s)

2.48

1.52

3.03

4.09

Six-Minute Walk Test (m)

20.28 (66.53 ft)

21.86 (71.72 ft)

19.57 (64.20 ft)

33.47 (109.8 ft)

5.72

6.07

5.48

9.44

Gait speed (cm/s)

measures compared with previous research. One factor that may have enhanced performance on all clinical tests in the present study was the careful use and progression of cuing to facilitate optimal performance. Although we anticipated that performance consistency from one trial to the next perhaps would suffer with increasing dementia, the steady and scripted use of verbal and tactile cuing to optimize performance was carefully implemented; this may have consistently facilitated the best performance. Both Nordin et al8 and van Iersel et al10 commented that the use of cuing was the key to the successful administration of the TUG in subjects with cognitive impairment in their recent reliability studies. In all of the studies reviewed that addressed cuing, the authors either expressed simply a general statement that cuing was allowed4,5,10 or reported a dichotomy of cuing versus no cuing.8 We believe that careful use of cuing was an asset to consistency of performance, contributing to the high test-retest reliability findings for the clinical tests in our study. Perhaps our careful progression of cuing was pivotal in the successful administration of the TUG in the moderately severe to severe AD group, as Tappen et al4 were unable to administer the TUG to their subjects with comparable MMSE scores. Our participants’ cuing needs were rated and 576

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documented (verbal cue/gesture, modeling/demonstration, physical/ tactile prompt, progressive amounts of physical guidance) and were consistent from one testing session to the next. Not surprisingly, participants with moderately severe to severe AD required more substantive prompting and guiding for performance of the outcome measures than those with mild to moderate AD. Six of our 51 participants, all from the moderately severe to severe AD group, required handheld guiding assistance of one person to complete the outcome measures. Without the physical guidance of the researcher, these participants would not have been able to complete the tests. A recent publication by Hauer and Oster47 reiterates that measuring functional performance in people with dementia is very complex and cautions researchers that when we provide external cues to patients, perhaps we are measuring the reliability and quality of the external cuing (ie, the researcher’s performance) as opposed to, or as well as, the patients’ performance. In contrast, we contend that a consistent progression of cuing to facilitate best possible performance may be the optimal way to administer clinical tests to people with AD or dementia. The use of a consistent cuing paradigm, in conjunction with following other suggestions related to establishing rapport and maintaining a nonthreatening environment, may allow the

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clinician or researcher to repeatedly elicit the most favorable performance from an individual with AD. Our findings demonstrate that although test-retest reliability (relative reliability) for the clinical tests was excellent, there was still a substantial degree of variability of performance for individual participants from one test session to the next (absolute reliability). The SEM and MDC90 were calculated to objectify these findings. Because the SEM is based on an assumption of normal distribution, probabilities of the normal curve can be applied to SEM values.11 Values from Table 4 can be translated to clinical performance using these principles. For instance, there is a 68% probability that a repeated measure of the TUG will be within ⫾1.52 seconds (1 SEM) of the original score for an individual with mild to moderate AD and a 96% probability that a repeated measure will be within 3.04 seconds (2 SEMs) of the original score. For an individual with moderately severe to severe AD, there is a 96% probability that a repeated measure of the TUG will be within ⫾6.06 seconds (2 SEMs) of the original score. This could be useful information when examining repeat performances of individuals with AD on the TUG. The dichotomy of dementia levels is important in interpreting clinical findings here, as a difference in performance of approximately 4 to 5 seconds likely represents a change beyond the expected variability in performance in a patient June 2009

Reliability and Validity of Outcome Measures for Alzheimer Disease who is less cognitively impaired, whereas this same change of approximately 4 to 5 seconds would be within the expected variability of performance in a patient who is more profoundly impaired. The SEM findings for the TUG were consistent with what was anticipated, with the group with a higher level of dementia showing more variability of performance compared with the group with a lower level of dementia. However, this was not the case with the 6MWT or gait speed data. Differences in SEM between groups for the 6MWT and gait speed were small (⬃10%), with the mild to moderate AD group showing greater variability of performance than the moderately severe to severe AD group. Given the small difference between groups, clinically, it seems appropriate to use the SEM for all individuals if calculating expected performance on repeated measures of the 6MWT and gait speed, irrespective of dementia level. Based on these findings, there is a 96% probability that a repeated measure of the 6MWT will be within ⫾40.5 m (133 ft) (2 SEMs) of the initial score. There is a 96% probability that a repeated measure of gait speed will be within ⫾11.44 cm/s (2 SEMs) of the initial measurement. These numbers give wide ranges of performance that would fall into the “expected” level of variability on these tests, but still could be clinically useful in the identification of “true” changes in individuals with AD. The TUG is the only one of the outcome measures we studied that has previously been assessed for absolute reliability. Nordin et al8 studied the reliability of TUG scores with participants stratified by cognitive level. As in our study, they hypothesized that increased cognitive impairment would increase the variability of TUG scores, but they found that variability of performance was reJune 2009

lated not to cognitive level, but to time to complete the TUG. Also like our study, although their calculated ICCs were high (.91 and .92 for intrarater and intertester reliability, respectively), individual variability also was high. Using logarithmically transformed data, the authors created a calculation for expected variability of TUG performance. This method revealed a large degree of variability or measurement error, such that if an individual performed the TUG in 20 seconds, the expected range of performance on a repeated measure could be between 13.2 and 30.3 seconds. If an individual’s performance was 30 seconds, the expected range of a repeated measure could be between 26.4 and 60.6 seconds. Despite similarities in our general study findings, we used substantially different statistical mechanisms to assess absolute reliability. Our findings suggest that a smaller change in performance on the TUG (ie, 4.09 seconds) than proposed by Nordin et al may represent a clinically significant change. Again, it is possible that our structured and consistent use of cuing and our efforts to maximize participant comfort and minimize environmental stress were effective in minimizing variability of performance, resulting in more consistency across trials. Our final research goal was to identify performance differences between groups stratified by level of dementia. There were significant differences in performance between the mild to moderate AD group and the moderately severe to severe AD group for the TUG, the 6MWT, and gait speed. The findings of the present study, within the context of published data for the TUG,5,10,48,49 the 6MWT,4,48,50 and gait speed10,51 in individuals with dementia, clearly represent a degradation of performance with the progression of dementia, and this performance decline is beyond that seen with

normal aging. Admittedly, this is piecing together data cross-sectionally; a longitudinal study would be helpful to confirm this observation and would be a useful contribution to the literature. The present study indicates that the TUG, the 6MWT, and gait speed (using the GAITRite system) are reliable measures for use with individuals with AD. Recently, interpreting change scores and identifying clinically significant changes in performance have become an explicit focus of the physical therapy profession.14 Clinicians are encouraged to understand how changes in scores translate to clinical relevance. To that end, this study presents MDC90 scores that provide meaningful criteria for assessing performance changes for people with AD on the TUG, the 6MWT, and the gait speed test (Tab. 4). Minimal detectable change is the magnitude of change that a measurement must demonstrate to exceed the anticipated measurement error and variability.14,46 If a change in score occurs, in either direction, that is greater than MDC90, one can be 90% confident that the difference was not due to measurement error or patient variability. In comparison with the SEM, this provides an even more conservative estimate of a change in score that is clinically meaningful. Rabheru52 recently published a call for the expansion of the mechanism for disease staging and milestones in people with AD, stating that although cognitive milestones are important, functional and behavioral milestones may help to enhance the general picture of the progression of AD. The functional measures in the present study could potentially be a component of the staging process. Van Iersel et al44 suggested that a reasonable goal of research should be to identify the minimal clinically important changes in gait variables

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Reliability and Validity of Outcome Measures for Alzheimer Disease in the AD population. The present study suggests that if a gait speed change of greater than 9.44 cm/s is detected in an individual with AD, one can be 90% confident that this represents a “true” change. This information could be helpful in interpreting clinical and research findings related to performance changes in gait speed. This study provides the information to make similar judgments with repeated TUG and 6MWT scores in individuals with AD. Limitations There were some limitations of this study. The varied clinical presentation of participants bodes well for the generalizability of the study findings, but the limited geographical (northern Virginia) and socioeconomic (upper middle class) variability of the group may threaten the external validity of the study. The logistics of using a single researcher for data collection influenced sample size and made it impossible to blind the scorer to the dementia level of the patient, which would be ideal in this type of study.

Conclusions This study demonstrated excellent test-retest reliability for the TUG, the 6MWT, and gait speed in individuals with AD. Significant differences were found in performance of these outcome measures between the mild to moderate AD group and the moderately severe to severe AD group, with the participants who were less cognitively impaired outperforming those who were more cognitively impaired. Despite very high ICCs for test-retest reliability, there was notable individual variability in the performance of these measures. Presentation of SEM and MDC90, for each of the measurement tools, provides clinicians with meaningful thresholds for identifying changes beyond those expected from measurement error and individual variability (ie, “true” change) in individuals with AD. We 578

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are confident that the consistent and scripted use of cuing with participants was instrumental in the successful administration of the outcome measures and contributed to consistency of participant performance across trials. These findings are relevant for both clinicians and researchers. It is our hope that MDC90 values for the TUG, the 6MWT, and gait speed presented here will be helpful in monitoring performance changes over time and assessing the effectiveness of physical therapy and exercise interventions in individuals with AD. Dr Ries and Dr Echternach provided concept/idea/research design. Dr Ries provided writing, data collection and analysis, project management, participants, facilities/equipment, institutional liaisons, and clerical support. All authors provided consultation (including review of the manuscript before submission). This research project was approved by the Nova Southeastern University Institutional Review Board (Research Protocol No. HPD-ALL08280604Exp). This study was conducted in partial fulfillment of the requirements for Dr Ries’ PhD degree in physical therapy from Nova Southeastern University. A poster presentation of this research was given at the Combined Section Meeting of the American Physical Therapy Association; February 9 –12, 2009; Las Vegas, Nevada. This article was received August 23, 2008, and was accepted March 9, 2009. DOI: 10.2522/ptj.20080258

References 1 2008 Alzheimer’s disease facts and figures. Alzheimers Dement. 2008;4:110 –133. 2 Rolland Y, Pillard F, Klapouszczak A, et al. Exercise program for nursing home residents with Alzheimer’s disease: a 1-year randomized, controlled trial. J Am Geriatr Soc. 2007;55:158 –165. 3 Santana-Sosa E, Barriopedro MI, LopezMojares LM, et al. Exercise training is beneficial for Alzheimer’s patients. Int J Sports Med. 2008;29:845– 850. 4 Tappen RM, Roach KE, Buchner D, et al. Reliability of physical performance measures in nursing home residents with Alzheimer’s disease. J Gerontol A Biol Sci Med Sci. 1997;52:M52–M55.

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5 Thomas VS, Hageman PA. A preliminary study on the reliability of physical performance measures in older day-care center clients with dementia. Int Psychogeriatr. 2002;14:17–23. 6 Miller E, Whalen R, Biehl J, et al. The reliability of the senior fitness test for assisted living dwellers with different cognitive abilities. Paper presented at: Annual Conference & Exposition of the American Physical Therapy Association; June 30 – July 3, 2004; Chicago, Illinois. 7 Rockwood K, Awalt E, Carver D, MacKnight C. Feasibility and measurement properties of the Functional Reach and the Timed Up and Go tests in the Canadian Study of Health and Aging. J Gerontol A Biol Sci Med Sci. 2000;55:M70 –M73. 8 Nordin E, Rosendahl E, Lundin-Olsson L. Timed “Up & Go” Test: reliability in older people dependent in activities of daily living—focus on cognitive state. Phys Ther. 2006;86:646 – 655. 9 Rockwood K, Strang D, MacKnight C, et al. Interrater reliability of the Clinical Dementia Rating in a multicenter trial. J Am Geriatr Soc. 2000;48:558 –559. 10 van Iersel MB, Benraad CE, Rikkert MG. Validity and reliability of quantitative gait analysis in geriatric patients with and without dementia. J Am Geriatr Soc. 2007; 55:632– 634. 11 Domholdt E. Rehabilitation Research: Principles and Applications. 3rd ed. St Louis, MO: Elsevier Saunders; 2005. 12 Rothstein JM, Echternach JL. Primer on Measurement: An Introductory Guide to Measurement Issues. Alexandria, VA: American Physical Therapy Association; 1993. 13 Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Practice. 2nd ed. Upper Saddle River, NJ: Prentice Hall Health; 2000. 14 Haley SM, Fragala-Pinkham MA. Interpreting change scores of tests and measures used in physical therapy. Phys Ther. 2006;86:735–743. 15 Reisberg B. Functional assessment staging (FAST). Psychopharmacol Bull. 1988;24: 653– 659. 16 Reisberg B, Ferris SH, Franssen E. An ordinal functional assessment tool for Alzheimer’s-type dementia. Hosp Community Psychiatry. 1985;36:593–595. 17 Reisberg B, Ferris SH, Anand R, et al. Functional staging of dementia of the Alzheimer type. Ann NY Acad Sci. 1984;435: 481– 483. 18 Reisberg B, Ferris SH, Franssen E. Practical geriatrics: an ordinal functional assessment tool for Alzheimer’s-type dementia. Hosp Community Psychiatry. 1985;36: 593–595. 19 Sclan SG, Reisberg B. Functional assessment staging (FAST) in Alzheimer’s disease: reliability, validity, and ordinality. Int Psychogeriatr. 1992;4(suppl 1):55– 69.

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Reliability and Validity of Outcome Measures for Alzheimer Disease 20 Staples S. Alzheimer’s disease: modifying instructions and approach to enhance performance. Paper presented at: Combined Sections Meeting of the American Physical Therapy Association; February 23–27, 2005; New Orleans, Louisiana. 21 Haak NJ. Maintaining connections: understanding communication from the perspective of the person with dementia. Alzheimer’s Care Quarterly. 2002;3: 116 –131. 22 Kovach CR, Henschel H. Planning activities for patients with dementia: a descriptive study of therapeutic activities on special care units. J Gerontol Nurs. 1996;22: 33–38. 23 Patterson JT, Wessel J. Strategies for retraining functional movement in persons with Alzheimer disease: a review. Physiother Can. 2002;54:274 –280. 24 Auer SR, Sclan SG, Yaffee RA, Reisberg B. The neglected half of Alzheimer disease: cognitive and functional concomitants of severe dementia. J Am Geriatr Soc. 1994; 42:1266 –1272. 25 Davis CM. The role of the physical and occupational therapist in caring for the victim of Alzheimer’s disease. Phys Occup Ther Geriatr. 1986;4(3):15–28. 26 Hoppes S, Davis LA, Thompson D. Environmental effects on the assessment of people with dementia: a pilot study. Am J Occup Ther. 2003;57:396 – 402. 27 Davis LA, Hoppes S, Chesbro SB. Cognitive-communicative and independent living skills assessment in individuals with dementia: a pilot study of environmental impact. Top Geriatr Rehabil. 2005;21:136 –143. 28 Souren LE, Franssen EH, Reisberg B. Neuromotor changes in Alzheimer’s disease: implications for patient care. J Geriatr Psychiatry Neurol. 1997;10:93–98. 29 Oddy R. Promoting mobility in patients with dementia: some suggested strategies for physiotherapists. Physiother Pract. 1987;3:18 –27. 30 Vogelpohl TS, Beck CK, Heacock P, Mercer SO. “I can do it!” Dressing: promoting independence through individualized strategies. J Gerontol Nurs. 1996;22(3): 39 – 42; quiz 48.

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31 Beck CK, Heacock P, Rapp CG, Mercer SO. Assisting cognitively impaired elders with activities of daily living. American Journal of Alzheimer’s Care and Related Disorders & Research. 1993;8(6):11–20. 32 Podsiadlo D, Richardson S. The timed “Up & Go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39:142–148. 33 Guyatt GH, Sullivan MJ, Thompson PJ, et al. The 6-minute walk: a new measure of exercise capacity in patients with chronic heart failure. Can Med Assoc J. 1985;132: 919 –923. 34 Harada ND, Chiu V, Stewart AL. Mobilityrelated function in older adults: assessment with a 6-minute walk test. Arch Phys Med Rehabil. 1999;80:837– 841. 35 Lord SR, Menz HB. Physiologic, psychologic, and health predictors of 6-minute walk performance in older people. Arch Phys Med Rehabil. 2002;83:907–911. 36 Bilney B, Morris M, Webster K. Concurrent related validity of the GAITRite walkway system for quantification of the spatial and temporal parameters of gait. Gait Posture. 2003;17:68 –74. 37 Menz HB, Latt MD, Tiedemann A, et al Reliability of the GAITRite walkway system for the quantification of temporospatial parameters of gait in young and older people. Gait Posture. 2004;20: 20 –25. 38 Alexander NB, Mollo JM, Giordani B, et al. Maintenance of balance, gait patterns, and obstacle clearance in Alzheimer’s disease. Neurology. 1995;45:908 –914. 39 Merory JR, Wittwer JE, Rowe CC, Webster KE. Quantitative gait analysis in patients with dementia with Lewy bodies and Alzheimer’s disease. Gait Posture. 2007;26: 414 – 419. 40 Nakamura T, Meguro K, Yamazaki H, et al. Postural and gait disturbance correlated with decreased frontal cerebral blood flow in Alzheimer disease. Alzheimer Dis Assoc Disord. 1997;11:132–139. 41 O’Keeffe ST, Kazeem H, Philpott RM, et al. Gait disturbance in Alzheimer’s disease: a clinical study. Age Ageing. 1996;25: 313–316.

42 Reed R, Yochum K, Alcott S, Meredith K. Gait characteristics of subjects with senile dementia of the Alzheimer’s type [abstract]. J Am Geriatr Soc. 1992;40:SA79. 43 Tanaka A, Okuzumi H, Kobayashi I, et al. Gait disturbance of patients with vascular and Alzheimer-type dementias. Percept Mot Skills. 1995;80(3 Pt 1):735–738. 44 van Iersel MB, Hoefsloot W, Munneke M, et al. Systematic review of quantitative clinical gait analysis in patients with dementia. Z Gerontol Geriatr. 2004;37: 27–32. 45 Visser H. Gait and balance in senile dementia of Alzheimer’s type. Age Ageing. 1983;12:296 –301. 46 Stratford PW. Getting more from the literature: estimating the standard error of measurement from reliability studies. Physiother Can. 2004;56:27–30. 47 Hauer K, Oster P. Measuring functional performance in persons with dementia. J Am Geriatr Soc. 2008;56:949 –950. 48 Steffen TM, Hacker TA, Mollinger L. Ageand gender-related test performance in community-dwelling elderly people: SixMinute Walk Test, Berg Balance Scale, Timed Up & Go Test, and gait speeds. Phys Ther. 2002;82:128 –137. 49 Toulotte C, Fabre C, Dangremont B, et al. Effects of physical training on the physical capacity of frail, demented patients with a history of falling: a randomised controlled trial. Age Ageing. 2003;32:67–73. 50 Roach KE, Tappen RM. Factors related to decline in ambulation ability in institutionalized individuals with Alzheimer’s disease [abstract]. J Geriatr Phys Ther. 2004;27: 119 –120. 51 Verghese J, Wang C, Lipton RB, et al. Quantitative gait dysfunction and risk of cognitive decline and dementia. J Neurol Neurosurg Psychiatry. 2007;78:929 –935. 52 Rabheru K. Disease staging and milestones. Can J Neurol Sci. 2007;34(Suppl 1):S62–S66.

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Research Report

The Lower Extremity Functional Scale Has Good Clinimetric Properties in People With Ankle Fracture Chung-Wei Christine Lin, Anne M. Moseley, Kathryn M. Refshauge, Anita C. Bundy C-W.C. Lin, BPhty, PGDipHSc, PhD, is NHMRC Postdoctoral Research Fellow, Musculoskeletal Division, The George Institute for International Health, PO Box M201, Missenden Rd, The University of Sydney, New South Wales, 2050 Australia. Address all correspondence to Dr Lin at: clin@george. org.au. A.M. Moseley, BAppSc, GradDip AppSc, PhD, is Senior Research Fellow, Musculoskeletal Division, The George Institute for International Health, The University of Sydney. K.M. Refshauge, DipPhty, GradDipManipTher, MBiomedE, PhD, is Director, Research & Innovation, and Associate Dean, Faculty of Health Sciences, The University of Sydney. A.C. Bundy, BS, MS, ScD (Therapeutic Studies), is Head of Discipline and Chair of Occupational Therapy, Faculty of Health Sciences, The University of Sydney. [Lin C-WC, Moseley AM, Refshauge KM, Bundy AC. The Lower Extremity Functional Scale has good clinimetric properties in people with ankle fracture. Phys Ther. 2009;89:580 –588.] © 2009 American Physical Therapy Association

Background. There is limited information on the clinimetric properties of questionnaires of activity limitation in people after ankle fracture.

Objective. The purpose of this study was to investigate the clinimetric properties of the Lower Extremity Functional Scale, an activity limitation questionnaire, in people with ankle fracture.

Design. This was a measurement study using data collected from 2 previous randomized controlled trials and 1 inception cohort study. Methods. Participants with ankle fracture (N⫽306) were recruited within 7 days of cast removal. Data were collected at baseline and at short- and medium-term follow-ups. Internal consistency and construct validity were assessed using Rasch analysis. Concurrent validity, responsiveness, and floor and ceiling effects were evaluated.

Results. The Lower Extremity Functional Scale demonstrated high internal consistency (␣⬎.90). The variance in activity limitation explained by the items was high (98.3%). Each item had a positive correlation with the overall scale, and most items supported the unidimensionality of the scale. These findings suggest that the scale has high internal consistency and construct validity. The scale also demonstrated high concurrent validity and responsiveness in the short term and no floor or ceiling effects. However, the scale would benefit from more-challenging items, as evident at the medium-term follow-up. Limitations. This was a secondary analysis of existing data sets. Conclusion. The Lower Extremity Functional Scale is a useful tool to monitor activity limitation in people with ankle fracture up to the short-term follow-up. Moredifficult items may need to be added to improve the responsiveness of the scale for longer-term follow-up.

Post a Rapid Response or find The Bottom Line: www.ptjournal.org 580

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Clinimetric Properties of the Lower Extremity Functional Scale

T

he Lower Extremity Functional Scale is a measure of activity limitation developed for musculoskeletal conditions of the lower extremity.1 On this scale, participants rate the difficulty in performing 20 activities of the lower extremity on a 5-point scale (0⫽“extreme difficulty or unable to perform activity,” 4⫽“no difficulty”). The responses are totaled to give a score ranging from 0 to 80, with 0 indicating high levels of activity limitation and 80 indicating low levels of activity limitation. In a heterogeneous population with lower-limb conditions, the Lower Extremity Functional Scale was found to have high internal consistency (␣⫽.96) and high test-retest reliability (r⫽.86) and correlated well with the physical function subscale and the physical component summary scores of the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) (r⫽.80 and .64, respectively).1,2 In addition, the degree of difficulty of the 20 items and their response options (ie, 0 – 4) have been examined,3 and this hierarchy of items (ie, from least difficult to most difficult) provides suggestions for activities that can be used to progress patients in their rehabilitation.4 Since the initial development and clinimetric testing of the scale on a heterogeneous population with lower-limb conditions, the properties of the Lower Extremity Functional Scale have been examined in populations with a single condition (eg, ankle sprain,5 anterior knee pain,6 joint replacement7–9), generally demonstrating robust results in

Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on May 7, 2009, at www.ptjournal.org.

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internal consistency,7–9 concurrent validity,7–9 and responsiveness.5–9 Activity limitation is common after ankle fracture.10 –13 The Lower Extremity Functional Scale is one questionnaire that can be used to monitor improvement in activity limitation after ankle fracture. Despite showing good clinimetric properties in a heterogeneous population with lowerlimb conditions, including ankle fracture,1 properties of the Lower Extremity Functional Scale have not been investigated specifically in people with ankle fracture. Such an investigation is worthwhile because people with ankle fracture may have limitations in different lower-limb activities or experience a different degree of limitation in some activities compared with people with problems at other lower-limb joints. For example, sitting and rolling, 2 of the activities on the Lower Extremity Functional Scale, may not be challenging for people with ankle fracture but would be challenging for people with hip or knee problems. Other commonly used questionnaires measuring activity limitation after ankle fracture are the Olerud Molander Ankle Score14 and the American Orthopedic Foot and Ankle Society (AOFAS) Ankle-Hindfoot Scale.15 There is little information, however, on the clinimetric properties of these scales.10,11,16,17 There is a need to establish the clinimetric properties of these questionnaires of activity limitation for people with ankle fracture. The purpose of this study was to investigate the properties of the Lower Extremity Functional Scale specifically in people with ankle fracture. Internal consistency, construct validity, concurrent validity, responsiveness, and floor and ceiling effects were examined.

Method Data from 3 recently completed studies (N⫽306 in total) were used to

examine the properties of the Lower Extremity Functional Scale in people with ankle fracture.18 –20 Ethical approval was obtained from the participating institutions prior to the conduct of the studies. Study 1 Moseley et al18 conducted a randomized controlled trial of 150 adults to investigate the effectiveness of stretching in addition to a physical therapy exercise program. Participants were recruited from the outpatient physical therapy departments of 2 teaching hospitals in Sydney, Australia, after cast removal. The inclusion criteria were: ankle fracture treated with cast immobilization with or without surgical fixation, cast removed within the preceding 5 days, approval to bear weight as tolerated or partially, no current and significant injuries or pathologies, reduced dorsiflexion passive range of motion (at least 5° less than the unaffected ankle) at cast removal, and referral for outpatient physical therapy. Blinded measurement of outcomes occurred at baseline and at 4 and 12 weeks after entry to the study. The trial found no difference in outcomes among treatment groups, so data from all participants were analyzed together for the current investigation. Study 2 Lin et al19 conducted a randomized controlled trial of 94 adults investigating the effectiveness of joint mobilization in addition to a physical therapy exercise program. Participants were recruited from the outpatient physical therapy departments of 3 teaching hospitals in Sydney, Australia, after cast removal. The inclusion criteria were: ankle fracture treated with cast immobilization with or without surgical fixation, cast removed in the preceding 7 days, approval to bear weight as tolerated or partially, no current and significant injuries or pathologies, pain in the ankle on equal weight

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Clinimetric Properties of the Lower Extremity Functional Scale bearing at cast removal of at least 2 out of 10 on a numerical pain rating scale,21 and referral for outpatient physical therapy. Blinded assessment of outcomes occurred at baseline and at 4, 12, and 24 weeks after entry into the study. The study showed no differences in outcomes between treatment groups, so data from all participants were analyzed together for the current investigation. Study 3 Hancock et al20 conducted an inception cohort study of 62 adults to investigate the predictors of outcome after ankle fracture. Participants were recruited from the outpatient orthopedic clinics of 2 teaching hospitals in Sydney, Australia, at the time of cast removal. The inclusion criteria were: ankle fracture treated with cast immobilization for 3 weeks or longer with or without surgical fixation and approval to bear weight as tolerated or partially. Participants with compensable injury were excluded. Outcome assessments occurred at 6 and 26 weeks after entry into the study. Outcome Measures The Lower Extremity Functional Scale1 was used to measure activity limitation in all 3 studies. In studies 1 and 2, activity limitation also was measured using walking speed and stepping rate on stairs. Walking speed (in meters per second) was measured over a 10-m distance as participants walked as fast and as well as possible without a walking aid. Stepping rate (steps per second) was measured as participants ascended and descended 4 stairs 3 times without using the rail. The average of the 3 attempts was used for both measures. The speed of walking and climbing stairs is commonly used to document outcome in people with reduced mobility and has high test-retest reliability.22,23 In study 3, activity limitation also was measured using the Olerud Molander 582

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Ankle Score.14 The Olerud Molander Ankle Score consists of items of activity limitation (stair climbing, running, jumping, squatting, work and daily activities, use of support for walking) and impairments (pain, stiffness, swelling) and is scored from 0 to 100, with a score of 100 indicating the best possible outcome. It was used as a comparison measure in our investigation of concurrent validity because the Olerud Molander Ankle Score is the most commonly used assessment of activity limitation in studies investigating the effects of rehabilitation for ankle fracture.24

sion 3.64.2).* Rasch analysis converts raw data into interval scores by logarithmic conversion.28,29 Internal consistency of the Lower Extremity Functional Scale was evaluated by the internal reliability coefficient (equivalent of the Cronbach ␣) of the overall scale and the correlation of each individual item to the overall scale.

A global perceived effect scale25 was used to provide an external criterion of the responsiveness of the Lower Extremity Functional Scale. A scale of this kind is the most frequently used external criterion of improvement with which changes in scores on other outcome measures are compared.25–27 In study 1, the global perceived effect was measured on a 5-point scale (“worsened,” “the same,” “improved a little,” “improved a lot,” and “recovered”). In study 2, the global perceived effect was measured on an 11-point scale, from “vastly worse” (⫺5) to “completely recovered” (⫹5). No baseline data on the Lower Extremity Functional Scale were available for study 3; therefore, data from study 3 were omitted from the analysis of responsiveness.

To assess construct validity, the variance in activity limitation explained by the Lower Extremity Functional Scale was analyzed using principal components analysis of the residuals generated by WINSTEPS. In addition, a hierarchy for each item on the Lower Extremity Functional Scale and each participant was created. Item difficulty and participant ability were compared with the assumption made by the Rasch model, which expects that the less-difficult items are more easily accomplished by all participants than the more-difficult items and that a more-able participant (ie, with less activity limitation) is more likely to accomplish a difficult item than a less-able participant (ie, with more activity limitation).28,30 This comparison is demonstrated as 2 pairs of goodness-of-fit (infit and outfit) statistics. Infit statistics are sensitive to responses on items that are closely matched to a participant’s activity limitation. Outfit statistics are sensitive to responses on items that are at the extremes of a participant’s activity limitation.

Data Analysis We examined the internal consistency, construct validity, concurrent validity, responsiveness, and floor and ceiling effects of the Lower Extremity Functional Scale. Internal consistency and construct validity of the Lower Extremity Functional Scale were examined by Rasch analysis28 using WINSTEPS software (ver-

Both goodness-of-fit statistics generate a mean square and a z standardized statistic. The ideal mean square has a value of 1.0,31 indicating that the item being tested conforms to the expectations of the Rasch model and contributes to a single construct measured by the overall scale (ie, unidimensionality).30,32 A mean square value greater than 1.5 indi-

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* Winsteps, PO Box 811322, Chicago, IL 60681-1322.

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Clinimetric Properties of the Lower Extremity Functional Scale cates that the item does not contribute to or distort the scale, and a mean square value greater than 2 indicates that the item distorts the scale.33 Because the aim of the current investigation was to evaluate the properties of an existing scale, rather than to devise a new scale, we adopted a liberal criterion in assessing goodness-of-fit statistics. Only items with a mean square value greater than 2.0 (which indicates that the item distorts the unidimensionality of the scale)33 and a z standardized statistic less than ⫺2.0 or greater than 2.028 were considered for removal from the scale. A Rasch map of item difficulty and participant ability was generated to examine item redundancy and gaps. The ordering of response options (ie, 0 – 4) for each item also was examined. A separate Rasch analysis was conducted for each of the 3 different time points, that is, baseline (studies 1 and 2, n⫽244), short-term follow-up (4 or 6 weeks, all studies, n⫽273), and medium-term follow-up (24 or 26 weeks, studies 2 and 3, n⫽148). Data that were missing due to participant withdrawal from the studies (5.8%) were omitted from analysis. Concurrent validity was assessed at both the short-term (4 or 6 weeks) and medium-term (24 or 26 weeks) follow-ups. We used Pearson correlation coefficients (r) to determine associations between the Lower Extremity Functional Scale scores and walking speed (studies 1 and 2, n⫽230, at the short-term follow-up; study 2, n⫽83, at the medium-term follow-up), stepping rate on stairs (studies 1 and 2, n⫽230, at the shortterm follow-up; study 2, n⫽84, at the medium-term follow-up), and the Olerud Molander Ankle Score (study 3, n⫽60, at both short- and mediumterm follow-ups). For the Rasch analysis, missing data due to participant withdrawal were omitted for evaluaJune 2009

tion of concurrent validity, responsiveness, and floor or ceiling effects (the amount of missing data for each analysis ranged from 3.2% to 11.7%). Two aspects of responsiveness were assessed in both the short-term follow-up (baseline to 4 weeks; studies 1 and 2, n⫽233) and the mediumterm follow-up (baseline to 24 weeks; study 2, n⫽90). The ability of the Lower Extremity Functional Scale to change over time (internal responsiveness)34 was measured using effect size35 and standardized response mean.36 Effect size was calculated as the mean change score (ie, the difference between follow-up score and the baseline score) divided by the standard deviation of the baseline score.35 Standardized response mean was calculated as the mean change score divided by the standard deviation of the change score.36 For both effect size and standardized response mean, a result of greater than 0.80 would indicate that the Lower Extremity Functional Scale had high internal responsiveness.34,37 The ability of the Lower Extremity Functional Scale to detect change in relation to an external criterion (external responsiveness)34 was measured using the Guyatt responsiveness ratio38 and the receiver operating characteristic (ROC) curve.39 The Guyatt responsiveness ratio was calculated as the mean change for participants whose change scores reached the external criterion (the global perceived effect scale) for improvement, divided by the standard deviation of the change for participants whose change scores did not reach the criterion for improvement. The Lower Extremity Functional Scale was considered to have high external responsiveness if the Guyatt responsiveness ratio was greater than 1.96 and the area under the ROC curve was ⱖ0.70.40 Ratings on the external criterion (ie, the global perceived effect scale) were

dichotomized to indicate improvement or lack of improvement. The criteria for improvement were “improved a lot” or “recovered” on the 5-point scale in study 1 and a score of ⫹3 or above on the 11-point scale in study 2. These cutoff points were chosen in order to dichotomize participants into those who had made a reasonable level of improvement and those who had not. Floor or ceiling effects of the total score on the Lower Extremity Functional Scale were examined for baseline (studies 1 and 2, n⫽244), shortterm follow-up (all studies, n⫽282), and medium-term follow-up (studies 2 and 3, n⫽144) scores. Floor or ceiling effects were considered to be present if more than 15% of the participants achieved the lowest or highest possible score, respectively.40 Funding Source for the Study Funding for the studies described in this report was received from the Motor Accidents Authority of New South Wales, Australia, the National Health and Medical Research Council, Australia, the New South Wales Institute of Sport, Australia, and The University of Sydney. Dr Lin was funded by the National Health and Medical Research Council, Australia.

Results The average age of the participants was 45.1 years (SD⫽15.7). About 60% of the cohort had a unimalleolar fracture, and more than half (56.7%) of the cohort had surgical fixation. Participant characteristics and scores on the Lower Extremity Functional Scale are given in Table 1. The Rasch analysis indicated that the Lower Extremity Functional Scale had high internal consistency in people with ankle fracture at all time points (␣⫽.92 at baseline, .94 at the short-term follow-up, and .90 at the medium-term follow-up). Similarly, item correlation was comparable

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Clinimetric Properties of the Lower Extremity Functional Scale Table 1. Characteristics of the Participantsa Characteristic Age (y) Sex (female/male) Fracture severity (unimalleolar/bimalleolar or trimalleolar/missing) Fracture management (surgical/conservative)

Study 2 (nⴝ94)

Study 3 (nⴝ62)

Total (Nⴝ306)

45.9 (15.5)

41.6 (14.6)

49.0 (16.8)

45.1 (15.7)

79/71

43/51

32/30

154/152

85/59/6

61/33/0

37/25/0

183/117/6

83/67

56/38

34/28

173/133

44.9 (12.7)

42.9 (8.3)

43.2 (8.1)

43.9 (10.7)

Lower Extremity Functional Scale score at baseline (/80)

28.80 (11.88)

33.68 (12.62)

N/A

30.68 (12.37)

Lower Extremity Functional Scale score at the shortterm (4 or 6 wk) follow-up (/80)

53.48 (13.70)

56.04 (12.71)

51.10 (13.29)

53.79 (13.39)

Lower Extremity Functional Scale score at the longterm (24 or 26 wk) follow-up (/80)

N/A

71.93 (10.63)

65.70 (12.30)

69.44 (11.70)

Length of cast immobilization (d)

a

Study 1 (nⴝ150)

Means (SD) are given for continuous data, and counts are given for categorical data. N/A⫽not applicable, as data were not collected at this time point.

Table 2. Goodness-of-Fit Statistics for the Lower Extremity Functional Scale Items That Failed to Conform to Rasch Expectationsa Infit Statistics Mean Square

Mean Square

z Standardized Statistic

Hopping

1.59

2.9

9.90

7.8

Hobbies, recreational or sporting activities

1.47

3.5

3.43

8.2

Sitting for 1 hour

1.32

2.2

2.20

3.6

Short-term follow-up

Sitting for 1 hour

1.25

1.4

2.06

2.2

Medium-term follow-up

Sitting for 1 hour

1.37

1.4

3.89

2.5

Measurement Baseline

a

Outfit Statistics

z Standardized Statistic

Item

The misfit (mean square greater than 2.00 and z standardized statistic less than ⫺2.0 or greater than 2.0) occurred in the outfit statistics of all items.

across the 3 time points. All items of the Lower Extremity Functional Scale had a positive correlation with the overall scale, ranging from .21 (“sitting for 1 hour” at the mediumterm follow-up) to .86 (“running on uneven ground” at the medium-term follow-up). The variance explained by the items on the scale was high (92.0% at baseline and 94.2% and 95.9% at the short- and medium-term follow-ups, respectively). Item misfits most frequently occurred at baseline than at either of the follow-ups, but most items had goodness-of-fit statistics within the accepted range (Tab. 2). The misfitting occurred in the outfit statistics for all of the misfit items. “Sitting for 1 hour” was a misfit at all time points. 584

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Difficulty of the items ranged from “sitting for 1 hour” (least difficult) to “making sharp turns while running fast” or “running on uneven ground” (most difficult). At baseline and the short-term follow-up, there was an adequate spread of items differentiating the progress of participants from low to high ability (ie, high to low activity limitation) and no overlapping of items. At the mediumterm follow-up, the spread of items was adequate for participants of low to medium ability, but there was no item for a small proportion of participants who had high ability (ie, low activity limitation; Figure). The response options (0 – 4) progressed in a sequential manner for most items at all time points, indicating that as

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overall scores increased, the item scores also increased. Concurrent validity of the Lower Extremity Functional Scale was excellent compared with the Olerud Molander Ankle Score at the short- and medium-term follow-ups (r⫽.80 and .87, respectively). The correlation with walking speed and stepping rate on stairs was moderate at the short-term follow-up (r⫽.61 and .63, respectively) but poor at the medium-term follow-up (r⫽.24 and .39, respectively). The Lower Extremity Functional Scale had high internal responsiveness at both the short- and mediumterm follow-ups (Tab. 3). The exterJune 2009

Clinimetric Properties of the Lower Extremity Functional Scale

Figure. Rasch map of item difficulty and participant ability at the medium-term follow-up (n⫽148). This is plotted on a logit scale (7 to ⫺4), with 0 indicating the item with the average difficulty. Each logit (logarithm of odds units) represents an increase in the odds of a participant succeeding on an item by 2.716 times.30 Items placed on the same level and separated by semicolons have identical item difficulty. Each # represents 2 observations.

nal responsiveness also was high at the short-term follow-up (Tab. 3). At the medium-term follow-up, the Guyatt responsiveness ratio was below the threshold level (1.96). AlJune 2009

though the mean area under the ROC curve showed that the Lower Extremity Functional Scale had high external responsiveness, the 95%

confidence interval included values below 0.70, suggesting uncertainty. No participant scored the lowest possible score of 0/80 at baseline or

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Clinimetric Properties of the Lower Extremity Functional Scale Table 3. Responsiveness of the Lower Extremity Functional Scalea Short-term Follow-up (Baseline to 4 wk)

Medium-term Follow-up (Baseline to 24 wk)

Effect size

1.92

3.33

Standardized response mean

1.91

2.95

Measure Internal responsiveness

External responsiveness

a

Guyatt responsiveness ratio

1.99

1.74

Area under the ROC curve

0.79 (95% CI⫽0.70–0.88)

0.84 (95% CI⫽0.57–1.10)

ROC⫽receiver operating characteristic, CI⫽confidence interval.

at the short- or medium-term followup, indicating no floor effect. In addition, the Lower Extremity Functional Scale did not have a ceiling effect at baseline or at the short-term follow-up (proportion of participants scoring the highest possible score of 80/80 was 0% for both time points). The proportion of participants scoring the highest possible score at the medium-term follow-up (14%) was below but close to the threshold of 15%.

Discussion and Conclusions Our findings suggest that the Lower Extremity Functional Scale has good clinimetric properties for evaluating people with ankle fracture. The Lower Extremity Functional Scale demonstrated high internal consistency and construct validity and was capable of capturing the progress of people in the short term. In general, the Lower Extremity Functional Scale correlated well with other measures of activity limitation. It was responsive to change in the short term and had no floor or ceiling effects. However, there was uncertainty on the medium-term responsiveness of the Lower Extremity Functional Scale, which may be related to a lack of difficult items that could reflect changes in activity limitation for participants of high ability during this period. High internal consistency and construct validity of the Lower Extrem586

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ity Functional Scale were demonstrated using Rasch analysis. At all time points, the scale had a high internal consistency and explained a high variance in activity limitation. All items of the scale had a positive correlation with the overall scale, and most items had goodness-of-fit statistics within the accepted range, indicating that the items contributed to the unidimensionality of the scale. The Rasch analysis also showed that the progression of activity limitation could be captured both across the items and sequentially within most items. There was an adequate spread of items to reflect changes in activity limitation of participants from the time of cast removal to 6 weeks later. Overall, the hierarchy of item difficulty of the Lower Extremity Functional Scale in people with ankle fracture was comparable to that of a heterogeneous population of people with lower-limb conditions.3 Findings from the Rasch analysis, however, suggest that a few modifications could be made when using this scale specifically for people with ankle fracture. First, “sitting for 1 hour” had high outfit statistics at all time points, indicating that it distorted the unidimensionality of the scale. In addition, “sitting for 1 hour” was the easiest item on the hierarchy and one that most participants could easily accomplish at all time points. These findings suggest that this item could be removed from the scale

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when used in people with ankle fracture. Second, the Rasch map (Figure) revealed that there was an inadequate number of items that could monitor the progress of a small proportion of participants with high ability (ie, low activity limitation) at the medium-term (24 or 26 weeks) follow-up. Therefore, if the Lower Extremity Functional Scale is to be used in people with low activity limitation, in people who need to achieve a high level of function (eg, elite athletes), or for long-term follow-up after ankle fracture, moredifficult items would need to be added to the scale to reflect changes of activity limitation in these people. In assessing concurrent validity, we examined the associations of the Lower Extremity Functional Scale to other commonly used measures of activity limitation: walking speed, stepping rate on stairs, and the Olerud Molander Ankle Score. The Lower Extremity Functional Scale correlated well with all of these measures in the short term. In the medium term, concurrent validity was high compared with the Olerud Molander Ankle Score, but was low compared with walking speed and stepping rate on stairs. These findings may be due to the fact that walking and stair climbing are activities that are relatively easy to perform (Figure), so although improvement in these activities could be expected in the short term, this improvement would plateau after the initial recovery period. In contrast, both the Lower Extremity Functional Scale and the Olerud Molander Ankle Score include activities that are more difficult (eg, running). Thus, a low correlation with walking speed or stepping rate in the medium term may be a reflection of a plateau in improvement in walking and stair climbing and indicates the inadequacy of the use of a single task to quantify activity limitation. Our findings concur with studies of concurJune 2009

Clinimetric Properties of the Lower Extremity Functional Scale rent validity of the Lower Extremity Functional Scale in other populations, which showed that correlation of the Lower Extremity Functional Scale was high with other multi-item measures of activity limitation (r⫽.64 –.88),1,7,8,9 such as the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC),41 but low to moderate with single-item measures of activity limitation (r⫽ .07–.59),8 such as the Six-Minute Walk Test. Although the Lower Extremity Functional Scale showed the ability to change in the short term and the medium term (internal responsiveness) and the ability to detect change against an external criterion in the short term (external responsiveness), there was uncertainty in the external responsiveness in the medium term. Our results at the medium-term follow-up were not definitive. The wide confidence intervals of the area under the ROC curve at the medium-term follow-up (Tab. 3) may have been due to the smaller sample size of the data available at this time point (n⫽90). We used the global perceived effect scale as the external criterion because it is commonly used for this purpose, but part of the uncertainty surrounding the external responsiveness of the Lower Extremity Functional Scale and the difference between findings on the internal and external responsiveness at the medium term may be attributed to the uncertain validity and reliability of the global perceived effect scale.42 Our finding on the external responsiveness of the Lower Extremity Functional Scale at the medium-term follow-up is closely related to 2 other findings. First, the proportion of participants scoring the highest possible score at the medium-term follow-up (ie, 14%) was close to the recommended cutoff (ie, 15%) for a ceiling effect,40 suggesting a reduced sensiJune 2009

tivity to monitor change beyond this time period. Second, the Rasch item map indicated that the Lower Extremity Functional Scale did not have enough difficult items to capture the progress in the people with high ability (ie, low activity limitation) at the medium-term follow-up. One limitation of the current study is that we do not have data after 26 weeks from the time of cast removal. If improvement in activity limitation continues to be made beyond our follow-up period, then it is likely that the Lower Extremity Functional Scale may demonstrate a ceiling effect and inadequate responsiveness. We used existing data sets to assess clinimetric properties of the Lower Extremity Functional Scale. Future research could collect a cohort of subjects for a longer period of time (more than 26 weeks/6 months after cast removal) to validate the findings of this study and investigate responsiveness and ceiling effects in the long term. Although we did not have the optimal study design for assessing clinimetric properties, our study presents the most complete information to date on the clinimetric properties of a questionnaire of activity limitation in ankle fracture. Little information is available on the clinimetric properties of other questionnaires. Previous studies in people with ankle fracture11 or ankle or foot problems17 showed that the concurrent correlation of the Olerud Molander Ankle Score and the AOFAS Ankle-Hindfoot Scale with the physical component of the SF-36 was moderate (r⫽.58)11 and low (r⫽.34).17 No data are available on other clinimetric properties. Until more-complete information is available on other questionnaires of activity limitation, our results support the use of the Lower Extremity Functional Scale in the short term to monitor activity limitation in people after ankle fracture.

Clinimetric properties of the Lower Extremity Functional Scale have previously been tested in a heterogeneous population of people with lower-limb conditions and some homogeneous populations of people with lower-limb conditions. Our findings confirm that the Lower Extremity Functional Scale has high internal consistency, construct validity, and concurrent validity; no floor or ceiling effects; and good responsiveness in the short term for people with ankle fracture. Responsiveness in the medium term warrants further validation. Nevertheless, the good clinimetric properties demonstrated by the Lower Extremity Functional Scale indicate that this scale provides a useful tool, at least in the short term, for monitoring activity limitation in people after ankle fracture. Dr Lin, Dr Moseley, and Dr Refshauge provided concept/idea/research design, writing, project management, and fund procurement. Dr Lin and Dr Moseley provided data collection and institutional liaisons. All authors provided data analysis. Dr Bundy provided research design (Rasch analysis) and writing. The authors thank Dr Mark Hancock and Mike Linacre for their assistance in this research. Funding for the studies described in this report was received from the Motor Accidents Authority of New South Wales, Australia, the National Health and Medical Research Council, Australia, the New South Wales Institute of Sport, Australia, and The University of Sydney. Dr Lin was funded by the National Health and Medical Research Council, Australia. Data were collected at Hornsby Hospital, Ryde Hospital, Royal North Shore Hospital, Royal Prince Alfred Hospital, and St. Vincent’s Hospital, Sydney, Australia. This article was received September 19, 2008, and was accepted March 19, 2009. DOI: 10.2522/ptj.20080290

References 1 Binkley JM, Stratford PW, Lott SA, Riddle DL; North American Orthopaedic Rehabilitation Research Network. The Lower Extremity Functional Scale (LEFS): scale development, measurement properties, and clinical application. Phys Ther. 1999;79: 371–383.

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Clinimetric Properties of the Lower Extremity Functional Scale 2 Ware JE Jr, Sherbourne CD. The MOS 36Item Short-Form Health Survey (SF-36), I: conceptual framework and item selection. Med Care. 1992;30:473– 483. 3 Stratford PW, Hart DL, Binkley JM, et al. Interpreting lower extremity functional status scores. Physiother Can. 2005;57: 154 –162. 4 Haley SM, Fragala-Pinkham MA. Interpreting change scores of tests and measures used in physical therapy. Phys Ther. 2006;86:735–743. 5 Alcock G, Stratford PW. Validation of the Lower Extremity Functional Scale on athletic subjects with ankle sprains. Physiother Can. 2002;54:233–240. 6 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. 7 Jogi P, Kramer JF, Birmingham T. Comparison of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the Lower Extremity Functional Scale (LEFS) questionnaires in patients awaiting or having undergone total knee arthroplasty. Physiother Can. 2005;57:208 –216. 8 Stratford PW, Binkley JM, Watson J, HeathJones T. Validation of the LEFS on patients with total joint arthroplasty. Physiother Can. 2000;52:97–105. 9 Stratford PW, Kennedy DM, Hanna SE. Condition-specific Western Ontario McMaster Osteoarthritis Index was not superior to region-specific Lower Extremity Functional Scale at detecting change. J Clin Epidemiol. 2004;57:1025–1032. 10 Nilsson G, Nyberg P, Ekdahl C, Eneroth M. Performance after surgical treatment of patients with ankle fractures: 14-month follow-up. Physiother Res Int. 2003;8: 69 – 82. 11 Ponzer S, Nasell H, Bergman B, Tornkvist H. Functional outcome and quality of life in patients with Type B ankle fractures: a two-year follow-up study. J Orthop Trauma. 1999;13:363–368. 12 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. 13 Vandenborne K, Elliott MA, Walter GA, et al. Longitudinal study of skeletal muscle adaptations during immobilization and rehabilitation. Muscle Nerve. 1998;21: 1006 –1012. 14 Olerud C, Molander H. A scoring scale for symptom evaluation after ankle fracture. Arch Orthop Trauma Surg. 1984;103: 190 –194. 15 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.

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16 Button G, Pinney S. A meta-analysis of outcome rating scales in foot and ankle surgery: is there a valid, reliable, and responsive system? Foot Ankle Int. 2004;25: 521–525. 17 SooHoo NF, Samimi DB, Vyas RM, Botzler T. Evaluation of the validity of the Foot Function Index in measuring outcomes in patients with foot and ankle disorders. Foot Ankle Int. 2003;27:38 – 42. 18 Moseley AM, Herbert RD, Nightingale EJ, et al. Passive stretching does not enhance outcomes in patients with plantarflexion contracture after cast immobilization for ankle fracture: a randomized controlled trial. Arch Phys Med Rehabil. 2005;86: 1118 –1126. 19 Lin CC, Moseley AM, Haas M, et al. Manual therapy in addition to physiotherapy does not improve clinical or economic outcomes after ankle fracture. J Rehabil Med. 2008;40:433– 439. 20 Hancock MJ, Herbert RD, Stewart M. Prediction of outcome after ankle fracture. J Orthop Sports Phys Ther. 2005;35: 786 –792. 21 Huskisson EC. Measurement of pain. Lancet. 1974;9:1127–1131. 22 Brach JS, Perera S, Studenski S, Newman AB. The reliability and validity of measures of gait variability in community-dwelling older adults. Arch Phys Med Rehabil. 2008;89:2293–2296. 23 Kennedy DM, Stratford PW, Wessel J, et al. Assessing stability and change of four performance measures: a longitudinal study evaluating outcome following total hip and knee arthroplasty. BMC Musculoskelet Disord. 2005;6:3. 24 Lin CWC, Moseley AM, Refshauge KM. Rehabilitation for ankle fractures in adults. Cochrane Database Syst Rev. 2008; 3:CD005595. 25 Pengel LH, Refshauge KM, Maher CG. Responsiveness of pain, disability, and physical impairment outcomes in patients with low back pain. Spine. 2004;29:879 – 883. 26 Beurskens AJ, de Vet HC, Koke AJ. Responsiveness of functional status in low back pain: a comparison of different instruments. Pain. 1996;65:71–76. 27 Hagg O, Fritzell P, Nordwall A; Swedish Lumbar Spine Study Group. The clinical importance of changes in outcome scores after treatment for chronic low back pain. Eur Spine J. 2003;12:12–20. 28 Bond TG, Fox CM. Applying the Rasch Model: Fundamental Measurement in the Human Sciences. Mahwah, NJ: Lawrence Erlbaum Publishers; 2007. 29 Streiner DL, Norman GR. Health Measurement Scales. A Practical Guide to Their Development and Use. Oxford, United Kingdom: Oxford University Press; 2003.

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30 Tennant A, Penta M, Tesio L, et al. Assessing and adjusting for cross-cultural validity of impairment and activity limitation scales through differential item functioning within the framework of the Rasch model: the PRO-ESOR project. Med Care. 2004;42:I37–I48. 31 Wright BD, Linacre JM. Reasonable meansquare fit values. Rasch Meas Trans. 1994;8:370. 32 Hays R, Morales LS, Reise SP. Item response theory and health outcomes measurement in the 21st century. Med Care. 2000;38:28 – 42. 33 Linacre JM. A User’s Guide to WINSTEPS, MINISTEP Rasch-Model Computer Programs. Chicago, IL: Winsteps.com; 2007. 34 Husted JA, Cook RJ, Farewell VT, Gladman DD. Methods for assessing responsiveness: a critical review and recommendations. J Clin Epidemiol. 2000;53:459 – 468. 35 Kazis LE, Anderson JJ, Meenan RF. Effect sizes for interpreting changes in health status. Med Care. 1989;27:S178 –S189. 36 Katz JN, Larson MG, Phillips CB, et al. Comparative measurement sensitivity of short and longer health status instruments. Med Care. 1992;30:917–925. 37 Cohen J. Statistical Power Analysis for the Behavioral Sciences. New York, NY: Academic Press; 1969. 38 Guyatt G, Walter S, Norman G. Measuring change over time: assessing the usefulness of evaluative instruments. J Chronic Dis. 1987;40:171–178. 39 Deyo RA, Diehr P, Patrick DL. Reproducibility and responsiveness of health status measures statistics and strategies for evaluation. Control Clin Trials. 1991; 12: S142–S158. 40 Terwee CB, Bot SDM, de Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007; 60: 34 – 42. 41 Bellamy N, Buchanan WW, Goldsmith CH, et al. Validation study of WOMAC: a health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee. J Rheumatol. 1988;15:1833–1840. 42 Norman GR, Stratford PW, Regehr G. Methodological problems in the retrospective computation of responsiveness to change: the lesson of Cronbach. J Clin Epidemiol. 1997;50:869 – 879.

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Research Report Evaluation of an Item Bank for a Computerized Adaptive Test of Activity in Children With Cerebral Palsy Stephen M. Haley, Maria A. Fragala-Pinkham, Helene M. Dumas, Pengsheng Ni, George E. Gorton, Kyle Watson, Kathleen Montpetit, Nathalie Bilodeau, Ronald K. Hambleton, Carole A. Tucker

Background. Contemporary clinical assessments of activity are needed across the age span for children with cerebral palsy (CP). Computerized adaptive testing (CAT) has the potential to efficiently administer items for children across wide age spans and functional levels.

Objective. The objective of this study was to examine the psychometric properties of a new item bank and simulated computerized adaptive test to assess activity level abilities in children with CP.

Design. This was a cross-sectional item calibration study. Methods. The convenience sample consisted of 308 children and youth with CP, aged 2 to 20 years (X⫽10.7, SD⫽4.0), recruited from 4 pediatric hospitals. We collected parent-report data on an initial set of 45 activity items. Using an Item Response Theory (IRT) approach, we compared estimated scores from the activity item bank with concurrent instruments, examined discriminate validity, and developed computer simulations of a CAT algorithm with multiple stop rules to evaluate scale coverage, score agreement with CAT algorithms, and discriminant and concurrent validity.

Results. Confirmatory factor analysis supported scale unidimensionality, local item dependence, and invariance. Scores from the computer simulations of the prototype CATs with varying stop rules were consistent with scores from the full item bank (r⫽.93–.98). The activity summary scores discriminated across levels of upperextremity and gross motor severity and were correlated with the Pediatric Outcomes Data Collection Instrument (PODCI) physical function and sports subscale (r⫽.86), the Functional Independence Measure for Children (Wee-FIM) (r⫽.79), and the Pediatric Quality of Life Inventory–Cerebral Palsy version (r⫽.74).

Limitations. The sample size was small for such IRT item banks and CAT development studies. Another limitation was oversampling of children with CP at higher functioning levels.

S.M. Haley, PT, PhD, FAPTA, is Associate Director, Health and Disability Research Institute, School of Public Health, Boston University, Medical Campus, 580 Harrison Ave, 2nd Floor, Boston, MA 02218 (USA). Address all correspondence to Dr Haley at: [email protected]. M.A. Fragala-Pinkham, PT, MS, is Research Associate, Research Center for Children With Special Health Care Needs, Franciscan Hospital for Children, Boston, Massachusetts. H.M. Dumas, PT, MS, is Manager, Research Center for Children With Special Health Care Needs, Franciscan Hospital for Children. P. Ni, MD, MPH, is Senior Data Analyst, Health and Disability Research Institute, School of Public Health, Boston University. G.E. Gorton, BS, is Director, Clinical Outcomes Assessment Laboratory, Shriners Hospital for Children, Springfield, Massachusetts. K. Watson, PT, DPT, is Research Specialist, Shriners Hospital for Children, Philadelphia, Pennsylvania. K. Montpetit, OT, MScOT, is Head of Occupational Therapy and Outcomes Coordinator, Shriners Hospital for Children, Montreal, Quebec, Canada. Author information continues on next page.

Conclusions. The new activity item bank appears to have promise for use in a CAT application for the assessment of activity abilities in children with CP across a wide age range and different levels of motor severity. Post a Rapid Response or find The Bottom Line: www.ptjournal.org June 2009

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Computerized Adaptive Testing of Activity in Children With CP N. Bilodeau, OT, MScOT, is Occupational Therapist, Shriners Hospital for Children, Montreal. R.K. Hambleton, PhD, is Executive Director, Center for Educational Assessment, Department of Educational Policy, Research and Administration, University of Massachusetts, Amherst, Massachusetts. C.A. Tucker, PT, PhD, PCS, is Associate Professor, Department of Physical Therapy, College of Health Professions, Temple University, Philadelphia, Pennsylvania. [Haley SM, Fragala-Pinkham MA, Dumas HM, et al. Evaluation of an item bank for a computerized adaptive test of activity in children with cerebral palsy. Phys Ther. 2009;89:589 – 600.] © 2009 American Physical Therapy Association

Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on May 7, 2009, at www.ptjournal.org.

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T

he importance of using valid and reliable measures to evaluate the impact of surgical, pharmacological, and therapeutic interventions for children with cerebral palsy (CP) is well accepted.1– 4 Over the past decade, clinicians and researchers have placed a renewed emphasis on activity-level measures to evaluate the impact of health care interventions on children’s physical functioning in home, school, and community settings.5–7 The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) defines activity as the execution of specific tasks or actions by an individual.8 We used this definition to guide the development of an activity scale highlighting physical functioning. We included physical tasks and skills from the mobility; self-care; domestic life; and community, social, and civic life components of the ICF. We excluded tasks and skills that had a primary focus on cognition and behavior. The use of parent-report measures is an accepted method for documenting the physical functioning of a child with CP in home and community environments.6,9 –11 Parentreport measures such as the Pediatric Evaluation of Disability Inventory (PEDI)12 and the Pediatric Outcomes Data Collection Instrument (PODCI)13 are commonly used in clinic and research settings to measure activitylevel abilities in children with CP. Other instruments, such as the Activity Scale for Kids (ASK),14 the Pediatric Quality of Life–Cerebral Palsy version (PedsQL-CP),15 the Functional Assessment Questionnaire (FAQ),16 and the Functional Mobility Scale (FMS),17 also have been used to measure activity-level changes in children with CP. These measures yield data that are reliable and valid; however, as individual instruments, all have limitations. The FAQ and FMS concentrate on functional mo-

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bility only, whereas the ASK, PEDI, and PODCI include other areas of function such as self-care and play, but may not assess mobility skills in sufficient depth. The PODCI combines health-related quality-of-life questions with physical function questions, thereby limiting content breadth and specificity.18 The PEDI and PODCI can take 30 minutes or more to administer, which often creates a substantial response burden in a busy clinic or a research study with multiple outcome measures. Other limitations of these scales include ceiling and floor effects when used across wide age and ability ranges and limited item content, especially in the areas of more-complex tasks.3 There is a need for a parent-report measure that: (1) can be used to document activity abilities at program and individual child levels, (2) is inclusive of young children and teen age groups, and (3) is feasible to administer in a clinical setting. Yet, fixed-length instruments that cover a broad range of ages and functional abilities often have too many items and are overly burdensome. Using traditional methods, it has become clear that no single, fixed-length instrument can meet these content and psychometric standards for children and youth with CP throughout a wide age range (2–21 years).19 The use of computerized adaptive testing (CAT) provides an alternative approach to these measurement and practical issues.20 Computerized adaptive testing utilizes a software algorithm that selects questions appropriate to the child’s functional ability by using previous responses to create a score estimate. Item information functions,20 based on the locations and discrimination of each item, form the basis for the selection of each new item within the CAT program, as the item with the maximum information at the current score level is chosen. In effect, items June 2009

Computerized Adaptive Testing of Activity in Children With CP administered in a CAT are customized to the individual parent-report of the child’s functional level by skipping items that are clearly too easy or too difficult for the child’s expected capabilities, given the previous responses. Computerized adaptive testing software shortens or lengthens the test to achieve the desired precision and scores all children on a standard metric so that results can be compared across children. The potential advantages of CAT programs in the evaluation of functional abilities of children have been documented previously.21–28

Table 1. Demographic Characteristics of Samplea Variable

Value

Age (y) X

10.68

SD

4.0

Range

2–20

Age groups (y), count (%) ⬍5

17 (5.52)

5–9

114 (37.01)

10–14

123 (39.94)

15–19

50 (16.23)

ⱖ20

4 (1.30)

% female

45.13

Ethnicity, % Hispanic or Latino

8.12

Race, count (%) (n⫽303)

Starting from a list of items adapted from existing instruments and newly created items, we collected parentreport data on a new item bank to measure the ability of children with CP to perform activities in their home and community environments. Our goal was to build an item bank that would cover relevant clinical ages (2–21 years) and levels of severity of children and youth with CP typically seen at the Shriners Hospitals for Children (SHC) orthopedic hospitals. In order to fully assess the potential usefulness of the item bank, we created simulations of CAT scores based on the data collected during the item bank calibration phase. Computerized adaptive testing simulations are a common approach for investigating the merits of an item bank and its potential for providing the foundation for a CAT program.29 During the simulation program, as items are selected for administration to parents, responses are taken directly from the actual data set. The complete set of activity item responses and subsequent score estimates serve as the criteria against which CAT-based scores are compared. The purpose of this study was to examine initial psychometric properties (unidimensionality; local item dependence; item invariance, includJune 2009

% Asian

9 (2.97)

% other

12 (3.96)

% African American

22 (2.26)

% white

260 (85.9)

Gross Motor Functional Classification System level, count (%) I

75 (24.35)

II

91 (29.55)

III

79 (25.65)

IV

37 (12.01)

V

26 (8.44)

Manual Ability Classification System level, count (%) I

94 (30.52)

II

122 (39.61)

III

55 (17.86)

IV

18 (5.84)

V

19 (6.17)

Type of cerebral palsy, count (%) (n⫽307) Diplegic

145 (47.23)

Hemiplegic

73 (23.78)

Quadriplegic

89 (28.99)

Environment/school, count (%) (n⫽306) No school

13 (4.2)

Preschool

11 (3.6)

Day school

219 (71.3)

Residential school

45 (14.7)

Home school

13 (4.2)

College/university, lives at home

3 (1.3)

College/university, lives on campus

2 (0.7)

Respondents’ education level, count (%) (n⫽247) Less than 9th grade

a

2 (0.81)

Some high school

12 (4.86)

High school graduate

58 (23.00)

Some college

60 (24.26)

College graduate

79 (31.50)

Graduate school

36 (15.57)

N⫽308 unless otherwise specified.

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Computerized Adaptive Testing of Activity in Children With CP ing stability across groups and differential item functioning [DIF]; scale coverage; score agreement with CAT algorithms; and discriminant and concurrent validity) of an activity item bank and resulting simulated CAT program designed specifically to assess activity level and physical function in children with CP. Our long-term goal was to create a series of multifaceted item banks that can assess global physical health, upperand lower-extremity skills, and activity via CAT technology for the monitoring of functional outcomes and the assessment of change with interventions.30 In this article, we report on the results of the activity scale.

Method Participants Parent-report data were collected on a convenience sample of 308 children and youth with CP. Inclusion criteria were: a diagnosis of CP, ages 2 to 20 years, and parents with a primary language of English. Participants were excluded if they had had surgical or pharmacological interventions within the past 6 months. Often after these interventions, deterioration in ambulation or hand function may be observed due to orthopedic restrictions, and children’s functional abilities may not correlate with their baseline abilities or overall severity level. Data were collected across 3 SHC orthopedic hospitals in Philadelphia, Pennsylvania, Montreal, Canada, and Springfield, Massachusetts, and at Franciscan Hospital for Children (FHC), Boston, Massachusetts. The mean age of the sample was 10.7 years (SD⫽4.0). Demographic characteristics of the sample are presented in Table 1. Our sample is not fully representative of population data reported elsewhere,31 as we have underrepresented children with more-severe gross motor disabilities. Because 2 of the 3 SHC sites were motion laboratory-based facili592

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ties, it was typical at those sites to recruit primarily ambulatory participants. Activity Item Bank The original activity item pool contained 70 items that sampled physical functioning in home and community settings. These items were identified from review of similar instruments and related literature, as well as through discussion with clinicians and families. Conceptually, we decided that daily activity tasks typically involved a combination of upper- and lower-extremity skills, required several steps to complete, and included skills needed for family routines, play, and school activities. The areas of focus in this construct included basic and instrumental activities of daily living (ADL) and sports, play, and recreation activities. Based on the judgment of clinicians and researchers at SHC and FHC and the results of cognitive testing,32 we were able to reduce the items to be tested from 70 to 45. Items were removed if item wording appeared ambiguous, an item had similar content to items in the loweror upper-extremity skills scales, items depended on adaptive devices, or activities were not relevant for all children (such as putting on a brace or doing a home exercise program). Procedure Activity items along with items from the 3 other scales (global physical health, lower-extremity and mobility, and upper-extremity skills) were administered to parents using a PCbased tablet. The global physical health scale33 assesses pain and fatigue, the upper-extremity skills scale34 samples functional status in hand and dexterity skills, and the lower-extremity and mobility scale35 examines lower-extremity functioning and mobility, including mobility with devices. In a few cases (n⫽11), parents who were unable to complete the survey during the clinic

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visit completed it at home using a Web-based interface. For the calibration testing, the activity items were rated by a parent or caregiver and were judged on the basis of the following 5-point rating scale: 0⫽“unable to do,” 1⫽“with much difficulty,” 2⫽“with some difficulty,” 3⫽“with a little difficulty,” and 4⫽“without any difficulty.” External Measures Severity of CP initially was rated by the parents and then confirmed by the research staff using the Gross Motor Function Classification System (GMFCS),36 which rates children on a 5-point severity scale based primarily on ambulatory ability, and the Manual Ability Classification System (MACS),37 which categorizes children on a 5-point severity scale based on hand function and dexterity. Both classification systems have been shown have reliability and validity for use in children and youth with CP.37–39 Concurrent validity comparisons were chosen on the basis of whether the instruments were currently used across many of the SHC hospitals. To serve as concurrent validity comparisons, subsets of parents also completed the PODCI40 (n⫽168), the PedsQL-CP15 (n⫽77), and the Functional Independence Measure for Children (Wee-FIM)41 (n⫽113). The PODCI was developed specifically to assess changes following pediatric orthopedic interventions for a broad range of diagnoses, including CP. The dimension most similar to the new activity scale was the subdomain of physical function and sports. The Wee-FIM is a standard outcome measure used in many of the SHC hospitals, and its scores include a motor function score. The PedsQL-CP is an adapted form of the generic PedsQL developed specifically for children with CP. The most relevant subscale within the PedsQLCP is daily activity. June 2009

Computerized Adaptive Testing of Activity in Children With CP Data Analysis Unidimensionality. Item Response Theory (IRT) and CAT methods assume certain measurement properties of item sets. These include the assumptions of unidimensionality, local independence, and stability of item parameters (item invariance) across groups (eg, types of CP). Item sets that violate these assumptions may be less effective in modeling the latent variable and may limit the accuracy of a CAT instrument.42,43 We tested the latent structure of the activity items by confirmatory factor analyses (CFAs)44 and evaluated item loadings and residual correlations among items using Mplus software.45,* Model fit was assessed by multiple fit indexes such as the Comparative Fit Index (CFI), the Tucker Lewis Index (TLI), and root mean square error approximation (RMSEA). Recent simulation reports suggest that for most of the fit indexes, it is difficult to establish strict cutoff criteria.46,47 We used unweighted least squares means and variance-adjusted estimation methods, which are more precise when analyzing small to moderatesize samples with skewed categorical data.48,49 Four pieces of evidence were reviewed to determine the extent to which a unidimensional model adequately represented the activity scale: (1) item loadings on the primary factor, the percentage of variance attributed to the first factor, and the ratio of eigenvalues between the first and second factors; (2) results from overall model fit tests; (3) residual correlations between all possible pairs of items; and (4) the patterns of inter-item correlations among items. We retained items with factor loadings greater than 0.4 in the item bank. We considered items with residual correlations greater than 0.2 to be locally dependent items.50

* Muthe´n & Muthe´n, 3463 Stoner Ave, Los Angeles, CA 90066.

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Item calibrations, fit, and score estimates. The item parameters for each scale were estimated using the Graded Response Model (GRM), but by restricting the slope parameter to a single value.51 This oneparameter logistic model using GRM was selected as the best solution for this phase of the project because of the relatively small sample size and the observation that most of the items had high, but similar, pointbiserial correlations, suggesting that discrimination did not vary much across items. The item parameters and fit statistics were calculated using PARSCALE,51,† which is based on marginal maximum likelihood estimation. We evaluated item fit using the likelihood ratio chi-square statistic. Probability values less than .05 suggest item misfit. We evaluated the individual scores by weighted maximum likelihood estimation.52 The individual scores were standardized to a mean of 50 and standard deviation of 10 (T-scale). Item invariance. To examine item parameter stability, we grouped the participants into high- and lowfunction groups according to activity ability level and calculated the correlation between the item parameters estimated based on those 2 groups. With IRT, the child’s score on an item should depend entirely on the latent variable (ability to perform activities). Significant DIF indicates that variables other than the activity variable, such as age (⬍11 years, ⱖ11 years), type (hemiplegic, diplegic, quadriplegic), or severity of CP (as assessed with the GMFCS or the MACS), are likely influencing the responses.53 The analysis of DIF was conducted using ordinal logistic regression.54 If a variable produced significant model coefficients and explained more than 2% of the vari† Scientific Software International Inc, 7383 N Lincoln Ave, Ste 100, Lincolnwood, IL 607121747.

ance, considering the total score, then an item was considered to exhibit DIF. Because of the number of items that were analyzed in the final item bank (36 items), the alpha level was set to .0014 (using the Bonferroni adjustment, .05/36). If the likelihood ratio test was statistically significant and the R-square change was greater than .07, we designated that as large DIF. If the likelihood ratio test was statistically significant and the R-square change was between .035 and .07, we designated that as moderate DIF. Otherwise, values indicated small DIF. Scale coverage. To evaluate the matching of item content with the estimated activity scores of the sample, we produced parallel item maps in which item category expected values55 and person scores were plotted on the same metric (X⫽50, SD⫽10). The expected value is the sum of the category values multiplied by their probabilities:

冘 j ⫻ P 共␪ 兲, m

E i (␪)⫽

ij

j⫽1

where Ei(␪) is the expected value for item i at score level ␪, m is the number of rating scale categories, and Pij(␪) is the category probability for item i category j at score ␪. The logit score that is the best estimate of the expected value is in the middle range of each response category. For each item, the expected value of each response category (5 per item) was plotted in this item map. These expected item response category values are used rather than step estimates because the expected values are more representative of the full content range of each item. The content range was based on estimated locations of the item-response categories that represent the lowest and highest levels of ability of the sample. In addition, we identified

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Computerized Adaptive Testing of Activity in Children With CP Table 2. Confirmatory Factor Analysis Results From the Activity Item Bank Variable

Activity (45 Items)

No. of items

45

36

486.276 (90, ⬍.001)

334.074 (78, ⬍.001)

Comparative Fit Index

0.884

0.936

Tucker-Lewis Index

0.982

0.989

Root mean square error approximation

0.120

0.103

0.521⬃0.915

0.607⬃0.918

.674

.708

␹2 (df, P)

Standardized factor loadings Average R-square a

Activity (36 Items)

a

Average R-square is the average variation in the items that could be explained by this one factor.

the number of individuals who received the highest possible score (ceiling) and the lowest possible score (floor). CAT real data simulations. We based the activity CAT algorithms on the HDRI software24 developed at the Health and Disability Research Institute, Boston, Massachusetts. The CAT software includes options for item selection, score estimation using weighted likelihood,52 and stop rules based on either the number of items, level of precision, or both. We used a real data simulation approach for investigating the merits of CAT; that is, the complete set of the actual item responses of parents to estimate their ability in activity items (IRT criterion score) served as the criterion against which scores from the CAT were compared. As items were selected for administration in the simulation, responses were taken from the actual data set. We selected the item “getting up from the floor” to be the first activity item administered to all participants because its difficulty parameter was in the middle of the range and content seemed appropriate for most children. After each response, an estimated score based on all administered items to that point in the simulation and the associated standard error was calculated. The selection of the next item was based on the item that could 594

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provide the highest information at the estimated score. We established specific stop rules based on the number of items (5, 10, or 15) and did not use precision for stop rule decisions. The validity of this real data simulation approach for studying CAT estimated scores assumes that people respond in much the same way to items regardless of their context; that is, items that precede or follow or short versus long forms would not influence a person’s responses to items. Basically, this is the assumption of independence of item responses that is made with all common IRT models. In the present study, we developed 3 CAT scores in the simulations to reflect the 3 stop rules based on number of items (CAT-15, CAT-10, and CAT-5). These simulated scores were compared with a “gold standard” (ie, the actual IRT latent trait score for activity estimated by the full item bank). Discriminant and concurrent validity. Our logic in analyzing the concurrent and discriminant validity was to determine whether the person score estimates from the full item bank and the 3 CAT versions could produce interpretable scores. The ability of the full item bank and each CAT version (5-, 10-, and 15item stop rules) to discriminate between groups of children based on levels of severity was evaluated by

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comparing average scores across the MACS and GMFCS levels using oneway analysis-of-variance tests with post hoc comparisons. Because of the relatively small numbers in GMFCS and MACS levels IV and V, we combined them. To assess concurrent validity, Pearson correlations were calculated between the full item bank and the PODCI physical function and sports skills summary score, the WeeFIM motor score, and the PedsQL-CP daily activity and school activity subscales. Funding Source for the Study This study was supported by the Shriners Hospital for Children Foundation (grant 8957) and an Independent Scientist Award to Dr Haley (National Center on Medical Rehabilitation Research/National Institute of Child Health and Human Development/National Institutes of Health, grant K02 HD45354 – 01A1).

Results We reduced the available activity items from 45 to 36 items as the final item bank. These 36 items met all of the criteria for the final item bank and were incorporated into the CAT simulation program. Items were removed based on poor item fit, low discrimination, or redundant content, as described below. The Cronbach alpha for the 36-item scale was .98. Unidimensionality Based on the final item bank of 36 items, one factor explained 72% of the item variance, and all of the factor loadings were moderate to very high (range⫽0.607– 0.918). The ratio of the first factor to the second factor was 18.8:1. The CFI and TLI values indicated acceptable fit; the RMSEA of 0.103 was higher than the acceptable range. A summary of the CFA results for the 45- and 36item scales is provided in Table 2. The average inter-item correlation was .70 (SD⫽.09). Based on the multiple fit indexes, factor analysis, June 2009

Computerized Adaptive Testing of Activity in Children With CP and inter-item correlation results, we concluded that the unidimensionality assumptions of the activity scale were met. There were no residual correlations greater than .2, so the local independence assumption also was satisfied. Item Calibrations and Fit The data fit the GRM fixed slope (␹2⫽842, df⫽815, P⫽.243). The item fit was generally acceptable in the final item bank, with the exception of 2 items (“eats a meal” [P⫽.014] and “gets into and out of a car” [P⫽.02]). We chose to retain these items in the bank due to their importance of content or their location along the activity scale.

Figure 1. Item map for activity scale. The item categories are represented by the activity summary score that produces the expected value in the middle of each category range. The expected value is defined by the sum of the category values multiplied by their probabilities.

Item Invariance We examined item parameters stability by grouping participants into high- and low-function groups according to activity ability level; the correlation between the item parameters estimated based on those 2 groups was .88. The activity items in the final item bank are listed in the Appendix. No DIF was noted for MACS level. Only one item (“climbs and moves on high playground equipment”) showed moderate DIF for age. Two items (“hops and skips while playing games with other children of similar age, such as during hopscotch or a relay race” and “prepares to eat a meal”) showed moderate DIF in CP diagnosis. Children with quadriplegia had more difficulty with these 2 items compared with children with either hemiplegia or diplegia. Three similar items (“prepares to eat a meal,” “crosses a quiet 2-lane neighborhood street,” and “keeps up with other children of similar age while walking up stairs”) showed moderate DIF in GMFCS levels, with children with greater gross motor severity having more difficulty with these items. Because of their important content, as indicated during the cogJune 2009

Figure 2. Discriminant validity of the activity scale with the Manual Activity Classification System. Bar graphs depict average score (95% confidence interval) at different manual severity levels with different Computerized Adaptive Test item stop rules in comparison with the full item bank.

Figure 3. Discriminant validity of the activity scale with the Gross Motor Function Classification System. Bar graphs depict average score (95% confidence interval) at different gross motor severity levels with different Computerized Adaptive Test item stop rules in comparison with the full item bank.

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Computerized Adaptive Testing of Activity in Children With CP Table 3. Comparison of Scores From Simulated Computerized Adaptive Testing (CAT) and Full Item Bank Activity (36 Items) Variablea

X

SD

Range

Full item bank

50.67

8.91

28.3–74.0

CAT-15

50.63

8.89

28.6–72.6

.979

Discussion

CAT-10

50.54

8.87

28.9–71.7

.971

CAT-5

50.38

8.88

29.5–69.9

.933

Assessment of the conduct of daily activities at home and school is a key component of an overall health and functional evaluation for children with CP.6,18 The ability of children with CP to perform age-related daily activities can offer significant challenges and can help determine the long-term effects of specific interventions and the quality of an overall rehabilitation and physical therapy program. The determination of the impact of interventions, both at the program level and for individual children with CP, has become complicated. Different hospitals, clinics, and programs, both within and outside the SHC system, use current parent-report instruments cannot easily be compared. The results of this study suggest that a single activity scale might provide a uniform assessment approach for children with CP across a wide age range and across multiple levels of severity.

r

a

CAT-15⫽CAT version with 15-item stop rule, CAT-10⫽CAT version with 10-item stop rule, and CAT5⫽CAT version with 5-item stop rule.

nitive testing sessions, we did not remove any of the DIF items at this time. In the future, these items may be removed or revised. Scale Coverage We found generally good coverage of the sample with the 36 items, as indicated in Figure 1, which displays the item map of person scores and expected response category values for all 36 items. For example, the expected category value for “unable to do” for the item “eats a meal” (easiest item) is about 26 on the mean of 50 (SD⫽10) metric. The expected category value for “without any difficulty” for the most-difficult item (“hikes or jogs for 2 or more miles”) is about 75. Locations for all of the other categories for the other items in between are depicted in Figure 1. There were minimal ceiling effects (n⫽3 [1%]) and floor effects (n⫽11 [3.6%]). A couple of areas along the vertical item category scale (around a score of 50 to 60 in Fig. 1) had some small gaps in content coverage. CAT Simulations As reported in Table 3, the descriptive statistics for scores from the 10and 15-item CAT simulations were quite similar to those for the full item bank score. The mean score of the 5-item CAT was slightly lower than the full item bank score, and the variance and range of the 5-item CAT scores were identical. The Pearson 596

was r⫽.86 for scores from the full item bank. All of the Wee-FIM motor scores (r⫽.79) and the PedsQL-CP daily activity scores (r⫽.74) were strongly correlated with the new activity item bank scores.

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correlations between CAT scores and the full item bank scores were quite strong, even in the 5-item CAT simulation, indicating that the CAT scores accurately captured the information from the entire item bank. Discriminant and Concurrent Validity Because of the relatively small number of participants in GMFCS and MACS levels IV and V, the groups were combined for discriminant analyses. The full activity scale with 36 items was able to discriminate across known groups of upperextremity (F3,284⫽53.59, P⬍.0001) and gross motor (F3,287⫽99.58, P⬍.0001) severity levels (Figs. 2 and 3). Post hoc tests yielded significant results across all categories. In addition, 5-item (F3,286⫽92.16, P⬍.0001), 10-item (F3,286⫽101.99, P⬍.0001), and 15-item (F3,287⫽98.55, P⬍.0001) simulated CAT scores were able to discriminate among GMFCS categories, and 5-item (F3,283⫽46.82, P⬍.0001), 10-item (F3,283⫽53.53, P⬍.0001), and 15-item (F3,284⫽53.67, P⬍.0001) simulated CAT scores were able to discriminate among MACS categories. In 5-item CAT simulations, the only adjacent pair that did not show a significant difference was the comparison between the MACS levels II and III. When compared with the PODCI physical function and sports subscale, the activity scale correlation

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Based on the CFAs and item fit analyses, the final set of activity items were sufficiently unidimensional to meet the assumption of IRT modeling. A number of items with large misfit were removed; for example, “social dancing” could be accomplished by, at a very rudimentary level, children in wheelchairs, and children with high levels of physical functioning ability may choose not to take part in dancing activities due either to lack of peer acceptance or to being uncomfortable with the activity. We did keep in the bank a few items that exceeded the threshold for DIF or fit. These items were retained mainly for content. By keeping items in the bank that exhibit either DIF or misfit, the estimation of June 2009

Computerized Adaptive Testing of Activity in Children With CP scores may have been affected negatively. However, these items appeared to have trivial effect on the CAT-15 scores and likely a small effect on the CAT-10 scores. Using the full 36 final items, we found minimal ceiling and floor effects across a very diverse sample of children with CP with a wide age range. The children with the minimum score (n⫽11) were not in the range of 2 to 5 years; the youngest child who received a minimum score was 7 years of age, and the average age of children who received a minimum score was 12 years. These findings indicate that the coverage for all ages was appropriate; we had some problems covering children with the most-severe activity restrictions. We did have relatively small numbers of children at both the low and high ends of the age range of 2 to 21 years. This creates some limitation in knowing how well the scale works for the entire age range. We hope in the future to sample more children in the lower (2–5 years) and higher (14 –21 years) age groups to make sure the item bank is robust for these age groups. As shown in Figure 1, we found only small gaps in item coverage along the full activity scale. A previous study19 has reported major problems with ceiling effects for children with CP at GMFCS level I and floor effects for children with CP at GMFCS levels IV and V. We will need to address the floor effects for children who are most severely involved in future item bank development. The results of the CAT simulations indicate that the 5-, 10-, and 15-item models yield accurate estimates of activity in children with CP. Several other studies on the development of CAT models also have conducted simulations using real data sets, comparing responses to all items in the item bank with CAT simulations of various lengths.21,24,27,28 We believe June 2009

these simulations are likely good approximations of actual CAT administrations, yet some overestimation is possible. In future studies, administration of the full item bank along with the CAT models is recommended in prospective clinical studies to examine accuracy in real clinical situations. These preliminary data indicate that the full item bank and all 3 CAT versions can discriminate among GMFCS and MACS levels for children with CP. It is noteworthy that all of the simulated CAT versions were able to discriminate across the 4 categories (combined IV and V) of the GMFCS and MACS. One limitation we should note is that although the GMFCS is valid for children up through the age of 12 years, we applied it to the entire sample. Future work should use the expanded and revised version of the GMFCS.56 We found the activity scale unable to discriminate between MACS levels II and III. In contrast, we found the companion scale on upper-extremity skills clearly discriminated between these 2 levels.34 The PODCI physical function and sports subscale, the PedsQL-CP daily activity scale, and the Wee-FIM motor scale appear to measure related activity concepts, as indicated by their high positive correlations. Our sample size was relatively small for the analyses that we conducted. The effects of a small sample size were minimized by using a oneparameter model. In the future, a larger sample will be used for the calibration work so that we can be more confident of the findings and extend our analyses to using 2parameter models, if warranted. We decided to publish results at this stage because the findings were compelling and this work is one of the first examples of developing a CAT for children with CP. Our data are not fully representative of popu-

lation-based studies of children with CP, as we have underrepresented children with more-severe limitations in mobility. Nevertheless, we had sufficient low-level activity items for most of the children with low activity levels. We acknowledge an additional concern in the interpretation of the data. We combined arguably 2 modes of data collection—collection of data in the clinic and data collection by parents at home (n⫽11) using the Internet. We combined these modes primarily to increase our sample size. This difference in mode may have created some error and bias; however, we believe any error or bias was small. Although most indicators we used (TLI, CFI, inter-item correlations, factor analysis results) suggested good fit to a unidimensional scale, the RMSE was lower than ideal. These findings may have been due to our effort at putting some nontraditional activity items into the item pool, such as taking part in indoor games and sports. We felt these items were important to the activity scale and should be able to be scaled into one activity scale. Future work will be needed to confirm these findings. There are a number of additional steps in our CAT development that will be needed prior to expectations for widespread use. First, we have conducted test-retest reliability on the activity CAT, and the results will be presented soon in a future report. We are currently testing the sensitivity and responsiveness of the activity CAT in a series of children with lower-extremity surgeries. Another approach has been to expand the item bank to include children with conditions other than CP. In our first phase, we are building and testing new items for children with brachial plexus birth palsy. This effort also may help fill in some items that are

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Computerized Adaptive Testing of Activity in Children With CP needed at the lower end of the activity continuum.

Montpetit, Ms Bilodeau, Dr Hambleton, and Dr Tucker provided consultation (including review of manuscript before submission).

If successful, CAT versions will be used within the SHC system to evaluate activity changes in children with CP after orthopedic surgeries and conservative interventions such as bracing, therapy, and spasticity (hypertonicity) management medications and injections. Using CAT versions of the other scales (global physical health, upperand lower-extremity skills) in conjunction with the activity scale will assist physical therapists and other clinicians in understanding the relationship among changes in different functional areas following rehabilitation interventions.

Human subject approval was obtained at each participating institution and through the Boston University Institutional Review Board.

Conclusion The activity item bank met the required IRT assumptions and covered the range of activity seen in children with CP between ages 2 to 20 years. Based on the CAT simulations, CAT versions of the activity scale yielded summary scores comparable to summary scores estimated using all items and could discriminate across CP severity levels at the same magnitude as the full set of items. We conclude that this initial item bank development work has the potential to produce a CAT that efficiently assesses activity functioning in children with CP. Dr Haley, Ms Fragala-Pinkham, Ms Dumas, Dr Ni, Mr Gorton, Dr Watson, and Dr Tucker provided concept/idea/research design. Dr Haley, Ms Fragala-Pinkham, Ms Dumas, Dr Ni, and Dr Tucker provided writing. Ms Fragala-Pinkham, Ms Dumas, Dr Ni, Mr Gorton, Dr Watson, Ms Montpetit, Ms Bilodeau, and Dr Tucker provided data collection. Dr Haley, Dr Ni, Mr Gorton, Dr Hambleton, and Dr Tucker provided data analysis. Dr Haley and Dr Tucker provided project management. Dr Tucker provided fund procurement and facilities/equipment. Ms FragalaPinkham, Ms Dumas, Mr Gorton, Ms Montpetit, Ms Bilodeau, and Dr Tucker provided participants. Ms Dumas, Ms Montpetit, and Dr Tucker provided institutional liaisons. Ms Fragala-Pinkham, Ms Dumas, Dr Ni, Ms

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This study was supported by the Shriners Hospital for Children Foundation (grant 8957) and an Independent Scientist Award to Dr Haley (National Center on Medical Rehabilitation Research/National Institute of Child Health and Human Development/National Institutes of Health, grant K02 HD45354-01A1). This article was received January 8, 2009, and was accepted March 17, 2009. DOI: 10.2522/ptj.20090007

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10 Pirpiris M, Gates PE, McCarthy JJ, et al. Function and well-being in ambulatory children with cerebral palsy. J Pediatr Orthop. 2006;26:119 –124. 11 Majnemer A, Mazer B. New directions in the outcome evaluation of children with cerebral palsy. Semin Pediatr Neurol. 2004;11:11–17. 12 Haley SM, Coster WJ, Ludlow LH, et al. Pediatric Evaluation of Disability Inventory: Development, Standardization, and Administration Manual. Boston, MA: Trustees of Boston University; 1992. 13 Daltroy LH, Cats-Baril WL, Katz JN, et al. The North American Spine Society Outcome Assessment Instrument: reliability and validity tests. Spine. 1996;21:741–749. 14 Young N, Williams J, Yoshida K, Wright J. Measurement properties of the Activities Scale for Kids. J Clin Epidemiol. 2000; 53:125–137. 15 Varni JW, Burwinkle TM, Berrin SJ, et al. The PedsQL in pediatric cerebral palsy: reliability, validity, and sensitivity of the Generic Core Scales and Cerebral Palsy Module. Dev Med Child Neurol. 2006; 48:442– 449. 16 Novacheck TF, Stout JL, Tervo R. Reliability and validity of the Gillette Functional Assessment Questionnaire as an outcome measure in children with walking disabilities. J Pediatr Orthop. 2000;20:75– 81. 17 Graham HK, Harvey A, Rodda J, et al. The Functional Mobility Scale. J Pediatr Orthop. 2004;24:514 –520. 18 Harvey A, Robin J, Morris M, et al. A systematic review of measures of activity limitation for children with cerebral palsy. Dev Med Child Neurol. 2008;50:190 –198. 19 McCarthy ML, Silberstein CE, Atkins EA, et al. Comparing reliability and validity of pediatric instruments for measuring health and well-being of children with spastic cerebral palsy. Dev Med Child Neurol. 2002;44:468 – 476. 20 Wainer H. Computerized Adaptive Testing: A Primer. Mahwah, NJ: Lawrence Erlbaum Associates; 2000. 21 Coster WJ, Haley SM, Ni P, et al. Assessing self-care and social function using a computer adaptive testing version of the pediatric evaluation of disability inventory Arch Phys Med Rehabil. 2008;89:622– 629. 22 Mulcahey MJ, Haley SM, Duffy T, et al. Measuring physical functioning in children with spinal impairments with computerized adaptive testing. J Pediatr Orthop. 2008;28:330 –335. 23 Jacobusse G, van Buuren S. Computerized adaptive testing for measuring development of young children. Stat Med. 2007; 26:2629 –2638. 24 Haley SM, Ni P, Ludlow LH, FragalaPinkham MA. Measurement precision and efficiency of multidimensional computer adaptive testing of physical functioning using the Pediatric Evaluation of Disability Inventory. Arch Phys Med Rehabil. 2006; 87:1223–1229.

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Computerized Adaptive Testing of Activity in Children With CP 25 Haley SM, Fragala-Pinkham MA, Ni P. Sensitivity of a computer adaptive assessment for measuring functional mobility changes in children enrolled in a community fitness programme. Clin Rehabil. 2006;20: 616 – 622. 26 Haley SM, Ni P, Hambleton RK, et al. Computer adaptive testing improves accuracy and precision of scores over random item selection in a physical functioning item bank. J Clin Epidemiol. 2006;59:1174 – 1182. 27 Haley SM, Ni P, Fragala-Pinkham MA, et al. A computer adaptive testing approach for assessing physical function in children and adolescents. Dev Med Child Neurol. 2005; 47:113–120. 28 Haley SM, Raczek AE, Coster WJ, et al. Assessing mobility in children using a computer adaptive testing version of the Pediatric Evaluation of Disability Inventory (PEDI). Arch Phys Med Rehabil. 2005;86: 932–939. 29 Sands W, Waters BK, McBride JR. Computerized Adaptive Testing: From Inquiry to Operation. Washington DC: American Psychological Association; 1997. 30 Tucker CA, Haley SM, Watson K, et al. Physical function for children and youth with cerebral palsy: item bank development for computer adaptive testing J Pediatr Rehabil Med. 2008;1:237–244. 31 Howard J, Soo B, Graham H, et al. Cerebral palsy in Victoria: motor types, topography and gross motor function. J Paediatr Child Health. 2005;41:479 – 483. 32 Dumas HM, Watson K, Fragala-Pinkham MA, et al. Cognitive interviewing to elicit parent feedback of test items for assessing physical function in children with cerebral palsy. Pediatr Phys Ther. 2008;20:356 – 362. 33 Haley SM, Ni P, Dumas HM, et al. Measuring global physical health in children with cerebral palsy: illustration of a bi-factor model and computerized adaptive testing. Qual Life Res. 2009 Feb 17 [Epub ahead of print]. 34 Tucker CA, Montpetit K, Bilodeau N, et al. Assessment of children with cerebral palsy using a parent-report computer adaptive test, I: upper extremity skills. Dev Med Child Neurol. In press.

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35 Tucker CA, Gorton GE, Watson K, et al. Assessment of children with cerebral palsy using a parent-report computer adaptive test, II: lower extremity and mobility skills Dev Med Child Neurol. In press. 36 Palisano RJ, Rosenbaum PL, Walter S, et al. Development and reliability of a system to classify gross motor function in children with cerebral palsy. Dev Med Child Neurol. 1997;39:214 –223. 37 Eliasson A, Krumlinde-Sundholm L, Ro ¨ sblad B, et al. The Manual Ability Classification System (MACS) for children with cerebral palsy: scale development and evidence of validity and reliability. Dev Med Child Neurol. 2006;48:549 –554. 38 Morris C, Kurinczuk JJ, Fitzpatrick R, Rosenbaum PL. Who best to make the assessment? Professionals’ and families’ classifications of gross motor function in cerebral palsy are highly consistent. Arch Dis Child. 2006;91:675– 679. 39 Wood E, Rosenbaum PL. The Gross Motor Function Classification System for cerebral palsy: a study of reliability and stability over time. Dev Med Child Neurol. 2000; 42:292–296. 40 Daltroy LH, Liang MH, Fossel AH, Goldberg MJ; Group POID. The POSNA Pediatric Musculoskeletal Functional Health Questionnaire: report on reliability, validity, and sensitivity to change. J Pediatr Orthop. 1998;18:561–571. 41 Guide for the Functional Independence Measure for Children (WeeFIM) of the Uniform Data System for Medical Rehabilitation, Version 4.0: Community/ Outpatient. Buffalo, NY: State University of New York at Buffalo; 1993. 42 Hambleton RK, Swaminathan H, Rogers H. Fundamentals of Item Response Theory. Newbury Park, CA: Sage Publications; 1991. 43 van der Linden W, Hambleton RK. Handbook of Modern Item Response Theory. Berlin, Germany: Springer; 1997. 44 Mislevy RJ. Recent developments in the factor analysis of categorical variables. J Ed Stat. 1986;11:3–31. 45 Muthen BO, Muthen L. Mplus User’s Guide. Los Angeles, CA: Muthen & Muthen; 1998.

46 Fan X, Sivo S. Sensitivity of fit indices to model misspecification and model types. Multivariate Behav Res. 2007;42:509 – 529. 47 Chen F, Curran P, Bollen K, et al. An empirical evaluation of the use of fixed cutoff points in RMSEA test statistic in structural equation models. Social Methods Research. 2008;36:462– 494. 48 Xime´nez C. A Monte Carlo study of recovery of weak factor loadings in confirmatory factor analysis. Structural Equation Modeling. 2006;13:587– 614. 49 Maydeu-Olivares A. Limited information estimation and testing of Thurstonian models for paired comparison data under multiple judgment sampling. Psychometrika. 2001;66:209 –228. 50 Reeve BB, Hays RD, Bjorner JB, et al. Psychometric evaluation and calibration of healthrelated quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Med Care. 2007;45(5 suppl 1):S22–S31. 51 Muraki E, Bock RD. PARSCALE: IRT Item Analysis and Test Scoring for Rating— Scale Data. Chicago, IL: Scientific Software International; 1997. 52 Warm TA. Weighted likelihood estimation of ability in item response theory. Psychometrika. 1989;54:427– 450. 53 Hariharan S, Rogers H. Detecting differential item functioning using logistic regression procedures. J Ed Meas. 1990;27:361–370. 54 Crane PK, Gibbons LE, Ocepek-Welikson K, et al. A comparison of three sets of criteria for determining the presence of differential item functioning using ordinallogistic regression. Qual Life Res. 2007; 16(suppl 1):69 – 84. 55 Lai J-S, Cella D, Chang C-H, et al. Item banking to improve, shorten and computerize self-reported fatigue: an illustration of steps to create a core item bank from the FACIT-Fatigue Scale. Qual Life Res. 2003;12:485–501. 56 Palisano RJ, Rosenbaum P, Bartlett D, Livingston MH. Content validity of the expanded and revised Gross Motor Function Classification System. Dev Med Child Neurol. 2008;50:744 –750.

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Computerized Adaptive Testing of Activity in Children With CP Appendix. Item Characteristics and Differential Item Functioning (DIF) Item Difficultya

Pb

Item Score Correlationc

Eats a meal

⫺1.246

.014

.61

Plays freely in the house with other children

⫺0.983

.931

.68

Gets in and out of his/her own bed

⫺0.855

.495

.69

Uses a computer

⫺0.613

.157

.54

Moves around to play with other children

⫺0.46

.698

.74

Gets around in crowded indoor areas

⫺0.419

.816

.72

Cleans up spills on the floor using a rag or a cloth

⫺0.349

.269

.76

Wipes a counter or table

⫺0.331

.413

.77

Item Content

Gets up from the floor

-0.308

.497

.75

Gets into and out of a car

⫺0.271

.02

.81

Uses a public restroom

⫺0.168

.75

.82

Climbs and moves on low playground equipment

⫺0.095

.142

.80

Takes a bath

⫺0.094

.635

.82

Manages a backpack

⫺0.076

.173

.80

Crosses a quiet 2-lane neighborhood street

⫺0.071

.189

.64

Participates in indoor sports or games

⫺0.03

.445

.74

Dresses his or her lower body

⫺0.023

.298

.80

0.008

.171

.82

Takes a shower

DIFd

4

Eats in a cafeteria setting

0.058

.891

.77

Participates in gym class or a group exercise program

0.085

.643

.69

Sets and clears the table for family meals

0.148

.093

.84

Prepares to eat a meal

0.198

.066

.76

4, 5

Keeps up with other children of similar age while walking up stairs

0.412

.892

.80

4

Takes out the garbage

0.479

.629

.80

Cleans the floor using a broom and dustpan

0.502

.19

.81

Plays games or sports that involve kicking a ball with other children of similar age, such as kickball or soccer

0.525

.34

.74

Participates in competitive-level sports

0.608

.082

.61

Makes simple repairs

0.63

.33

.70

Climbs and moves on high playground equipment

0.646

.793

.75

Changes a bed

0.652

.721

.77

Moderately heavy housework

0.69

.666

.77

Yard work

0.723

.16

.78

Launders his or her own clothes using a washer and dryer

0.747

.956

.71

Hops and skips while playing games with other children of similar age, such as during hopscotch or a relay race

0.887

.982

.71

Rides a bicycle without training wheels in the neighborhood

1.053

.625

.61

Hikes or jogs for 2 or more miles

1.263

.688

.65

1

5

a

Logit scale. Likelihood ratio chi-square test P value for each item. Correlation between the item and the person score. d DIF definitions: 1⫽DIF across ages, 2⫽DIF across sexes, 3⫽DIF across Manual Ability Classification System groups, 4⫽DIF across Gross Motor Function Classification System groups, 5⫽DIF across cerebral palsy types (quadriplegic, diplegic, hemiplegic). b c

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Case Report Training of Walking Skills Overground and on the Treadmill: Case Series on Individuals With Incomplete Spinal Cord Injury Kristin E. Musselman, Karim Fouad, John E. Misiaszek, Jaynie F. Yang

Background and Purpose. Walking in the home and community is an important goal for individuals with incomplete spinal cord injury (iSCI). Walking in the community requires various skills, such as negotiating curbs, doors, and uneven terrain. This case report describes the use of a method to retrain walking overground that is intensive, variable, and relevant to daily walking (skill training). The aims of this case series were to determine the effectiveness of skill training in a small group of people with iSCI and to compare skill training with body-weight–supported treadmill training (BWSTT) in the same individuals.

Case Description. Four individuals who were a median of 2.7 years (interquartile range [IQR]⫽12.8) after iSCI participated in alternating phases of intervention, each 3 months long. All patients started with BWSTT. Two patients subsequently engaged in skill training while the other 2 patients engaged in BWSTT, after which a third phase of intervention (opposite to the second) was repeated.

Outcomes. The Modified Emory Functional Ambulation Profile, the 10-Meter Walk Test, the 6-Minute Walk Test, the Berg Balance Scale, and the Activities-specific Balance Confidence Scale were administered before training, monthly throughout training, and 3 months after training. Discussion. Overall improvements in walking speed met or exceeded the minimal clinically important difference for individuals with iSCI (ⱖ0.05 m/s), particularly during the skill training phase (skill training: median⫽0.09 m/s, IQR⫽0.13; BWSTT: median⫽0.01 m/s, IQR⫽0.07). Walking endurance, obstacle clearance, and stair climbing also improved with both types of intervention. Three of the 4 patients had retained their gains at follow-up (retention of walking speed: median⫽92%, IQR⫽63%). Thus, the findings suggest that skill training was effective in this small group of individuals.

K.E. Musselman, BScPT, MSc, is a PhD candidate, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, Alberta, Canada. K. Fouad, PhD, is Professor, Faculty of Rehabilitation Medicine, Centre for Neuroscience, University of Alberta. J.E. Misiaszek, PhD, is Professor, Department of Occupational Therapy, Faculty of Rehabilitation Medicine, Centre for Neuroscience, University of Alberta. J.F. Yang, BScPT, PhD, is Professor, Department of Physical Therapy, Faculty of Rehabilitation Medicine, Centre for Neuroscience, 2-50 Corbett Hall, University of Alberta, Edmonton, Alberta, Canada T6G 2G4. Address all correspondence to Dr Yang at: [email protected]. [Musselman KE, Fouad K, Misiaszek JE, Yang JF. Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury. Phys Ther. 2009;89: 601– 611.] © 2009 American Physical Therapy Association

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Training of Walking Skills in Incomplete Spinal Cord Injury

T

here has been considerable interest in body-weight–supported treadmill training (BWSTT) after incomplete spinal cord injury (iSCI).1 The ultimate goal of gait retraining after iSCI is successful ambulation in the home and community. Walking in the real world encompasses a variety of walking skills, such as negotiating doors, uneven surfaces, slopes, curbs, and obstacles.2 Few studies have investigated whether BWSTT is effective practice for this diverse set of walking skills. The only study that considered functional walking status suggests that BWSTT does not transform individuals with a chronic, American Spinal Injury Association (ASIA) C iSCI into community walkers.3

Greater improvements in walking ability are seen when the training closely resembles the functional task of walking (ie, is task specific).4 Body-weight–supported treadmill training is a very constrained task of repetitive stepping with little variation. Work in animals suggests that repetitive training of one specific task results in improved performance of that task, but at the expense of related, untrained tasks.5,6 Thus, it is unclear how specific walking training should be. Perhaps a highly constrained task is not optimal for community walking.2 Intensive training of a variety of relevant walking skills may better prepare individuals for community walking. A small number of studies have combined BWSTT with overground train-

Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on May 7, 2009, at www.ptjournal.org.

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ing for individuals with iSCI, either concurrently1,7–9 or as a training progression.10 None of the overground training has been based on comprehensive, empirical information of what is required for community living. Here, we report the findings from a case series involving 4 individuals with iSCI who participated in alternating blocks of BWSTT and overground training of walking skills (henceforth called skill training). The tasks practiced in skill training were known to be important for community ambulation.2 The tasks were varied daily to approximate the situation in daily life. The training was intensive—about 1 hour a day, a minimum of 3 times per week, over 3 months. The tasks were challenging (ie, rated as difficult by the patients and could induce falls). Our aims were to determine the effectiveness of skill training and to compare its effectiveness with the method of BWSTT in a small group of individuals.

Patient History and Review of Systems Volunteers were recruited through the Edmonton branch of the Canadian Paraplegic Association and rehabilitation clinics in Edmonton, Alberta. To be included, the patients must have been: (1) ⱖ10 months postinjury and (2) able to walk 5 m overground with or without walking devices or physical assistance. Patients were asked not to begin a new exercise or rehabilitation program or to change medications during the intervention. Informed written consent was obtained from the patients. Patient characteristics are shown in Table 1. Medical histories were noteworthy only for iSCI, with the exception of patient 3, who also had a mild brain injury. Initial walking ability varied among the patients, as indicated by a range of 6 to 12 on the Walking Index for Spinal Cord Injury II (WISCI II). The WISCI II is a 21-

Number 6

point ordinal scale that rates an individual’s ability to walk 10 m based on the braces, devices, and assistance needed.11 The WISCI II has concurrent validity and good reliability in the population with spinal cord injury.12 Prior to training, patient 2 could walk at least 100 m independently with devices and was a home ambulator (ie, he walked at home and used a wheelchair in the community). In contrast, patients 1, 3, and 4 were able to walk short distances only and used a wheelchair for mobility in all environments. The patients were considered good candidates for skill training because they all could walk short distances overground. Moreover, all 4 patients were community dwelling, but did limited or no walking in the community. Skill training might enhance their participation and independence in community walking. Two additional patients were recruited, but dropped out after the first phase (BWSTT) of training for reasons unrelated to the training. One patient left because of severe pain, which was present prior to the training and was not made worse or better by the training. The other patient fell at home and sustained a dislocated shoulder. This individual was a community ambulator prior to training.

Intervention

All patients completed ⱖ9 months of training. They received 3 months of BWSTT and then were allocated to 1 of 2 treatment groups using a random permuted blocks method. The allocation to treatment group was not concealed from the experimenters. Patients 1 and 2 received 3 months of skill training followed by 3 months of BWSTT. Patients 3 and 4 received the training in the reverse order. Patient 4 was involved in an additional 2 blocks of training, also June 2009

Training of Walking Skills in Incomplete Spinal Cord Injury Table 1.

of training to increase comparability. Rest breaks were taken as needed.

Characteristics of Patientsa Patient Variable

1

2

Age (y)

42

61

Sex

Female

Injury level

T2

3

4

24

47

Male

Female

Male

L1

T10

C5

Years postinjury

1.0

4.4

0.9

23.0

Mechanism of injury

Surgery

Fall

Car accident

Hockey

Medications

Baclofen Diovanb

Tegretolb

Baclofen

None

ISCSCI

C

C

C

C

WISCI II

9

12

6

9

Walking aid

2WW

2 FCs

4WW/1PA

St.W

Braces

2 AFOs

2 AFOs

2 AFOs

2 AFOs

Comfortable walking speed (m/s)

0.07

0.61

0.18

0.11

6-minute walk (m)

25

191

50

39

Living situation

House, family

House, family

House, family

House, family

Employed?

No

No

No

Yes

a

Injury level⫽neurological level of injury as defined by the International Standards for Neurological Functional Classification of Spinal Cord Injury14 (ISCSCI), WISCI II⫽Walking Index for Spinal Cord Injury II, 4WW⫽ 4-wheeled walker, 2WW⫽2-wheeled walker, St.W⫽standard walker, FC⫽ forearm crutches, 1PA⫽assistance of one person required, AFO⫽ankle-foot orthosis. Values for comfortable walking speed and 6-minute walk represent scores at the beginning of training on the 10-Meter Walk Test and 6-Minute Walk Test, respectively. b Novartis Pharmaceuticals Corp, One Health Plaza, East Hanover, NJ 07936.

presented in an alternating order. There were no breaks between the blocks. The single-case, alternating treatment design allowed each patient to act as his or her own control. We randomly allocated patients to treatment groups to offset any carryover effects.13

Training Programs Skill training and BWSTT lasted about 1 hour a day (including rest breaks), with a target frequency of 5 days per week for 3 months. The programs were administered by a physical therapist, with the assistance of a volunteer, as needed. Braces were worn during both types

Skill training. The researchers and 2 physical therapists developed the aim and principles of skill training. The aim was to engage patients in challenging walking tasks. Skill training was based on 3 principles. First, tasks practiced were those known to be important for daily walking.2 Second, a variety of environments and conditions was used to approximate the situation in daily life. Third, the tasks practiced were sufficiently challenging to induce errors because learning is augmented in situations where errors are induced rather than suppressed.15,16 The tasks practiced in skill training were grouped into 5 categories, with the frequency of training specified a priori (Tab. 2). The proportion of time spent training each of the categories was determined by the therapist and varied from day to day. Walking aids were permitted during skill training. Three measures were used to gauge how challenging the training was. First, patients rated how difficult they found each training task on a visual analog scale, from 0 (“very easy”) to 10 (“extremely difficult, would fall without assistance”). Our target was a difficulty rating of ⱖ7. This target was based on the therapist’s observation that a rating of 7 was associated with a need for sig-

Table 2. Skill Training Categories Skill Training Category

Examples of Tasks

Training Frequency

Walking balance

Walking on different surfaces/in different directions/in windy conditions Walking and reaching

5 times/week

Skilled walking tasks

Negotiating obstacles, stairs, curbs, sloped surfaces, crowded environments, narrow spaces, doors

5 times/week

Walking with secondary task

Walking and looking/reaching/talking/carrying an object/pushing an object

5 times/week

Endurance

Walking long distances (ie, ⱖ100 m) indoors/outdoors

2–3 times/week

Speed

Walking short distances (ie, ⱕ25 m) at fast pace indoors/outdoors Crossing intersections

2–3 times/week

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Training of Walking Skills in Incomplete Spinal Cord Injury Table 3. Description of Skill Training by Patienta Patient 1

2

3

4i

4ii

No. of sessions/week

Variable

4.5⫾0.7

4.1⫾0.6

3.2⫾1.1

3.0⫾1.0

2.9⫾0.8

Session time (min)

33⫾8

44⫾7

31⫾8

39⫾12

32⫾7

% time Balance

19⫾10

24⫾8

24⫾13

26⫾11

29⫾10

Skilled walking

24⫾10

28⫾10

20⫾9

25⫾12

27⫾14

Secondary tasks

19⫾13

25⫾9

30⫾13

25⫾13

21⫾11

Endurance and speed

38⫾12

23⫾9

26⫾15

25⫾19

23⫾15

5.7⫾1.2

8.9⫾1.0

7.3⫾2.6

6.9⫾1.4

8.6⫾1.3

Difficulty Balance Skilled walking

5.4⫾1.0

9.1⫾0.9

7.1⫾2.1

7.0⫾1.8

8.4⫾1.0

Secondary tasks

5.1⫾1.2

8.6⫾0.9

8.1⫾2.2

6.6⫾1.5

7.5⫾2.0

14.9⫾1.0

17.6⫾2.6

13.0⫾2.5

13.0⫾0.9

12.5⫾2.3

No. of near falls

Borg RPE

1.7⫾1.2

2.8⫾1.5

7.4⫾3.2

2.1⫾1.8

1.4⫾1.1

No. of walking surfaces/tasks negotiated

2.6⫾1.3

3.5⫾1.6

2.6⫾1.2

2.4⫾1.3

3.1⫾1.3

10.7

63.5

20.9

11.1

15.0

Curbs Stairs

73.2

53.8

62.8

47.2

50.0

Slopes/ramps

19.6

69.2

32.6

30.6

37.5

Doors

23.2

75.0

39.5

44.4

22.5

5.4

15.4

16.7

11.1

5.0

Narrow spaces

12.5

71.2

16.7

33.3

22.5

Carrying objects

41.1

73.1

61.9

52.8

32.5

Obstacles

26.8

57.7

25.6

50.0

60.0

0

13.5

4.7

0

0

Crowded places

Intersections a

Patient 4i and patient 4ii refer to the first and second blocks of skill training, respectively, for patient 4. The number of sessions/week, session duration excluding rests, percentage of time spent on each category, difficulty ratings, Borg Rating of Perceived Exertion (RPE), number of near falls, and number of surfaces encountered per session are expressed as mean⫾standard deviation. Difficulty ratings were measured at the midpoint of the training category. Encounters with the remaining tasks (ie, curbs, stairs, slopes/ramps, doors, crowded places, narrow spaces, carrying objects, obstacles, and intersections) are expressed as a percentage: (number of training days encountered/total number of training days) ⫻ 100%. Balance refers to the training category walking balance.

nificant concentration or resulted in a loss of balance that the patient could self-correct. Second, the therapist recorded the number of near falls (ie, unable to recover balance and the fall was prevented by the therapist) experienced during each session. Our target was ⱖ1 near fall per training session. Third, the Borg Rating of Perceived Exertion (RPE)17 was used to gauge the perceived cardiovascular load (target: Borg RPE of 13/20 [“somewhat hard”] or higher) because endurance was one of the categories of tasks in the train604

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ing (Tab. 2). During training, if the difficulty ratings were above or below the target level, the therapist adjusted the task accordingly (eg, change walking aid or size of obstacle). Parameters for each skill training session were documented with a standardized table. Table 3 summarizes this information for each patient. Four main categories of tasks were targeted (Tab. 3). Skill training varied somewhat among the patients because of each individual’s abilities. For example, patients 1 and 4 did not

Number 6

practice crossing traffic intersections because their walking speeds were not sufficiently high to attempt the task safely. To further verify that the skill training administered by the therapist was meeting the expectations of the study, a researcher videotaped a full training week for patients 1, 3, and 4. An independent reviewer identified from the videotape: (1) the number of times per week each of the skill training categories was practiced, (2) the number of different June 2009

Training of Walking Skills in Incomplete Spinal Cord Injury Table 4. Description of Body-Weight–Supported Treadmill Training (BWSTT) Parameters for All Patientsa Patient

Time (min)

Days/Week

BWS

Treadmill Speed (m/s)

Borg RPE

1i

31⫾8

3.9⫾0.9

41⫾3

0.64⫾0.09

15.0⫾1.2

1ii

25⫾4

4.0⫾1.2

24⫾6

0.85⫾0.07

14.0⫾0.6

2i

23⫾5

3.8⫾1.1

0

0.99⫾0.08

18.3⫾0.7

2ii

37⫾6

4.3⫾1.0

0

1.26⫾0.25

19.9⫾0.2

3i

22⫾5

3.1⫾1.0

30⫾7

0.77⫾0.17

12.2⫾1.2

3ii

25⫾7

3.0⫾1.0

18⫾4

1.08⫾0.08

12.4⫾1.4

4i

37⫾7

3.5⫾0.8

36⫾8

4ii

29⫾4

2.9⫾0.9

30⫾0

4iii

25⫾6

3.0⫾0.6

22⫾12

0.5⫾0 0.72⫾0.23 0.5⫾0

14.5⫾1.5 15.0⫾0.0 13.3⫾0.6

a

Patients 1, 2, and 3 received 2 training blocks of BWSTT (denoted by subscripts i and ii), and patient 4 received 3 blocks of BWSTT (denoted by subscripts i, ii, and iii). Time⫽average duration of one session, excluding rests. Days/week⫽average number of sessions attended per week. BWS⫽body-weight support expressed as a percentage of the patient’s body weight. Borg RPE⫽Borg Rating of Perceived Exertion. Values are expressed as mean⫾standard deviation.

environments within which training occurred each day, and (3) which of the important walking skills2 were targeted in that training week. The independent review indicated that the criteria of skill training were met with respect to the target frequency for training categories and environments. The majority of relevant walking tasks2 were practiced during the week, but walking in a crowded environment and walking on a slippery surface were consistently missed. BWSTT. A standard treadmill equipped with an overhead counterweight system (custom made) was used. Training criteria were determined as follows: (1) training speed was the maximum speed tolerated by the patient and always was greater than a patient’s overground walking speed, (2) amount of bodyweight support was the lowest possible without a patient’s knees and hips collapsing into flexion during stance, and (3) the body-weight support and speed selected had to allow a bout duration of at least 3 minutes. Manual assistance was provided to the lower extremities or trunk as needed. Patients were permitted to hold side rails for stability while walking. The rails were positioned at about chest height to prevent weight bearing through the arms. June 2009

The BWSTT was progressed when one of the following criteria was met: (1) a Borg RPE of ⬍13 or (2) the ability to walk for more than 10 minutes with minimal physical assistance. Progressions involved increasing the speed or decreasing bodyweight support. If the speed reached 1.0 m/s, body-weight support was reduced rather than increasing the speed further. Otherwise, the therapists and patients decided whether to increase speed or decrease bodyweight support. For patient 2, who required no body-weight support, progressions involved increasing speed and duration of walking and adding arm swing. The Borg RPE was monitored during each BWSTT session. The parameters of BWSTT are summarized in Table 4 for each patient. There was a trend toward longer walking times for skill training than for BWSTT (compare Tabs. 3 and 4). Patient 2 completed his second block of BWSTT in his own home because he lived 150 km from Edmonton, and he did not require body-weight support. The therapist visited his home prior to this second bout of BWSTT to set up the training program, and she maintained daily telephone or e-mail contact with him to ensure training quality and to rec-

ommend progressions. Patient 2 recorded the training parameters and Borg RPE for each training day. Outcome Measures Testing of clinical measures was done prior to the beginning of training, monthly during training, and at the end of training. Follow-up assessments were conducted 3 months after training, and an additional assessment at 6 months after training was conducted for patient 2. A therapist who was blind to group allocation assessed all of the patients. This was possible because the assessing therapist worked at a different institution and carried out all assessments in the evenings. The assessor and patients were instructed regarding the blinding. There were no breaches to the blinding. Patients used the same walking aids in all assessments except the Modified Emory Functional Ambulation Profile (mEFAP) (see below), which accounts for changes in walking aids. The clinical measures were assessed in the following order: 1. The Berg Balance Scale measures static and dynamic standing balance.18 Its measurement properties have been established in individuals with iSCI.19 Both BWSTT and skill training could affect balance. The best possible score is

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Training of Walking Skills in Incomplete Spinal Cord Injury 56, with a score of less than 45 being associated with a risk for falls in elderly people.20 The minimal clinically important difference (MCID) is 6 points in individuals with stroke,21 but it is not known for the iSCI population. 2. The mEFAP evaluates walking ability based on timed performance of 5 walking tasks (walking 5 m on a smooth floor and on carpet, the Timed “Up & Go” Test, negotiating obstacles, and stair climbing).22,23 The total score reflects the total time (in seconds) needed to complete the tasks. Ambulation aids and physical assistance are accounted for by a multiplication factor. The reliability and validity of scores for this scale have been established.22 An option for forearm crutches was added to the scoring of the mEFAP (multiplication factor⫽7) because they are a common aid used by individuals with iSCI. This was the most quantitative measure of walking skill available that suited the abilities of our patients. The MCID for this measure is not known. 3. The 6-Minute Walk Test measures walking endurance.24 The score is the total distance (in meters) traveled in 6 minutes. The test yields scores that are valid and reliable for individuals with iSCI.25 This measure was used because endurance was one of the aims of our training. The MCID was estimated to be 54 m for individuals with chronic obstructive lung disease26 and is unknown for those with SCI. 4. The 10-Meter Walk Test was used to measure comfortable and fast walking speeds. For fast walking speed, patients were instructed to walk as fast as they could without losing their balance. The 10-m walk test yields scores that are 606

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valid and reliable for individuals with iSCI.25 The MCID was estimated to be 0.05 to 0.06 m/s for a group of community-dwelling individuals with iSCI.27 5. The Activities-specific Balance Confidence (ABC) Scale requires patients to rate their confidence (from 0% [“no confidence”] to 100% [“complete confidence”]) in their ability to maintain balance during 16 functional activities.28 The ABC Scale was shown to have acceptable psychometric properties in individuals with stroke.29 It provided a measure of each patient’s opinion, independent of the objective measures of performance. The MCID is not known, but a score of 67% was a threshold that separated “fallers” from “nonfallers” among communitydwelling older people.30

Findings Figure 1A shows mEFAP scores during training and follow-up for each patient. The change scores are shown above or below the trace for each phase of training (ie, score at end of phase ⫺ score at beginning of phase). Patients 1 and 3 showed improvement during skill training and BWSTT, whereas there was a tendency for patients 2 and 4 to show greater improvement with skill training than with BWSTT. Retention of gains was estimated as follows: [(follow-up score ⫺ score at beginning of training)/(score at end of training – score at beginning of training)] ⫻ 100%. Gains on the mEFAP were maintained after training, with the exception of patient 4 (retention of gains 3 months after training: median⫽99.5%, interquartile range [IQR]⫽51%). Changes in comfortable walking speed (Fig. 1B) and fast walking speed (not shown in the figure) were very similar. The change scores are shown above or below the trace for

Number 6

each phase of training for comparison with the known MCID (ⱖ0.05 m/s) for people with iSCI.27 Patient 4 showed the smallest overall change and the least retention of gains at follow-up. The other 3 patients showed improvements (greater MCID) during the skill training phase. Patients 1 and 3 also showed gains (greater MCID) for one of the BWSTT phases. Retention of gains at follow-up was good except for patient 4 (median⫽92%, IQR⫽83%). Qualitatively, changes in performance of the 6-minute walk test (not shown in Fig. 1) were similar to those seen for comfortable walking speed (Fig. 1B). The improvement in measurements from beginning to end of all training was 75, 47, 85, and 8 m for patients 1 through 4, respectively. Two change scores exceeded the MCID reported for individuals with chronic obstructive pulmonary disease (change of 54 m26). Retention of gains was good for patients 1, 2, and 3 (median⫽103%, IQR⫽98%). Results from the Berg Balance Scale varied among the patients, but, for the most part, minor gains were made. Total improvements over the entire training period were 9, 0, 10, and 5 for patients 1 through 4, respectively. Results from the ABC Scale also varied among the patients. Interestingly, increases in balance confidence were consistently seen during skill training (median⫽11%, IQR⫽9%), but such increases were seen much less frequently during BWSTT (median⫽⫺2%, IQR⫽14%). In all cases, however, the scores on the ABC Scale remained below 67%, scores that suggest a risk for falling in older people.30 Functional Walking Status Training led to changes in functional walking status in 2 patients. Patient 2 was walking for short distances (ie, ⬍100 m) in the community after training. Patient 1 was walking within June 2009

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Figure 1. Modified Emory Functional Ambulation Profile (mEFAP) scores (A) and comfortable walking speeds (B) during training and follow-up for each patient. Each plot shows the data from one patient (patient number shown on far left). Numbers above/below the traces indicate the change in score from the beginning to the end of a training phase (black lines⫽body-weight–supported treadmill training [BWSTT], blue lines⫽skill training). A decrease in score on the mEFAP indicates an improvement because the mEFAP is a timed measure.

the home (including going up and down stairs) after training, but continued to use her wheelchair in the community. Functional walking status did not change for patients 3 and 4, although patient 3 walked daily within her home for exercise. Group Data The median value (and range) of the change in clinical scores is shown in Figure 2. In Figure 2A, the data are collapsed across each block of training, regardless of the type of training. The scores shown are change scores (ie, change score⫽score at end of training ⫺ score at beginning of training). For most patients, greater improvements were made in the latter blocks of training (ie, months 4 –9 of training). In Figure 2B, the data are collapsed across each type of training, regardless of when it occurred. With the exception of the Berg Balance Scale, all June 2009

measures tended to show greater gains with skill training than with either block of BWSTT.

Discussion We show that an intensive program to retrain walking skills overground may be as effective as BWSTT in this small group of patients. Clinically important changes were seen in walking speed for all patients over the whole duration of the training and during the skill training portion alone for 3 of the 4 patients. The same 3 patients also showed good retention of gains 3 months after training terminated. Effectiveness of Skill Training and BWSTT Overall, the findings suggest that skill training resulted in gains in walking speed, endurance, balance confidence, and performance of several walking skills (ie, as assessed

with the mEFAP) in our patients (Fig. 2B). Patient 2 showed considerably greater gains on all outcome measures, except for the Berg Balance Scale, during skill training compared with BWSTT. Because patient 2 completed the second block of BWSTT in his home, we cannot rule out the possibility that this training was different from the training that the other patients received in the laboratory. This is unlikely, however, as he also showed minimal improvement during the first block of BWSTT. To determine whether his results biased the findings in favor of skill training, the analysis was redone without his data. The median and range of scores changed very little for the ABC Scale and Berg Balance Scale (Fig. 2B, black dots show median). The median scores on the mEFAP, 6-Minute Walk Test, and 10Meter Walk Test, however, were generally more similar across train-

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Figure 2. Median values (horizontal lines) and ranges of scores (blue boxes) for the Berg Balance Scale, Activities-specific Balance Confidence (ABC) Scale, walking speed, 6-Minute Walk Test, and Modified Emory Functional Ambulation Profile (mEFAP). (A) Scores were collapsed for each type of training, regardless of when the training occurred (training phase: A⫽first, B⫽second, C⫽third). (B) Scores were collapsed for each block of training, regardless of the method of training (training phases: TT1⫽first phase of body-weight– supported treadmill training, TT2⫽second phase of body-weight–supported treadmill training, ST⫽skill training). Black dots show median when patient 2 is removed. 608

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Training of Walking Skills in Incomplete Spinal Cord Injury ing methods once patient 2’s data were removed. For example, the change in score from TT1 (first phase of BWSTT) was more similar to ST (skill training) for the mEFAP when data from patient 2 were removed (ie, dots closer together than median lines in Fig. 2B), and change scores for TT2 (second phase of BWSTT) were more similar to ST for the 6-Minute Walk Test and the 10-Meter Walk Test. Skill training and BWSTT, as implemented in this case series, are quite different. The only similarities are that both require a training frequency of 3 to 5 times per week and a moderate cardiovascular load (ie, Borg RPE ⱖ13/20). The BWSTT involved repetitive practice of forward stepping movements, typically with little variation except changes in speed and amount of body-weight support. Body-weight–supported treadmill training, as reported by other authors, has not always been confined to stereotypical stepping on the treadmill. For example, some authors have included overground training as soon as possible (reviewed in Behrman et al31). In all forms of BWSTT, however, patients wear a harness that supports some of their body weight and provides trunk stability, likely reducing balance demands in comparison with overground training. Although the amount of body-weight support is reduced as the patient progresses, the demands on balance were likely still less than walking overground in our patients, as the handrails were available for stability if needed. In contrast, skill training requires full weight bearing and challenges balance well beyond walking on level ground. It encompasses practice of more than 10 walking tasks frequently encountered in daily life,2 such as negotiating obstacles, doors, stairs, curbs, and crowded environments, in varying situations and June 2009

environments. We speculate that the incorporation of varied walking situations facilitates the patient’s ability to adapt, which is necessary for community and household walking.2 The degree of challenge (ie, near falls) and the use of tasks similar to those in daily life may have contributed to the increase in patient confidence and skill. Therefore, we suggest, as other authors have suggested,32 that BWSTT may not be sufficient for training balance and adaptability during walking. Perhaps skill training should be considered a progression of BWSTT for walking retraining because BWSTT can be implemented when walking ability is low. It was difficult to equate the intensity of the 2 forms of training because they are very different in nature. The patients judged the 2 forms of training to be equally intensive (Borg RPEs in Tabs. 3 and 4). There was, however, a trend for the sessions to be longer during skill training than during BWSTT (Tabs. 3 and 4). Thus, we cannot discount the possibility that the longer session durations of skill training contributed to the outcomes reported here. In retrospect, other measures of dosage, such as step count or distance covered, would have been useful to include. There are surprisingly few reports comparing walking outcomes with BWSTT and overground training. In a study of people with acute iSCI, no differences in a number of walkingrelated outcome measures (ie, Functional Independence Measure for Locomotion, walking speed, 6-Minute Walk Test, Berg Balance Scale, and WISCI II) were reported between individuals who trained using BWSTT and those who trained overground.9 That study, however, remained under-powered statistically, despite the impressive recruitment of 117 subjects. Similarly, BWSTT and overground training (both with electrical stimulation) were found to be

equally effective at improving walking speed, step length, and step symmetry in individuals with chronic iSCI,33 but that study also was statistically under-powered. In our case series, when training was begun early (ie, patients 1 and 3, both about 1 year postinjury), gains in walking were seen regardless of the type of training. In contrast, patients 2 and 4 (4.4 and 23 years postinjury, respectively) tended to show more improvement with skill training (Fig. 1). The possibility that skill training may be especially effective for individuals who were injured some time previously would be valuable to explore with a large number of patients in the future. Relationship Between Long-term Training and Ongoing Improvement in Walking Ability The patients continued to show improvement with long-term training (ie, ⱖ6 months). For example, improvements were seen in mEFAP scores and walking speed for at least 6 months of training in patient 2 and up to 9 months or more for the other patients (Fig. 1). These findings are consistent with those of Hicks and colleagues.34 They reported that about half of their subjects with SCI showed improved ability to walk overground, as measured with a modified version of a scale by Wernig et al,35 throughout 12 months of BWSTT.34 Thus, there are benefits to extending the length of walking retraining for iSCI beyond the typical 3 months. Indeed, both patients 2 and 4 required ⱖ3 months to show initial improvements. For some individuals with iSCI, ⱖ3 months of training is needed to bring about meaningful change. Practice and Minimum Ability Needed for Retention of Gains The 3 patients who showed good retention of gains after training continued to walk at home. Regular walking is necessary to retain func-

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Training of Walking Skills in Incomplete Spinal Cord Injury tion.33–36 Skill training may have facilitated retention of walking ability, as it allowed practice of relevant walking skills in an appropriate environment. Perhaps this type of practice provided our patients with the confidence to perform these skills on their own (as shown for the ABC Scale in Fig. 2B). Patient 4 was the exception. Not only did patient 4 report no walking after training, but he also had the lowest walking speed at the end of training (0.15 m/s). Thus, there may be a minimum walking speed, below which walking is not realistic in the home. Limitations Two difficulties were identified in the implementation of skill training. First, individuals differed in their willingness to take risks (Tab. 3, number of near falls). Ways to increase the patient’s confidence to take risks during training should be sought. Second, 2 tasks—walking in a crowded environment and walking on a slippery surface—were frequently omitted. Both tasks are difficult to simulate in a clinical environment. Innovative ways to incorporate these tasks into training would be useful in the future. There was surprisingly little change in Berg Balance Scale scores with either form of training (Fig. 2). At the beginning of training, scores on the Berg Balance Scale were low (11 for patient 1; 8 for patients 2 and 3; and 22 for patient 4); thus, there may have been a floor effect. The Berg Balance Scale does not permit the use of walking aids, which all of our patients required for standing and walking activities. Furthermore, the Berg Balance Scale score may not reflect the dynamic balance needed for walking. This is a small-scale, single-case series. Thus, we cannot generalize beyond our group of patients. The case series describe a systematic, over610

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ground training program that could be used for study with a larger cohort of patients. Such future studies would benefit from a better measure of the skills needed for community walking. We used the mEFAP, which includes some skilled walking tasks, but does not consider other walking tasks known to be commonly performed in everyday life, such as negotiating ramps, curbs, doors, and uneven surfaces and walking while carrying objects.2 Unfortunately, this is also true of other gait-related scales for the iSCI population.37 There is a great need for better walking scales to evaluate skillful aspects of walking.

Conclusions The promising results of this case series suggest that skill training may be an effective method for individuals with iSCI who have some preexisting ability to walk. Future studies could modify skill training to include individuals who do not have adequate strength (force-generating capacity), endurance, postural control, or balance to stand upright and step. For example, other authors have described systems to support body weight while walking overground that could be used for training.33,38,39 Such a system would allow variable, overground practice of many of the walking tasks needed for daily life.2 Likewise, some skilled tasks, such as obstacle clearance, have been executed on a treadmill with body-weight support.40,41 It may be feasible to practice other important walking tasks on the treadmill, such as negotiating different walking surfaces and carrying objects while walking. Either approach would enable individuals with limited walking ability to participate in variable practice of relevant walking skills.

man and Dr Yang provided writing and data analysis. Ms Musselman provided data collection, project management, and patients. Dr Fouad, Dr Misiaszek, and Dr Yang provided fund procurement. Dr Yang provided facilities/equipment. The authors thank the therapists, Jennifer McPhail, Colleen Budzinski, and Kelly Brunton, for their participation. They thank Ashley Cripps and Rosie Vishram for technical assistance. They also thank the patients and student volunteers for their time and effort. This project was approved by the Health Research Ethics Board, University of Alberta, and Capital Health Edmonton. Some findings from this project were presented at the International Congress of the World Confederation for Physical Therapy; June 5, 2007; Vancouver, British Columbia, Canada; and at the Festival of International Conferences on Caregiving, Disability, Aging and Technology (FICCDAT) Advances in Neurorehabilitation; June 17, 2007; Toronto, Ontario, Canada. This work was supported by the Christopher and Dana Reeve Foundation (K.F., J.E.M., J.F.Y.). Ms Musselman was supported by scholarships from the Canadian Institutes of Health Research and the Alberta Heritage Foundation for Medical Research/Neuroscience Canada. This article was received August 21, 2008, and was accepted March 11, 2009. DOI: 10.2522/ptj.20080257

References 1 Wernig A, Mu ¨ ller S, Nanassy A, Cagol E. Laufband therapy based on “rules of spinal locomotion” is effective in spinal cord injured persons. Eur J Neurosci. 1995;7: 823– 829. 2 Musselman KE, Yang JF. Walking tasks encountered by urban-dwelling adults and persons with incomplete spinal cord injuries. J Rehabil Med. 2007;39:567–574. 3 Field-Fote EC. Combined use of body weight support, functional stimulation, and treadmill training to improve walking ability in individuals with chronic incomplete spinal cord injury. Arch Phys Med Rehabil. 2001;82:818 – 824. 4 Salbach NM, Mayo NE, Wood-Dauphine´e S, et al. A task-oriented intervention enhances walking distance and speed in the first year post stroke: a randomized controlled trial. Clin Rehabil. 2004;18: 509 –519. 5 Edgerton VR, de Leon RD, Tillakaratne N, et al. Use-dependent plasticity in spinal stepping and standing. Adv Neurol. 1997;72:233–247.

All authors provided concept/idea/project design and consultation (including review of manuscript before submission). Ms Mussel-

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Training of Walking Skills in Incomplete Spinal Cord Injury 6 Girgis J, Merrett D, Kirkland S, et al. Reaching training in rats with spinal cord injury promotes plasticity and task-specific recovery. Brain. 2007;130:2993–3003. 7 Protas EJ, Holmes SA, Qureshy H, et al. Supported treadmill ambulation training after spinal cord injury: a pilot study. Arch Phys Med Rehabil. 2001;82:825– 831. 8 Behrman AL, Lawless-Dixon AR, Davis SB, et al. Locomotor training progression and outcomes after incomplete spinal cord injury. Phys Ther. 2005;85:1356 –1371. 9 Dobkin B, Apple D, Barbeau H, et al. Weight-supported treadmill vs overground training for walking after acute incomplete SCI. Neurology. 2006;66:484 – 493. 10 Behrman AL, Harkema SJ. Locomotor training after human spinal cord injury: a series of case studies. Phys Ther. 2000;80: 688 –700. 11 Ditunno PL, Ditunno JF. Walking Index for Spinal Cord Injury (WISCI II): scale revision. Spinal Cord. 2001;39:654 – 656. 12 Ditunno JF, Ditunno PL, Graziani V, et al. Walking Index for Spinal Cord Injury (WISCI): an international multicenter validity and reliability study. Spinal Cord. 2000;38:234 –243. 13 Franklin RD, Allison DB, Gorman BS. Design and Analysis of Single-Case Research. Mahwah, NJ: Lawrence Erlbaum Associates Inc; 1996. 14 Maynard FM Jr, Braken MB, Creasey G, et al. International Standards for Neurological Functional Classification of Spinal Cord Injury. Spinal Cord. 1997;35:266 – 274. 15 Patton JL, Stoykov ME, Kovic M, MussaIvaldi FA. Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors. Exp Brain Res. 2006;168:368 –383. 16 Reisman DS, Wityk R, Silver K, Bastian AJ. Locomotor adaptation on a split-belt treadmill can improve walking symmetry poststroke. Brain. 2007;130(pt 7):1861–1872. 17 Borg G, Linderholm H. Perceived exertion and pulse rate during graded exercise in various age groups. Acta Medica Scand Suppl. 1967;472:194 –206. 18 Berg KO, Wood-Dauphine´e SL, Williams JI, Gayton D. Measuring balance in the elderly: preliminary development of an instrument. Physiother Can. 1989;41: 304 –311.

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19 Ditunno JF, Barbeau H, Dobkin BH, et al. Validity of the walking scale for spinal cord injury and other domains of function in a multicenter clinical trial. Neurorehabil Neural Repair. 2007;21:539 –550. 20 Berg KO, Wood-Dauphine´e SL, Williams JI, Maki B. Measuring balance in the elderly: validation of an instrument. Can J Public Health. 1992;83(suppl 2):S7–S11. 21 Stevenson TJ. Detecting change in patients with stroke using the Berg Balance Scale. Aust J Physiother. 2001;47:29 –38. 22 Wolf SL, Catlin PA, Gage K, et al. Establishing the reliability and validity of measurements of walking time using the Emory Functional Ambulation Profile. Phys Ther. 1999;79:1122–1133. 23 Baer HR, Wolf SL. Modified Emory Functional Ambulation Profile: an outcome measure for the rehabilitation of poststroke gait dysfunction. Stroke. 2001;32: 973–979. 24 Guyatt GH, Sullivan MJ, Thompson PJ, et al. The 6-minute walk: a new measure of exercise capacity in patients with chronic heart failure. Can Med Assoc J. 1985;132: 919 –923. 25 van Hedel HJA, Wirz M, Dietz V. Assessing walking ability in subjects with spinal cord injury: validity and reliability of 3 walking tests. Arch Phys Med Rehabil. 2005;86: 190 –196. 26 Redelmeier DA, Bayoumi AM, Goldstein RS, Guyatt GH. Interpreting small differences in functional status: the Six Minute Walk test in chronic lung disease patients. Am J Respir Crit Care Med. 1997;155: 1278 –1282. 27 Musselman KE. Clinical significance testing in rehabilitation research: what, why, and how? Phys Ther Rev. 2007;12: 287–296. 28 Powell LE, Myers AM. The Activitiesspecific Balance Confidence (ABC) Scale. J Gerontol A Biol Sci Med Sci. 1995;50: M28 –M34. 29 Botner EM, Miller WC, Eng JJ. Measurement properties of the Activities-specific Balance Confidence Scale among individuals with stroke. Disabil Rehabil. 2005; 27:156 –163. 30 Lajoie Y, Gallagher SP. Predicting falls within the elderly community: comparison of postural sway, reaction time, the Berg Balance Scale, and the Activitiesspecific Balance Confidence (ABC) scale for comparing fallers and non-fallers. Arch Gerontol Geriatr. 2004;38:11–26.

31 Behrman AL, Bowden MG, Nair PM. Neuroplasticity after spinal cord injury and training: an emerging paradigm shift in rehabilitation and walking recovery. Phys Ther. 2006;86:1406 –1425. 32 van Hedel HJA. Weight-supported treadmill versus over-ground training after spinal cord injury: from a physical therapist’s point of view [letter to the editor]. Phys Ther. 2006;86:1444 –1445. 33 Field-Fote EC, Lindley SD, Sherman AI. Locomotor training approaches for individuals with spinal cord injury: a preliminary report of walking-related outcomes. J Neurol Phys Ther. 2005;29:127–137. 34 Hicks AL, Adams MM, Martin Ginis K, et al. Long-term body-weight–supported treadmill training and subsequent follow-up in persons with chronic SCI: effects on functional walking ability and measures of subjective well-being. Spinal Cord. 2005;43: 291–298. 35 Wernig A, Nanassy A, Mu ¨ ller S. Maintenance of locomotor abilities following Laufband (treadmill) therapy in para- and tetraplegic persons: follow-up studies. Spinal Cord. 1998;36:744 –749. 36 Wirz M, Colombo G, Dietz V. Long-term effects of locomotor training in spinal humans. J Neurol Neurosurg Psychiatry. 2001;71:93–96. 37 Lam T, Noonan VK, Eng JJ; SCIRE Research Team. A systematic review of functional ambulation outcome measures in spinal cord injury. Spinal Cord. 2008;46: 246 –254. 38 Miller EW, Quinn ME, Seddon PG. Body weight support treadmill and overground ambulation training for two patients with chronic disability secondary to stroke. Phys Ther. 2002;82:53– 61. 39 Patton J, Brown DA, Peshkin M, et al. KineAssist: design and development of a robotic overground gait and balance therapy device. Top Stroke Rehabil. 2008;15: 131–139. 40 Lam T, Dietz V. Transfer of motor performance in an obstacle avoidance task to different walking conditions. J Neurophysiol. 2004;92:2010 –2016. 41 van Hedel HJA, Waldvogel D, Dietz V. Learning a high-precision locomotor task in patients with Parkinson’s disease. Mov Disord. 2006;21:406 – 411.

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Invited Commentary

Andrea L. Behrman

Successful community ambulation should be the ultimate goal of locomotor rehabilitation. To this end, Musselman and colleagues1 assess the effect of rehabilitation to achieve the very practical skills required to walk daily in an individual’s home and community after spinal cord injury (SCI). The current case series1 is an important step in bringing the topic of how to best retrain walking to the forefront of discussion for rehabilitation research and clinical practice and provides several important points toward developing effective rehabilitation strategies and measures of walking recovery. The diversity of outcomes across the 4 patients serves as a catalyst to address several critical areas of inquiry as researchers design studies with the goal of guiding clinical practice for walking recovery. Physical rehabilitation targeting walking recovery after neurologic injury, and specifically after SCI, is in its infancy. Due to the emerging shift in this field, it is critical to distinguish functional recovery from functional compensation. Functional recovery means that the motor pattern is restored to perform a task as performed preinjury. Functional compensation, though, means that the task is accomplished but using alternative, new behavioral strategies.2 These definitions are not to indicate that there cannot be a blending of these responses within an individual. Recovery of walking is a relatively new goal for physical rehabilitation after SCI, whereas compensation for sensorimotor deficits (eg, use of braces, assistive devices, or a wheelchair to compensate for sensorimotor deficits) has been the mainstay of rehabilitation for mobility after SCI. With functional recovery as a goal, a framework and under-

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standing of the tasks required to achieve restoration of the movement patterns and specific tasks for daily walking are needed. Forssberg’s3 and Barbeau’s4 models for walking control identify 3 neural control tasks that contribute to successful walking: (1) production of a reciprocal stepping pattern, (2) dynamic stability during forward propulsion (steady-state walking), and (3) the ability to adapt the locomotor pattern in response to the demands of the environment and the individual’s own behavioral goals (eg, step over an obstacle, stop suddenly, carry a backpack). The work by Musselman et al1 is consistent with the third neural control task, as their goal is rehabilitation of locomotor adaptability skills that are critical to effective everyday walking. Collectively, the work of Forssberg, Barbeau, Musselman and colleagues, and others provides a framework from which to develop: (1) therapeutic interventions for walking recovery and (2) measures to evaluate walking recovery specific to each control component. Defining community ambulation and the specific skills supporting it is of value for rehabilitation of walking after SCI, stroke, and other neurologic disorders. Such definitions also may be of value to the rehabilitation of walking due to musculoskeletal dysfunction (eg, after total hip replacement). The tasks selected for training, in this instance, were based on previous work that identified the skills critical to community ambulation for urban-dwelling adults and people with incomplete SCI.5 This was, as the authors note, a step toward using empirical information as a rationale for a training program. This is an important step and contri-

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bution. Complementary work by Shumway-Cook et al6 also identified 8 dimensions of a necessary skill set for community ambulation in the geriatric population and contributes to the evolving empirical basis for skill training.5 Skill deficits should be identified via evaluation and targeted in therapy. Developing and providing a systematic roadmap for clinicians relative to retraining community ambulation tasks and progression is of tremendous importance. A critical question in motor control and learning is whether every different task must be trained (taskspecific training), or whether underlying, fundamental motor skills can be learned, then generalized or transferred to other tasks. For instance, stepping over a puddle requires that an individual adequately push off with the limb that will step over the puddle, voluntarily increase the length of his or her step, perhaps prolong the time in single-limb support, maintain upright balance during this event, and successfully load the limb and maintain support upon landing. This act may predominantly require control of the spatial parameters of a step using proactive control. In contrast, suddenly seeing a snake in your path may require a large, quick diverted step to miss the snake, followed by a rapid walk forward on the path. This task requires spatial-temporal adjustments and postural control for successful adaptation of the locomotor pattern. Locomotor adaptation also is necessary under reactive conditions such as experiencing an unexpected jostle from contact with another individual walking on a crowded street. Steps are quickly altered to locate the body’s center of mass within its base of support. Whether every skill for community ambulation must be

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Training of Walking Skills in Incomplete Spinal Cord Injury retrained is unknown. If so, the retraining becomes incredibly burdensome on therapist and patient. Thus, it is critical to determine whether fundamental motor skills common to specific community skills can be identified, retrained, and transferred. Effective progression is an important ingredient of training and is welldefined and executed by Musselman et al.1 The authors describe a 3-pronged, novel protocol for advancing the degree of difficulty and challenge to the patient during “skill training.” Task selection and goals were set based on: (1) the patient’s self-rating of task difficulty; (2) the need to challenge attention and balance, including the integration of at least one fall or near fall per training session; and (3) achievement of perceived cardiovascular load of “somewhat hard” according to the Borg Rating of Perceived Exertion. Knowing the patient’s own perception of task difficulty candidly directs the next focal point of training. Challenging the patient’s balance during walking to the point of falling or near falls presents an opportunity to knowingly attempt a difficult task and learn to prepare or respond. Providing these opportunities to succeed and learn from “errors” may enhance balance recovery and motor planning. In addition, perceived cardiovascular load provides insight into the demands of the training experience and, thus, how to progress with increasing load. Interestingly, the patients used assistive devices and braces overground and were given the option to use parallel bars on the treadmill during training. Thus, the lower extremities were not “full weight bearing,” as the upper limbs also bore weight through assistive devices. As the authors suggested, this is likely to have interrupted development of effective responses to imbalance or task deJune 2009

mands without the aid of external support. It is critical to consider the training environment and appreciate that skill training with assistive devices may advance walking skills with a compensatory, assistive device and not independent unassisted walking. Walking with an assistive device and walking without an assistive device are likely 2 different skills and, thus, 2 distinct goals. Although not used in the current case series, the authors propose the use of an overhead body-weight support (BWS) system during training overground, based on the benefits of BWS. Such a system may enhance the individual’s ability to develop appropriate neuromuscular preparation and responses for dynamic balance during advanced locomotor tasks. In this environment, skill training without and with assistive devices may be incorporated. In addition, and as noted by the authors, an overground BWS system may provide a sense of safety and comfort, allowing greater risk taking during challenging skills that typically produce errors or near falls. The 2 interventions used by the authors are described as: (1) “skill training” and (2) body-weight–supported treadmill training. Both environments, though, support skill training. Expanding the description to include the skills addressed in each distinct environment may more clearly distinguish the 2 interventions. In contrast to the skill training overground, skill training in the treadmill environment focused on increasing speed and decreasing BWS during walking bouts (up to 10 minutes) that require exertion. From the descriptions, it appears that training on the treadmill may more effectively promote rapid step transition, increased step length, greater lowerextremity load bearing, and more postural control during steady-state walking. As identified by the authors,1 other possibilities for skill training, such as speed changes and

stepping over obstacles, could occur on the treadmill, although they were not included in this work. Thus, “body-weight–supported treadmill training” is not a uniform term for a therapeutic intervention, but more appropriately designates the equipment being used.7 Alternatively, the article title distinguishes skill training simply based on the location of the intervention. The differences in the 2 settings and types of training also are readily distinguished by the inclusion of task-specific training relative to everyday demands on walking overground with assistive devices during the training overground. The difference in training protocols overground and on the treadmill with BWS suggests that the focus of training using the treadmill to date has been on retraining stepping and somewhat steady-state walking balance. What is the role of the treadmill and BWS in rehabilitation for walking recovery? Dobkin et al8 and Behrman et al9 used these tools for retraining the capacity to step and balance upright, as well as to transfer training guidelines and improved skills to overground and community ambulation. Van Hedel et al10 and Visintin et al11 focused on the treadmill with BWS as the sole environment for retraining walking. Other researchers9,12 Behrman et al9 and Field-Fote et al12 also used the treadmill to introduce locomotor adaptability training, and other researchers13 have used it predominantly to address aerobic training and endurance. The particular goal is important to drive the specific training protocol. Musselman et al1 chose to focus on stepping capacity in the treadmill environment and, thus, to compare and contrast this approach with a protocol of training specific community-derived skills for home and community ambulation in the overground environment with assistance. The distinction is valuable in

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Training of Walking Skills in Incomplete Spinal Cord Injury comparing interventions in this article and those already published in the literature, noting the active ingredients of each and the specific aims of the defined interventions. The authors1 selected standardized, clinic-based outcome measures for balance and walking ability. The measures represent the best of what is currently available clinically, with some specific to SCI and with published data of clinically meaningful differences. Standardized measures of dynamic walking stability that have reliability and validity remain lacking in our toolbox of clinical assessments. The Dynamic Gait Index (DGI)14 may offer some advantage over the Berg Balance Scale (BBS) in that the patient walks during the test and, for example, is asked to change speed, step over an obstacle, and turn. The BBS typically is conducted without an assistive device and may assess an individual’s true balance capacity in standing, sitting, and transitional movements. As the authors comment, the BBS, however, does not address dynamic stability specific to walking. For DGI testing, a patient may use his or her assistive device. Testing the patient with and without an assistive device, though, may readily distinguish between compensation and recovery of balance function. Although timed walking tests have significant merit, such tests also may mask improvements in balance and overall walking control. For example, a patient progressing from a rolling platform walker to a rolling walker has certainly gained in overall walking control. However, a change in the device also may be accompanied by a decrease in gait speed as the individual recalculates balance strategies specific to the new device. The Modified Emory Functional Ambulation Profile was an appropriate task-specific outcome comparable to the skills trained overground. Perfor614

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mance tested with a device indicates the benefit of skill training relative to a device. Improvements in skill that resulted in a change in device or greater balance or control also would be valuable, indicating recovery of neuromuscular function. Outcomes for the 4 individuals varied and were associated specifically with task-specific training, with 2 patients improving ambulatory status to: (1) walking in the home (began at 0.11 m/s with a 2-wheeled walker) and (2) part-time ambulation in the community (began at 0.61 m/s with bilateral crutches). Use of a device to quantify and analyze communitybased stepping activity, such as a step activity monitor or other monitoring apparatus, may be helpful in understanding the specific gains measured in the clinic and their meaningfulness relative to actual home- and community-based ambulation.15 The 4 patients began their rehabilitation programs with different starting points represented by their selfselected gait speed, ranging from 0.07 m/s (nontherapeutic range) to 0.61 m/s (consistent with homebased ambulation),16,17 and used different types of assistive devices (ie, 2-wheeled walkers, bilateral forearm crutches, or a 4-wheeled walker with physical assistance). This heterogeneity of ability is certainly reflective of the population with incomplete SCI and is a result of many factors. Is there, however, a neuromotor control threshold or capacity upon which “skill training,” as defined here, is a prerequisite? Although challenging the nervous system is necessary throughout locomotor training, do the components of stepping and dynamic balance in a controlled walking environment— without environmental challenges— preclude training highly skilled tasks of locomotor adaptability for community ambulation? Improvements while training in the BWS and tread-

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mill environment also were observed, indicating the ability to walk at faster speeds with decreasing BWS. Do such improvements transfer to diminished reliance on assistive devices overground (improved Walking Index for Spinal Cord Injury scores) and the capacity to change to a more-permissive assistive device (less-stable device) as greater lowerextremity load bearing or better upright postural control is achieved? The potential value of task-specific therapy is brought into focus by this case series with 2 of the 4 patients with chronic SCI improving their functional ambulation status relative to the home and community, respectively. Sustained improvements in 3 of the 4 patients for walking speed, endurance, and balance confidence may point to necessary achievement of critical thresholds of behavior for long-term training effects and self-training beyond the clinic. Prolonged training (3– 6 months) with continued gains challenges our (United States) current state of acute, time-limited rehabilitation. Rehabilitation for walking would benefit from application of a framework to guide clinical decision making that delineates the goal of functional recovery from the goal of functional compensation. Outcome measures similarly require distinction as to whether functional change is based on recovery of neuromuscular function or use of more-effective compensation strategies. The case series by Musselman et al1 challenges us, as clinicians and researchers, to systematically address rehabilitation of skill development specific to community ambulation. This goal is valuable for clinicians working with individuals after SCI, stroke, or other central nervous system injuries to regain walking function. This case series advances our thought and stimulates progress by providing the groundwork for hypothesis building and testing to develop the best practice June 2009

Training of Walking Skills in Incomplete Spinal Cord Injury for rehabilitation and recovery of walking. A.L. Behrman, PT, PhD, is Associate Professor, Department of Physical Therapy, College of Public Health and Health Professions, University of Florida, PO Box 100154, Gainesville, FL 32610-0154 (USA), and Research Scientist, Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, Florida. Address all correspondence to Dr Behrman at: abehrman@ phhp.ufl.edu. DOI: 10.2522/ptj.20080257.ic

References 1 Musselman KE, Fouad K, Misiaszek JE, Yang JF. Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury. Phys Ther. 2009;89:601– 611. 2 Levin MF, Kleim JA, Wolf SL. What do motor “recovery” and “compensation” mean in patients following stroke? Neurorehabil Neural Repair. 2009;23:313–319.

Author Response We thank Behrman for her thoughtful commentary1 on our case report.2 She raises a number of important points to which we would like to respond.

Distinction Between Functional Recovery and Functional Compensation We fully agree with the distinction between functional recovery and functional compensation raised in the commentary, and the different levels at which compensation and recovery occur (neuronal, performance, and activity).3 We did not attempt to distinguish between functional recovery and functional compensation in either form of training. Our focus was on accomplishing the task rather than the method by which it was accomplished. The use

June 2009

3 Forssberg H. Spinal locomotor functions and descending control. In: Sjolund B, Bjourkland RA, eds. Brainstem Control of Spinal Mechanisms. Amsterdam, the Netherlands: Elsevier-Biomedical; 1982: 253–271. 4 Barbeau H. Locomotor training in neurorehabilitation: emerging rehabilitation concepts. Neurorehabil Neural Repair. 2003;17:3–11. 5 Musselman KE, Yang JF. Walking tasks encountered by urban-dwelling adults and persons with incomplete spinal cord injuries. J Rehabil Med. 2007;39:567–574. 6 Shumway-Cook A, Patla AE, Stewart A, et al. Environmental demands associated with community mobility in older adults with and without mobility disabilities. Phys Ther. 2002;82:670 – 681. 7 Behrman AL, Plummer-D’Amato P. “What’s in a name?” Revisited [guest editorial]. Phys Ther. 2008;88:6 –9. 8 Dobkin B, Apple D, Barbeau H, et al; for the Spinal Cord Injury Locomotor Trial (SCILT) Group. Weight-supported treadmill vs over-ground training for walking after acute incomplete SCI. Neurology. 2006;66:484 – 493. 9 Behrman AL, Lawless-Dixon AR, Davis SB, et al. Locomotor training progression and outcomes after incomplete spinal cord injury. Phys Ther. 2005;85:1356 –1371.

10 Van Hedel HJ, Wirth B, Dietz V. Limits of locomotor ability in subjects with a spinal cord injury. Spinal Cord. 2005;43:593– 603. 11 Visintin M, Barbeau H, Korner-Bitensky N, Mayo NE. A new approach to retrain gait in stroke patients through body weight support and treadmill stimulation. Stroke. 1998;29:1122–1128. 12 Field-Fote EC, Lindley SD, Sherman AL. Locomotor training approaches for individuals with spinal cord injury: a preliminary report of walking-related outcomes. J Neurol Phys Ther. 2005;29:127–137. 13 Ivey FM, Hafer-Macko CE, Macko RF. Taskoriented treadmill exercise training in chronic hemiparetic stroke. J Rehabil Res Dev. 2008;45:249 –259. 14 Shumway-Cook, Woollacott M. Motor Control: Theory and Practical Applications. Baltimore, MD: Williams & Wilkins; 1995. 15 Cavanaugh JT, Coleman KL, Gaines JM, et al. Using step activity monitoring to characterize ambulatory activity in community-dwelling older adults. J Am Geriatr Soc. 2007;55:120 –124. 16 Perry J, Garrett M, Gronley JK, Mulroy SJ. Classification of walking handicap in the stroke population. Stroke. 1995;26; 982–989. 17 Van Hedel HJ, Wirtz M, Dietz V. Gait speed in relation to categories of functional ambulation after spinal cord injury. Neurorehabil Neural Repair. 2009;23:343–350.

Kristin E. Musselman, Karim Fouad, John E. Misiaszek, Jaynie F. Yang

of braces was allowed in both types of training, as was the use of walking aids in skill training, both of which involve functional compensation at all levels. With the fairly severe injuries sustained by the patients in this study and the chronic state of these injuries, we speculate that functional compensation was necessary. The distinction between encouraging recovery versus compensation would dictate different strategies of retraining. As Behrman mentioned, learning to walk with assistive devices is likely a very different task from learning to walk without assistive devices. Would learning one assist or interfere with the other? This is a critical question for the future. Moreover, it is important to keep in mind that training in a way that facil-

itates functional recovery at the activity level does not necessarily mean that there will be functional recovery at the performance and neuronal levels. Grasso and colleagues4 demonstrated convincingly that training with body-weight–supported treadmill training (BWSTT) (ie, facilitating functional recovery) in individuals with incomplete spinal cord injury resulted in improvement in kinematics of the walking, but the improvements were a result of muscle activity that deviated substantially from that of individuals without injury. Research that focuses on the potential contribution of each process to the restoration of walking will be very important. We speculate that the contribution of each process will be different— due to the different

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Training of Walking Skills in Incomplete Spinal Cord Injury for rehabilitation and recovery of walking. A.L. Behrman, PT, PhD, is Associate Professor, Department of Physical Therapy, College of Public Health and Health Professions, University of Florida, PO Box 100154, Gainesville, FL 32610-0154 (USA), and Research Scientist, Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, Florida. Address all correspondence to Dr Behrman at: abehrman@ phhp.ufl.edu. DOI: 10.2522/ptj.20080257.ic

References 1 Musselman KE, Fouad K, Misiaszek JE, Yang JF. Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury. Phys Ther. 2009;89:601– 611. 2 Levin MF, Kleim JA, Wolf SL. What do motor “recovery” and “compensation” mean in patients following stroke? Neurorehabil Neural Repair. 2009;23:313–319.

Author Response We thank Behrman for her thoughtful commentary1 on our case report.2 She raises a number of important points to which we would like to respond.

Distinction Between Functional Recovery and Functional Compensation We fully agree with the distinction between functional recovery and functional compensation raised in the commentary, and the different levels at which compensation and recovery occur (neuronal, performance, and activity).3 We did not attempt to distinguish between functional recovery and functional compensation in either form of training. Our focus was on accomplishing the task rather than the method by which it was accomplished. The use

June 2009

3 Forssberg H. Spinal locomotor functions and descending control. In: Sjolund B, Bjourkland RA, eds. Brainstem Control of Spinal Mechanisms. Amsterdam, the Netherlands: Elsevier-Biomedical; 1982: 253–271. 4 Barbeau H. Locomotor training in neurorehabilitation: emerging rehabilitation concepts. Neurorehabil Neural Repair. 2003;17:3–11. 5 Musselman KE, Yang JF. Walking tasks encountered by urban-dwelling adults and persons with incomplete spinal cord injuries. J Rehabil Med. 2007;39:567–574. 6 Shumway-Cook A, Patla AE, Stewart A, et al. Environmental demands associated with community mobility in older adults with and without mobility disabilities. Phys Ther. 2002;82:670 – 681. 7 Behrman AL, Plummer-D’Amato P. “What’s in a name?” Revisited [guest editorial]. Phys Ther. 2008;88:6 –9. 8 Dobkin B, Apple D, Barbeau H, et al; for the Spinal Cord Injury Locomotor Trial (SCILT) Group. Weight-supported treadmill vs over-ground training for walking after acute incomplete SCI. Neurology. 2006;66:484 – 493. 9 Behrman AL, Lawless-Dixon AR, Davis SB, et al. Locomotor training progression and outcomes after incomplete spinal cord injury. Phys Ther. 2005;85:1356 –1371.

10 Van Hedel HJ, Wirth B, Dietz V. Limits of locomotor ability in subjects with a spinal cord injury. Spinal Cord. 2005;43:593– 603. 11 Visintin M, Barbeau H, Korner-Bitensky N, Mayo NE. A new approach to retrain gait in stroke patients through body weight support and treadmill stimulation. Stroke. 1998;29:1122–1128. 12 Field-Fote EC, Lindley SD, Sherman AL. Locomotor training approaches for individuals with spinal cord injury: a preliminary report of walking-related outcomes. J Neurol Phys Ther. 2005;29:127–137. 13 Ivey FM, Hafer-Macko CE, Macko RF. Taskoriented treadmill exercise training in chronic hemiparetic stroke. J Rehabil Res Dev. 2008;45:249 –259. 14 Shumway-Cook, Woollacott M. Motor Control: Theory and Practical Applications. Baltimore, MD: Williams & Wilkins; 1995. 15 Cavanaugh JT, Coleman KL, Gaines JM, et al. Using step activity monitoring to characterize ambulatory activity in community-dwelling older adults. J Am Geriatr Soc. 2007;55:120 –124. 16 Perry J, Garrett M, Gronley JK, Mulroy SJ. Classification of walking handicap in the stroke population. Stroke. 1995;26; 982–989. 17 Van Hedel HJ, Wirtz M, Dietz V. Gait speed in relation to categories of functional ambulation after spinal cord injury. Neurorehabil Neural Repair. 2009;23:343–350.

Kristin E. Musselman, Karim Fouad, John E. Misiaszek, Jaynie F. Yang

of braces was allowed in both types of training, as was the use of walking aids in skill training, both of which involve functional compensation at all levels. With the fairly severe injuries sustained by the patients in this study and the chronic state of these injuries, we speculate that functional compensation was necessary. The distinction between encouraging recovery versus compensation would dictate different strategies of retraining. As Behrman mentioned, learning to walk with assistive devices is likely a very different task from learning to walk without assistive devices. Would learning one assist or interfere with the other? This is a critical question for the future. Moreover, it is important to keep in mind that training in a way that facil-

itates functional recovery at the activity level does not necessarily mean that there will be functional recovery at the performance and neuronal levels. Grasso and colleagues4 demonstrated convincingly that training with body-weight–supported treadmill training (BWSTT) (ie, facilitating functional recovery) in individuals with incomplete spinal cord injury resulted in improvement in kinematics of the walking, but the improvements were a result of muscle activity that deviated substantially from that of individuals without injury. Research that focuses on the potential contribution of each process to the restoration of walking will be very important. We speculate that the contribution of each process will be different— due to the different

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Training of Walking Skills in Incomplete Spinal Cord Injury forms of injury and the different stages postinjury. Understanding when recovery is possible and when compensation is needed will be essential to guide the prescription for interventions.

Does Every Task Need to Be Trained? This is an important and practical question to which there is no conclusive answer. Recent research in motor learning, however, suggests that training every task may not be necessary. Computational theories of motor learning suggest that our nervous system is able to cope with the vast and varied environment in which we live by a modular approach to motor control.5 The idea is that when we learn to do a specific task, the memory of how to do this task is stored in modular form, in restricted regions of the nervous system such as the cerebellum.6 Memory of different tasks or subtasks would occupy different modules. Thus, when we encounter a new situation, previously stored modules can be used either on their own or in combination to meet the new demands.5

questions can be answered more easily. If motor memory indeed does exist in modular format, and if different modules can be retrieved in different combinations to meet new demands, then it will be necessary to work out the minimum number of modules or learning situations needed in order for an individual to cope with the walking encountered in daily life. This is an exciting— but not trivial—problem.

Is There a Threshold Ability Above Which Skill Training Becomes Successful? Defining the patient characteristics that predict success for any rehabilitation intervention is of paramount importance. A manuscript is in preparation that addresses the ability of clinical and electrophysiological measures for predicting success with BWSTT in our group of individuals with chronic injuries. In time, we hope to have similar answers for other forms of training.

Improvement in Skill With Both BWSTT and Skill Training Some experimental evidence to support this idea has been obtained in restricted upper-limb movements,7 but a great deal more research will be needed to test this hypothesis. Moreover, the concept has not been tested in an injured system, which may respond differently. For example, there may be more limited resources (ie, neurons and pathways) after injury, which may restrict the capacity for learning.8 If a certain amount of neuronal “real estate” is needed to support a range of learning, reduced “real estate” because of injury may mean that less learning can be supported. Some of these questions, especially regarding injury, would be useful to address in animal models, in which mechanistic

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We agree that both forms of training, as implemented in our case series, trained different aspects of walking skills. The fact that no environmental challenges (eg, obstacles, uneven ground) were introduced during BWSTT did not preclude improvement in overground walking. Both forms of training not only led to improved walking speed overground, but to reduced reliance on assistive devices. We collected data on the Walking Index for Spinal Cord Injury II (WISCI II),9,10 but did not report the data in the article. Both forms of training resulted in improved Walking Index for Spinal Cord Injury II (WISCI II) scores, indicating a decreased reliance on walking aids in some patients. Patient 3 improved

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during the first BWSTT phase (WISCI II score changed from 6 to 9) and improved further during skill training (WISCI II score changed from 9 to 12). Patient 1 showed improvement during the skill training phase (WISCI II score changed from 9 to 12). The other 2 patients did not show changes in the WISCI II score. In summary, there is much work ahead of us, important work that will inform practice. We hope our case report and Behrman’s commentary will stimulate thought and discussion that eventually will lead to better outcomes in mobility for individuals with insults to the nervous system. DOI: 10.2522/ptj.20080257.ar

References 1 Behrman AL. Invited commentary on: “Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury.” Phys Ther. 2009;89:612– 615. 2 Musselman KE, Fouad K, Misiaszek JE, Yang JF. Training of walking skills overground and on the treadmill: case series on individuals with incomplete spinal cord injury. Phys Ther. 2009;89:601– 611. 3 Levin MF, Kleim JA, Wolf SL. What do motor “recovery” and “compensation” mean in patients following stroke? Neurorehabil Neural Repair. 2009;23: 313–319. 4 Grasso R, Ivanenko YP, Zago M, et al. Distributed plasticity of locomotor pattern generators in spinal cord injured patients. Brain. 2004;127:1019 –1034. 5 Wolpert DM, Kawato M. Multiple paired forward and inverse models for motor control. Neural Networks. 1998;11:1317–1329. 6 Imamizu H, Kuroda T, Miyauchi S, et al. Modular organization of internal models of tools in the human cerebellum. Proc Natl Acad Sci U S A. 2003;100:5461–5466. 7 Ghahramani Z, Wolpert DM. Modular decomposition in visuomotor learning. Nature. 1997;386:392–395. 8 Girgis J, Merrett D, Kirkland S, et al. Reaching training in rats with spinal cord injury promotes plasticity and task specific recovery. Brain. 2007;130:2993–3003. 9 Ditunno PL, Dittuno JF. Walking Index for Spinal Cord Injury (WISCI II): scale revision. Spinal Cord. 2001;39:654 – 656. 10 Ditunno JF, Ditunno PL, Graziani V, et al. Walking Index for Spinal Cord Injury (WISCI): an international multicenter validity and reliability study. Spinal Cord. 2000;38:234 –243.

June 2009

Scholarships, Fellowships, and Grants News from the Foundation for Physical Therapy Recent Publications by Foundation-Funded Researchers “Effect of Laterally Wedged Foot Orthoses on Rearfoot and Hip Mechanics in Patients With Medial Knee Osteoarthritis,” by Robert J. Butler, Joaquin A. Barrios, Todd Royer, and Irene S. Davis, has been published in the June 2009 issue of the Journal of Prosthetics and Orthotics. Joaquin Barrios, PT, DPT, PhD, received a Promotion of Doctoral Studies (PODS) scholarship of $7,500 from the Foundation in 2006 to study “Biomechanics and Movement Science.” “Neural Correlate of the Contextual Interference Effect in Motor Learning: A Kinematic Analysis,” by Chien-Ho Lin, Beth E. Fisher, Allan D. Wu, Yi-An Ko, Lung-Yee Lee, and Carolee J. Winstein, appeared in the May 2009 issue of the Journal of Motor Behavior. Beth Fisher, PT, PhD, received several awards from the Foundation: a $6,500 scholarship in 1997– 1998; a $15,000 PODS II scholarship in 1998 to study “Functional Brain Correlates for Pre-movement Planning and Compensatory Scaling in Rapid Aimed Movements”; and a $40,000 Research Grant in 2008 for “Comparison of Two Locomotor Training Programs on Brain and Behavior in Early Parkinson Disease.” Carolee Winstein, PT, PhD, FAPTA, received a $4,462 grant in 1986 to study “Relative Frequency of Information Feedback in Motor

June 2009

Performance and Learning” and a $25,942 grant in 1993 for “Deficits in Movement-Related Information Processing After Stroke: A Behavioral and Kinematic Study.” She also was primary investigator of the Foundation’s $1.5 million Clinical Research Network, a multisite study from 2003 to 2007 of the effects of strengthening exercises in 4 patient groups: adults poststroke, children with cerebral palsy, adults with chronic spinal cord injury and shoulder pain, and adults with orthopedic low back pain.

Foundation Announces Student Intern The Foundation for Physical Therapy has announced that MaryEllen Petrie (Figure), Marquette Figure. MaryEllen Petrie University, is joining the Foundation as a summer intern. In this position at the Foundation office, Petrie will help build the Research Match database, a new APTA/Foundation initiative, by inputting physical therapist researcher biographical data. She also will help to develop the 22nd Marquette Challenge, which kicks off in October at National Student Conclave in Miami, Florida. Petrie, who is from the St Louis area, will graduate in 2010 with a Bachelor of Arts Degree in Spanish for the Medical Professions and will continue working toward a Doctorate of Physical Therapy degree, also at Marquette University, with graduation targeted for 2012.

Foundation’s Dinner Dance at PT 2009—Celebrating 30 Years of Research The Foundation for Physical Therapy will celebrate 30 years of research at the annual Dinner Dance on June 11th during the APTA Annual Conference in Baltimore. Dinner Dance tickets must be purchased before PT 2009. Tickets can be purchased when registering for annual conference online at www.apta. org or by calling 800/999-2782, ext 3395. The Dinner Dance will take place at the Holiday Ballroom in the Hilton Baltimore, at 6:30 pm to midnight. New this year, Georgia State– Marquette Challenge winners will be announced during the reception, sponsored by Preferred Therapy Providers Inc. The complimentary Dinner Dance reception is open to all conference attendees. Special thanks to HPSO/CNA, title sponsor of the Foundation Dinner Dance for the 9th consecutive year. For more information, contact Barbara Malm at 800/875-1378, ext 8502, or barbaramalm@apta. org. [DOI: 10.2522/ptj.2009.89.6.617]

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Membership Statistics For the interest of American Physical Therapy Association (APTA) members, a tabular summary of membership figures for 10-year intervals from 1948 to 2008 appears below.

Physical Therapist

1948

1958

1968

1978

1988

1998

2008

3,352

5,692

9,697

23,189

38,191

47,608

49,784

58

253

333

247

685

1,211

1,909

2,299

Postprofessional Student Life

8

65

240

Retired Honorary

87 12

8

16

18

18

12

10

262

985

2,058

4,248

6,513

13,592

13,442

Physical Therapist Assistant

984

2,125

7,829

5,078

Physical Therapist Assistant Student

510

856

3,311

1,860

29,692

49,167

74,594

72,807

Physical Therapist Student

Total

3,634

6,750

12,011

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.

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Product News Scale

Ultrasound Components

Pain Relief Spray

Tanita Corp

ITT Acoustic Sensors

Performance Health Inc

Tanita introduces the PH-740 digital handrail scale with an extrawide 30-in × 25-in low platform. This portable acute care scale allows accessibility for patients with disabilities. It features an automatic body mass index calculation, as well as RS-232 and USB outputs to accommodate most electronic medical record applications. www.tanita.com/en

Injury Treatment

ITT supplies custom piezo ceramic components for ultrasound products. Piezo products are the heart of ultrasonic therapy devises and ultrasound equipment. The company can assist with the design and manufacture of ultrasonic hand pieces. www.ittind.com

www.biofreeze.com

Disinfectant Spray Parker Laboratories

Power Seat Uplift Technologies Inc

CoolSystems Inc

The Game Ready Injury Treatment System is a pneumatic cryotherapy system designed for use by physical therapists, professional sports teams, and athletic trainers and for use in hospitals, orthopedic clinics, and occupational health clinics. The system simultaneously delivers adjustable cold therapy and intermittent compression to the affected area to help speed recovery from injuries and surgery.

Thera-Biofreeze Pain Relieving Spray is formulated with natural menthol, methyl sulfonyl methane, Ilex, and a new blend of botanical ingredients to treat pain and discomfort associated with arthritis, painful joints, sore or strained muscles, and other conditions. The spray is available in a new 2-oz bottle as well as the 4-oz patient size for home care and a 16-oz size for inclinic treatments.

The portable Uplift Power Seat, an electric-powered cushion, and the Uplift Seat Assist, a mechanical lifting cushion, are both designed to gently and safely ease users in and out of almost any armchair or sofa. Using a patented LeveLift technology, the devices can lift users weighing up to 300 lb on a level plane without a forward dumping motion.

Parker introduces Protex Disinfectant Spray, a one-step disinfectant for a broad spectrum of pathogens, including MRSA, HIV, and staph. Protex can be used to disinfect ultrasound transducers, probes, mammography compressor plates, and other hard, nonporous, nonsurgical surfaces. The spray is EPA approved. www.parkerlabs.com

www.up-lift.com

www.gameready.com June 2009

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Product News

Software

Thera-Band Foot Roller

Software

Eclipse/MPN Software Systems Inc

The Hygenic Corp

BioEx Systems

ECLIPSE Practice Management Software has been used daily at thousands of locations for more than 20 years, according to the company. The software includes billing, scheduling, electronic health records, daily notes, an extensive alerts system, certified HIPAA-compliant electronic claims and remittance, security features, and many reports that have been fine-tuned by client feedback. www.galactek.com

The Thera-Band Foot Roller is made of supple natural rubber and is intended for patients who need relief from foot pain caused by such common conditions as plantar fasciitis and over-activity. (Therapeutic exercises for a variety of conditions are illustrated on the box.) In all applications, the Foot Roller can be chilled or frozen to help reduce inflammation. www.Thera-Band.com

Fitness Maker is an integrated software system designed specifically to aid in fitness assessment, testing, goal achievement, and development of fitness programs. Features include capture and storage of records for an unlimited number of clients, support for multiple therapists, flagging of client health-risk issues, and 20 predefined goals that can be added to or edited by the user. www.bioexsystems.com

Ad Index HPSO............................................................ Cover 2 Parker Laboratories ....................................... Cover 4

APTA Products and Services Coding and Payment Guide for the Physical Therapist ..................................... Cover 3 Membership ....................................................... 618 National Physical Therapy Month ....................... 522

www.apta.org/adinfo For more information about these companies and their products

Index to General Information Found at: www.apta.org

Physical Therapy (PTJ)

Accredited Education Programs—Changes ....................................... Education Accredited Education Programs—Full Listings ................................... Education Awards ................................................... Member Services Bylaws ................................................. APTA Communities Call for Nominations ........................... APTA Communities Code of Ethics ....................................... APTA Communities

Abstracts of Papers Accepted for Presentation at Annual Conference (added every May) .......................... www.ptjournal.org/ misc/annualcon.dtl Submission Guidelines ......................... www.ptjournal.org/ misc/ifora.dtl In Memoriam ...........................................................March Index (Author/Subject) .......................................December Mary McMillan Lecture ..................................... November Membership Statistics .................................................June Presidential Address ........................................... November Statement of Ownership ....................................December

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