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

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April 2009

Research Reports

Volume 89

Number 4

Case Reports

324

Falls in the Medicare Population

351

333

Muscle Lengthening During Passive Shoulder Motions and Stretching Techniques

Ergonomic Intervention for Upper-Extremity and Neck Pain

361

Constraint-Induced Movement Therapy in Individuals After Cerebral Hemispherectomy

342

Longitudinal Construct Validity of the GMFM-88 and GMFM-66

Perspectives 370

Sleep and Motor Learning

384

A Sensorimotor Agility Exercise Program for People With Parkinson Disease

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The Bottom Line The Bottom Line is a translation of study findings for application to clinical practice. It is not intended to substitute for a critical reading of the research article. Bottom Lines are written by invitation only.

Eric K Robertson EK Robertson, PT, DPT, OCS, is Assistant Professor, Department of Physical Therapy, Medical College of Georgia.

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

Shumway-Cook A, Ciol MA, Hoffman J, Dudgeon BJ, Yorkston K, Chan L. Falls in the Medicare Population: Incidence, Associated Factors, and Impact on Health Care. Phys Ther. 2009;89:324–332. What problems did the researchers set out to study, and why? Falls represent a major health problem in the elderly population, but the current literature has not examined the incidence of falls in the general population or in the Medicare population. Medicare is the largest health insurance program in the United States, so this information could help close a large gap in present knowledge about the impact of falls. In addition to examining the incidence of falls in the Medicare population, the investigators wanted to examine the factors related to medically injurious and recurrent falls as well as to examine health care provider response to falls and aggregate health costs as a function of fall status. What data were used in this study? Data were collected from 12,669 Medicare beneficiaries, who received a survey via a multistage, stratified sampling procedure that was designed to provide a representative sample of the entire population of Medicare beneficiaries. What new information does this study offer? The results of this study support previous data that falls are common (occurring in 22% of this sample) and often are associated with increased health care utilization costs. It was estimated that, in 2002, 3.7 million people had a single fall, and 3.1 million people had recurrent falls, with 2.2 million people reporting a fall-related injury. Forty-eight percent of Medicare beneficiaries who had a fall discussed the fall with a health care provider, and 60% of those individuals reported receiving information or guidance on fall prevention. The study identifies sociodemographic factors associated with increased likelihood of recurrent and injurious falls. What new information does this study offer for patients? This study provides information that falls are common in older persons and often result in injuries and higher health care costs. It is critical that health care providers understand as much as possible about falls as they work to prevent them. This study suggests that health care providers might be missing chances to help prevent falls, and that patients might not be reporting all falls. The study also suggests that people should report falling to a health care provider and should make sure that they know how to reduce their risk for falling. How did the researchers go about the study? A 6-question supplement that addressed issues related to falls was added to the 2002 Medicare Current Beneficiary Survey (MCBS). The MCBS is a longitudinal, ongoing survey sponsored by the Centers for Medicare and Medicaid Services. The survey examined self-reported factors related to falls, including incidence, provider response, and injuries related to falls in the previous 12 months. Cost data were obtained from Medicare claims summary data for 2002.

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The Bottom Line How might the results be applied to physical therapist practice? This information provides a current estimate of the rate and impact of falls in the Medicare population, as well as information about provider response to falls. This study suggests that health care providers might be missing opportunities to provide fall prevention services to older people and that not all falls are reported. Physical therapists can serve a primary role in identifying fallers by routinely asking older individuals about their fall history and by performing screening examinations in those who may be at risk for falls. Given evidence supporting the efficacy of fall prevention programs, the results from this study may signal an opportunity for physical therapists to have a beneficial impact on this population and on health care utilization costs. What are the limitations of the study, and what further research is needed? This study provides self-reported data from one year. A recall period of 12 months might have resulted in an under-reporting of falls. Furthermore, “falls” were not specifically defined, and provider response to falls was measured indirectly. Because the data were from a single year, the logistic regression models that were used could not determine risk, only association. Future research should examine specific risk factors related to falls, factors affecting the reporting of falls, provider response to falls, and more specific data about costs from injuries sustained in falls.

April 2009

Volume 89 Number 4 Physical Therapy ■ 323

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

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 JM 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

President: R Scott Ward, PT, PhD

Statistical Consultants

Vice President: Randy Roesch, PT, MBA, DPT

Steven E Hanna, PhD, Hamilton, Ont, Canada; John E Hewett, PhD, Columbia, MO; Hang Lee, PhD, Boston, MA; Samuel Wu, PhD, Gainesville, FL

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 CF McDavitt, PT, DPT, MS, FAAOMPT; Paul A Rockar Jr, PT, DPT, MS; Lisa K Saladin, PT, PhD; John G Wallace Jr, PT, MS, OCS

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; 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

Founded in 1921, Physical Therapy (PTJ) is the official publication of the American Physical Therapy Association (APTA) and is an international, scholarly, peer-reviewed journal. PTJ serves APTA members, other health care professionals, and patients/clients by (1) documenting basic and applied knowledge related to physical therapy, (2) providing evidence to guide clinical decision making, and (3) publishing a variety of research that is relevant to the field and diverse opinions that are based in scholarly arguments. PTJ, like the profession it serves, strives to enhance the health and well-being of all members of society.

April 2009

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.

Technologies. Ingenta provides online document delivery for articles published since September 1988. Full-text articles are available for free at www.ptjournal.org 12 months after the publication date. Full text also is provided through DataStar, Dialog, EBSCOHost Academic Search, Factiva, InfoTrac, ProFound, and ProQuest.

Reprints

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

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

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Research Report

Falls in the Medicare Population: Incidence, Associated Factors, and Impact on Health Care Anne Shumway-Cook, Marcia A Ciol, Jeanne Hoffman, Brian J Dudgeon, Kathryn Yorkston, Leighton Chan A Shumway-Cook, PT, PhD, FAPTA, is Professor Emeritus, Department of Rehabilitation Medicine, Box 356490, University of Washington, Seattle, WA 981956490 (USA). Address all correspondence to Dr Shumway-Cook at: [email protected].

Background and Purpose. Falls are a major health problem in the elderly community; however, questions regarding incidence, risk factors, and provider response to falls exist. The purpose of this study was to examine the incidence of falls, associated factors, health care costs, and provider response to falls among Medicare beneficiaries.

MA Ciol, PhD, is Research Associate Professor, Department of Rehabilitation Medicine, University of Washington.

Participants. The participants were 12,669 respondents to the Medicare Current

J Hoffman, PhD, is Assistant Professor, Department of Rehabilitation Medicine, University of Washington.

(medically injurious versus not medically injurious) were created from the falls supplement to the MCBS. Means and proportions for the entire Medicare population were estimated using sampling weights. The association between sociodemographic variables and fall status was modeled using ordinal or binary logistic regression. Aggregate health costs by fall category were estimated from claims data.

BJ Dudgeon, OT, PhD, is Associate Professor, Department of Rehabilitation Medicine, University of Washington. K Yorkston, PhD, is Professor, Department of Rehabilitation Medicine, University of Washington. L Chan, MD, MPH, is Chief, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD 208921604. [Shumway-Cook A, Ciol MA, Hoffman J, et al. Falls in the Medicare population: incidence, associated factors, and impact on health care. Phys Ther. 2009;89:324 –332.]

Beneficiaries Survey (MCBS).

Methods. Categories of number of falls (none, one, recurrent) and injury type

Results. Population estimates of falls reported in 2002 ranged from 3.7 million (single fall) to 3.1 million (recurrent falls), with an estimated 2.2 million people having a medically injurious fall. Recurrent falls were more likely with increased age, being female, being nonwhite, reporting fair or poor health, and increased number of limitations in personal activities of daily living and instrumental activities of daily living and comorbidities. Although estimates of the actual costs of falls could not be determined, “fallers” consistently had larger utilization costs than “nonfallers” for the year 2002. Fewer than half (48%) of the beneficiaries reported talking to a health care provider following a fall, and 60% of those beneficiaries reported receiving fall prevention information. Discussion and Conclusions. Falls are common and may be associated with significant health care costs. Most importantly, health care providers may be missing many opportunities to provide fall prevention information to older people.

© 2009 American Physical Therapy Association

Post a Rapid Response or find The Bottom Line: www.ptjournal.org 324

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alls are a major health problem in the elderly community, increasing the risk for mortality, morbidity, disability, and frailty.1,2 Among older adults, falls are the leading cause of death from injury.3 Forty percent of hospital admissions of older adults were the result of fall-related injuries, resulting in an average length of stay of 11.6 days.3 Approximately one half of older adults hospitalized for fall-related injuries are discharged to nursing homes.4 Falls that do not lead to injury often begin a downward spiral of fear that leads to inactivity and decreased strength (force-generating capacity), agility, and balance and often results in loss of independence in normal activities of self-care.5

Because of the association of falls with mortality, morbidity, and disability, several studies have investigated the incidence of falls and associated risk factors among cohorts of elderly people, including those living in the community,1,6 those who are institutionalized,7 and those with specific comorbidities.8 The Centers for Disease Control and Prevention estimates that approximately one third of people 65 years of age and older fall each year.9 Although there have been several population-based studies examining the incidence of injurious falls,7–9 the incidence of falls in the general population, and among Medicare recipients specifically, has not been investigated. Given that Medicare is the largest health insurance program in the United States, with 44 million enrollees whose medical care costs $271 billion per year,10 this represents a large gap in our knowledge. In addition, Medicare has led to significant changes for elderly people in both better health and risk-reduction, thereby reducing mortality and improving care. Further examination of falls in this population could lead to changes in care that may improve health and functioning as individuals age. April 2009

Falls represent a challenge to all health care professionals, but especially to physical therapists, who provide specialized expertise in several areas, including screening highrisk populations, assessment of risk factors related physical function (eg, balance, gait, strength), and implementation of risk-reduction strategies, including development of exercise programs, selection and training in the use of assistive devices, patient education, and identification of potential risks and barriers in the home.9 A better understanding of the incidence of falls, especially medically injurious falls, among Medicare beneficiaries has health policy implications because incidence rates can be used by physical therapists and other health care professionals to justify the development of new programs designed to target older adults at risk for falls. Clinical guidelines related to fall prevention recommend that on a yearly basis all adults over the age of 65 years should be asked by a health care provider whether they have had a fall; among those who report a fall, efforts should be directed at determining the causes of falls, and strategies to reduce future risk should be implemented.11 There is, however, limited information regarding the extent to which guidelines are being implemented, including how often older adults discuss falls with a health care provider, and the extent to which risk factors are assessed and managed. In 2002, a 6-question supplement was added to the health and functioning questionnaire portion of the Medicare Current Beneficiary Survey (MCBS) to address issues related to falls, including incidence and provider response. The purpose of this study was to use the falls supplement to the MCBS to provide a national estimate of the incidence of falls in the Medicare population, to identify

factors associated with having recurrent falls or medically injurious falls, to examine health care provider response to reported falls, and to compare aggregate health care costs as a function of fall status.

Method Sampling Frame The MCBS is a longitudinal survey of the Medicare population sponsored by the Centers for Medicare and Medicaid Services, which started in 1992 and is still ongoing.10 To obtain a nationally representative sample of Medicare beneficiaries, the MCBS uses a multistage, stratified sampling design. The United States is divided into 107 primary sampling units, which are further divided into clusters by postal ZIP codes. Medicare beneficiaries within each cluster are selected by systematic random sampling by age strata, with oversampling of adults aged 85 years and older. The multistage sampling scheme is used to create weights that allow estimation of means and proportions at national and regional levels. Each person in the sample is followed for up to 4 years, and every

Available With This Article at www.ptjournal.org • Special Podcast: Alan Jette and Justin Moore, APTA Director of Federal Government Affairs, discuss health care research provisions in the stimulus bill. Available April 10th at http:// www.ptjournal.org/misc/ podcasts.dtl. • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on February 19, 2009, at www.ptjournal.org.

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Falls in the Medicare Population year about one third of the sample is renewed by removing people who have been in the sample for 4 years and adding a new group of older adults. Each year a person is interviewed every 4 months, with the questions about health and functioning asked only during the autumn interview. Therefore, this ongoing survey allows for certain types of longitudinal analysis. However, because the falls supplement was implemented in the health and function interview only for 2 years, we had to limit our data analysis to a crosssectional analysis of the 2002 MCBS. A total of 12,669 beneficiaries (65 years or older) were included in the 2002 MCBS and were given the community questionnaire and falls supplement. Interviews with beneficiaries living in institutions (eg, skilled nursing facilities) are not included in the community survey data. Beneficiaries participating in the community survey were interviewed in person or by proxy. Data were collected on a wide variety of items, including use of health services, medical care expenditures, sources of payment, and health status and functioning. Demographic and behavioral information such as income, education level, and living arrangements also was collected. MCBS Falls Supplement The MCBS 2002 falls supplement was used to determine the selfreported incidence of falls and health care provider response to those falls. Responses to 2 questions—“In the past 12 months have you fallen down?” and “How many times in the last year have you fallen down?”—were used to estimate incidence of fall category: none, one, and recurrent falls (⬎1). Responses to the question “In that fall(s), did you hurt yourself badly enough to get medical help?” were used to establish incidence of medically injurious falls. Responses to 3 questions— 326

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“Did you talk to a doctor/medical professional about that fall(s)?” “Did the health care provider talk with you to understand why you fell?” and “Did the health care provider talk with you about how to prevent falls?”— were used to characterize health care provider response to falls. Cost and Use Data Cost data were used to determine total annual cost and cost by type of use as a function of fall category. Summary data from Medicare health care claims for 2002 were used to estimate average annual costs in dollars for home health, inpatient, outpatient, medical provider, and prescription medicine events. Sociodemographic and Clinical Characteristics Variables of interest, other than age and sex, were divided into binary categories and included race (white of non-Hispanic origin versus nonwhite), marital status (currently married versus not married), socioeconomic status (SES, annual income of $25,000 or more versus less), education (less than high school versus high school or more),12 living status (alone versus living with others), self-report of general health (endorsing fair or poor health versus good to excellent health), and smoking status (currently a smoker versus not currently a smoker). The number of comorbidities was determined by a simple count of the respondent’s endorsements of 18 clinical conditions, such as cancer, hypertension, diabetes, acute myocardial infarction, coronary heart disease, stroke, rheumatoid arthritis or osteoarthritis, Alzheimer disease, Parkinson disease, emphysema, and hip fracture. A nonresponse to a comorbidity item was classified as not having that comorbidity. Body mass index (BMI) was calculated using the individual’s self-reported height and weight and was grouped into 3 categories: overweight (BMIⱖ30), un-

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derweight (BMIⱕ18), or in the normal range (18⬍BMI⬍30). Personal activities of daily living (ADLs) included in the survey were bathing, dressing, eating, getting in and out of chairs, walking, and using the toilet. Instrumental activities of daily living (IADLs) included in the survey were use of the telephone, light housework, heavy housework, meal preparation, shopping, and money management. Limitations in ADLs and IADLs were determined using beneficiary responses to the question “Because of a health or physical problem, do you have any difficulty _______?” Possible responses were “yes,” “no,” or “doesn’t do.” A response of “doesn’t do” triggered a follow-up question as to whether the respondent did not do the activity for health or physical reasons. If the response was “yes,” the respondent was classified as having difficulty with that activity. The number of ADLs or IADLs in which a person had difficulties was categorized into 3 groups: no ADL or IADL difficulties, 1 to 3 ADL or IADL difficulties, and 4 to 6 ADL or IADL difficulties. Data Analysis Incidence of falls during the year prior to the interviews was estimated using the weights provided by the multistage sampling scheme used in the MCBS.10 These estimates were calculated for the entire Medicare population, as well as for subgroups defined by sociodemographic and clinical variables. For the subgroup of “fallers,” simple means and proportions were used because this subsample did not contain individuals in all primary sampling units, precluding us from using the weighted estimation. The t test was used to compare age in the groups with and without medically injurious falls. The chisquare test was used for all other categorical variables.

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Falls in the Medicare Population Ordinal logistic regression,13 using the weights provided by the MCBS sampling scheme, was used to study associations between the categories of falls (no falls, 1 fall, or 2 or more falls) and the sociodemographic and clinical factors. This analysis was not an analysis of risk factors since the data were collected in a crosssectional fashion. Instead, it was a means of finding variables that should be studied in future longitudinal studies. Simple binary logistic regression (without weights) was used to model medically injurious falls (“yes” versus “no”) in order to identify potentially important variables for future longitudinal studies of injurious falls. Although the logistic regressions were an exploratory analysis as opposed to a confirmatory analysis, we considered variables to be statistically significant at the .05 level. Analyses were performed using SPSS version 15* and Intercooled Stata 10.0† software.

weight or overweight, had at least one ADL or IADL difficulty, and had 4 or more comorbidities.

Results

The ordinal logistic regression analysis examined the factors associated with being in 1 of 3 categories of falling (no falls, 1 fall, and 2 or more falls). The likelihood of being in the higher categories of falling (1 fall and 2 or more falls) increased with advancing age (odds ratio [OR]⫽1.01, P⫽.02, 95% confidence interval [CI]⫽1.00 –1.02), being female (OR⫽1.14, P⫽.01, CI⫽1.03–1.27), being white (OR⫽1.40, P⬍.001, CI⫽1.20 –1.63), reporting fair or poor health (OR⫽1.20, P⫽.001, CI⫽1.08 –1.34), reporting more ADL or IADL limitations and comorbidities (OR⫽1.94 [CI⫽1.72–2.18] and 2.39 [CI⫽1.90 –3.00] for ADL categories compared with none; OR⫽1.54 [CI⫽1.37–1.73] and 1.94 [CI⫽1.59 – 2.35] for IADL categories compared with none; OR⫽1.32 [CI⫽1.06 – 1.64], 1.74 [CI⫽1.39 –2.16], and 2.54 [CI⫽1.91–3.39] for categories of comorbidity compared with none; all Pⱕ.01). Education (P⫽.90), SES (P⫽.32), marital status (P⫽.24),

Incidence and Sociodemographic and Clinical Characteristics by Fall Category Table 1 summarizes the estimated incidence of falls and compares the distribution of sociodemographic and clinical characteristics by fall category. From the MCBS, we estimated that 22.1% of Medicare beneficiaries 65 years of age and older fell in the previous year, representing 6.86 million people. Recurrent falls occurred in 10% of this population, translating to 3.1 million people. Mean age was slightly higher for fallers than for nonfallers. Among the fallers, there were higher percentages of women, white non-Hispanic participants, and participants who were not married, had lower education, had a lower SES, were living alone, reported fair or poor health, were either under* SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606. † StataCorp LP, 4905 Lakeway Dr, College Station, TX 77845.

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Table 2 shows sociodemographic and clinical characteristics of fallers by the categories of falls requiring versus not requiring medical attention. Thirty-three percent of the participants who reported at least one fall in the previous year required medical attention for at least one fall. This percentage would translate roughly to an estimated 2.23 million older adults who require medical attention due to a fall. Older adults who required medical attention tended to be slightly older, with higher proportions of women, participants who were not married, and participants who were living alone, reported fair or poor health, were not smoking (though this may be because this was an older group), had at least one ADL or IADL difficulty, and had more comorbidities.

smoking status (P⫽.46), living status (P⫽.11), and BMI categories (P⫽.93 and .78) were not statistically significant in the model. For injurious falls, only the subset of participants who had at least one fall was analyzed. The likelihood of having an injurious fall increased for being female (OR⫽1.56, P⬍.001, CI⫽1.30 –1.88), having an SES of $25,000 or more (OR⫽1.28, P⫽.01, CB⫽1.06 –1.55), not being married (OR⫽1.30, P⫽.04, CI⫽1.01–1.65), reporting poor or fair health (OR⫽1.31, P⫽.006, CI⫽1.08 –1.59), and not being a current smoker (OR⫽1.41, P⫽.03, CI⫽1.03–1.92). Age (P⫽.12), race (P⫽.98), education (P⫽.42), living status (P⫽.67), BMI categories (P⫽.93 and .54), and categories of ADL (P⫽.81 and .06), IADL (P⫽.81 and .41), and comorbidities (P⫽.30, .28, and .23) were not statistically significant in the model. Provider Response to Falls Health care provider response to falls as reported by Medicare beneficiaries is summarized in the Figure. Among beneficiaries who reported falls, fewer than half (⬇48%) reported talking to a health care professional about their fall. Of those who did report talking to a health care provider, 75% indicated that their health care provider tried to understand the circumstances and reasons for the fall, and 61% reported receiving fall prevention information following their fall. Aggregate Health Care Costs Table 3 compares health care costs (mean US dollars per year by health care category and total costs) among the 3 fall status categories (no falls, 1 fall, and 2 or more falls). Compared with older adults reporting no falls, total aggregate health care costs were $2,000 (29%) higher in older adults reporting 1 fall and $5,600 (79%) higher among those reporting

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Falls in the Medicare Population Table 1. Weighted Estimates of Incidence and Sociodemographic and Clinical Characteristics by Category of Number of Falls in the Previous Year, With 95% Confidence Intervals (in Parentheses) Falls in Previous Year Characteristic Sample size

None

a

9,685

Estimated incidence, %

77.9 (77.0–78.8)

Estimated population, in millions

24.20 (23.93–24.47)

Mean age, y

74.9 (74.8–75.1)

1 1,580 12.1 (11.4–12.7) 3.75 (3.54–3.96) 76.7 (76.4–77.0)

2 or More 1,329 10.0 (9.5–10.6) 3.11 (2.94–3.29) 76.6 (76.2–77.1)

Sex: % male

44.2 (43.3–45.4)

33.7 (31.8–35.9)

40.1 (37.3–42.8)

Race: % white non-Hispanic

86.0 (84.8–87.2)

88.7 (87.0–90.3)

88.7 (86.4–91.0)

Marital status: % married

56.8 (55.6–57.9)

49.8 (47.2–52.3)

51.7 (48.3–55.0)

Education: % less than high school

28.7 (27.3–30.1)

30.0 (27.6–32.5)

37.6 (34.6–40.6)

Socioeconomic status: % with income of less than $25,000/y

55.4 (53.9–56.9)

62.1 (59.2–65.0)

64.5 (61.5–67.4)

Living status: % living alone

31.0 (29.9–32.0)

37.3 (34.7–39.9)

32.3 (29.4–35.3)

Health status: % poor or fair

18.9 (18.1–19.8)

25.8 (23.5–28.1)

41.6 (38.7–44.5)

Current smoker: % yes

11.6 (10.8–12.4)

9.0 (7.4–10.5)

11.1 (9.4–12.8)

1.7 (1.4–2.0)

2.0 (1.3–2.9)

2.5 (1.5–3.4)

18–30

78.2 (77.2–79.2)

74.9 (72.5–77.3)

73.2 (70.5–75.8)

ⱖ30

20.0 (19.1–21.0)

23.0 (20.7–25.4)

24.3 (21.7–26.9)

0 difficulties

77.5 (76.5–78.6)

63.9 (61.1–66.6)

38.7 (35.8–41.6)

1–3 difficulties

18.7 (17.7–19.7)

29.7 (27.2–32.2)

44.3 (41.7–47.0)

4–6 difficulties

3.7 (3.4–4.1)

6.5 (5.2–7.7)

17.0 (14.7–19.3)

0 difficulties

69.3 (68.5–70.7)

53.6 (50.7–56.6)

33.6 (30.7–36.4)

1–3 difficulties

24.5 (23.5–25.6)

35.4 (32.7–38.1)

43.3 (40.8–45.9)

4–6 difficulties

5.8 (5.3–6.3)

11.0 (9.2–12.7)

23.1 (20.4–25.7)

None

10.0 (9.3–10.7)

5.6 (4.4–6.9)

3.4 (2.6–4.5)

1–3

62.2 (61.1–63.3)

56.3 (53.6–59.0)

41.9 (39.2–44.6)

4–6

24.6 (23.6–25.6)

32.6 (30.1–35.1)

41.6 (38.9–44.4)

3.2 (2.8–3.5)

5.5 (4.4–6.6)

13.1 (11.1–15.1)

Body mass index: % in category ⱕ18

Personal activities of daily living: % with difficulties

Instrumental activities of daily living: % with difficulties

Comorbidities: % with

7 or more a

Seventy-five individuals did not provide information on falls in the previous year.

recurrent falls. The distribution of costs as a percentage of total costs by health care category was similar across the 3 fall status categories, with a range of 3% to 5% of health care dollars spent on home health, 30% to 36% spent on inpatient care, 30% to 36% spent on provider costs, 11% to 13% spent on outpatient costs, and 17% to 19% spent on medications. Total health care costs were 328

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$4,100 (44%) higher for beneficiaries reporting medically injurious falls compared with those with nonmedically injurious falls. Among those with medically injurious falls, inpatient costs contributed 39% to total health care costs, compared with 32% in those with nonmedically injurious falls.

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Discussion and Conclusions This study estimated that 22% of community-dwelling Medicare beneficiaries 65 years of age and older have one or more falls in the previous year, slightly less than a previously published estimate of 30%.1 Consistent with other published reports,14 recurrent falls recalled retrospectively were reported by 10% of this population. Higher rates of reApril 2009

Falls in the Medicare Population Table 2. Sociodemographic and Clinical Characteristics of “Fallers” by Category of (at Least 1) Medically Injurious Versus Non-Medically Injurious Fall Medically Injurious Falla Characteristic Sample size, %c Mean age, y (SD)

Pb

No

Yes

1,961 (67.4)

947 (32.6)

77.7 (7.7)

78.9 (7.7)

⬍.001

Sex: % male

41.1

30.1

⬍.001

Race: % white non-Hispanic

89.3

88.9

.92

Marital status: % married

51.5

42.2

⬍.001

Education: % less than high school

35.9

35.2

.73

Socioeconomic status: % with income of less than $25,000/y

65.0

64.9

.97

Living status: % living alone

34.8

40.5

.003

Health status: % poor or fair

31.9

37.5

.003

Current smoker: % yes

10.0

7.0

.007

2.5

2.7

18–30

74.3

77.1

ⱖ30

23.2

20.2

0 difficulties

51.7

46.1

1–3 difficulties

38.0

37.7

4–6 difficulties

10.3

16.2

0 difficulties

44.2

38.0

1–3 difficulties

39.6

39.6

4–6 difficulties

16.2

22.4

4.6

3.3

1–3

49.9

46.8

4–6

36.6

39.4

9.0

10.6

Body mass index: % in category ⱕ18

.18

Personal activities of daily living: % with difficulties ⬍.001

Instrumental activities of daily living: % with difficulties ⬍.001

Comorbidities: % with None

7 or more

.07

a

Using nonweighted proportion. b P value from t test for age and from chi-square test for all other variables. c One person reporting a fall did not report on injury type.

current falls (25%) have been reported among community-dwelling elderly people followed prospectively for 3 years.15 Having recurrent falls was associated with increased age, being female, being white, reporting fair or poor health, and increased limitations in activities of daily life, consistent with other published reports.16,17 Medically injurious falls were reported by 33% of the fallers in this April 2009

population and, consistent with other reports,16,17 were associated with being female, having an SES of $25,000 or more, not being married, reporting poor or fair health, and not being a smoker. This study did not find that the rate of injurious falls increased with age, BMI, ADL or IADL disability, or comorbidity, as reported by other authors.7 Our study also showed a strong relationship between fall status and health care costs, consistent with the study

by Rizzo et al,18 who reported a monotonic relationship between health care costs and the frequency and severity of falls among Medicare beneficiaries. Our study showed that only half of older adults who fell reported discussing this with their health care provider. Among those who reported a fall-related discussion, 74% reported their health care provider attempted to ascertain the cause of

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Figure. Medicare beneficiary–reported provider response to falls.

the fall, and 61% reported receiving information on strategies to prevent future falls. These results suggest that a significant number of older adults who fall are not discussing the event with a health care provider. In addition, among those who did report falls to a health care provider, almost half reported failure to receive follow-up services related to the assessment and management of risk factors for falls. Again, this finding is consistent with other reports

that health care providers underdetect and undermanage falls.19 Several authors20,21 have cited both patient-centered and system barriers to adherence to clinical guidelines related to fall prevention in older adults. Provider training in conjunction with education targeting older adults may be necessary to successfully implement an effective fall risk assessment and management program.20,21 Strategies to reduce falls

among both geriatric and neurologic populations have been identified as a high priority in the profession of physical therapy, as evidenced by the American Physical Therapy Association’s participation in the National Falls Prevention Coalition. However, there is no consensus as to best practices related to fall prevention that are uniformly and consistently adopted across physical therapists.

Table 3. Health Care Costs (Mean Dollars During Year After Reported Fall) by Fall Category No. of Falls Variable Total expenses

Medical Attention Required

None (nⴝ7,247)

1 (nⴝ1,128)

2 or More (nⴝ867)

No (nⴝ1,386)

Yes (nⴝ634)

7,049

9,113

12,647

9,387

13,507

Itemized expenses Home health

215

388

666

320

962

Inpatient

2,123

3,281

4,319

3,047

5,275

Medical provider

2,537

2,925

3,782

3,027

3,903

804

972

1,638

1,191

1,415

1,370

1,547

2,242

1,802

1,952

Outpatient Prescribed medication

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April 2009

Falls in the Medicare Population A recent study demonstrated that a multifactorial intervention, which included physical therapy, was not effective in decreasing falls in a population of community-dwelling older adults.22 Mahoney et al22 used a randomized control trial to investigate the impact of a moderate-intensity, multifactorial, community-based fall prevention program in 349 older adults (65 years of age and older) with a history of falls. The primary outcome was number of falls over a 12-month period. Participants in the intervention group received 2 inhome visits from either a trained nurse or physical therapist who assessed fall risk factors and made recommendations based on an intervention algorithm. The control group received a home safety assessment. The intervention algorithm evaluated medications, vision, balance and gait, some neurologic deficits, cognition, mood, home functioning, and home safety. Recommendations were mailed to the participants’ primary physician, and participants were asked to see their primary physician within 1 month to review recommendations. The recommendation to refer a participant for physical therapy was triggered by one of the following conditions: moderate impairment on the Berg Balance Test, abnormal gait on the Performance-Oriented Mobility Assessment, inability to stand for 30 seconds on a hard or foam surface with eyes open, or a history of pain while walking or exercising. Optional triggers including loss of balance with a sternal nudge, positive Romberg test, absent vibratory sensation at the ankle or metatarsophalangeal joint, inability to stand for 30 seconds on a hard or foam surface with eyes closed, a score less than 80 on the Activities Specific Balance Confidence Scale, and potentially risky mobility-related activity during the performance of daily activities. Physical therapists were asked to prescribe a home exercise program April 2009

at the end of therapy and to encourage patients to participate in a group exercise program. Adherence to recommendations including physical therapy and exercise was determined through monthly telephone calls and or return of a monthly exercise calendar. Mahoney and colleagues22 found no significant difference between the control and intervention groups with respect to falls. The study showed that although 84% of the participants were referred for physical therapy, one third of them refused physical therapy. The reasons cited for refusing physical therapy included difficulty traveling, concern about cost, and disbelief in its efficacy. In addition, the authors reported that among participants who attended physical therapy sessions, one half received one-time balance exercise instruction rather than a course of physical therapy, many physical therapists did not prescribe a home exercise program at the end of therapy, and there was limited progression of balance exercises. Finally, the authors reported inconsistency across physical therapists regarding the frequency, duration, and intensity of therapy needed to reduce falls.22 These findings suggest a need in the profession of physical therapy to identify and implement a consistent approach to management of falls due to physical factors such as reduced strength and impaired balance and gait among older adults. A major limitation of this study was bias associated with a 12-month recall period. A recall period of 12 months has been shown to have good specificity but poor sensitivity.23 Our recall period of 12 months likely resulted in an underreporting of falls; thus, incidence rates are likely underestimated. “Falls” were not explicitly defined within the survey and thus were subject to respondents’ individual interpretation. In

addition, health care provider response to reported falls was not measured directly but instead was determined by beneficiary report. It is possible that older adults may not have perceived some interventions, such as referral for management of gait and balance problems, as a strategy for reducing fall risk, thus failing to include this in their summary of provider response. Our cost analysis examined per annum costs by fall category. We were unable to determine what percentage of costs were fall related, although fallers consistently had higher costs compared with nonfallers. However, it is possible that the higher costs are due to comorbidity conditions (eg, diabetes) that require higher health care utilization and are not a direct consequence of the falls. Finally, in the logistic regression models, there are 2 limitations. Although a person can be followed for up to 4 years in the MCBS, the available data for falls were crosssectional, as the MCBS was applied during one round of the survey. Therefore, the logistic models can assess only association, and they cannot assess risk of falling. Additionally, factors statistically associated with being a recurrent faller or having an injurious fall in those models may be influenced by the correlation between variables used in the model. Despite these limitations, this study provides the first national annual incidence estimate of falls among adults 65 years of age and older in the Medicare population and identified factors associated with being a recurrent faller or experiencing a medically injurious fall. This study confirms previous work suggesting that falls are common among elderly people and may lead to injury and increased medical costs. It extends the current literature by examining health care provider response to falls. Because there is growing con-

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Falls in the Medicare Population sensus that interventions for prevention of falls are effective,8 these interventions should be provided routinely to elderly individuals who have fallen or who are at risk for falls. Our data suggest that this is not the case. Physical therapists are uniquely prepared to provide appropriate intervention. Clinicians not only should be aware of the high incidence of falls among communitydwelling elderly people and those factors that are associated with falls, but also should adopt consistent practices related to assessment and management of fall risk in elderly people. All patients above the age of 65 years should be asked about fall history, with follow-up screening for underlying risk factors, including balance, gait, and lower-extremity strength, in high-risk populations. Management of fall risk factors based on current best evidence needs to be integrated into physical therapist practices, and standardized measures to examine outcomes related to fall and risk factors need to be established. Finally, further research is needed to examine the effectiveness of physical therapy strategies for managing falls in both geriatric and neurologic populations. All authors provided concept/idea/research design and writing. Dr Shumway-Cook, Dr Ciol, Dr Hoffman, and Dr Chan provided data analysis and interpretation. Dr Chan provided project management, fund procurement, facilities/equipment, institutional liaisons, and consultation (including review of manuscript before submission). A poster presentation of this research was given at the American Congress of Rehabilitation Medicine–American Society of Neurorehabilitation 2006 Joint Congress; September 27-October 1, 2006; Boston, Massachusetts.

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This study was supported with funding from Centers for Disease Control and Prevention (MM-0625– 04/04) through an Extramural Project Grant with the Association of Academic Medical Centers. Additional resources were provided by the Centers for Medicare and Medicaid Services. This article was received April 5, 2007, and was accepted December 29, 2008. DOI: 10.2522/ptj.20070107

References 1 Hausdorff JM, Rios DA, Edelber HK. Gait variability and fall risk in community-living older adults: a 1-year prospective study. Arch Phys Med Rehabil. 2001;82:1050 – 1056. 2 Hornbrook MC, Stevens VJ, Wingfield DJ, et al. Preventing falls among communitydwelling older persons: results from a randomized trial. Gerontologist. 1994;34:16 – 23. 3 Centers for Disease Control and Prevention. Web-based Injury Statistics Query and Reporting System (WISQARS) [Online], 2003. National Center for Injury Prevention and Control, Centers for Disease Control and Prevention (producer). Available at: www.cdc.gov/ncipc/wisqars. Accessed July 26, 2006. 4 Sattin RW, Lambert Huber DA, DeVito CA, et al. The incidence of fall injury events among the elderly in a defined population. Am J Epidemiol. 1990;131:1028 –1037. 5 Laird RD, Studenski S, Perera S, Wallace D. Fall history is an independent predictor of adverse health outcomes and utilization in the elderly. Am J Manag Care. 2001;7: 1133–1138. 6 Tinetti ME, Williams CS. The effect of falls and fall injuries on functioning in community-dwelling older persons. J Gerontol A Biol Sci Med Sci. 1998;53:M112. 7 Gillespie LD, Gillespie WJ, Robertson MC, et al. Interventions for preventing falls in elderly people. Cochrane Database Syst Rev. 2003;4:CD000340. 8 Chang JT, Morton SC, Rubenstein LZ, et al. Interventions for the prevention of falls in older adults: systematic review and metaanalysis of randomized clinical trials. BMJ. 2004;328:680 – 683. 9 Rubenstein LZ. Falls in older people: epidemiology, risk factors and strategies for prevention. Age Ageing. 2006;35(suppl 2):37– 41. 10 Centers for Medicare & Medicaid Services Web site. Available at: http://www.cms.hhs. gov/mcbs. Accessed September 24, 2006.

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11 American Geriatrics Society. Guideline for the prevention of falls in older persons. J Am Geriatr Soc. 2001;49:664 – 672. 12 Chan L, Doctor JN, MacLehose RF, et al. Do Medicare patients with disabilities receive preventive services? A populationbased study. Arch Phys Med Rehabil. 1999;80:642– 646. 13 Hosmer DW, Lemeshow S. Applied Logistic Regression. New York, NY: John Wiley & Sons Inc; 1989. 14 Morris M, Osborne D, Hill K, et al. Predisposing factors for occasional and multiple falls in older Australians who live at home. Aust J Physiother. 2004;50:153–159. 15 Pluijm SM, Smit JH, Tropm EA, et al. A risk profile for identifying communitydwelling elderly with a high risk for recurrent falling: results of a 2-year prospective study. Osteoporos Int. 2006;17:417– 425. 16 Stevens JA. Falls among older adults: risk factors and prevention strategies. In: Falls Free: Promoting a National Falls Prevention Action Plan. Washington, DC: National Council on Aging; 2004:3–19. 17 Annual rate of nonfatal medically attended fall injuries among adults aged ⬎65: United States 2001–2203. MMWR. 2006; 31:857. 18 Rizzo JA, Friedkin R, Williams CS, et al. Health care utilization and costs in a Medicare population by fall status. Med Care. 1998;36:1174 –1188. 19 Rubenstein LZ, Solomon DH, Roth CP, et al. Detection and management of falls and instability in vulnerable elders by community physicians. J Am Geriatr Soc. 2004;52:1527–1531. 20 Chou WC, Tinetti ME, King MB, et al. Perceptions of physicians on the barriers and facilitators to integrating fall risk evaluation and management into practice. J Gen Intern Med. 2006;21:117–122. 21 Fortinsky RH, Iannuzzi-Sucich M, Baker DI, et al. Fall-risk assessment and management in clinical practice: views from healthcare providers. J Am Geriatr Soc. 2004;52:1522–1526. 22 Mahoney JE, Shea TA, Przybelski R, et al. Kenosha county falls prevention study: a randomized, controlled trial of an intermediate-intensity, community-based multifactorial falls intervention. J Am Geriatr Soc. 2007;55:489 – 498. 23 Ganz DA, Higashi T, Rubenstein LZ. Monitoring falls in cohort studies of community-dwelling older people: effect of the recall interval. J Am Geriatr Soc. 2005;53:2190 –2194.

April 2009

Research Report Lengthening of the Pectoralis Minor Muscle During Passive Shoulder Motions and Stretching Techniques: A Cadaveric Biomechanical Study Takayuki Muraki, Mitsuhiro Aoki, Tomoki Izumi, Misaki Fujii, Egi Hidaka, Shigenori Miyamoto

Background and Purpose. Lengthening of the pectoralis minor muscle (PMi) during passive shoulder motions and the effect of stretching techniques for this muscle are unclear. The purposes of this study were: (1) to investigate the amount and pattern of the lengthening between passive shoulder motions and (2) to determine which stretching technique effected the greatest change in PMi length. Methods. Nine fresh cadaveric transthoracic specimens were used. Lengthening in the lateral and medial fiber group of the PMi was directly measured during 3 passive shoulder motions (flexion, scaption, and external rotation at 90° of abduction) and 3 stretching techniques (scapular retraction at 0° and 30° of flexion and horizontal abduction) for this muscle. The measurement was conducted by using a precise displacement sensor.

Results. Although the length of the PMi linearly increased during all shoulder motions, lengthening during flexion and scaption was steeper and significantly larger than that during external rotation at 90 degrees of abduction. For the stretching techniques, scapular retraction at 30 degrees of flexion and horizontal abduction stretched the PMi more than scapular retraction at 0 degrees of flexion. In comparison with lengthening at 150 degrees of flexion, scapular retraction at 30 degrees of flexion significantly stretched the medial fiber group of the muscle. Discussion and Conclusion. The extensive lengthening of the PMi is necessary during shoulder motions, especially flexion and scaption. Scapular retraction at 30 degrees of flexion makes the greatest change in PMi length. This study suggests the importance of the PMi in shoulder motion and provides anatomical and biomechanical evidence that might guide appropriate selection of stretching techniques.

T Muraki, PT, PhD, is Doctoral Student, Doctoral Course of Physical Therapy, Graduate School of Health Sciences, Sapporo Medical University, South 1, West 17, Chuo-ku, Sapporo 060-8556, Japan. Address all correspondence to Dr Muraki at: [email protected]. M Aoki, MD, PhD, is Associate Professor, Department of Physical Therapy, School of Health Sciences, Sapporo Medical University. T Izumi, PT, MS, is Doctoral Student, Doctoral Course of Physical Therapy, Graduate School of Health Sciences, Sapporo Medical University. M Fujii, PT, MS, is Doctoral Student, Doctoral Course of Physical Therapy, Graduate School of Health Sciences, Sapporo Medical University. E Hidaka, PT, MS, is Doctoral Student, Doctoral Course of Physical Therapy, Graduate School of Health Sciences, Sapporo Medical University. S Miyamoto, PT, PhD, is Professor, Department of Physical Therapy, Hokkaido Bunkyo University, Sapporo, Japan. [Muraki T, Aoki M, Izumi T, et al. Lengthening of the pectoralis minor muscle during passive shoulder motions and stretching techniques: a cadaveric biomechanical study. Phys Ther. 2009; 89:333–341.] © 2009 American Physical Therapy Association Post a Rapid Response or find The Bottom Line: www.ptjournal.org

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T

he potential relationship of scapular position and motion to shoulder disorders has made them of great interest to many clinicians and researchers.1– 6 Studies using 3-dimensional motion analysis clarified the details of the scapular motion during shoulder motion.7–10 Upward and external rotation and posterior tilting of the scapula were seen during shoulder elevation, regardless of elevation plane.8,10 Similar scapular motions also were confirmed near the end range of external rotation at 90 degrees of abduction.8 The differences in scapular motion between people who are healthy and patients with shoulder disorders have been investigated. Previous studies demonstrated decreases in scapular posterior tilting, upward rotation, and external rotation during shoulder elevation in patients with subacromial impingement compared with participants who were healthy.11–13 In patients with shoulder instability, a decrease of scapular motion was observed from 0 to 90 degrees of shoulder elevation.2,14 These losses in scapular motion led to narrowing of the subacromial space1,15 and altered glenohumeral motions,8 contributing to injuries of the labrum, joint cartilage, and cuff tendons of the shoulder joint.

Available With This Article at www.ptjournal.org • Video: “Lengthening of the Pectoralis Minor Muscle” • The Bottom Line clinical summary

The pectoralis minor muscle (PMi) is the sole muscle connecting the scapula and anterior side of the thoracic region and functions to depress the scapula. Therefore, shortening of this muscle is expected to restrain scapular motion in the superior and posterior direction. A previous study16 indicated that the resting length of the PMi during standing with the arm at the side affected the scapular kinematics. Based on these findings, techniques to stretch the PMi are performed in clinical practice to lengthen the muscle.17–21 In order to increase the distance between the insertion and origin of the PMi, the scapula is manipulated directly or indirectly without glenohumeral motion in these stretching techniques. However, to our knowledge, no study has investigated the amount of PMi lengthening associated with shoulder motions and how far the specific techniques stretch the muscle. In order to measure lengthening of the PMi directly, we developed a transthoracic cadaveric model capable of simulating passive shoulder motion, including glenohumeral and scapulothoracic joint motion.22 The purposes of this study were: (1) to investigate the amount and pattern of PMi lengthening during passive shoulder motions and (2) to examine PMi stretching techniques to obtain greatest change in length. Information provided by this study is useful to understand how lengthening of the PMi is related to shoulder motions we studied and how various stretches affect the muscle. It also is useful to direct patient care related to stretching the PMi when tightness is determined.

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Method

• Audio Abstracts podcast

Preparation of the Specimen Nine transthoracic specimens were harvested from fresh cadavers obtained after acquisition of informed consent prior to death. The mean

This article was published ahead of print on February 26, 2009, at www.ptjournal.org.

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age was 84 years (range⫽67–96). The transthoracic specimen included the thoracic cage and the C4 through T12 vertebral bodies. Specimens with evidence of rotator cuff tear, osteoarthritis, or contracture were excluded. Specimens were kept in a freezer at –20°C after disarticulation, and then thawed at room temperature 24 hours prior to the experiment. Thawing was confirmed through 10 repetitions of preconditioned shoulder movement in each of 6 directions: flexion, abduction, internal and external rotation, and horizontal adduction and abduction. At this point, the study specimens were selected according to the following criteria for shoulder range of motion: (1) more than 150 degrees of flexion and (2) 90 degrees of external rotation at 90 degrees of abduction. In order to measure the PMi directly, the skin, subcutaneous tissue, and pectoralis major muscle were removed, as needed, before the measurement. The specimen was secured in the upright position on a wooden pole by inserting Kirschner wire at the thoracic spine and sternum (Fig. 1). This setup allowed the shoulder to move freely as previously reported in the literature.22 The experiment was performed at room temperature (22°C), and the specimens were kept moist by spraying with saline solution every 5 to 10 minutes. Measurement of PMi Lengthening The PMi originates from the third, fourth, and fifth ribs; runs superolaterally, converging, and inserting at the coracoid process; and forms a shape similar to a triangle. Lengthening of muscle fibers on the lateral side (fibers originating from the fifth rib) and medial side (fibers originating from the third rib) could differ because of the differing angles relative to the line of force. Thus, the lengthening on both the lateral and

April 2009

Muscle Lengthening During Passive Shoulder Motions and Stretching Techniques medial fiber groups of the PMi was measured in this study (Fig. 2). Two precise displacement sensors (Pulse coder*), each consisting of a coil sensor and a brass pipe, were used to determine the change in length. Displacement was measured by detecting the position of the brass pipe relative to a coil sensor that generated the magnetic field. Analog data of the displacement were represented and recorded on a digital scaling meter (HV35†) that converted the data to a digital format. The device had a range of measurement of 40 mm, and its accuracy was 0.1 mm root mean square. These sensors were mounted on the center of the muscle belly of the medial and lateral fibers, parallel to the muscle fiber, in order to accurately reflect the shortening and lengthening behavior of the muscle. A preliminary study confirmed that the center part of the muscle was lengthened most during shoulder motions. The center of the muscle belly was determined by measuring its length and width with a digital caliper. Fishhook-like barbed points attached to each coil sensor and brass pipe prevented the sensor from slipping out of the muscle. Passive Shoulder Motions and Stretching Techniques For passive shoulder motion, muscle lengthening was measured during flexion, elevation in the scapular plane (scaption), and external rotation at 90 degrees of abduction (ER90), which were expected to lengthen the PMi based on anatomical knowledge and scapular motions measured by a previous study.8 The measurement was performed in a range of 0 to 150 degrees, in 30degree increments, for flexion and scaption, whereas measurement from * LEVEX, Fujikogyo Bldg 2f 102, Minamimachi, Shichijogoshonouchi, Shimogyo-Ku, Kyoto, Japan. † Allied Control Co Ltd, 3-5-5, Sotokanda, Chiyoda-Ku, Tokyo 101-0021 Japan.

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Figure 1. Illustration of the experimental setting. Two pulse coder sensors were attached on the lateral and medial fiber groups of the pectoralis minor muscle. Another illustration in the upper right box is an enlargement of the pulse coder.

0 to 90 degrees in 15-degree increments was used for ER90. Neutral position was defined as 0 degrees of elevation with neutral rotation in the shoulder joint. Furthermore, in the neutral position, the scapula was settled so that the medial border was perpendicular to the ground and the scapular spine was angled 30 degrees anterior relative to the coronal plane.23 Three standard stretching techniques were selected for this study. Figure 3 shows each technique performed on the cadaveric specimen in this study. The first technique was scapular retraction at 0 degrees of flexion (retraction-0). With this technique, the examiner manually applied a posterior force on the coracoid process17,18 (Fig. 3A). The second technique was scapular retraction at 30 degrees of flexion (retraction-30). The examiner flexed the shoulder joint and applied a posterosuperior force to the elbow along the longitudinal axis of the humerus (Fig. 3B). The third technique

was horizontal abduction at 90 degrees of external rotation (horizontal abduction).19 –21,24 The examiner abducted the shoulder joint with 90 degrees of external rotation and then horizontally abducted it by applying posterior force to the proximal humerus (Fig. 3C). All techniques were performed to the position of end-feel by one examiner (TI). Each position was maintained for more than 10 seconds, until no increase or decrease in lengthening values was observed. The measurement was repeated 3 times for each shoulder motion and stretching technique. The measurement order was randomized in order to eliminate the stretching effect. Data Analysis For the normalization of the data, the lengthening ratio of the PMi during all shoulder motions and stretching techniques was calculated by the following formula:

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Muscle Lengthening During Passive Shoulder Motions and Stretching Techniques was performed with a statistical software package (StatView for Windows version 5.0.1‡). The alpha level was set to .05.

Results Lengthening During Passive Shoulder Motions The lengthening ratio in the lateral and medial fiber groups of the PMi during each passive shoulder motion is shown in Figure 4. In flexion and scaption, a similar pattern of the increase in lengthening ratio for both fiber groups was observed regardless of the different elevation plane. This curve pattern was characterized by small increases (0.8%–1.8%) up to 30 degrees and large increases (4.0%–25.5%) after that (Fig. 4A and 4B). A video of the lengthening of the pectoralis minor muscle during passive elevation in the scapular plane is available at www.ptjournal.org. At 150 degrees of both flexion and scaption, the lengthening ratio achieved in the lateral and medial fiber groups was 50% and 40%, respectively. In ER90, the PMi was less-steeply lengthened compared with flexion and scaption (Fig. 4C).

Figure 2. Anterolateral view of the pectoralis minor muscle on the left side during shoulder elevation in the scapular plane. This picture shows 3 origins of the pectoralis minor muscle. Arrows indicate the lateral and medial fibers of the muscle.

where ⌬L and L are the displacement of the PMi and the distance of the sensor at the neutral position, respectively. A 2-way repeated-measures analysis of variance (ANOVA) was used to test the differences of lengthening ratio regarding end position of shoulder motion and muscle fiber group factors and stretching technique and muscle fiber group factors. Bonferroni multiple comparisons were used as a post 336

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hoc test for the factors of end position of shoulder motion and stretching technique in each fiber group. After finding stretching techniques that showed a greater lengthening ratio, a 2-way repeated-measures ANOVA and a Dunnett multiple comparison test were used to compare the lengthening ratios in the stretching techniques with 150 degrees of flexion, while determining muscle fiber group factor. Statistical analysis

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A 2-way repeated-measures ANOVA showed significant differences in the maximum lengthening ratio among the 3 motions (F2,32⫽14.52, P⬍.001). However, there was no significant difference between the 2 muscle fiber groups (F1,16⫽1.43, P⫽.249). No significant interaction between passive shoulder motion and muscle fiber group was shown (F2,32⫽0.07, P⫽.937). Post hoc tests showed that the lengthening ratios at 150 degrees of flexion and scaption were significantly greater than at 90 degrees of ER90 for both muscle fiber groups, although the difference between flexion and scaption was not significant (Tab. 1).

‡ SAS Institute Inc, PO Box 8000, Cary, NC 60606.

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Figure 3. Stretching techniques simulated in this study: (A) scapular retraction at 0 degrees of flexion, (B) scapular retraction at 30 degrees of flexion, and (C) horizontal abduction at 90 degrees of external rotation. Arrows show the direction in which stretching force is applied.

Lengthening Ratio During Stretching Techniques There were significant differences in the lengthening ratio among the 3 stretching techniques (F2,32⫽51.26, P⬍.001), whereas no significant difference between the 2 muscle fiber groups was shown (F1,16⫽.19, P⫽.673). There was no interaction between stretching technique and muscle fiber group (F2,32⫽2.45, P⫽.102). Of the 3 stretching techniques, the lengthening ratios during retraction-30 and horizontal abduction were significantly greater than that during retraction-0 for both muscle fiber groups (Tab. 2). The mean lengthening ratio during April 2009

retraction-30 was largest, but this was not significantly different from horizontal abduction. Comparison of Lengthening Ratio Between Stretching Techniques and Shoulder Flexion Of the 3 stretching techniques, retraction-30 and horizontal abduction, which showed greater lengthening ratios than retraction-0, were compared with 150 degrees of flexion. A significant difference in lengthening ratio among retraction30, horizontal abduction, and 150 degrees of shoulder flexion was shown (F2,32⫽9.08, P⬍.001). There was no significant interaction be-

tween these shoulder positions and muscle fiber group (F2,32⫽0.10, P⬍.901). For retraction-30, although the post hoc test showed no significant difference compared with the lengthening ratio at 150 degrees of flexion in the lateral muscle fiber group, the lengthening ratio was significantly greater in the medial muscle fiber group (P⬍.05). For the horizontal abduction, the lengthening ratio was smaller than 150 degrees of shoulder flexion for both muscle fiber groups, but not significant.

Discussion The PMi has been considered to be lengthened with scapular upward

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Figure 4. Relationship between the lengthening of the lateral and medial fibers versus angle in each shoulder motion: (A) flexion, (B) scaption, and (C) external rotation at 90 degrees of abduction. The marker and bar in the relationship curves represent the mean lengthening and standard deviation, respectively.

and external rotation and posterior tilting, which occur during shoulder elevation and external rotation at 90 degrees of abduction.8 These scapular motions are expected to move the coracoid process, which is the insertion of the PMi, superiorly and posteriorly, thereby increasing the distance between the origin and insertion of the muscle. Thus, the lengthening of the PMi might be estimated from the amount of the scapular motion or distance between its origin and insertion. However, anatomically, the PMi originates from different 3 ribs and converges into 1 muscle. Accurate measurement of the length of each of these muscles is difficult in vivo. Therefore, in order to determine the exact lengthening 338

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of this muscle, direct measurement is necessary. The measurement technique used in this study enabled us to measure the lengthening of the PMi directly. This study demonstrated that 150 degrees of flexion and 150 degrees of scaption significantly lengthened the PMi compared with 90 degrees of ER90. In addition, the slope of the curve of the PMi length increased greatly with angle during flexion and scaption, whereas ER90 was lengthened gradually. These findings can be explained in terms of the scapular motions during flexion, scaption, and ER90. McClure et al8 observed larger scapular posterior tilting, up-

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ward rotation, and external rotation in flexion and scaption than in ER90. The lengthening ratios in flexion and scaption were almost 50% for the lateral muscle fiber group and 40% for the medial muscle fiber group relative to the lengths in the neutral position. Muraki and colleagues25,26 previously observed the lengthening of the rotator cuff muscles relative to the length in the same position as in this study. Of the rotator cuff muscles, the lower fibers of the subscapularis muscle were lengthened the most: 26.6% during external rotation at horizontal abduction. This difference in muscle lengthening patterns is interesting and is considered to come from anatomical features of April 2009

Muscle Lengthening During Passive Shoulder Motions and Stretching Techniques these muscles. The PMi is located on the anterior part of the scapulothoracic joint and lengthened with scapular motion, whereas the subscapularis muscle originates from the subscapular fossa, inserting at the lesser tuberosity and being lengthened with humeral motion. Because the lengthening ratio of the PMi during scaption and flexion was greater than that of rotator cuff muscles, shortening of this muscle by contracture could restrict the scapular motion. The 3 stretching techniques used were modified for this study. Evjenth and Hamberg27 introduced scapular retraction with flexion as a selective stretching technique for the PMi in their textbook. However, they did not clearly describe the exact angle of shoulder flexion. The flexion angle was set to 30 degrees for 2 reasons. First, it is reasonable to stretch the muscle along muscle fiber direction, which is close to 30 degrees relative to the coronal plane, as this has been shown to lengthen fibers the most. Second, approximately 90 degrees of flexion causes pain in a patient with subacromial impingement. Therefore, 30 degrees of flexion is considered to be more comfortable than a higher angle of flexion, as well as the angle closest to the line of force. As we expected, retraction-30 greatly lengthened the PMi compared to retraction-0. In comparison with the lengthening ratio at 150 degrees of flexion, this technique significantly lengthened the medial and lateral muscle fiber groups. These findings indicate that retraction-30 is useful for maintaining or obtaining the PMi length necessary to reach 150 degrees of flexion. Horizontal abduction also significantly lengthened the PMi. In a previous study,24 self-stretching by horizontal abduction was reported to April 2009

Table 1. Lengthening Ratio (%) of the Lateral and Medial Muscle Fibers at the End Range of Each Shoulder Motiona Flexion-150

Scaption-150

ER90 90°

48.6 (15.2)

48.3 (13.7)

41.2 (12.8)

Lateral muscle fiber group Mean (SD) P (vs Scaption-150)

.916

P (vs ER90 90°)

.011b

.014b

41.6 (12.9)

41.7 (12.8)

Medial muscle fiber group Mean (SD) P (vs Scaption-150)

.984

P (vs ER90 90°)

.013b

33.4 (12.3)

.012b

a Flexion-150⫽150 degrees of flexion, Scaption-150⫽150 degrees of elevation in the scapular plane, ER90 90°⫽90 degrees of external rotation at 90 degrees of abduction. b Statistically significant.

Table 2. Lengthening Ratio (%) of the Lateral and Medial Muscle Fibers During Each Stretching Techniquea Retraction-0

Retraction-30

H Abduction

19.5 (17.0)

52.1 (15.4)

47.1 (12.1)

Lateral muscle fiber group Mean (SD) P (vs Retraction-30)

⬍.001b

P (vs H Abduction)

⬍.001b

.320

Medial muscle fiber group Mean (SD)

24.3 (11.4)

P (vs Retraction-30)

⬍.001b

P (vs H Abduction)

⬍.001b

46.4 (14.3)

40.7 (13.3)

.076

a

Retraction-0⫽scapular retraction at 0 degrees of flexion, Retraction-30⫽scapular retraction at 30 degrees of flexion, H Abduction⫽horizontal abduction at 90 degrees of external rotation. b Statistically significant.

stretch the PMi more than scapular retraction with the arm at the side (0° of flexion) or 90 degrees of external rotation at 90 degrees of abduction. This stretching technique often is included in rehabilitation programs for patients with subacromial impingement.19 –21 However, in terms of the comparison of the lengthening at 150 degrees of flexion, this technique did not stretch the PMi as much as retraction-30. In addition, the average lengthening during this technique was somewhat less than lengthening obtained at 150 degrees of flexion. Therefore, the effect of the horizontal abduc-

tion on the PMi might be less than retraction-30. Our findings demonstrated that retraction-0 lengthened the PMi approximately half as much as other techniques. Scapular retraction in the supine position with the arm at the side has classically been used to test the length of the PMi.18 Such a result seems reasonable because this retraction shifts the coracoid process, the insertion of the PMi, posteriorly relative to the thorax. However, posterior shift of the coracoid process alone might be insufficient to stretch the PMi.

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Muscle Lengthening During Passive Shoulder Motions and Stretching Techniques The PMi showed little change in length at lower shoulder flexion angles because the coracoid process did not move superiorly. Particularly until 30 degrees of shoulder flexion was reached, previous studies8,28 showed little scapular and clavicular motions. The PMi actually started lengthening from 30 degrees of flexion. Furthermore, horizontal abduction lengthened the muscle similarly to retraction-30. This finding may suggest the importance of moving the coracoid process posteriorly as well as superiorly. Thus, we believe that applying passive force to the scapula in both superior and posterior directions, as with retraction-30, is the most effective maneuver to stretch the PMi because it appeared to be consistent with the traditional concept of increase in the distance between the origin and insertion of the muscle. Limitations The limitations of this study should be considered. First, shoulder joint motion in this experiment may differ from in vivo motion, as a cadaveric shoulder was used. According to previous data,29,30 the scapular motion was small up to 30 degrees, but greatly increased after that during scaption, similar to our lengthening data. This study might be able to simulate the in vivo motion properly. Second, this study did not determine tensile properties on the PMi. Therefore, altered viscoelastic and other material behaviors of cadaver muscle, which are reported to be quite different from those of muscles in vivo, were not accounted for. Gottsauner-Wolf et al31 and Leitschuh et al32 compared the tensile properties of muscle immediately after death and in frozen and thawed specimens. Breaking strength and stiffness of frozen and thawed specimens were 50% to 60%, respectively, of those in specimens taken immediately after death. Further340

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more, Van Ee et al33 compared the tensile properties of muscles before and after postmortem rigor. There were no differences in breaking strength or stiffness; however, toe regions of postmortem muscles were elongated compared with muscles before rigor mortis. In this study, we kept specimens at room temperature after thawing for longer than 6 hours, and they were preconditioned with 10 repetitions of joint stretching in each direction before the experiment. Third, the pectoralis major muscle and clavi-pectoral fascia were removed in order to expose the PMi. It is possible that the tension of the pectoralis major muscle restricts scapular motions, while the clavipectoral fascia is thought to have a role in holding the PMi; therefore, removal of these tissues might affect the behavior of the muscle. Finally, there was little spinal motion during shoulder motion because the specimen was secured at the thoracic spine. The motion of the thoracic spine, which is the base of the PMi, could affect lengthening. However, the spinal motion during flexion and scaption from 0 degrees to 150 degrees is small.34 The influence of the spinal motion also was considered to be small.

Conclusion This study utilizing fresh transthoracic specimens suggests that significant lengthening of the PMi is observed during shoulder motions, especially flexion and scaption. Based on our findings, scapular retraction at 30 degrees of flexion is the stretching technique that causes the greatest change in the length of the PMi. Clinically, this study suggests the importance of the PMi in shoulder motion and provides the anatomical and biomechanical background for choosing the appropriate stretching techniques. Although the

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amount of the passive lengthening in the PMi in vitro was estimated by this experiment, the effectiveness of these techniques on muscle in vivo was not studied. This issue should be investigated in further studies. Dr Muraki and Dr Aoki provided concept/ idea/research design. Dr Muraki provided writing and data analysis. Dr Muraki, Mr Izumi, Ms Fujii, and Ms Hidaka provided data collection. Dr Aoki provided project management. Dr Miyamoto provided facilities/ equipment and consultation (including review of manuscript before submission). The authors thank Dr Haruyuki Tatsumi, Dr Gen Murakami, Dr Eiichi Uchiyama, and Dr Daisuke Suzuki for their assistance in the collection of specimens. They also thank Hiroshi Takasaki, Sadanori Ohshiro, and Hitoshi Miyamoto for their assistance during the experiment. This study was performed in the Department of Physical Therapy and the Department of Anatomy, Sapporo Medical University, as a thesis of the Graduate School of Health Sciences. An oral presentation of this research was given at the International Congress of the World Confederation for Physical Therapy; June 2– 6, 2007; Vancouver, British Columbia, Canada. This article was received August 13, 2008, and was accepted January 9, 2009. DOI: 10.2522/ptj.20080248

References 1 Flatow EL, Soslowsky LJ, Ticker JB, et al. Excursion of the rotator cuff under the acromion: patterns of subacromial contact. Am J Sports Med. 1994;22:779 –788. 2 Ogston JB, Ludewig PM. Differences in 3-dimensional shoulder kinematics between persons with multidirectional instability and asymptomatic controls. Am J Sports Med. 2007;35:1361–1370. 3 Ozaki J. Glenohumeral movements of the involuntary inferior and multidirectional instability. Clin Orthop Relat Res. 1989; 238:107–111. 4 Rundquist PJ. Alterations in scapular kinematics in subjects with idiopathic loss of shoulder range of motion. J Orthop Sports Phys Ther. 2007;37:19 –25. 5 Warner JJ, Micheli LJ, Arslanian LE, et al. Scapulothoracic motion in normal shoulders and shoulders with glenohumeral instability and impingement syndrome: a study using Moire topographic analysis. Clin Orthop Relat Res. 1992;285:191–199.

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Muscle Lengthening During Passive Shoulder Motions and Stretching Techniques 6 Weiser WM, Lee TQ, McMaster WC, McMahon PJ. Effects of simulated scapular protraction on anterior glenohumeral stability. Am J Sports Med. 1999;27:801– 805. 7 Ludewig PM, Cook TM, Nawoczenski DA. Three-dimensional scapular orientation and muscle activity at selected positions of humeral elevation. J Orthop Sports Phys Ther. 1996;24:57– 65. 8 McClure PW, Michener LA, Sennett BJ, Karduna AR. Direct 3-dimensional measurement of scapular kinematics during dynamic movements in vivo. J Shoulder Elbow Surg. 2001;10:269 –277. 9 Meskers CG, Vermeulen HM, de Groot JH, et al. 3D shoulder position measurements using a six-degree-of-freedom electromagnetic tracking device. Clin Biomech (Bristol, Avon). 1998;13:280 –292. 10 van der Helm FC, Pronk GM. Threedimensional recording and description of motions of the shoulder mechanism. J Biomech Eng. 1995;117:27– 40. 11 Ludewig PM, Cook TM. Alterations in shoulder kinematics and associated muscle activity in people with symptoms of shoulder impingement. Phys Ther. 2000; 80:276 –291. 12 Lukasiewicz AC, McClure P, Michener L, et al. Comparison of 3-dimensional scapular position and orientation between subjects with and without shoulder impingement. J Orthop Sports Phys Ther. 1999;29: 574 –583. 13 Endo K, Ikata T, Katoh S, Takeda Y. Radiographic assessment of scapular rotational tilt in chronic shoulder impingement syndrome. J Orthop Sci. 2001;6:3–10. 14 Paletta GA Jr, Warner JJ, Warren RF, et al. Shoulder kinematics with two-plane x-ray evaluation in patients with anterior instability or rotator cuff tearing. J Shoulder Elbow Surg. 1997;6:516 –527. 15 Solem-Bertoft E, Thuomas KA, Westerberg CE. The influence of scapular retraction and protraction on the width of the subacromial space: an MRI study. Clin Orthop Relat Res. 1993;296:99 –103.

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16 Borstad JD, Ludewig PM. The effect of long versus short pectoralis minor resting length on scapular kinematics in healthy individuals. J Orthop Sports Phys Ther. 2005;35:227–238. 17 Burkhart SS. Internal impingement of the shoulder. Instr Course Lect. 2006;55: 29 –34. 18 Kendall FP, McCreary EK, Provance PG, et al. Muscles: Testing and Function With Posture and Pain. 5th ed. Baltimore, MD: Lippincott Williams & Wilkins: 2005. 19 Ludewig PM, Borstad JD. Effects of a home exercise programme on shoulder pain and functional status in construction workers. Occup Environ Med. 2003;60:841– 849. 20 McClure PW, Bialker J, Neff N, et al. Shoulder function and 3-dimensional kinematics in people with shoulder impingement syndrome before and after a 6-week exercise program. Phys Ther. 2004;84:832– 848. 21 Wang CH, McClure P, Pratt NE, Nobilini R. Stretching and strengthening exercises: their effect on three-dimensional scapular kinematics. Arch Phys Med Rehabil. 1999; 80:923–929. 22 Aoki M, Takasaki H, Muraki T, et al. Strain on the ulnar nerve at the elbow and wrist during throwing motion. J Bone Joint Surg Am. 2005;87:2508 –2514. 23 Itoi E, Morrey BF, An KN. Biomechanics of the shoulder. In: Rockwood CA, Matsen FA III, Wirth MA, Lippitt SB, eds. The Shoulder. Philadelphia, PA: WB Saunders Co; 2004:223–267. 24 Borstad JD, Ludewig PM. Comparison of three stretches for the pectoralis minor muscle. J Shoulder Elbow Surg. 2006;15: 324 –330. 25 Muraki T, Aoki M, Uchiyama E, et al. The effect of arm position on stretching of the supraspinatus, infraspinatus, and posterior portion of deltoid muscles: a cadaveric study. Clin Biomech (Bristol, Avon). 2006;21:474 – 480.

26 Muraki T, Aoki M, Uchiyama E, et al. A cadaveric study of strain on the subscapularis muscle. Arch Phys Med Rehabil. 2007;88:941–946. 27 Evjenth O, Hamberg J. Muscle Stretching in Manual Therapy—A Clinical Manual: The Extremities. Alfta, Sweden: Alfta Rehab Forlag: 1984. 28 Ludewig PM, Behrens SA, Meyer SM, et al. Three-dimensional clavicular motion during arm elevation: reliability and descriptive data. J Orthop Sports Phys Ther. 2004;34:140 –149. 29 Doody SG, Freedman L, Waterland JC. Shoulder movements during abduction in the scapular plane. Arch Phys Med Rehabil. 1970;51:595– 604. 30 Poppen NK, Walker PS. Normal and abnormal motion of the shoulder. J Bone Joint Surg Am. 1976;58:195–201. 31 Gottsauner-Wolf F, Grabowski JJ, et al. Effects of freeze/thaw conditioning on the tensile properties and failure mode of bone-muscle-bone units: a biomechanical and histological study in dogs. J Orthop Res. 1995;13:90 –95. 32 Leitschuh PH, Doherty TJ, Taylor DC, et al. Effects of postmortem freezing on tensile failure properties of rabbit extensor digitorum longus muscle tendon complex. J Orthop Res. 1996;14:830 – 833. 33 Van Ee CA, Chasse AL, Myers BS. Quantifying skeletal muscle properties in cadaveric test specimens: effects of mechanical loading, postmortem time, and freezer storage. J Biomech Eng. 2000;122:9 –14. 34 Crosbie J, Kilbreath SL, Hollmann L, York S. Scapulohumeral rhythm and associated spinal motion. Clin Biomech (Bristol, Avon). 2008;23:184 –192.

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Research Report Longitudinal Construct Validity of the GMFM-88 Total Score and Goal Total Score and the GMFM-66 Score in a 5-Year Follow-up Study Annika Lundkvist Josenby, Gun-Britt Jarnlo, Christina Gummesson, Eva Nordmark A Lundkvist Josenby, PT, MSc, is a PhD student, Department of Health Sciences, Division of Physiotherapy, Lund University, Lund, Sweden, and Pediatric Physiotherapist, Children’s Hospital, Lund University Hospital, S-221 85 Lund, Sweden. Address correspondence to Mrs Lundkvist Josenby at: annika. [email protected]. GB Jarnlo, PT, PhD, is Associate Professor, Department of Health Sciences, Division of Physiotherapy, Lund University. C Gummesson, PT, PhD, is Senior Lecturer, Department of Health Sciences, Division of Physiotherapy, Lund University. E Nordmark, PT, PhD, is Senior Lecturer, Department of Health Sciences, Division of Physiotherapy, Lund University. [Lundkvist Josenby A, Jarnlo GB, Gummesson C, Nordmark E. Longitudinal construct validity of the GMFM-88 total score and goal total score and the GMFM-66 score in a 5-year follow-up study. Phys Ther. 2009;89:342–350.] © 2009 American Physical Therapy Association

Background. The Gross Motor Function Measure (GMFM) is the instrument most commonly used to measure gross motor function in children with cerebral palsy (CP). Different scoring options have been developed, and their measurement properties have been assessed. Limited information is available regarding longitudinal construct validity.

Objective. The objective of this research was to study the longitudinal construct validity of 3 scoring options: the 88-item GMFM (GMFM-88) total, the GMFM-88 goal total, and the 66-item GMFM (GMFM-66).

Design. A clinical measurement design was used in this study. Methods. Forty-one children with CP diplegia who were undergoing selective dorsal rhizotomy (SDR) were monitored with the GMFM for 5 years. The mean age at SDR was 4.4 years (range⫽2.5– 6.6). Two subgroups for gross motor function before surgery were created according to the Gross Motor Function Classification System (GMFCS): GMFCS levels I to III and GMFCS levels IV and V. This study included results obtained before SDR and at 6, 12, and 18 months and 3 and 5 years after SDR. The effect size (ES) and the standardized response mean (SRM) were calculated.

Results. At 6 months postoperatively, ES and SRM values were small (ⱕ0.5) for all GMFM scoring options. The GMFM-88 total and goal total scores showed large changes in ES values (range⫽0.8 – 0.9) and SRM values (range⫽0.9 –1.3) at 12 months postoperatively, whereas the GMFM-66 scores showed lower ES values (range⫽0.3– 0.4) and SRM values (range⫽0.7– 0.8) for both subgroups. Later postoperatively, larger values for longitudinal construct validity were found. The ES and SRM values generally were lower for the GMFM-66 scores than for the GMFM-88 total and goal total scores. Limitations. All children underwent an extensive intervention, and changes in gross motor function were expected. Conclusion. All 3 scoring options showed large longitudinal construct validity in the long-term follow-up. The GMFM-88 total and goal total scores revealed large changes in gross motor function earlier postoperatively than the GMFM-66 scores.


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Longitudinal Construct Validity of GMFM-88 and GMFM-66

P

hysical therapists and other health care professionals are being urged to evaluate the effectiveness of their treatment methods. Evidence-based practice requires relevant, reliable, valid, and responsive outcome measures to evaluate treatment effects.1 There is a need for research to better define the psychometric properties of measures.2 Longitudinal construct validity is the extent to which an instrument can detect purposive change longitudinally within the construct it is intended to measure.3 Different terms, such as “responsiveness,” “sensitivity to change,” and “longitudinal construct validity” have been used; however, there is a lack of consensus.3,4 Longitudinal construct validity or responsiveness has been suggested by Liang3 to be considered an important component of outcome assessment and a distinct criterion for psychometric evaluation in clinical research. Different approaches can be used for the assessment. When a gold standard is available, the magnitude of change detected by a new instrument should be compared with the gold standard. Another option is to use an external criterion (eg, asking a child’s parents or health care provider to rate whether change has occurred).5 The effect size (ES) and the standardized response mean (SRM) are statistics that can be used to describe the size of the change detected and can be calculated to describe longitudinal construct validity. A large ES or SRM indicates that a studied measure detects a large change occurring within a group.6 The original Gross Motor Function Measure (GMFM), an 88-item measure also known as the GMFM-88, is a criterion-referenced observational measure specifically developed to evaluate changes in gross motor function over time in children across April 2009

the wide spectrum of ability levels in cerebral palsy (CP).7 The GMFM-88 has 5 dimensions: A–lying and rolling; B–sitting; C– kneeling and crawling; D–standing; and E–walking, running, and jumping. The items are scored from 0 to 3. All items are summarized and expressed as a value of total points for each dimension of the GMFM-88. The GMFM-88 total score is calculated as the mean score of all 5 dimensions, and the goal total score is the mean of individually selected dimensions (ranging between 1 and 4) constructed to increase responsiveness in the GMFM-88 (Tab. 1).7 The GMFM-88 total score is the mean of all dimensions, and the GMFM-88 goal total score is the mean of individually selected dimensions constructed to increase responsiveness (Tab. 1). The GMFM-88 total score has been the measure most often chosen to detect changes in gross motor function in evaluations of various interventions.8 –13 It is considered the gold standard for measuring gross motor function in children with CP. Few results have been published for the GMFM-88 goal total score.13–15 Studies have presented mainly clinical results and have explored the psychometric properties of the instrument less often. In the original GMFM validation study, 111 children with CP, 25 children with acquired brain injury, and 34 children who were developing typically were tested twice over 5 to 7 months.16 Correlations between scores for changes in motor function measured with the GMFM-88 and the judgments of changes by parents, therapists, and masked evaluators supported the hypothesis that the instrument would be responsive to both negative and positive changes.16 Bjornson et al17 studied 21 children with diplegia and quadriplegia and provided additional validation evidence of the responsiveness of the GMFM-88. Kolobe et al18 found that the GMFM-88 was able to detect

changes in motor function in 24 infants with CP over 6 months; the mean change was 4.2 points. Russell et al19 studied validity and responsiveness in 206 children with CP and found that the mean change in motor function detected by the GMFM-88 over 6 months was 3.5 points. Nordmark et al13 studied responsiveness in 18 children undergoing selective dorsal rhizotomy (SDR). The total and goal total scores were found to respond to changes in motor function over 6 and 12 months, especially for children with milder impairment. Vos-Vromans et al20 studied responsiveness in GMFM-88 total scores over 18 months in a population of children who had CP and who were 2 to 7 years of age; for the total score, the ES was 0.6 and the SRM was 0.9. Both interrater and intrarater reliability of GMFM-88 scores have been reported to be good. Nordmark et al21 found the interrater reliability (Kendall coefficient of concordance) to be .77 and .88 at the first and second assessments, respectively, and the intrarater reliability to be .68 at the second assessment (Kendall rank correlation).13 Bjornson et al17 found the GMFM to be consistent for the measurement of gross motor skills. Children with CP exhibited stable gross motor skills during repeated measurements. The intraclass correlation coefficients (ICCs) ranged from .76 to 1.00. The GMFM-88 has been used in different settings by therapists world-

Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on February 12, 2009, at www.ptjournal.org.

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Longitudinal Construct Validity of GMFM-88 and GMFM-66 Table 1. Characteristics of the Gross Motor Function Measure (GMFM)7 GMFM-887

Characteristic Purpose

Evaluation and determination of gross motor function capacity (descriptive, discriminative, predictive, and evaluative)

Evaluation and determination of gross motor function capacity (descriptive, discriminative, predictive, and evaluative)

Target group

Children with cerebral palsy; validated also for Down syndrome and used in children with osteogenesis imperfecta and acute lymphatic leukemia

Children with cerebral palsy only

Equipment

Common physical therapy tools or equipment defined in the manual and score sheet

Common physical therapy tools and equipment defined in the manual, score sheet, and Gross Motor Ability Estimator (GMAE) software

Administration

Clinical observation

Clinical observation

Estimated test time required

60–45 min

Not specified

Items

88

66

Scoring of single items

Ordinal 4-point scale for each item: 0⫽does not initiate task, 1⫽initiates task, 2⫽partially completes task, 3⫽completes task, NT⫽not tested; 3 trials allowed

Ordinal 4-point scale for each item: 0⫽does not initiate task, 1⫽initiates task, 2⫽partially completes task, 3⫽completes task, NT⫽not tested; 3 trials allowed

Scoring of items that participants could not perform or that were not tested

0 points

0 points, except for a possible score of “not tested” if a child is able but not willing to perform a task; this score will not affect the results negatively

Dimensions

Gross motor skills based on milestones in 5 dimensions: A, lying and rolling (17 items); B, sitting (20 items); C, kneeling and crawling (14 items); D, standing (13 items); and E, walking, running, and jumping (24 items)

Gross motor skills based on milestones; no separate dimensions

Scale scoring

Dimension score: percentage of accomplished tasks in each dimension (A–E) Total score: mean of 5 dimension scores Goal total score: individualized for each child and including only dimensions of selected goal areas, calculated as mean of included dimension scores

Interval score obtained with the GMAE software; a 95% confidence interval and a standard error of measurement are calculated with the software

Expected development

Available in tables according to age and Gross Motor Function Classification System (GMFCS) level in manual; all items can be accomplished by a 5-year-old child showing normal development

Available in tables according to age and GMFCS level in manual; all items can be accomplished by a 5-year-old child showing normal development

Interpretation tools

None

Item maps by item order and difficulty are obtained from the GMAE software

wide; however, there were limitations in the measure and how it was used.7 There was evidence that the reliability and the validity of the separate dimension scores were generally not as strong as for the measure as a whole. The interpretation of the total score also had its limitations, as children with different levels of motor function theoretically could have received the same score. Children with results in the middle of the scale had a greater potential to 344

GMFM-667

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change than those with results that were either lower or higher on the scale, as the difficulty scale contained more items in the middle than at the ends.7 The designers used the Rasch method to improve scoring, interpretation, and overall clinical and research utility.1 The most recent version is known as the GMFM-66, as it contains 66 of the original 88 items. The goal was to develop the GMFM-66 to be less vul-

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nerable than the GMFM-88 to missing items and to be more responsive for children with major functional limitations as well as children with minor functional limitations. The Rasch analysis revealed that 66 items contributed the most to the underlying construct of gross motor function. To improve reliability and validity, 22 items were deleted, and an interval scale was created. Of the 22 items, 13 were from the lying and rolling dimension, 5 were from the April 2009

Longitudinal Construct Validity of GMFM-88 and GMFM-66 sitting dimension, and 4 were from the kneeling and crawling dimension.

ments of meaningful improvements.

Russell et al22 published data on the psychometric properties of the GMFM-66. The GMFM-88 measurements obtained for 537 children with CP by 110 physical therapists were converted to GMFM-66 scores. Children were excluded if they had received intrathecal baclofen or botulinum toxin injections or had undergone SDR. The gross motor function in the 228 children who were reassessed after 12 months depended significantly on time, age, and severity of impairments. Other findings were that children younger than 5 years of age changed more than those older than 5 years of age and that children with less-severe motor impairments improved more than those with more-severe impairments. Russell et al22 found high testretest reliability, with an ICC of .9933, essentially the same as for the GMFM-88 (ICC⫽.9944). Wei et al23 found high levels of test-retest reliability and interrater reliability (ICC⫽.97 and .98, respectively) for a sample of 171 children.

We have not found any published study on the longitudinal construct validity of the 3 scoring options. The purpose of this study was to examine the longitudinal construct validity of the GMFM-88 total and goal total scores and the GMFM-66 score over 5 years in children with CP.

Wei et al23 explored the clinical consequences of deleting the 22 items from the GMFM-88 for children younger than 3 years of age. They found that the GMFM-66 was responsive even for these young children, who mainly had functional abilities assessed in lying, rolling, sitting, crawling, and kneeling positions. Wang and Yang24 evaluated the responsiveness of the GMFM-88 total score and the GMFM-66 score. They compared the scoring options with the external criterion of a therapist’s judgments of meaningful motor improvements at a follow-up at 3.5 months. They found the 2 scoring options to be equally responsive; however, the GMFM-66 was found to have better specificity than the GMFM-88 for the therapist’s judg-

April 2009

motor

Method Data were included from the first 41 children (28 boys and 13 girls) with spastic diplegia who underwent SDR combined with intensive physical therapy. The purposes of the intervention were to reduce spasticity and to yield gains in gross motor abilities.25 Statistically significant changes in gross motor function after SDR in children with CP have been reported previously.11 The mean age at surgery was 4.4 years (SD⫽1.1, range⫽2.5– 6.6). Gross motor function before surgery was classified according to the Gross Motor Function Classification System (GMFCS). This classification system is used to describe and classify functional abilities in children with CP in 1 of 5 levels (level I representing the fewest functional limitations and level V representing the most functional limitations) in 4 age groups: less than 2 years, 2 to 4 years, greater than 4 to 6 years, and greater than 6 to 12 years.26 The gross motor function of the children was classified as GMFCS levels I (n⫽1), II (n⫽9), III (n⫽13), IV (n⫽17), and V (n⫽1). According to the degree of severity of gross motor function preoperatively, the children were separated into 2 subgroups to assess changes within each subgroup. The subgroup including GMFCS levels I to III (n⫽23) included those children who walked, with or without walking aids, and needed only some assistance in everyday gross motor activities. The mean age at surgery was

4.6 years (SD⫽1.1, range⫽3.1– 6.6). The subgroup including GMFCS levels IV and V (n⫽18) included those children who had no or limited walking ability, even with the help of walking aids, and needed extensive assistance in everyday gross motor activities. The mean age at surgery was 4.1 years (SD⫽1.1, range⫽2.5– 5.9). All children were assessed before surgery and at 6, 12, and 18 months and 3 and 5 years after surgery. During play to motivate children to obtain optimal scores and minimize position changes, GMFM testing was performed by 1 physical therapist (EN). The assessments were observed, videotaped, and scored by another physical therapist (ALJ). If necessary, the videotape was referred to afterward to verify scoring. Before starting to use the instrument, both physical therapists were trained and examined by the test developers in administering the GMFM-88. The children were always tested without shoes, orthoses, or walking aids. The GMFM results were calculated as GMFM-88 total and goal total scores as described above and in Table 1. The goal dimensions in the GMFM-88 goal total score were individually selected by the physical therapists (EN and ALJ) for each child according to the clinically relevant goal areas. For a child with gross motor function classified in GMFCS level IV, the individual goals may be to independently come to a sitting position from lying on floor, crawl short distances, and be able to bear weight on both legs during standing transfers. The 3 dimensions sitting, kneeling and crawling, and standing would be selected as the most clinically relevant dimensions and goal areas. For the 5 dimensions, a median of 3 (range⫽1– 4) goal areas were selected. The goal total score was calculated as the mean of the scores for the selected dimensions.

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Longitudinal Construct Validity of GMFM-88 and GMFM-66 Table 2. Presurgery Mean, Standard Deviation (SD), and Median of the Different Gross Motor Function Measure (GMFM) Scoring Options for the Whole Group and the 2 Subgroups According to the Gross Motor Function Classification System (GMFCS) Levels I–III and IV and V

GMFCS Levels (n) I–V (41)a,b I–III (23)

a

IV and V (18)b

GMFM-88 Total Score

GMFM-88 Goal Total Score

GMFM-66 Score

X (SD)

Median

X (SD)

Median

X (SD)

Median

45.9 (19.1)

41.0

40.7 (16.3)

40.0

47.4 (9.8)

47.1

57.4 (16.6)

57.9

44.6 (16.3)

41.6

53.3 (8.1)

51.9

31.8 (10.7)

30.5

35.7 (15.3)

32.5

39.7 (5.6)

38.5

a

One child (GMFCS level III) was not tested in dimensions A and B before surgery or at 6 months after surgery, or in dimension A at 18 months after surgery. The GMFM-88 total score lacked data for GMFCS levels I to III and GMFCS levels I to V at these occasions for this child. b One child (GMFCS level IV) was not tested at 3 and 5 years after surgery. The GMFM-88 total score, GMFM-88 goal total score, and GMFM-66 score lacked data for GMFCS levels IV and V and GMFCS levels I to V at these occasions for this child.

The GMFM-66 score was obtained from the GMFM-88 total score with Gross Motor Ability Estimator software.7 The characteristics of the GMFM-88 and the GMFM-66 are shown in Table 1. Complete GMFM results were obtained for all except 2 children (Tabs. 2 and 3). None of the children had scores close to the minimum or the maximum; they all had the potential to show changes in motor function in the 3 different GMFM scoring options. The GMFM scores were normally distributed. Ethics According to the Swedish National Board of Health and Welfare, clinicians are obliged to secure quality of care by performing and reporting the results of clinical studies in everyday practice. Approval from an internal review board is not required for this type of research; subjects and all data were treated in accordance with the guidelines of the Helsinki Convention. Data Analysis For evaluation of the longitudinal construct validity of the GMFM scoring options, the ES and the SRM were used. The ES was calculated as the mean difference between the baseline score and the follow-up scores divided by the standard deviation of the baseline score. The SRM was calculated as the mean change score 346

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divided by the standard deviation of the change scores.5 Effect sizes of 0.2 to 0.5 were classified as small, values of 0.5 to 0.8 were classified as medium, and values of greater than 0.8 were classified as large.27 The ES and SRM were calculated for measurements obtained before surgery and at 6, 12, and 18 months and 3 and 5 years after surgery to study the longitudinal construct validity of the GMFM scoring options (as opposed to treatment effectiveness). Results were analyzed for the group as a whole and for the 2 subgroups. When comparing ES and SRM between the GMFM scoring options at the different time intervals, the preferable instrument can be determined depending on follow-up time and GMFCS level. Role of the Funding Sources The Linneá and Josef Carlsson Foundation and the Stiftelsen fo ¨ r Bistånd åt Ro ¨ relsehindrade i Skåne funded the first author (ALJ) to analyze data and prepare a manuscript for publication.

Results Presurgery mean and median values for GMFM-88 total score, GMFM-88 goal total score, and GMFM-66 score are presented in Table 2 for the group as a whole and for the 2 GMFCS subgroups. Longitudinal construct validity, in terms of ES and

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SRM, is shown in Table 3 and in Figures 1, 2, and 3. At 6 months after surgery, the ES and SRM were small (ⱕ0.5) for all 3 GMFM scoring options for the subgroups and for the group as a whole (Tab. 3, Figs. 1, 2, and 3). At 12 months after surgery, children in the subgroup including GMFCS levels I to III showed large changes in GMFM-88 total scores (ES⫽0.8 and SRM⫽1.3) and GMFM-88 goal total scores (ES⫽0.9 and SRM⫽1.2). Less change was seen in GMFM-66 scores at 12 months after surgery (ES⫽0.3 and SRM-0.8) (Tab. 3, Fig. 2). For children in the subgroup involving GMFCS levels IV and V, both GMFM-88 total and goal total scores showed large changes at 12 months after surgery (ES⫽0.8 and SRM⫽0.9), and GMFM-66 scores showed less change (ES⫽0.4 and SRM⫽0.7) (Tab. 3, Fig. 3). At 18 months after surgery, children in the subgroup involving GMFCS levels I to III showed large changes in GMFM-88 total scores (ES⫽0.8 and SRM⫽1.1) and goal total scores (ES⫽0.8 and SRM⫽0.9), and their GMFM-66 scores showed less change (ES⫽0.5 and SRM⫽0.8) (Tab. 3, Fig. 2). Children in the subgroup involving GMFCS levels IV and V showed large changes in GMFM total scores (ES⫽1.0 and SRM⫽1.1, and April 2009

Longitudinal Construct Validity of GMFM-88 and GMFM-66 Table 3. Mean Change, Standard Deviation (SD), Median Change, Effect Size (ES), and Standardized Response Mean (SRM) of the Different Gross Motor Function Measure (GMFM) Scoring Options for the Whole Group and the 2 Subgroups According to the Gross Motor Function Classification System (GMFCS) Levels I–III and IV and V GMFCS Levels I–V (nⴝ41)b,c

Score GMFM-88 total

GMFM-88 goal total

GMFM-66

Occasionsa Pre and 6 mo post

Mean Change (SD)

Median Change

ES

3.1 (12.0)

4.5

GMFCS Levels I–III (nⴝ23)b

SRM

Mean Change (SD)

Median Change

ES

0.2

0.3

2.1 (14.4)

3.8

GMFCS Levels IV and V (nⴝ18)c

SRM

Mean Change (SD)

Median Change

ES

SRM

0.1

0.1

4.5 (8.4)

5.5

0.4

0.5

Pre and 12 mo post

10.6 (9.5)

9.0

0.6

1.1

12.7 (9.8)

10.7

0.8

1.3

8.1 (8.7)

8.3

0.8

0.9

Pre and 18 mo post

12.0 (10.9)

9.6

0.6

1.1

13.4 (12.1)

12.8

0.8

1.1

10.4 (9.4)

8.7

1.0

1.1

Pre and 3 y post

15.5 (12.6)

16.6

0.9

1.2

16.2 (14.4)

13.5

1.0

1.1

14.7 (10.0)

17.0

1.4

1.5

Pre and 5 y post

20.2 (17.6)

20.5

1.1

1.1

23.7 (20.8)

22.4

1.4

1.1

15.6 (11.4)

18.5

1.5

1.4

Pre and 6 mo post

5.4 (13.3)

4.0

0.3

0.4

5.0 (11.5)

3.2

0.3

0.4

5.9 (15.6)

6.1

0.4

0.4

Pre and 12 mo post

13.1 (12.2)

10.5

0.8

1.1

14.4 (11.7)

10.0

0.9

1.2

11.4 (13.0)

11.0

0.8

0.9

Pre and 18 mo post

14.9 (14.3)

12.0

0.9

1.0

13.7 (15.3)

12.0

0.8

0.9

16.3 (13.2)

12.0

1.1

1.2

Pre and 3 y post

22.6 (16.7)

18.9

1.4

1.4

21.9 (17.9)

18.3

1.3

1.2

23.6 (15.3)

21.0

1.6

1.5

Pre and 5 y post

24.2 (18.3)

23.7

1.5

1.3

25.3 (21.5)

22.3

1.6

1.2

22.8 (13.1)

25.0

1.6

1.7

Pre and 6 mo post

1.2 (3.6)

1.1

0.1

0.3

1.3 (3.8)

1.1

0.1

0.3

1.1 (3.3)

1.1

0.2

0.3

Pre and 12 mo post

3.3 (4.5)

2.7

0.3

0.7

4.1 (5.2)

2.8

0.3

0.8

2.3 (3.3)

1.5

0.4

0.7

Pre and 18 mo post

4.0 (4.5)

4.3

0.4

0.9

4.4 (5.3)

4.8

0.5

0.8

3.5 (3.4)

3.6

0.6

1.0

Pre and 3 y post

7.7 (7.7)

5.9

0.8

1.0

9.3 (8.9)

7.7

1.2

1.0

5.4 (5.0)

4.6

1.0

1.1

Pre and 5 y post

8.9 (9.3)

7.4

0.9

1.0

11.4 (10.9)

9.0

1.4

1.0

5.7 (5.4)

5.8

1.1

1.0

a

Pre⫽before surgery, post⫽after surgery. One child (GMFCS level III) was not tested in dimensions A and B before surgery or at 6 months after surgery, or in dimension A at 18 months after surgery. The GMFM-88 total score lacked data for GMFCS levels I to III and GMFCS levels I to V at these occasions for this child. c One child (GMFCS level IV) was not tested at 3 and 5 years after surgery. The GMFM-88 total score, GMFM-88 goal total score, and GMFM-66 score lacked data for GMFCS levels IV and V and GMFCS levels I to V at these occasions for this child. b

goal total scores (ES⫽1.1 and SRM⫽1.2), and their GMFM-66 scores showed less change in ES (0.6) and a large change in SRM (1.0) (Tab. 3, Fig. 3).

Discussion

At 3 and 5 years after surgery, all 3 GMFM scoring options showed large changes for both the subgroup involving GMFCS levels I to III (ES⫽1.0 –1.6 and SRM⫽1.0 –1.2) and

We found that the 3 scoring options indicated progressive changes at short- and long-term follow-up after an extensive intervention for the group as a whole. Doubts have been raised about the longitudinal con-

April 2009

the subgroup involving GMFCS levels IV and V (ES⫽1.0 –1.6 and SRM⫽1.0 – 1.7) (Tab. 3, Figs. 2 and 3).

struct validity of GMFM-66 scores for children with more-severe disabilities, as many items in the lying and rolling, sitting, and kneeling and crawling dimensions were deleted.7 Our results indicated that the patterns of longitudinal construct validity between the 2 subgroups (GMFCS levels I to III and GMFCS levels IV and V) for the 3 scoring options were the same but that there were

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Longitudinal Construct Validity of GMFM-88 and GMFM-66 some differences among the scoring options. Both GMFM-88 total and GMFM-88 goal total scores showed larger changes earlier after surgery compared with GMFM-66 scores (Figs. 1, 2, and 3). The 2 GMFM-88 scoring options showed almost the same pattern for detecting changes in function during follow-up. After the 6-month follow-up, only small changes were seen in all 3 GMFM scoring options, and the low ES and SRM at 6 months confirmed the expected delay in gross motor progress. The goal total score has seldom been used in research reports. In clinical practice, we have found the goal total score to be useful for monitoring gross motor function changes. By identifying goal areas and deciding which dimensions to include in the goal total score, clinicians, the family, and the child can discuss the long-term expectations of the intervention. Specific items from these goal dimensions can be selected and used in short-term goal setting during rehabilitation after surgery; for example, the goal attainment scaling is well suited for this purpose.28

Figure 1. Effect size (ES) and standardized response mean (SRM) for the 88-item Gross Motor Function Measure (GMFM-88) total score, GMFM-88 goal total score, and 66-item GMFM (GMFM-66) score at various follow-up intervals for the group as a whole (Gross Motor Function Classification System [GMFCS] levels I to V) (n⫽41). Pre⫽before surgery, m⫽months, y⫽years.

Figure 2. The GMFM-66 scores indicated similar longitudinal construct validity for the 2 subgroups, which suggests that change in gross motor function was equally possible to detect with the GMFM-66 for the subgroup involving GMFCS levels I to III and the subgroup involving GMFCS levels IV and V despite the 22 deleted items. It was at 18 months and 3 years after surgery when large longitudinal construct validity was first seen. The early changes appear to be detected with the GMFM-88 goal total to a greater extent than with the GMFM-66. Wei et al23 found that the GMFM-66 could be used to detect changes in 348

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Effect size (ES) and standardized response mean (SRM) for the 88-item Gross Motor Function Measure (GMFM-88) total score, GMFM-88 goal total score, and 66-item GMFM (GMFM-66) at various follow-up intervals for the subgroup designated Gross Motor Function Classification System (GMFCS) levels I to III (n⫽23). Pre⫽before surgery, m⫽months, y⫽years.

gross motor function in children in the lying and rolling, sitting, and kneeling and crawling dimensions. For the children in the subgroup involving GMFCS levels IV and V in the present study, however, changes were detected by the GMFM-66 later during follow-up compared with the GMFM-88 total and goal total scores. These children were older than the children in the study of Shi et al24 and, therefore, were developing in gross motor function more slowly, in

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accordance with the gross motor function curves presented by Rosenbaum et al.29 Russell et al7 recommended that the GMFM-88 should be used when comparison of changes among children is not needed or when a young child or a child with gross motor function classified as GMFCS level V is being tested. In addition, the GMFM-88 should be used when a child with orthoses and aids is being tested or April 2009

Longitudinal Construct Validity of GMFM-88 and GMFM-66 other. The small differences indicate that the group scores studied were similarly distributed at baseline and at follow-ups. The interpretation of ES and SRM usually follows the guidelines of Cohen.27 Analyses and interpretation guidelines are based on statistical arguments rather than on the patient’s or therapist’s opinions of what constitutes an important change (eg, when using external criteria).6

Figure 3. Effect size (ES) and standardized response mean (SRM) for the 88-item Gross Motor Function Measure (GMFM-88) total score, GMFM-88 goal total score, and 66-item GMFM (GMFM-66) at various follow-up intervals for the subgroup designated Gross Motor Function Classification System (GMFCS) levels IV and V (n⫽18). Pre⫽before surgery, m⫽months, y⫽years.

when there is no access to a computer to obtain GMFM-66 scores. The GMFM-66 is recommended for research purposes, for comparing changes among children, and for monitoring the development of a single child over time, as the intervalscaled instrument is considered to provide a more reliable estimate of gross motor function.7 Compared with GMFM-66 scores, the earlier detection of large changes in GMFM-88 total and goal total scores among children with gross motor function classified as GMFCS levels IV and V is in agreement with our clinical impression. Gross motor function has been shown to depend on age and severity of functional impairments. The most rapid changes in GMFM results occur during the first 4 years of life, and a plateau phase is reached between 5 and 6 years, depending on the severity of CP, as indicated by GMFCS levels.29 The mean age of children at SDR in the present study was 4.4 years, and most of them were likely to continue to improve in gross motor function development for another 1 to 2 years before reaching their probable maximum scores at 6 to 7 years of age. Changes in funcApril 2009

tion during follow-up were expected because of the natural development of gross motor function and the effects of spasticity reduction. Different statistical methods have been used to evaluate longitudinal construct validity; ES and SRM appear to be the 2 most commonly used methods.6 For the children in the present study, the relatively large standard deviation of the scores obtained before surgery and the small changes that were found during the first 6 months after surgery resulted in low ES and SRM during the first 6 months compared with later after surgery. The change scores and standard deviation of the change scores (for calculation of SRM) were more homogenous than the change scores and standard deviation of the preoperative score (for calculation of ES). This was reflected by the relatively larger SRM than ES in at least all follow-up intervals up to 18 months after surgery (Tab. 3 and Figs. 1, 2, and 3). As expected, none of the children in the present study showed large changes in gross motor function at 6 months after surgery. In the present study, the ES and SRM did not differ significantly from each

In this study, we chose to investigate longitudinal construct validity of the 3 GMFM scoring options within 2 subgroups to provide readers with information on the measures’ performance in relation to the severity of function. Limitations All children underwent an extensive intervention initially, and changes in function were expected. A larger sample including more children with gross motor function classified at each GMFCS level may reveal more severity-dependent differences in longitudinal construct validity for the 3 GMFM scoring options.

Conclusion All scoring options showed large longitudinal construct validity in a longterm follow-up. The GMFM-88 total and goal total scores detected large changes in motor function earlier after surgery than the GMFM-66 scores in children with gross motor function classified as GMFCS levels I to III and GMFCS levels IV and V. All authors provided concept/idea/research design. Mrs Lundkvist Josenby provided writing and data analysis. Mrs Lundkvist Josenby and Dr Nordmark provided data collection, participants, and facilities/equipment. Dr Jarnlo provided project management. Dr Jarnlo, Dr Gummesson, and Dr Nordmark provided consultation (including review of manuscript before submission). The Linneá and Josef Carlsson Foundation and the Stiftelsen fo¨r Bistånd åt Ro¨relsehin-

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Longitudinal Construct Validity of GMFM-88 and GMFM-66 drade i Skåne provided funding to Ms Lundkvist Josenby to analyze data and prepare a manuscript for publication. This article was received January 31, 2008, and was accepted December 29, 2008. DOI: 10.2522/ptj.20080037

References 1 Avery LM, Russell DJ, Raina PS, et al. Rasch analysis of the Gross Motor Function Measure: validating the assumptions of the Rasch model to create an interval-level measure. Arch Phys Med Rehabil. 2003;84: 697–705. 2 Finch E, Brooks D, Stratford PW, Mayo NE. Physical Outcome Measures: A Guide to Enhanced Clinical Decision-Making. Toronto, Ontario, Canada: Canadian Physiotherapy Association; 2002. 3 Liang MH. Longitudinal construct validity: establishment of clinical meaning in patient evaluation instruments. Med Care. 2000;38:84 –90. 4 Gummesson C, Atroshi I, Ekdahl C. The Disabilities of the Arm, Shoulder and Hand (DASH) Outcome Questionnaire: longitudinal construct validity and measuring selfrated health change after surgery. BMC Musculoskelet Disord. 2003;4:11. 5 Stratford PW, Binkley FM, Riddle DL. Health status measures: strategies and analytic methods for assessing change scores. Phys Ther. 1996;76:1109 –1123. 6 Terwee CB, Dekker FW, Wiersinga WM, et al. On assessing responsiveness of health-related quality of life instruments: guidelines for instrument evaluation. Qual Life Res. 2003;12:349 –362. 7 Russell DJ, Rosenbaum PL, Avery L, Lane M. Gross Motor Function Measure (GMFM-66 and GMFM-88): User’s Manual. London, United Kingdom: MacKeith Press; 2002. 8 Bleyenheuft C, Filipetti P, Caldas C, Lejeune T. Experience with external pump trial prior to implantation for intrathecal baclofen in ambulatory patients with spastic cerebral palsy. Neurophysiol Clin. 2007;37:23–28.

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9 Bottos M, Benedetti MG, Salucci P, et al. Botulinum toxin with and without casting in ambulant children with spastic diplegia: a clinical and functional assessment. Dev Med Child Neurol. 2003;45:758 –762. 10 Krach LE, Kriel RL, Gilmartin RC, et al. GMFM 1 year after continuous intrathecal baclofen infusion. Pediatr Rehabil. 2005; 8:207–213. 11 McLaughlin J, Bjornson K, Temkin N, et al. Selective dorsal rhizotomy: meta-analysis of three randomized controlled trials. Dev Med Child Neurol. 2002;44:17–25. 12 Mittal S, Farmer J-P, Al-Atassi B, et al. Longterm functional outcome after selective posterior rhizotomy. J Neurosurg. 2002; 97:315–325. 13 Nordmark E, Jarnlo G-B, Hagglund G. Comparison of the Gross Motor Function Measure and Pediatric Evaluation of Disability Inventory in assessing motor function in children undergoing selective dorsal rhizotomy. Dev Med Child Neurol. 2000;42: 245–252. 14 Boyd RN, Dobson F, Parrott J, et al. The effect of botulinum toxin type A and a variable hip abduction orthosis on gross motor function: a randomized controlled trial. Eur J Neurol. 2001;8(suppl 5):109 –119. 15 Knox V, Evans AL. Evaluation of the functional effects of a course of Bobath therapy in children with cerebral palsy: a preliminary study. Dev Med Child Neurol. 2002; 44:447– 460. 16 Russell DJ, Rosenbaum PL, Cadman DT, et al. The Gross Motor Function Measure: a means to evaluate the effects of physical therapy. Dev Med Child Neurol. 1989;31: 341–352. 17 Bjornson KF, Graubert CS, McLaughlin J, et al. Test-retest reliability of the Gross Motor Function Measure in children with cerebral palsy. Phys Occup Ther Pediatr. 1998;18:51– 61. 18 Kolobe TH, Palisano RJ, Stratford PW. Comparison of two outcome measures for infants with cerebral palsy and infants with motor delays. Phys Ther. 1998;78: 1062–1072.

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19 Russell DJ, Rosenbaum PL, Gowland C. Gross Motor Function Measure Manual. 2nd ed. Owen Sound, Ontario, Canada: Mary Lane, Pediatric Physiotherapy Services; 1993. 20 Vos-Vromans DC, Ketelaar M, Gorter JW. Responsiveness of evaluative measures for children with cerebral palsy: the Gross Motor Function Measure and the Pediatric Evaluation of Disability Inventory. Disabil Rehabil. 2005;27:1245–1252. 21 Nordmark E, Ha¨gglund G, Jarnlo G-B. Reliability in Gross Motor Function Measure. Scand J Rehabil Med. 1997;29:25–28. 22 Russell DJ, Avery LM, Rosenbaum PL, et al. Improved scaling of the Gross Motor Function Measure for children with cerebral palsy: evidence of reliability and validity. Phys Ther. 2000;80:873– 885. 23 Wei S, Su-Juan W, Yuan-Gui L, et al. Reliability and validity of the GMFM-66 in 0to 3-year-old children with cerebral palsy. Am J Phys Med Rehabil. 2006;85:141–147. 24 Wang HY, Yang YH. Evaluating the responsiveness of 2 versions of the Gross Motor Function Measure for children with cerebral palsy. Arch Phys Med Rehabil. 2006;87:51–56. 25 Peacock WJ, Arens LJ, Berman B. Cerebral palsy spasticity: selective posterior rhizotomy. Pediatr Neurosci. 1987;13:61– 66. 26 Palisano RJ, Rosenbaum PL, Walter SD, 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. 27 Cohen C. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988. 28 Kiresuk T, Sherman R. Goal attainment scaling: a method for evaluating comprehensive community mental health programs. Community Mental Health Journal. 1968:441– 453. 29 Rosenbaum PL, Walter SD, Hanna SE, et al. Prognosis for gross motor function in cerebral palsy: creation of motor development curves. JAMA. 2002;288:1357–1368.

April 2009

Case Report

Ergonomic Intervention in the Treatment of a Patient With Upper Extremity and Neck Pain Philip Fabrizio

Background and Purpose. Work-related musculoskeletal disorders are widespread among computer users and costly to the health care system. Workstation setup and worker postures contribute to upper-extremity and neck symptoms among computer users. Ergonomic interventions such as work risk analysis and workstation modifications can improve workers’ symptoms. However, ergonomic interventions do not appear to be a common component of traditional physical therapy treatment.

Case Description. The patient was a 26-year-old woman with right upperextremity and neck pain referred for physical therapy. A course of traditional physical therapy treatment was performed followed by an ergonomic intervention.

P Fabrizio, PT, DPT, CEAS, is Clinical Instructor, Division of Physical Therapy, Georgia State University, PO Box 4019, Atlanta, GA 303024019 (USA). Address all correspondence to Dr Fabrizio at: [email protected]. [Fabrizio P. Ergonomic intervention in the treatment of a patient with upper extremity and neck pain. Phys Ther. 2009;89:351–360.] © 2009 American Physical Therapy Association

Outcomes. Following 4 weeks of traditional physical therapy, the patient showed a 1.0-cm improvement in her resting pain level but no change in her pain level during exacerbations on the visual analog scale. An ergonomic intervention was performed following traditional physical therapy. At the conclusion of the full course of treatment (traditional physical therapy plus ergonomic intervention), resting pain level decreased by 4.6 cm and exacerbation pain level decreased by 3.2 cm. Improvements in Rapid Upper Limb Assessment and Workstyle scores also were realized. Discussion. This case report demonstrates the importance of examining the work habits and work-related postures of a patient who complains of upper-extremity and neck pain that is exacerbated by work. Providing an ergonomic intervention in concert with traditional physical therapy may be the most beneficial course of treatment.

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

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obs requiring the use of a computer input device and video display terminal (VDT) often expose workers to awkward and sustained postures and repetitive motions of the upper extremities, which have been demonstrated as causes of work-related shoulder and neck pain.1 The US Department of Health and Human Services estimated that in 1996 7% of US men and 9% of US women experienced some form of work-related neck pain.1 The incidence of upper-extremity workrelated musculoskeletal disorder (MSD) claims for computer-related injuries increased from 1.6% of all upper-extremity injury claims in 1986 to 14.6% of all upper-extremity injury claims in 1993.2 The costs associated with upper-extremity workrelated disorders, although difficult to assess, have been estimated to be in excess of $563 million in the United States in 1993 for upperextremity work-related MSDs from all job types.3 A report examining the costs specific to work-related MSDs among VDT users showed an average cost per claim of $15,141 among VDT users in a petrochemical plant from 1990 to 1994.4 A recent estimate of the total costs associated with upper-extremity work-related MSDs put them in excess of $2 billion annually for the United States.5 The relationship between workrelated MSDs and VDT use was explored by Marcus and Gerr,6 who reported a 63% incidence of neck and shoulder symptoms among 416 female office workers using VDTs


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daily in their jobs. More recently, Korhonen et al7 found that the annual incidence of neck pain among Finnish VDT workers was 34%. Sillanpa¨ä et al8 found that the incidence of neck pain and shoulder pain among 979 VDT users was 63% and 23%, respectively. These authors8 indicated a strong association between mouse use, including mouse position, and workers’ pain symptoms. Hernandez et al9 reported an increased incidence of neck, shoulder, and hand work-related MSDs in 179 newspaper workers using VDTs compared with non-VDT users in the same company. Furthermore, they demonstrated that the type and amount of computer use and the posture of the worker were related to the incidence of work-related MSDs. The incidence of neck pain combined with the increased numbers of workers using VDTs prompted the US Occupational Safety and Health Administration (OSHA) to institute guidelines and ergonomic evaluation procedures for working safely with VDTs.10 The OSHA VDT guidelines allow companies to determine the presence of work-related MSD risk factors and provide specific recommendations for safe seating and VDT setup in order to protect office workers.10 Altering the position of office equipment such as the VDT or mouse input device has been shown to modify muscle activity and reduce symptom complaints.11–14 Cook and Kothiyal11 demonstrated that positioning the computer mouse closer to the keyboard and eliminating the numeric key pad resulted in a significantly lower deltoid muscle electromyographic activity in VDT users than when the mouse was placed in a position where the user was required to abduct the upper extremity and reach for the mouse. Static, low-level loading of the deltoid and upper trapezius muscles has been correlated with increased incidence

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of shoulder and neck pain.12 Marcus et al13 showed that there was a decrease in upper-extremity and neck symptoms in office workers who used more “ergonomically sound postures.” Specifically, a lower risk of work-related MSDs of the shoulder was associated with keyboard placement that put the elbows at a more neutral angle, described as “keyboard lower than elbow without arm abduction,” and a lower risk of neck symptoms was shown with a monitor position that allowed a head tilt angle of less than 3 degrees.13 Pillastrini et al14 and Hignett and McAtamney15 have shown that personalized ergonomic intervention, including a postural assessment and proper adjustments of the seat, desk, VDT, keyboard, and mouse, resulted in significant decreases in pain and Rapid Entire Body Assessment (REBA) scores for office workers using VDTs for 20 hours per week. Ergonomic interventions, although primarily designed to benefit the worker, also may benefit the company. The implementation of an ergonomic intervention has been shown to decrease work-related MSD claim costs.4 During the period of 1995–1998, Lewis et al4 implemented an ergonomic intervention program among VDT users in a petrochemical plant. Individual claim costs were reduced from an average of $15,141 before intervention to and an average of $1,553 after intervention. Ergonomic interventions are based on reducing awkward postures that occur while the client is at the workstation while performing work tasks. Physical therapists have unique knowledge and training in identifying awkward postures and performing the appropriate tests and measures to determine the causes and consequences of awkward postures. However, in my experience, an assessment of a patient’s awkward April 2009

Ergonomic Intervention for Upper Extremity and Neck Pain working postures is rarely made by the physical therapist while the patient demonstrates those postures at the workstation. Postural assessments usually are made while the patient is in the clinic and generally in the standing and seated positions. Furthermore, interventions for awkward postures assessed only in the clinic usually do not involve workstation modifications or work habit modifications. An ergonomic assessment and workstation modifications have been shown to reduce the incidence of work-related MSDs in a variety of work settings.4,11,13,14 From the aforementioned research, it may be concluded that the inclusion of an ergonomic assessment and intervention in the treatment of an office worker with complaints of neck and shoulder pain can result in improved patient outcomes when combined with traditional physical therapy treatment. The current literature demonstrates ergonomic interventions on a company-wide scale but does not examine the inclusion of an ergonomic intervention added after a course of traditional physical therapy treatment as a plan of care. The purpose of this case report is to describe the effects of traditional physical therapy treatment of a patient with right-sided neck and shoulder pain and the subsequent outcomes associated with ergonomic evaluation and intervention that were initiated after the traditional treatment.

Patient History and Review of Systems The patient was a 26-year-old woman with a chief complaint of right upper-extremity pain and right-sided neck pain who was referred for physical therapy with orders from her primary care physician for “physical therapy for neck strain, evaluate and treat.” The patient initially described her pain as a dull ache of insidious onset approximately 3 months prior and worsening since that time. The pain appeared, to her, April 2009

to radiate from her neck into her shoulder and arm, with pain intensity at the time of her initial appointment equal to 5.5/10 cm on a visual analog scale (VAS). The VAS was assessed by having the patient mark her pain rating on a 10-cm line between “no pain” (0 cm) or “the worst imaginable pain” (10 cm).16 The VAS has been shown to have good reliability for assessing acute pain (intraclass correlation coefficient⫽.99), good validity for measurement of chronic pain and temperature, and a minimum clinical significant difference of 1.6 cm.16,17 The patient described her 24-hour pain pattern as decreased pain in the morning (VAS score of 3.2 cm) and increasing pain as the day progressed (VAS score of 6.4 cm), which she noticed daily during her 40-minute drive home from work. She also described her pain as limiting her time spent at her computer station and “making her work uncomfortable.” The physician’s report and the patient’s past medical history were unremarkable, with no indication of any systemic disorders, neurological or cardiovascular concerns, or previous injuries to the upper extremities, neck, or back. The patient was employed as an administrative secretary with a job requirement of typing and VDT use for 65% to 75% of her day. The remaining daily tasks were equally divided among using the telephone, scheduling appointments, and filing paperwork. She had been at her current position for 6 months and noted that a new partner had joined the law firm in the past 4 months and that her typing and VDT workload had increased to 85% as a result.

Examination The patient initially was seen in an outpatient physical therapy clinic and underwent traditional evaluation and treatment, which are outlined below. The patient was right-hand

dominant. Observation of her posture in a standing position revealed a forward head posture with bilateral forward shoulders. The thoracic spine curve was unremarkable, and the lumbar curve was slightly lordotic. Upper-extremity posture demonstrated an elevated right shoulder and increased bulk of the right periscapular muscles. Significant physical examination findings are summarized below. Active range of motion (AROM) of the cervical spine and upper extremities was within normal limits for all motions. Muscle length examination revealed tightness of the bilateral pectoralis minor muscles, and manual muscle tests revealed weakness in the bilateral middle and lower trapezius muscles. Neer and HawkinsKennedy tests were positive for shoulder impingement on the right, and upper-limb tension tests were positive for median nerve entrapment in the arm. The Neer and Hawkins-Kennedy tests have shown sensitivity of 75% to 88.7% and 92.1%, respectively, for subacromial impingement and a high specificity value of 96%.18,19 Palpation revealed increased bulk with an active myofascial trigger point (MTrP) in the right upper trapezius muscle and right levator scapulae muscle distal attachment. At the initial visit, the patient completed the QuickDASH outcome tool, scoring 50 on the disability symptom score and 75 on the work and sport/performing arts modules (Table).20 The QuickDASH is a shorter version of the original Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire that has demonstrated good agreement with the DASH (intraclass correlation coefficient⫽.96) and good test-retest reliability (intraclass correlation coefficient⫽.93) related to function, where higher values indicate a greater level of disability.20 The

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Ergonomic Intervention for Upper Extremity and Neck Pain Table. Outcome Scores for the 4 Intervals of Testinga

Outcome Measure

Initial Visit

VAS (cm) (present/worst/best)

5.5/6.4/3.2

VAS difference from initial visit (cm) (present/worst/best)

After 4 Weeks of Traditional Physical Therapy

Initial Ergonomic Assessment and Intervention

4 Weeks After Initial Ergonomic Intervention

4.5/6.4/2.2

4.5/6.0/2.2

0.9/2.0/0

1.0/0/1.0

1.0/0.4/1.0

4.6/4.4/3.2

QuickDASH (disability/work/sports)

50/75/75

36/50/50

36/50/50

0/6/6

RULA12,13

Not performed

Not performed

7

1

Workstyle short-form survey10

Not performed

Not performed

52

10

a

VAS⫽visual analog scale, QuickDASH⫽shorter version of the original Disabilities of the Arm, Hand, and Shoulder outcome measure, RULA⫽Rapid Upper Limb Assessment.

QuickDASH does not appear to have established values for minimum clinical significant difference. The diagnosis by the treating physical therapist was Guide to Physical Therapist Practice musculoskeletal preferred practice pattern 4E (“Impaired Joint Mobility, Motor Function, Muscle Performance, and Range of Motion Associated With Localized Inflammation”) and musculoskeletal preferred practice pattern 4F (“Impaired Joint Mobility, Motor Function, Muscle Performance, Range of Motion, and Reflex Integrity Associated With Spinal Disorders”).21 The patient indicated that her goals for physical therapy were to be painfree, to work at her desk without symptoms for 1 hour, and to participate in yoga and aerobics sessions without being interrupted by her symptoms.

Traditional Physical Therapy Intervention Physical therapy treatment commenced at a frequency of 3 times per week for 4 weeks. Initially, manual soft tissue techniques and spray and stretch were used to relieve the MTrPs in the right upper quarter.22 The patient received an education program on treatment day 1 consisting of posture correction, a home exercise program of strengthening exercises for the middle and lower trapezius, and self-neurodynamic gliding exercises. 354

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The in-clinic treatments, started on treatment day 2, consisted of manual neurodynamic gliding for the median nerve, soft tissue mobilization and MTrP release, and a therapeutic exercise program consisting of exercising on an upper-body ergometer followed by progressive resistive exercises for the periscapular muscles. The patient was consistent with her physical therapy appointments, attending 12 of 12 sessions over 4 weeks, and reported consistency with her daily home program. Following 4 weeks of traditional physical therapy, the patient’s MTrPs were resolved, neurodynamic testing and impingement tests were negative, and posture, as examined visually by the treating physical therapist, was improved. The patient reported her pain level at that time as 4.5 cm (VAS), with exacerbations of 6.4 cm (VAS) and abatement of symptoms to 2.2 cm (VAS) (Table). The changes in the patient’s symptoms were 1.0 cm for present pain and 1.0 cm for best level of pain, and the minimum clinically significant difference has been established as 1.6 cm.17 The QuickDASH disability symptom score was reduced from 50 to 36, and scores on the sports/performing arts modules were reduced from 75 to 50 for each module (Table). During the traditional physical therapy treatment and the subsequent ergonomic assessment and treatment, the patient continued to perform her normal work duties.

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Ergonomic Assessment Following completion of traditional physical therapy, the patient was referred to another physical therapist for an ergonomic work risk analysis (WRA). The physical therapist performing the WRA was a Certified Ergonomic Assessment Specialist (Back School of Atlanta) and had 8 years of experience in performing ergonomic assessments. The pain rating and the QuickDASH scores were repeated, and the Workstyle short-form measure of work demands was assessed.23 The WRA was completed using the Occupational Safety and Health Administration (OSHA) W-1 Basic Screening Tool,24 the OSHA VDT workstation checklist10 (Appendix), and the Rapid Upper Limb Assessment (RULA).25,26 The OSHA W-1 Basic Screening Tool identifies risk factors for workrelated MSDs related to awkward postures, repetition, force, contact stress, and vibration and is a general assessment tool for use in all types of industry.24 The OSHA VDT workstation checklist is used specifically for identifying risk factors for workrelated MSDs associated with workstation postures and devices.10 The OSHA assessment tools are a logical primary step in ergonomics assessment because they are readily available, simple, and easy to use and are supported by current research and NIOSH recommendations. The RULA tool is used to estimate the risks of April 2009

Ergonomic Intervention for Upper Extremity and Neck Pain work-related upper-limb disorders and scores the worker’s awkward postures at the workstation into action levels ranging from 1 (“sound positioning/safe”) to 7 (“worst posture/immediate risk for injury”).25,26 The initial WRA identified risk factors for work-related MSDs using the OSHA W-1 Basic Screening Tool in the categories of awkward postures and repetition. The OSHA VDT workstation checklist revealed specific risks for work-related MSDs related to positioning of the head, neck, shoulders, and trunk, as well as seating issues. The VDT workstation checklist also identified risks associated with keyboard and mouse position, monitor position, and lack of document holder, wrist rests, and telephone hands-free headset. The RULA tool identified risks associated with shoulder abduction and elevation, forearm flexion, wrist flexion and ulnar deviation, neck flexion and rotation, trunk flexion and rotation, and leg position. The initial RULA score was 7, indicating the need for immediate ergonomic intervention.25,26 The RULA score presented for this case report represents only the affected side. The RULA was completed for the noninvolved side, but the data are not presented here to preserve the clarity of the case. The WRA involved the therapist observing the patient for a 2-hour period while she performed her normal work duties on what was deemed by the patient to be a typical day of work. The awkward postures were averages of what had been visualized by the therapist. The subsequent scores were an average of the postures and positions as seen over the examination period. In addition to the WRA performed by the therapist, the patient completed a Workstyle short-form survey. The Workstyle short form survey measures the individual’s perception of his or her job and workstation in April 2009

relation to symptoms in the following categories: working through the pain, social reactivity, limited workplace support, deadlines and pressure, self-imposed workplace and workload, breaks, mood, and autonomic response.23 The Workstyle short-form survey has been shown to have good internal consistency (␣⫽.89) and good test-retest reliability (r⫽.88) and is correlated with measures of pain (r⫽.41) and upperextremity symptoms (r⫽.33).23 The Workstyle score for the current patient was 52, with an “at risk” score defined as greater than 28.23 The Workstyle short-form survey was completed following the observation period. A specific description of the patient’s workstation follows. The patient’s monitor was low and offset; the top of the monitor was positioned below eye level; and the monitor was set to the left of the work surface, requiring flexed and rotated trunk and neck postures. The keyboard was positioned on the desk surface, higher than the elbow position, resulting in bilateral wrist extension and shoulder elevation. The mouse was positioned 25.4 cm (10 in) away from the keyboard, requiring right arm abduction and shoulder elevation. The chair height and seat pan angle could not be adjusted, contributing to increased trunk and neck flexion and unsupported bilateral foot position and contact stress in the popliteal fossa.

Ergonomic Intervention The ergonomic intervention was undertaken immediately after completing the scoring of the outcome measures and followed guidelines in OSHA document 3092, “Working With Video Display Terminals,” which describe head, trunk, upperextremity, and lower-extremity positioning that is in agreement with current research regarding safe VDT working postures.10 An adjustable

seat from an unused workstation was substituted for the patient’s seat. The new seat height was adjusted to accommodate the monitor viewing angle combined with a relaxed leg and foot position, as well as the shoulder and elbow positions that are described below. An adjustable chair provides a platform from which all other adjustments can be manipulated. The addition of an adjustable seat, combined with ergonomic education, has been shown to reduce pain complaints in workers whose jobs required sitting for four hours per day while working at a VDT.27 Rempel et al28 demonstrated that adding a properly fitted, adjustable chair significantly reduced shoulder and neck pain in seated workers. The height and seat pan of the patient’s new chair were adjusted to allow proper positioning of the trunk and upper extremities with the elbows at 80 degrees of flexion, elbows higher than the keyboard, and neutral wrist position of 0 degrees of flexion or extension while resting on the keyboard or mouse. The neutral shoulder/elbow/wrist position is designed to decrease muscle activation during seated postures that may be caused by constant low-level loading of the upper-extremity muscles. Previous research12,29 has shown that constant low-level muscle loading at the shoulder, neck, and forearms produced by positioning the elbow and wrist in non-neutral postures leads to an increase in pain at the shoulder, neck, and wrist. The mouse was positioned at the right upper corner of the keyboard to eliminate excessive shoulder abduction and decrease muscle activation and fatigue.30,31 The monitor height was adjusted to the proper eye level by using a 10.16-cm (4-in) riser, and the monitor was positioned directly in front of the patient’s view to approximate the appropriate viewing angle and distance from the patient’s eyes.32 Previous work by Marcus et

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Ergonomic Intervention for Upper Extremity and Neck Pain al13 showed that monitor height adjustment requiring less than a 3-degree tilt angle produced a significant decrease in neck and shoulder symptoms. Subsequent intervention involved ordering a split keyboard to reduce ulnar deviation strain.33 Marklin and Simoneau33 demonstrated that using a split keyboard, compared with a conventional keyboard, reduced ulnar deviation by as much as 10 degrees, allowing the wrist to be at a more neutral position and reducing RULA wrist position score. A keyboard tray and mouse tray were ordered and later incorporated to better align input devices while reducing the shoulder/elbow/wrist awkward postures.11,30,31 A document holder was later implemented to reduce head and neck movement and to reduce the chance that the patient would encounter a head tilt angle that put her at risk for neck pain.13 The patient also was educated on the postural adjustments made to her body and her workstation and was instructed to take 20second “microbreaks” as a means to break any sustained posture and relieve her symptoms by reducing myoelectric activity in the shoulder girdle musculature.34 Each microbreak consisted of a 20-second period of standing stretches (AROM for shoulder flexion, wrist flexion and extension, and scapular adduction) performed every 30 minutes while at her desk. The duration of the ergonomic intervention consisted of 2 hours of assessment combined with the immediate workstation changes discussed above. A single 1-hour follow-up visit occurred 1 week after the initial ergonomic intervention to implement the new devices that were ordered and to review patient education regarding the new working postures.

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Outcome The outcome measures were reassessed at 1 month following implementation of the ergonomic intervention. During the period following the ergonomic intervention and to the day of the reassessment, the patient was no longer being treated with formal physical therapy and reported continuing her home exercise program 4 days per week. The results of the reassessment are summarized in the Table and briefly presented here. The patient’s “present level of pain” rating on the VAS decreased by 1.0 cm following 4 weeks of traditional physical therapy and decreased by an additional 3.6 cm following the ergonomic intervention period. The patient’s “worst pain” rating did not decrease during traditional physical therapy, but showed a decrease of 4.4 cm following the ergonomic intervention. The patient’s “best pain” rating improved by 1.0 cm following traditional physical therapy and by an additional 2.2 cm following the ergonomic intervention. The QuickDASH disability score improved by 28% following traditional physical therapy and by 100% following the ergonomic intervention. The RULA and Workstyle ratings improved by 86% and 81%, respectively, following the ergonomic intervention. Four weeks after the ergonomic intervention, the patient’s outcome scores for disability, pain, and work risk showed greater improvement than during traditional physical therapy alone.

Discussion The purpose of this case report was to describe the effects of traditional physical therapy and ergonomic intervention in the treatment of a patient with neck and shoulder pain. It appears that the combined interventions of ergonomic assessment and modifications following 4 weeks of traditional physical therapy provided a greater decrease in symptoms than the patient experienced during tradi-

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tional physical therapy alone. However, it is difficult to say whether either intervention was more beneficial. Additionally, it is important to note that assessments using the RULA and Workstyle tools were not performed prior to beginning traditional physical therapy. Therefore, a true comparison between treatments cannot be accurately assessed using the RULA and Workstyle tools. The patient had been continuing her home exercise program from the traditional physical therapy stage through the ergonomic intervention and had been instructed on proper postural corrections during traditional physical therapy. She also had been continuing to work at full capacity in her current position. Therefore, it may not be appropriate to conclude that the ergonomic intervention was the sole mechanism for the patient’s pain relief. Although it has previously been demonstrated that improvements in neck and upper-extremity pain can be seen following adjustments to the workstation combined with postural adjustments of the worker, the role of exercise provided through the initial traditional physical therapy protocol and the educational component provided to the patient also need to be considered.35 A possible confounding element in the current case is the home exercise program. Patients experiencing neck pain previously demonstrated a decrease in pain symptoms and a decreased disability score following 6 weeks of exercise therapy alone when compared with controls.36 Perhaps, in the present case, a greater portion of the decrease in symptoms was realized through the patient’s continuing her home exercise program rather than through the introduction of ergonomic interventions. Previous research also has shown that initial education regarding ergonomic postures at VDT workstations April 2009

Ergonomic Intervention for Upper Extremity and Neck Pain can influence symptoms.37 The initial postural education during traditional physical therapy may have contributed to the end result. However, Ketola et al37 showed that a combination of ergonomic education and workstation modifications provided a greater positive effect on patients’ symptoms than ergonomic education alone. This finding may implicate one of the shortcomings of traditional physical therapy. In many cases, it seems physical therapists may discuss or show a patient the proper posture for sitting at a VDT, but without actual assessment and modification of the workstation, significant symptom relief may not be achieved. The evidence from Ketola et al37 would suggest that there is greater value in the therapist’s actually observing the patient in his or her natural working environment while performing the tasks required of the job. Patients may try to demonstrate artificially constructed work-related tasks in the clinic in the manner that they think the physical therapist wants to see. In the workplace, the bias is removed and the patient is more likely to perform tasks and exhibit postures more closely representative of his or her daily habits. It is equally important to note that the patient in this case underwent traditional physical therapy for an extended period with minimal improvement. The VAS scores reflect the minimal improvement in the patient’s symptoms after traditional treatment, with values remaining below the minimum clinically significant difference for the VAS. Had the ergonomic assessment and intervention been undertaken earlier in the treatment plan, perhaps the patient would have achieved her results in less time. In the current case, the VAS scores exceeded the minimum clinically significant difference after the completion of the full course of treatment, which included the ergoApril 2009

nomic intervention. At a time when the health care industry continually strives to provide efficient care, a treatment plan that is not yielding results should be reevaluated or, in the present case, where the combined treatment of traditional physical therapy and ergonomics was shown to be beneficial, the office assessment should have been performed earlier. In the current case, the patient completed 12 visits of traditional physical therapy without significant improvement of her symptoms. Had the ergonomic assessment and intervention taken place earlier and possibly during the traditional physical therapy, perhaps the patient would have achieved a decrease in symptoms in a timelier manner, thus removing any indication of possible overutilization of physical therapy. For example, the cost of the ergonomic assessment in this case was $300. The cost of the ergonomic interventions (workstation devices to modify posture) was approximately $150. Therefore, the total cost of the ergonomic assessment and intervention was $450. In contrast, the cost of traditional physical therapy in this case was approximately $1,200. An ergonomic assessment is a costeffective choice for the initial stages of treatment in patients with upperextremity dysfunction that may appear to be work-related. Furthermore, the range of costs in individual workstation modifications allows the ergonomic intervention phase to remain cost-effective. To more adequately assess the benefits of ergonomic intervention alone, the work risk assessment (RULA, Workstyle) should be performed prior to beginning a program of physical therapy treatment as a part of the initial evaluation procedures. Additionally, a course of ergonomic intervention should be explored prior to beginning physical therapy

to assess the interaction of ergonomic intervention with traditional physical therapy. The amount and type of education regarding workstation posture also needs to be controlled in order to assess the true impact of the ergonomic intervention. In the current report, it is difficult to assess the extent to which the initial introduction of physical therapy treatment may have been responsible for the patient’s progress. Would reversing the treatments, with an ergonomic intervention as the initial treatment and physical therapy intervention implemented 4 weeks later, show the same results? There is a need for continued research into and study of ergonomic intervention and its relationship to patient symptoms and its role in augmenting traditional physical therapy. One must consider that if ergonomic measures were to be implemented for all patients with seemingly workrelated upper-extremity and neck symptoms, there must be a screening mechanism to predict which patients would benefit from ergonomic intervention. This article was received July 8, 2008, and was accepted January 12, 2009. DOI: 10.2522/ptj.20080209

References 1 Bernard BP, ed. Musculoskeletal Disorders and Workplace Factors: A Critical Review of Epidemiologic Evidence for Work-Related Musculoskeletal Disorders of the Neck, Upper Extremity, and Low Back. Atlanta, GA: US Dept of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health; 1997. 2 Fogleman M, Brogmus G. Computer mouse use and cumulative trauma disorders of the upper extremities. Ergonomics. 1995;38:2465–2475. 3 Webster BS, Snook SH. The cost of compensable upper extremity cumulative trauma disorders. J Occup Med. 1994;36: 713–727. 4 Lewis RJ, Krawiec M, Confer E, et al. Musculoskeletal disorder worker compensation costs and injuries before and after an office ergonomics program. Int J Indust Ergon. 2002;29:95–99.

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Ergonomic Intervention for Upper Extremity and Neck Pain 5 Pilligan G, Herbert R, Hearns M, et al. Evaluation and management of chronic workrelated musculoskeletal disorders of the distal upper extremity. Am J Ind Med. 2000;37:75–93. 6 Marcus M, Gerr F. Upper extremity musculoskeletal symptoms among female office workers: associations with video display terminal use and occupational psychosocial stressors. Am J Ind Med. 1996;29:161–170. 7 Korhonen T, Ketola R, Toivonen, et al. Work-related and individual predictors for incident neck pain among office employees working with video display units. Occup Environ Med. 2003;60:475– 482. 8 Sillanpa¨ä J, Huikko S, Nyberg M, et al. Effect of work with visual display units on musculo-skeletal disorders in the office environment. Occup Med (Lond). 2003; 53:443– 451. 9 Hernandez LO, Gonzalez ST, Alcantara SM, Ramirez IM. Computer use increases the risk of musculoskeletal disorders among newspaper office workers. Arch Med Res. 2003;34:331–342. 10 Computer Workstation eTool. Occupational Safety and Health Administration Web site. Available at: http://www.osha. gov/SLTC/etools/computerworkstations/ index.html. Accessed December 12, 2008. 11 Cook CJ, Kothiyal K. Influence of mouse position on muscular activity in the neck, shoulder, and arm in computer users. Appl Ergon. 1998;29:439 – 443. 12 Mork PJ, Westgaard RH. Low-amplitude trapezius activity in work and leisure and the relation to shoulder and neck pain. J Appl Physiol. 2006;100:1142–1149. 13 Marcus M, Gerr F, Monteilh C, et al. A prospective study of computer users, II: postural risk factors for musculoskeletal symptoms and disorders. Am J Ind Med. 2002;41:236 –249. 14 Pallastrini P, Mugnai R, Farneti C, et al. Evaluation of two preventive interventions for reducing musculoskeletal complaints in operators of video display terminals. Phys Ther. 2007;87:536 –544. 15 Hignett S, McAtamney L. Rapid entire body assessment (REBA). Appl Ergon. 2000;31:201–205.

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16 Price DD, McGrath PA, Rafii A, Buckingham B. The validation of the visual analogue scales as ratio scale measures for chronic and experimental pain. Pain. 1983;17:45–56. 17 Gallagher EJ, Bijur PE, Latimer C, Silver W. Reliability and validity of a visual analog scale for acute abdominal pain in the ED. Am J Emerg Med. 2002;20:287–290. 18 C ¸ alis¸ M, Akgu ¨ n K, Birtane M, et al. Diagnostic values of clinical diagnostic tests in subacromial impingement syndrome. Am Rheum Dis. 2000;59:44 – 47. 19 MacDonald PB, Clark P, Sutherland K. An analysis of the diagnostic accuracy of the Hawkins and Neer subacromial impingement signs. J Shoulder Elbow Surg. 2000; 9:299 –301. 20 Gummesson C, Ward MM, Atroshi I. The shortened disabilities of the arm, shoulder and hand questionnaire (QuickDASH): validity and reliability based on responses within the full-length DASH. BMC Musculoskelet Disord. 2006;7:44. 21 Guide to Physical Therapist Practice. 2nd ed. Phys Ther. 2001;81:9 –746. 22 McPartland JM. Travell trigger pointsmolecular and osteopathic perspectives. J Am Osteopath Assoc. 2004;104:244 –249. 23 Feuerstein M, Nicholas RA. Development of a short form of the Workstyle measure. Occup Med. 2006;56:94 –99. 24 OSHA W-1 Basic Screening Tool. Occupational Safety and Health Administration Web site. Available at: http://www.osha. gov. Accessed December 12, 2008. 25 McAtamney L, Corlett EN. RULA: a survey method for the investigation of workrelated upper limb disorders. Appl Ergon. 1993;24:91–99. 26 McAtamney L, Corlett EN. Rapid Upper Limb Assessment (RULA). In: Stanton NA, Hedge A, Brookhuis K, et al, eds. Handbook of Human Factors and Ergonomics Methods. Boca Raton, FL: CRC Press; 2004:7.1–7.11. 27 Amick BC, Robertson MM, DeRango K, et al. Effect of office ergonomics intervention on reducing musculoskeletal symptoms. Spine. 2003;28:2706 –2711.

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28 Rempel DM, Wang PC, Janowitz I, et al. A randomized controlled trial evaluating the effects of new task chairs on shoulder and neck pain among sewing machine operators. Spine. 2007;32:931–938. 29 Keir PJ. The effect of typing posture on wrist extensor muscle loading. Hum Factors. 2002;44:392– 403. 30 Ahlstrom V, Kudrick B. Human Factors Criteria for the Design and Acquisition of Non-keyboard Interaction Devices: A Revision to Chapter 9 of the Human Factors Design Standard (DOT/FAA/CT). Atlantic City International Airport, NJ: Federal Aviation Administration, William J Hughes Technical Center; 2004. 31 Bernaards CM, Ariens GAM, Hildebrandt VH. The (cost-)effectiveness of a lifestyle physical activity intervention in addition to a work style intervention on the recovery from neck and upper limb symptoms in computer workers. BMC Musculoskel Disord. 2006;7:80 –91. 32 Ahlstrom V, Kudrick B. Human Factors Criteria for Displays: A Human Factors Design Standard Update of Chapter 5 (DOT/FAA/TC-07/11). Atlantic City International Airport, NJ: Federal Aviation Administration, William J Hughes Technical Center; 2007. 33 Marklin RW, Simoneau GG. Effect of setup configurations of split computer keyboards on wrist angle. Phys Ther. 2001;81: 1038 –1048. 34 McLean L, Tingley M, Scott RN, Richards J. Computer terminal work and the benefit of microbreaks. Appl Ergon. 2001;32: 225–237. 35 Bernaards CM, Ariens GAM, Simons M, et al. Improving work style behavior in computer workers with neck and upper limb symptoms. J Occup Rehabil. 2008; 18:87–101. 36 Chiu TT, Lam TH, Hedley AJ. A randomized controlled trial on the efficacy of exercise for patients with chronic neck pain. Spine. 2005;30:E1–E7. 37 Ketola R, Toivonen R, Hakkanen M, et al. Effects of ergonomic intervention in work with video display units. Scand J Work Environ Health. 2002;28:18 –24.

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Ergonomic Intervention for Upper Extremity and Neck Pain Appendix. Occupational Safety and Health Administration (OSHA) VDT Workstation Checklist10

Appendix D-2 to §1910.900: VDT Workstation Checklist: Using this checklist is one, but not the only, way an employer can comply with the requirement to identify, analyze, and control MSD hazards in VDT tasks. This checklist does not require that employees assume specific working postures in order for the employer to be in compliance. Rather, employers will be judged to be in compliance with paragraphs (k) and (m) of OSHA standards if they provide the employee with a VDT workstation that is arranged or designed in a way that would pass this checklist. WORKING CONDITIONS

Y

N

Y

N

Y

N

The workstation is designed or arranged for doing VDT tasks so it allows the employee’s: A. Head and neck to be about upright (not bent down/back). B. Head, neck, and trunk to face forward (not twisted). C. Trunk to be about perpendicular to floor (not leaning forward/backward). D. Shoulders and upper arms to be about perpendicular to floor (not stretched forward) and relaxed (not elevated). E. Upper arms and elbows to be close to body (not extended outward). F. Forearms, wrists, and hands to be straight and parallel to floor (not pointing up/down). G. Wrists and hands to be straight (not bent up/down or sideways toward little finger). H. Thighs to be about parallel to floor and lower legs to be about perpendicular to floor. I.

Feet to rest flat on floor or be supported by a stable footrest.

J.

VDT tasks to be organized in a way that allows employee to vary VDT tasks with other work activities or to take micro-breaks or recovery pauses while at the VDT workstation.

SEATING 1. Backrest provides support for employee’s lower back (lumbar area). 2. Seat width and depth accommodate specific employee (seat pan not too big/small). 3. Seat front does not press against the back of employee’s knees and lower legs (seat pan not too long). 4. Seat has cushioning and is rounded/has “waterfall” front (no sharp edge). 5. Armrests support both forearms while employee performs VDT tasks and do not interfere with movement. KEYBOARD/INPUT DEVICE The keyboard/input device is designed or arranged for doing VDT tasks so that: 6. Keyboard/input device platform(s) is stable and large enough to hold keyboard and input device. 7. Input device (mouse or trackball) is located right next to keyboard so it can be operated without reaching. 8. Input device is easy to activate and shape/size fits hand of specific employee (not too big/small). 9. Wrists and hands do not rest on sharp or hard edge.

(Continued)

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Ergonomic Intervention for Upper Extremity and Neck Pain Appendix. Continued

MONITOR

Y

N

Y

N

Y

N

Y

N

The monitor is designed or arranged for VDT tasks so that: 10. Top line of screen is at or below eye level so employee is able to read it without bending head or neck down/back. (For employees with bifocals/trifocals, see next item.) 11. Employee with bifocals/trifocals is able to read screen without bending head or neck backward. 12. Monitor distance allows employee to read screen without leaning head, neck, or trunk forward/backward. 13. Monitor position is directly in front of employee so employee does not have to twist head or neck. 14. No glare (eg, from windows, lights) is present on screen that might cause employee to assume an awkward posture to read screen. WORK AREA The work area is designed or arranged for doing VDT tasks so that: 15. Thighs have clearance space between chair and VDT table/keyboard platform (thighs not trapped). 16. Legs and feet have clearance space under VDT table so employee is able to get close enough to keyboard/input device. ACCESSORIES 17. Document holder, if provided, is stable and large enough to hold documents that are used. 18. Document holder, if provided, is placed at about the same height and distance as monitor screen so there is little head movement when employee looks from document to screen. 19. Wrist rest, if provided, is padded and free of sharp and square edges. 20. Wrist rest, if provided, allows employee to keep forearms, wrists, and hands straight and parallel to ground when using keyboard/input device. 21. Telephone can be used with head upright (not bent) and shoulders relaxed (not elevated) if employee does VDT tasks at the same time. GENERAL 22. Workstation and equipment have sufficient adjustability so that the employee is able to be in a safe working posture and to make occasional changes in posture while performing VDT tasks. 23. VDT workstation, equipment, and accessories are maintained in serviceable condition and function properly. PASSING SCORE ⫽ “YES” answer on all “working postures” items (A–J) and no more than two “NO” answers on remainder of checklist (1–23). a

MSD⫽musculoskeletal disorder, VDT⫽video display terminal.

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Case Report

Constraint-Induced Movement Therapy for Individuals After Cerebral Hemispherectomy: A Case Series Stella de Bode, Stacy L Fritz, Kristi Weir-Haynes, Gary W Mathern

Background and Purpose. This case report describes the feasibility and efficacy of the use of constraint-induced movement therapy (CIMT) in 4 individuals (aged 12–22 years) who underwent cerebral hemispherectomy (age at time of surgery⫽4 –10 years). The aims of this case series were: (1) to evaluate the feasibility of this therapeutic approach involving a shortened version of CIMT, (2) to examine improvements that occurred within the upper extremity of the hemiparetic side, (3) to investigate the feasibility of conducting brain imaging in individuals with depressed mental ages, and (4) to examine changes in the sensorimotor cortex following intervention. Case Description. The patients received a shortened version of CIMT for 3 hours each day for a period of 10 days. In addition, a standard resting splint was used for the unimpaired hand for an 11-day period. Each patient was encouraged to wear the splint for 90% of his or her waking hours. The following outcome measures were used: the Actual Amount of Use Test (AAUT), the Box and Block Test (BBT), and the upper-extremity grasping and motor portions of the Fugl-Meyer Assessment of Motor Recovery (FM). Outcomes. Immediately after therapy, improvements were found in AAUT and BBT scores, but no improvements were found in FM scores. Three patients underwent brain imaging before and after therapy and showed qualitative changes consistent with reorganization of sensorimotor cortical representations of both paretic and nonparetic hands in one isolated hemisphere. Discussion. The findings suggest that CIMT may be a feasible method of rehabilitation in individuals with chronic hemiparesis, possibly leading to neuroplastic therapy–related changes in the brain.

S de Bode, PhD, is Senior Researcher (Assistant Professor), Sector of Child Neuropsychology, University Medical Center Utrecht, Wilhelmina Children’s Hospital, KG 01.327.1, PO Box 85090, 3508 AB Utrecht, the Netherlands. Address all correspondence Dr de Bode at: [email protected]. SL Fritz, PT, PhD, is Clinical Assistant Professor, Department of Physical Therapy, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina. K Weir-Haynes, PT, is Professor, Department of Physical Therapy, Arnold School of Public Health, University of South Carolina. GW Mathern, MD, is Professor, Department of Neurosurgery, Mental Retardation Research Center and Brain Research Institute, David Geffen School of Medicine, University of California, Los Angeles. [de Bode S, Fritz SL, Weir-Haynes K, Mathern GW. Constraintinduced movement therapy for individuals after cerebral hemispherectomy: a case series. Phys Ther. 2009;89:361–369.] © 2009 American Physical Therapy Association

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CIMT in Individuals After Cerebral Hemispherectomy

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ntractable pharmaco-resistant epilepsy in children disrupts motor and cognitive development and impairs quality of life. When pathology and seizures involve an entire hemisphere of the brain, a surgical procedure known as cerebral hemispherectomy, in which an entire hemisphere is either removed or partially removed and completely disconnected, is performed. Hemispherectomy for seizure control often is performed in people with conditions such as cortical dysplasia, perinatal infarct, Rasmussen’s encephalitis, and Sturge-Weber syndrome.1 Hemispherectomy often completely arrests seizure activity, but results in residual hemiparesis on the contralateral side of the body.2 Hemispherectomy surgery comprises 16% of all pediatric epilepsy surgical cases.3 The study of resulting hemiparesis and brain reorganization, however, has wide applications for other pediatric populations with hemiparesis such as individuals with stroke, cerebral palsy, arteriovenous malformations, brain trauma, and partial cortical resections involving the sensorimotor cortex. Because the neural basis of brain reorganization following both developmental and acquired insults to sensorimotor cortices and resulting hemiparalysis is not fully understood, hemispherectomy research is important to unequivocally address the consequences of lesions resulting in the complete unilateral loss of original pathways subserving voluntary movements. This research may help to develop specific therapies target-


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ing the use and unmasking of the ipsilateral motor network and to elucidate both possibilities and limitations of rehabilitation in populations with the unavailable contralateral corticospinal tract. Individuals who have had a hemispherectomy exhibit different degrees of hemiplegia; however, the distal muscles of the upper extremity (UE) often are more severely involved.4 We conducted a case series to investigate the effects of constraintinduced movement therapy (CIMT) in this population. Constraint-induced movement therapy has been demonstrated to be an effective UE intervention for some individuals with hemiplegia.5–7 It is used mainly in people after a stroke to increase functional use of the neurologically weaker UE through massed practice of hand and arm tasks, while restraining the less-affected UE.8 The goals of CIMT are to overcome a learned non-use behavior and to improve functional use of the affected UE by “forcing” use of the affected UE. The focus of CIMT is on the continual plasticity of the cortex; thus, functional improvements should be able to occur at any time.9 In our experience, hemiplegia in children and young adults after hemispherectomy has a clinical presentation similar to those of individuals with a variety of conditions, such as cerebral palsy, stroke, and hydrocephalus. Although there are no formal comparison studies, we have observed similar motor and sensory impairments and similar functional limitations in our patients after hemispherectomy. We suggest that, similar to these other patient groups, the impairments seen in children after cerebral hemispherectomy have a negative effect on their quality of life and restrict their participation in mainstream activities, but the effects of novel therapeutic approaches in this population have not

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been addressed. Constraint-induced movement therapy has been introduced in pediatric populations relatively recently but not in individuals after hemispherectomy.10 The methodology behind CIMT has been successfully implemented in a pediatric population, and childfriendly guidelines have recently been formulated.11 The etiologies of children who participated in published CIMT studies included cerebral palsy, stroke, trauma, and unknown etiologies. The specifics of traditional CIMT require the restraint of the unaffected UE for 90% of the individual’s waking hours for 14 consecutive days. For 10 of the 14 days, the individual engages in 6 hours of intensive therapy involving repetitive tasks with the affected UE.12 Several studies have experimented with the therapeutic approach by changing duration, intensity, or dosage13–16 and indicated positive changes in UE function; however, only portions of the entire CIMT guidelines were utilized, and duration of both treatment and use of limb restraint varied. In our case series, data collection was completed prior to publication of the pediatric guidelines; however, the only main change from traditional CIMT was treatment for 3 hours per day versus the traditional 6 hours per day. The neurobiological substrate of motor learning has become an area of extensive research since the discovery that experience-driven motor learning causes reorganization of cortical maps.17 However, the neural substrate mediating partial sparing of function in individuals after hemispherectomy remains a poorly researched area and presents a challenge, given the frequency of depressed mental age in this population. In our case series, we applied functional imaging to examine partial recovery of paretic limb function April 2009

CIMT in Individuals After Cerebral Hemispherectomy in order to determine whether cortical reorganization can be manipulated through physical therapy to improve the recovery. After considering the status (effects of seizure medications, low fitness level), depressed mental ages, and decreased emotional maturity of our patients, we chose to use the “shortened” 3-hour method of CIMT to make its use more feasible in this population. The aims of this case series were: (1) to evaluate the feasibility of this therapeutic approach involving a shortened version of the CIMT within a small case series of individuals who had undergone hemispherectomy, (2) to examine improvements that occurred within the upper extremity of the hemiparetic side, (3) to investigate feasibility of conducting brain imaging in individuals with depressed mental ages, and (4) to examine changes in the sensorimotor cortex following intervention.

Patient History Examination and Selection Four individuals (1 male, 3 female) who underwent hemispherectomy to relieve intractable, drug-resistant seizure disorder associated with prenatal infarct (age range⫽12–22 years, age at time of surgery⫽4 –10 years, time after surgery⫽4 –18 years) were evaluated and trained at the Motor Rehabilitation Laboratory, University of South Carolina, Columbia. The patients’ mental ages were determined using the Peabody Picture Vocabulary Test (PPVT)18 and ranged from 5 to 11 years. All patients were seizure-free. Two patients had medicated seizure control, and 2 patients had achieved complete unmedicated seizure control. All patients and their guardians signed an informed consent and assent form approved by the institutional review board of the university. The patients were recruited from the pool of individuals from across April 2009

the United States who had undergone surgery at the UCLA Pediatric Epilepsy Surgery Program. Approximately 150 individuals had undergone surgery in this program at the time of the intervention, and about 10 to 15 individuals undergo surgery in the program annually.1 All patients had a clinical presentation of hemiplegia after hemispherectomy. None of the patients reported currently receiving rehabilitation. The primary functional inclusion criterion to participate in the therapy was the ability to release a massed flexion grasp.19 Additional inclusion criteria were: (1) ability to lift the hand from the lap to a standard-height table, indicating approximately 30 degrees of active shoulder flexion; (2) ability to follow simple instructions; (3) ability to sit independently without back or arm support for 5 minutes; (4) ability to stand for 2 minutes with assistance, if needed; and (5) at least half of the normal passive range of motion of all UE motions. Individuals were excluded if they: (1) had metal in their bodies, such as an implanted pacemaker or medication pump, metal plate in the skull, or metal objects in the eye or skull (due to functional magnetic resonance imaging [fMRI] safety requirements); (2) had a mental age lower than 41⁄2 years as evaluated by PPVT (to be able to follow commands, pay attention to trainers, and cooperate in a scanner during imaging sessions), or (3) lacked seizure control.

Intervention The patients received a shortened version of the CIMT for 3 hours each day, compared with the more traditional 6 hours, in order to accommodate for a variety of “challenges” (eg, low fitness level, cognitive and emotional impairments) found in this population. Participation was for a period of 10 days and was per-

formed during the summer, while the patients were out of school. The intervention consisted of 6 consecutive days of therapy, followed by 1 day off, and then the 4 remaining days of therapy. The intervention involved intensive therapy sessions, including practice of functional tasks with progressive levels of complexity. Throughout the therapy sessions, each patient was encouraged to use only the more-affected hand and arm and was limited in using the constrained hand during tasks. A standard resting splint was used for the unimpaired hand for the 11-day period of therapy. The goal was for the patients to wear the splint for 90% of their waking hours. Patients were encouraged to continue wearing the splint while away from therapy to promote use of the impaired UE during daily activities. During the therapy sessions, the intervention was provided on a oneon-one basis for individualized task development for each patient. The activities chosen for the therapy sessions consisted of sets of tasks and games that were performed using the impaired UE, such as grasping pick-up sticks, playing checkers, gripping and throwing tennis balls, and working puzzles. An activity log was used to document the tasks performed and progression of patients throughout the therapy sessions. With improvement in performance and knowledge of the tasks, the complexity and difficulty of the tasks were increased to continue to challenge the patients. The changes in the tasks included timing of tasks, increasing height or distance to perform the task, and increasing pattern complexity within the task. Functional tasks were used; however, they were modified to allow for success based on each patient’s degree of finger and hand control. There was no set amount of rest time, but the patients were encouraged to stay active throughout the 3 hours of

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CIMT in Individuals After Cerebral Hemispherectomy Table 1. Outcome Measures Useda Outcome Measure

a

Type of Measure

Scoring

Reliability and Norms

Actual Amount of Use Test (AAUT)22

Implicit measure of actual and spontaneous use of an upper extremity

After test administration, the videotape was scored based on measurements found by the Amount of Use (AOU) scale, a 3-point scale, the Quality of Movement (QOM) scale, and a 5point scale

Reliability based on unpublished pilot study37 (kappa⫽.69–.98)

Box and Block Test (BBT)21

Test of manual dexterity

Number of blocks that are transported in 1 min

Norms established in children21 (ICC⫽.96 in patients with neurological impairments)

Fugl-Meyer Assessment of Motor Recovery (FM)20

Used to evaluate upper- and lower-extremity motor function

0 (indicating hemiplegia) to 66 (indicating normal upper-extremity motor function) Grasp section: total of 14 points

Reliable (ICC⫽.80–.97 for grasp section) in patients with neurological impairments23 and in patients after hemispherectomy4

ICC⫽intraclass correlation coefficient.

CIMT, with no more than 10 minutes of rest per hour. All trainers were senior-level Doctor of Physical Therapy students and were overseen by a physical therapist. The same 4 trainers rotated working with the patients (1 or 2 trainers per day). Outcome Measures Prior to and following the completion of the therapy sessions, 2 evaluators (a physical therapist and a senior DPT student) obtained scores with the following outcome measures: the Fugl-Meyer Assessment of Motor Recovery (FM),20 the Box and Block Test (BBT),21 and the Actual Amount of Use Test (AAUT),22 consisting of the Amount of Use (AOU) scale and the Quality of Movement (QOM) scale (Tab. 1). Both evaluators were trained in the evaluations and used identical instructions and recording forms. In addition, 3 patients underwent an fMRI session prior to and following therapy, as described below. Scoring During the course of the intervention, rater reliability could have been a factor due to using 2 testers who were not masked to test session. Although standardization of delivery of measures was established, no independent measurement of inter364

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rater reliability was established for the FM or the BBT due to the high reliability of data obtained with these measures.23 During the scoring of the AAUT, 2 raters were used to ensure agreement. Both raters simultaneously analyzed and scored each videotape of activities comprising the AAUT according to the preestablished standards. Agreement on the score had to occur between both raters prior to a final scored decision. If agreement was not found, discussion occurred to determine a score that both raters could agree upon. fMRI Methods and Analysis Three patients who were able to cooperate with fMRI procedures (ie, were comfortable in a scanner room, could remain still, tolerated noise levels, and were capable of performing a functional paradigm) participated in pretherapy and posttherapy imaging sessions and were asked to squeeze a rubber ball during an fMRI scan. We used a rubber ball with loops for individual fingers (GripSaverPlus*). The fMRI studies were performed for both the paretic and nonparetic hands, paying particular attention to avoiding moving both hands synergistically (“mirror * Metolius, 63189 Nels Anderson Rd, Bend, OR 97701.

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movements”). Attempts to squeeze with a weaker hand sometimes result in mirror movements. In order to control for mirror movements, the patients practiced ball squeezing outside the scanner room and then in the scanner after they had been positioned supine. A therapist (SdB) remained with each patient during scanning, along with a physical therapist who monitored for the absence of mirror movements, monitored paradigm adherence, and counted the number of hand flexion and extension movements during each block. Sessions were repeated if mirror movements were noticed. The patients were cued to start squeezing the ball when they saw a Sesame Street character (Elmo) appear on a screen and to stop when Elmo disappeared. All patients practiced the Elmo paradigm outside of the scanner room and had no problems understanding instructions. During each 31⁄2-minute fMRI scan, the patients performed 5 trials of squeezing (20 seconds each) with five 20-second rest periods. The same procedure was repeated for their nonparetic side. The pressure of squeezing may affect the intensity and extent of a signal observed as the brain activates. Ideally, the total pressure generated by each inApril 2009

CIMT in Individuals After Cerebral Hemispherectomy dividual should be the same before and after therapy to conclude that observed changes are not due to greater strength (force-generating capacity) but are due to neuroplastic changes. To match a weaker squeeze by the paretic hand, all patients were instructed to squeeze with their nonparetic hand lightly as if they were squeezing a juice box, making sure juice does not spill out. The frequency of squeezing was kept constant between sessions. Functional MRI scans were obtained using a 3T Philips Intera scanner† at the Medical University of South Carolina, Charleston. A 3-dimensional T1weighed anatomical scan was obtained in a rapid FLASH acquisition (voxel size⫽1 ⫻ 1 ⫻ 1 mm, matrix size⫽256 ⫻ 256 ⫻ 160, 15° flip angle, echo time⫽5.7 milliseconds, repetition time⫽9.5 milliseconds per FLASH line, effective inversion time⫽800 milliseconds, frequency encoding head to foot with SENSE r⫽2 applied in the left-right direction). Functional imaging used a gradient echo planar imaging (EPI) sequence (EPI: repetition time⫽2,400 milliseconds, flip angle⫽80°, 36 slices with a slice thickness of 3.25 mm and with no gap oriented parallel to the anterior-posterior commissure line). The fMRI data were processed and displayed using FSL24 and MRIcro(n)25 software.

Table 2. Individual Fugl-Meyer Assessment of Motor Recovery Scores Upper-Extremity Motor Test

Upper-Extremity Grasping Test

Patient

Pretest

Posttest

Pretest

Posttest

1

39

44

4

4

2

37

39

4

6

3

46

50

5

7

4

54

45

2

6

analysis, and for each individual, the analysis phase correlated the signal intensity within each voxel over time using a boxcar model with predicted signal increase during the ball squeezing and predicted decrease during rest.

Outcome Table 2 and Figures 1 and 2 show the individual findings for each patient. Inferential statistics were not performed due to the small number of patients. Improvements in pretestposttest values following therapy were found following the therapy for all patients for the AOM scale of the AAUT (156%, 30%, 360%, and 10%, respectively) and for quality of movements as measured by the QOM scale of the AAUT (50%, 8%, 190%, and 20%, respectively), with means in change scores for the AAUT and quality of movements of 84.3% and 55%, respectively. Improvements in pretest-posttest values following

therapeutic intervention also were noted for the BBT (33%, 150%, 5%, and 64%, respectively). There was no difference for the FM UE motor test, with a 1% change noted in pretest-posttest values. As stated above, 3 of the 4 patients met the inclusion criteria for fMRI scanning. Imaging results for all 3 patients showed activation in their remaining sensorimotor (M1S1) cortex while squeezing with both paretic and nonparetic hands following training (Fig. 3). No signal on the paretic side was detected in patient 4 before training; however, her posttraining imaging results suggested that both hands were represented next to each other in the classical “hand” area of the remaining hemisphere (Fig. 4). The location of activation associated with the paretic hand was similar to that of the nonparetic hand, although it was much greater in spatial extent and included

Data Analysis Functional scans were co-registered onto anatomical scans and spatially smoothed according to a standard protocol,26 and a cutoff value of .30 (Pearson r coefficient, corresponding to a P value of less than .01 uncorrected) was used to calculate the number of activated voxels above threshold in an anatomically defined region of interest: S1M1. The missing hemisphere was masked prior to † Philips Healthcare, 3000 Minuteman Rd, Andover, MA 01810-1099.

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Figure 1. Individual Scores for the Actual Amount of Use Test (AAUT)

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CIMT in Individuals After Cerebral Hemispherectomy areas outside the primary sensorimotor areas before and after therapy in patients 2 and 3. There were no statistically significant changes in the extent of activation within S1M1 for the paretic hand in these 2 patients (P⫽.27 and .11, respectively). There were subtle changes in the M1S1 activation locations in both patients; however, despite the shift after training, activations were found mostly in motor cortical areas. Figure 2.

Discussion

Individual Scores for the Box and Block Test

Cortical hemispherectomy represents the maximally invasive surgical resection. It leaves the patient’s consequent functioning, including motor development, dependent on the remaining hemisphere only (although subcortical structures of the removed hemisphere usually are left intact). The advantages of CIMT intervention after a hemispherectomy in our case series were that all patients had similar lesions occurring at similar gestational ages (perinatal infarct), the type of injury from surgery was uniform, and recovery and reorganization mechanisms involved similar neuroanatomic reorganization. Potential difficulties in interpreting the findings from such a cohort, however, include heterogeneous ages at surgery, the effect of seizures and antiepileptic drugs, and developmental delays in the majority of individuals after hemispherectomy.

Figure 3. Functional magnetic resonance imaging (fMRI) activations of the paretic hand before therapy (green) and after therapy (red) and for the nonparetic hand (blue) for 2 of the 3 patients who underwent fMRI testing.

Therapy Duration: 3 Versus 6 Hours per Day In this case series, we found that a shortened version of the CIMT is a feasible and tolerable intervention for individuals with longstanding UE dysfunction due to hemispherectomy. A shortened intervention scheme also was particularly appropriate for our patients, who had decreased mental ages and limited ability to sustain motivation. Most of the current literature on CIMT has focused specifically on the

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CIMT in Individuals After Cerebral Hemispherectomy adult population. Two groups of authors, however, used a more “traditional” CIMT delivery for pediatric clients. DeLuca et al5 reported on their use of CIMT in children with an average age of 3.25 years. Karman et al14 investigated the use of CIMT for hemiplegic children with acquired brain injuries whose average age was 12.5 years. Similar to our case series, they also had a small sample size (N⫽7) and reported significant improvements in all patients. After careful consideration of the specifics of our patients, we decided to follow the suggestions of a report of 3 case studies of adults, which indicated that 3 hours of CIMT significantly improved motor function in individuals with chronic stroke.27 These authors concluded that 6 hours a day of CIMT may have caused frustration, boredom, or undue fatigue for their patients, translating to a decreased capacity for motor learning.28,29 In retrospect, we believe that a 3-hour intervention was an appropriate duration for our patients because of their mental and psychological disabilities.

level, and personal interests, we were able to ensure on-site adherence in all participants.

Adherence to CIMT During therapy, we were able to maximize adherence to wearing the restraint using strategies such as patient decision making about therapeutic activities and subsequent structured rewards.11 As with all reports of the use of CIMT, these accommodations were achieved at the expense of standardization of the intervention but were crucial for all patients, especially for the patient with the lowest mental age. Although the time frame of 3 hours of intervention daily was a standard, there was no standard protocol to follow to ensure consistency of the intervention across patients. We found that conducting CIMT in these patients was a challenging task. However, by creating individual routines that were congruent with each patient’s mental age, physical fitness

Outcome Measures In this case series, our intervention was associated with improved motor function and increased use of the hemiparetic extremity, as measured by the AAUT and BBT. Despite chronic, and often severe, impairment of hand function, all patients made improvements. The degree of improvement varied significantly among the patients (ie, from 10% to 360% for the AOU scale of the AAUT, from 8% to 190% for quality of movements as measured by the QOM scale of the AAUT, and from 5% to 150% for the BBT). Relatively larger improvements in these measures were made by the 2 patients with the lowest initial scores (patients 1 and 3). We propose that the FM may not be an appropriate instrument for measuring changes associated with this kind of therapy. In order to dem-

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Figure 4. Cortical representation of the nonparetic (blue) and paretic (red) hands in patient 4 following therapy.

onstrate improvement on the FM UE motor test, motor movements must advance from in synergy to out of synergy. However, the primary goal of CIMT is increased use of the affected limb. The training used in CIMT does not focus on facilitation or correction of synergistic patterns that may occur with increased tone (resistance to movement) and spasticity (velocity-dependent hypertonicity). As we did not have a control group, we cannot comment on whether documented gains were due to the intervention or to other factors affecting the results. In general, with a case report such as ours, the lack of treatment effect remains a distinct possibility. Our findings suggest that the time elapsed since hemispherectomy does not appear to be a factor limiting the efficacy of therapy in patients with chronic impairment. Improvements were seen even 18 years after hemispherectomy. However, the ef-

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CIMT in Individuals After Cerebral Hemispherectomy fect of this intervention may be different for children immediately after hemispherectomy. In addition, individual differences due to medical variables such as etiology of disease, seizure control, age at surgery, and cognitive level were problems associated with this case series and with prior research in individuals after hemispherectomy. These combined factors could affect outcomes following therapy and should be investigated as possible covariates. Neurobiological Mechanism of CIMT and fMRI Testing Rehabilitation in adults is believed to result in the experience-induced expansion of motor maps and related improvements in motor performance.30 Therapy-related improvements in hand function are shown to correlate with increases in fMRI activity in adults,31 and 2 distinct mechanisms of increased synaptic efficiency or reorganization involving extension and recruitment of additional cortical areas were proposed to explain these effects.32 The specific effects of CIMT on cortical reorganization following insult have only recently begun to be addressed. Constraint-induced movement therapy is believed to alter the representation of the UE within the primary motor cortex in adults.33 Only one study has investigated the effects of CIMT in younger patients with congenital hemiparesis and demonstrated increases in activation in the lesioned hemisphere following therapy.34 In contrast to those individuals with both hemispheres in place, we showed that the paretic side in our patients was controlled by the remaining, “healthy” hemisphere, suggesting that residual paretic hand motility is the result of either a partially spared ipsiateral corticospinal tract35 or axonal sprouting of the contalateral corticospinal tract.36 Cortical motor representations of paretic and nonparetic 368

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hands were overlapping or closely represented in all 3 patients who underwent fMRI testing. We conclude that functional imaging is a useful tool in this population and may help to detect reorganization in the remaining hemisphere following intervention. It remains to be seen whether CIMT is associated with the increase in the activation extent or intensity. We did not see an increase in activations, although we did observe subtle shifts in the location of activations that still remained within primary sensorimotor and supplementary motor areas. Due to the preliminary nature of this case report and the small number of patients, we did not investigate correlations between brain activations and motor improvements. We suggest that next step of similar studies should involve studying correlations between changes in fMRI activity and behavioral gains. Limitations of the Therapeutic Approach There are a few major limitations of our therapeutic approach. We were unable to determine to what extent cognitive limitations influenced the efficiency or interest of the patients. Many more individuals are needed to adequately control for all clinical variables associated with this group, such as age at surgery, age at seizure onset, and seizure medications. The additional limitations are: (1) the lack of pre-established interrater and intrarater reliability of outcome measurements for the evaluators and the fact that the testers were not masked to test sessions, (2) the lack of quantitative measures of squeezing pressure while measuring brain activation and the unknown effects of task practice, and (3) the lack of information on history of past rehabilitation. Although our case report suggests the feasibility of using CIMT in individuals after hemispherectomy, caution should be exercised to avoid

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the limitations of our treatment approach. Dr de Bode, Dr Fritz, and Dr Mathern provided concept/idea/project design. All authors provided writing and data analysis. Dr de Bode, Dr Fritz, and Ms Weir-Haynes provided data collection. Dr de Bode and Dr Fritz provided project management. Dr de Bode and Dr Mathern provided fund procurement. Dr de Bode provided patients. Dr Fritz provided facilities/equipment. Dr Mathern provided consultation (including review of manuscript before submission). The authors thank all of the participants and their families for their time, effort, and courage. They also are grateful to all students in the Department of the Exercise Science, University of South Carolina, who took part in this project for their devotion, creativity, and loving professionalism. This work was supported by National Institute of Diabetes and Digestive and Kidney Diseases/National Institutes of Health grant R21 HD050707. This article was received August 20, 2007, and was accepted January 12, 2009. DOI: 10.2522/ptj.20070240

References 1 Cook SW, Nguyen ST, Hu B, et al. Cerebral hemispherectomy in pediatric patients with epilepsy: comparison of three techniques by pathological substrate in 115 patients. J Neurosurg. 2004;100(2 Suppl Pediatrics):125–141. 2 Jonas R, Nguyen S, Hu B, et al. Cerebral hemispherectomy: hospital course, seizure, developmental, language, and motor outcomes. Neurology. 2004;62:1712–1721. 3 Harvey AS, Cross JH, Shinnar S, Mathern GW; ILAE Pediatric Epilepsy Surgery Taskforce. Defining the spectrum of international practice in pediatric epilepsy surgery patients. Epilepsia. 2008;49:146 –155. 4 de Bode S, Firestine A, Mathern GW, Dobkin B. Residual motor control and cortical representations of function following hemispherectomy: effects of etiology. J Child Neurol. 2005;20:64 –75. 5 DeLuca SC, Echols K, Ramey SL, Taub E. Pediatric constraint-induced movement therapy for a young child with cerebral palsy: two episodes of care. Phys Ther. 2003;83:1003–1013. 6 Gordon AM, Charles J, Wolf SL. Methods of constraint-induced movement therapy for children with hemiplegic cerebral palsy: development of a child-friendly intervention for improving upper-extremity function. Arch Phys Med Rehabil. 2005; 86:837– 844.

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CIMT in Individuals After Cerebral Hemispherectomy 7 Taub E, Uswatte G. Constraint-induced movement therapy: answers and questions after two decades of research. NeuroRehabilitation. 2006;21:93–95. 8 Taub E, Morris DM. Constraint-induced movement therapy to enhance recovery after stroke. Curr Atheroscler Rep. 2001; 3:279 –286. 9 Sterr A, Freivogel S, Schmalohr D. Neurobehavioral aspects of recovery: assessment of the learned nonuse phenomenon in hemiparetic adolescents. Arch Phys Med Rehabil. 2002;83:1726 –1731. 10 Taub E, Griffin A, Nick J, Gammons K, et al. Pediatric CI therapy for strokeinduced hemiparesis in young children. Dev Neurorehabil. 2007;10:3–18. 11 Gordon AM, Charles J, Wolf S. Methods of constraint-induced movement therapy for children with hemiplegic cerebral palsy: development of a child-friendly intervention for improving upper extremity function. Arch Phys Med Rehabil. 2005;86: 837– 844. 12 Fritz SL, Light KE, Clifford SN, et al. Descriptive predictors of outcomes following constraint-induced movement therapy for people after stroke. Phys Ther. 2006;86: 825– 832. 13 Charles J, Gordon AM. A critical review of constraint-induced movement therapy and forced use in children with hemiplegia. Neural Plast. 2005;12:245–261; discussion 263–272. 14 Karman N, Maryles J, Baker RW, et al. Constraint-induced movement therapy for hemiplegic children with acquired brain injuries. J Head Trauma Rehabil. 2003; 18:259 –267. 15 Page SJ, Sisto S, Johnston MV, Levine P. Modified constraint-induced therapy after subacute stroke: a preliminary study. Neurorehabil Neural Repair. 2002;16: 290 –295. 16 Sterr A, Elbert T, Berthold I, et al. Longer versus shorter daily constraint-induced movement therapy of chronic hemiparesis: an exploratory study. Arch Phys Med Rehabil. 2002;83:1374 –1377. 17 Kelly AMC, Garavan H. Human functional neuroimaging of brain changes associated with practice. Cereb Cortex. 2005;15: 1089 –1102.

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18 Dunn L. Peabody Picture Vocabulary Test (PPVT). Circle Pines, MN: American Guidance Service; 1981. 19 Fritz SL, Light KE, Patterson T, et al. Active finger extension predicts outcomes after constraint-induced movement therapy for individuals with hemiparesis after stroke. Stroke. 2005;36:1172–1177. 20 Gladstone DJ, Danells CJ, Black SE. The Fugl-Meyer Assessment of Motor Recovery After Stroke: a critical review of its measurement properties. Neurorehabil Neural Repair. 2002;16:232–240. 21 Mathiowetz V, Federman S, Wiemer D. Box and blocks test of manual dexterity: norms for 6 –19 year olds. Can J Occup Ther. 1985;52:241–245. 22 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. 23 Platz T, Pinkowski C, van Wijck F, et al. Reliability and validity of arm function assessment with standardized guidelines for the Fugl-Meyer Test, Action Research Arm Test and Box and Block Test: a multicentre study. Clin Rehabil. 2005;19:404 – 411. 24 FSL software. FMRIB Software Library, Release 3.2, University of Oxford. Available at: http://www.fmrib.ox.ac.uk/fsl/. 25 MRIcro(n) software. MRIcro Web site. Available at: http://www.sph.sc.edu/ comd/rorden/mricro.html. Accessed December 4, 2008. 26 de Bode S, Mathern GW, Bookheimer S, Dobkin B. Locomotor training remodels fMRI sensorimotor cortical activations in children after cerebral hemispherectomy. J Neurorehabil Neural Repair. 2007;20: 64 –73. 27 Sterr A, Freivogel S, Voss A. Exploring a repetitive training regime for upper limb hemiparesis in an in-patient setting: a report on three case studies. Brain Inj. 2002;16:1093–1107. 28 De Groot MH, Phillips SJ, Eskes GA. Fatigue associated with stroke and other neurologic conditions: implications for stroke rehabilitation. Arch Phys Med Rehabil. 2003;84:1714 –1720.

29 Staub F, Bogousslavsky J. Fatigue after stroke: a major but neglected issue. Cerebrovasc Dis. 2001;12:75– 81. 30 Williams PTJ, Gharbawie OA, Kolb B, Kleim JA. Experience-dependent amelioration of motor impairments in adulthood following neonatal medial frontal cortex injury in rats is accompanied by motor map expansion. Neuroscience. 2006;141: 1315–1326. 31 Johansen-Berg H, Dawes H, Guy C, et al. Correlation between motor improvements and altered fMRI activity after rehabilitative therapy. Brain. 2002;125:2731–2742. 32 Hamzei F, Liepert J, Dettmers C, et al. Two different reorganization patterns after rehabilitative therapy: an exploratory study with fMRI and TMS. Neuroimage. 2006; 31:710 –720. 33 Liepert J. Motor cortex excitability in stroke before and after constraint-induced movement therapy. Cogn Behav Neurol. 2006;19:41– 47. 34 Juenger H, Linder-Lucht M, Walther M, et al. Cortical neuromodulation by constraint-induced movement therapy in congenital hemiparesis: an fMRI study. Neuropediatrics. 2007;38:130 –136. 35 Eyre JA, Taylor JP, Villagra F. Evidence of activity-dependent withdrawal of corticospinal projections during human development. Neurology. 2001;57:1543–1554. 36 Holthausen H, Strobl K, Pieper T. Prediction of motor functions post hemispherectomy. In: Tuxhorn I, Holthausen H, Boenigk H, eds. Paediatric Epilepsy Syndromes and Their Surgical Treatment. London, United Kingdom: John Libbey; 1997:785–798. 37 Senesac C. Inter-rater and Intra-rater Reliability of the Pediatric Actual Amount of Use Test and the Pediatric Wolf Motor Function Test [master’s thesis]. Columbia, SC: Department of Exercise Science, School of Public Health, University of South Carolina; 2007.

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Perspective

Does Sleep Promote Motor Learning? Implications for Physical Rehabilitation Catherine F Siengsukon, Lara A Boyd CF Siengsukon, PT, PhD, is Research Assistant Professor, Department of Physical Therapy and Rehabilitation Science, University of Kansas Medical Center, 3901 Rainbow Blvd, Mail Stop 2002, Kansas City, KS 66160 (USA). Address all correspondence to Dr Siengsukon at: csiengsukon@ kumc.edu. LA Boyd, PT, PhD, is Assistant Professor and Canada Research Chair, University of British Columbia, Vancouver, British Columbia, Canada. [Siengsukon CF, Boyd LA. Does sleep promote motor learning? Implications for physical rehabilitation. Phys Ther. 2009;89: 370 –383.] © 2009 American Physical Therapy Association

Sleep following motor skill practice has repeatedly been demonstrated to enhance motor skill learning off-line (continued overnight improvements in motor skill that are not associated with additional physical practice) for young people who are healthy. Mounting evidence suggests that older people who are healthy fail to demonstrate sleep-dependent off-line motor learning. However, little is known regarding the influence of sleep on motor skill enhancement following damage to the brain. Emerging evidence suggests that individuals with brain damage, particularly following stroke, do benefit from sleep to promote off-line motor skill learning. Because rehabilitation following stroke requires learning new, and re-learning old, motor skills, awareness that individuals with stroke benefit from a period of sleep following motor skill practice to enhance skill learning could affect physical therapist practice. The objective of this article is to present the evidence demonstrating sleep-dependent off-line motor learning in young people who are healthy and the variables that may influence this beneficial sleep-dependent skill enhancement. In young people who are healthy, these variables include the stages of memory formation, the type of memory, the type of instruction provided (implicit versus explicit learning), and the task utilized. The neural mechanisms thought to be associated with sleep-dependent off-line motor learning also are considered. Research examining whether older adults who are healthy show the same benefits of sleep as do younger adults is discussed. The data suggest that older adults who are healthy do not benefit from sleep to promote off-line skill enhancement. A possible explanation for the apparent lack of sleep-dependent off-line motor learning by older adults who are healthy is presented. Last, emerging evidence showing that individuals with chronic stroke demonstrate sleep-dependent off-line motor skill learning and some of the possible mechanisms for this effect are considered.


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E

ach year, approximately 780,000 people in the United States experience a stroke,1 with more than half experiencing a persistent loss of function.2,3 Furthermore, stroke is a leading cause of disability in the United States.1 Stroke rehabilitation frequently includes learning new motor skills and re-learning old motor skills. As we do not completely understand how to best stimulate recovery of function through motor skill learning after stroke, research examining the mechanisms, procedures, or both that affect motor learning must be explored.

Mounting evidence demonstrates that sleep has an important role in motor learning and memory consolidation in young individuals who are healthy (defined as “neurologically intact” throughout this review) (see review articles4 –10). Memory consolidation refers to either the stabilization or the enhancement of a motor skill, referred to as off-line learning, through the passage of time without additional practice.11,12 Although some disagreement remains,13–17 sleep has been shown to enhance motor performance on a task “off-line” when no further physical practice has taken place.18 –22 Participants who sleep between practice and retention testing demonstrate improvements in task performance compared with participants who stay awake. This has been shown in a variety of simple motor skill tasks.18 –22 Sleep between practice and retention testing has resulted in a 20% overnight improvement in motor skill performance of a finger-tapping task19 and a 33% overnight improvement in performance of a finger-tothumb opposition task.22 A nap of 60 to 90 minutes has been demonstrated to be sufficient sleep to produce offline improvements in performance of motor tasks.23,24

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The role of sleep in off-line motor skill memory consolidation for young people who are healthy also may depend on other factors, including which stage of memory formation is considered, the type of memory being consolidated, whether instruction is provided (ie, implicit versus explicit learning), and the task. The manner in which sleepdependent off-line motor learning reconfigures neural circuits and the mechanisms underpinning the need for sleep to consolidate memories are questions currently under consideration. In this article, we will address each of the variables listed above that may affect sleepdependent off-line learning. Although sleep has been demonstrated to have an important role in off-line motor learning and memory consolidation in young people who are healthy, evidence suggests that sleep may not be critical for off-line motor learning in older people who are healthy.25–27 Changes in sleep architecture experienced by older people,28 –31 which may limit the potential benefits of sleep, are one likely explanation for the lack of sleep-related off-line motor learning in this group. Emerging evidence suggests that individuals with brain damage,32 particularly stroke,27,33 benefit from sleep to enhance offline motor skill learning. Individuals with damage to the prefrontal cortex demonstrated a reduction of nearly 14% in overnight response time on the serial reaction time (SRT) task.32 We recently found that people with stroke primarily in the middle cerebral artery distribution demonstrated a 12% overnight reduction in tracking error in an implicit version of a continuous tracking task and a 14% overnight reduction in error in an explicit version of the tracking task.27 We have proposed that people with chronic stroke may be able to capitalize on sleep architecture

changes that occur following stroke34,35 to experience sleepdependent skill enhancement. Based on our past and ongoing work, we believe that integration of sleep into clinical interventions may hasten recovery from stroke by allowing individuals to capitalize on sleepdependent off-line motor learning.

Sleep Overview Sleep is “defined behaviorally by four criteria: (1) reduced motor activity, (2) decreased response to stimulation, (3) stereotypic postures (in humans, for example, lying down with eyes closed), and (4) relatively easy reversibility (distinguishing it from coma, hibernation, and estivation).”36(p937) Sleep generally is classified into 2 different stages: non– rapid eye movement sleep (non-REM) and rapid eye movement (REM) sleep (Tab. 1). Non-REM sleep is divided into 4 characteristic substages corresponding to increasing depth of sleep, as shown using electroencephalograms (EEGs): stage 1 involves the transition from wakefulness to sleep and is characterized by sinusoidal alpha wave activity, stage 2 is characterized by sleep spindles and K complexes (clusters of lowand high-amplitude waves, respectively36), and stages 3 and 4 are grouped into slow-wave sleep (SWS) and are characterized by slow delta waves.36 Rapid eye movement sleep, also known as paradoxical sleep because the EEG pattern is similar to the normal awake pattern, is characterized by REMs, ponto-geniculooccipital spikes, and muscle atonia.36


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Sleep and Motor Learning Table 1. Summary of Sleep Stages Time Spenta (%) Type of Sleep Rapid eye movement

Characteristic Waveform From Electroencephalograms

Young Adults

Older Adults

Muscle atonia; rapid eye movements

Low-voltage, mixed-frequency pattern; ponto-geniculooccipital spikes

17–23

13–20

17

Slow rolling of eyes

Sinusoidal alpha wave activity (10 Hz)

3–7

7–12

13

Characteristic Activity

People With Stroke

Non-rapid eye movement Stage 1 Stage 2

Sleep spindles (12–14 Hz) and K complexes

45–55

39–55

61

Slow-wave sleep (stages 3 and 4)

High-amplitude slow delta waves (0.5–2 Hz)

19–25

5–16

5

a

25th–75th percentiles of sleep period times for 20-year-olds (young adults) and 60-year-olds (older adults) were derived from Danker-Hopfe et al.28 Average total sleep times for participants with chronic stroke (average age⫽49 years, range⫽18 –75 years) were derived from Vock et al.34

Adults fall asleep by entering nonREM sleep first, followed by REM sleep; these phases then alternate cyclically every 90 to 110 minutes through 4 to 6 cycles a night.36,37 The ratio of non-REM to REM sleep changes as the night progresses, with SWS being prevalent in the first half of the night and stage 2 non-REM and REM sleep dominating in the latter half of the night.37 Young adults spend the largest amount of sleep in stage 2 non-REM sleep, followed by REM sleep and SWS, with the least amount of time spent in stage 1 non-REM sleep (Tab. 1). Although a range of values is expected (as demonstrated by the 25th-75th percentile of sleep period time in Table 1 for a 20-year-old and a 60-year-old), aging individuals experience a reduction in total sleep time compared with young adults as well as decreased time spent in REM sleep and SWS,28,29 whereas the amount of time spent in stage 2 nonREM sleep remains fairly stable (Tab. 1).28 The decline in REM sleep begins around 50 years of age,28 whereas the reduction in SWS starts in adolescence and progresses with age.36 Older adults also experience a reduction in the number of sleep spindles,30,31 which are bursts of 372

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brain activity of 12 to 14 Hz38,39 occurring predominantly during stage 2 non-REM sleep. Based on the pattern of changes in sleep architecture with aging, we hypothesize that the normal evolution of sleep architecture associated with aging limits the ability of older adults who are healthy to benefit from sleepdependent off-line motor learning. Alterations in sleep patterns are a common experience for many people after stroke. Three to four months after the occurrence of stroke, nearly 60% of individuals experience insomnia.40 Sleep-wake disorders, such as insomnia, excessive daytime sleepiness or fatigue, or hypersomnia, are experienced by 20% to 40% of individuals following stroke and are attributable to a number of factors, including depression, sleep apnea, complications of the stroke, and medications.41 Following acute stroke, alterations in sleep architecture occur. These changes include a reduction in total sleep time and sleep efficiency as well as an increase in waking after the initiation of sleep.35,42,43 Reductions in REM sleep44 and stage 2 to 4 non-REM sleep42 also have been reported following acute stroke. Although the sleep parameters of people with

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chronic stroke are poorly characterized, evidence suggests sleep patterns may not normalize with a progression from acute to chronic stroke; 53% of people with chronic stroke (5–24 months poststroke; average age⫽49 years, range⫽18 –75 years; Tab. 1) showed different sleep EEG characteristics, including more time in stage 2 non-REM sleep while spending about the same amount of time in REM sleep,34 compared with published norms for a 49-year-old who was healthy.28 Furthermore, the number of sleep spindles increases from acute to chronic stroke.35 We propose that these changes in sleep characteristics actually enable people with chronic stroke to benefit from sleep and produce off-line motor skill learning.

Mechanisms Influencing Sleep-Dependent Off-line Motor Learning: Evidence From Young Adults Who Are Healthy Although sleep has been shown to promote off-line motor skill learning in young people who are healthy,18 –22 it appears that various factors may influence or interact with this beneficial effect of sleep. Each of these variables is discussed in more detail.

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Sleep and Motor Learning Stages of Memory Formation The role of sleep in motor learning likely depends on which stage of memory processing is being considered. Motor memory develops over time in at least 4 distinct stages (Tab. 2).45 The first stage is encoding or acquisition, when the memory is initially formed into a representation in the brain. This stage is followed by consolidation, when the memory is taken from a labile form and made more permanent. Walker and colleagues21,46 further divided consolidation into 2 different categories: stabilization and enhancement (Tab. 2). Stabilization refers to the maintenance of motor skill performance across time without further practice and is not dependent on sleep, whereas enhancement refers to an improvement in performance of a skill off-line and is thought to be dependent on the activity of sleep. The third step in motor memory processing is storage, when the memory is maintained in the brain over time. The final step is recall, when the motor memory is able to be brought out of storage for further use. Sleep may differentially affect each stage of motor memory processing, although consolidation appears to be the most frequently studied stage and may be the stage most affected by sleep. The permissive environment created during sleep allows the memory trace initially encoded during practice to be consolidated into a more-permanent form. This consolidated memory trace is thought to be fairly stable across time until recalled from memory during subsequent task practice. Following recollection, the motor memory is capable of being modified and is believed to undergo another period of consolidation (called “reconsolidation”) for that memory to again be placed into more-permanent storage. Reconsolidation also may be a sleep-dependent process, but more research is needed on this topic.10,47,48 April 2009

Table 2. Stages of Memory Formation Stage of Memory Formation

Description

Encoding

Memory representation formed

Consolidation

Memory becomes more permanent

Stabilization

Maintenance of motor skill performance off-line; not dependent on sleep

Enhancement

Improvement in performance of a skill off-line; sleep dependent

Storage

Maintenance of memory over time

Recall

Memory brought out of storage for use

Types of Memory The role of sleep in memory consolidation is thought to depend on the type of memory being considered. Typically, a memory is divided into 1 of 2 classifications: declarative memory, if the memory can be recalled consciously, such as memories of facts and events, and nondeclarative memory, if the memory cannot be recalled consciously, such as a memory of skill performance (ie, riding a bicycle).49,50 Procedural memory is a subset of nondeclarative memory and is assessed through the testing of motor skills.49 Declarative and procedural memories differ not only in the ability to consciously recall the memory but also in the brain areas involved supporting these memories. Declarative learning and memory depend on the integrity of the medial temporal lobe,51,52 whereas procedural learning and memory are supported by moredistributed neural circuits, including the sensorimotor cortex, the cerebellum, and the basal ganglia.53–55 Due to the distributed brain areas supporting procedural memory, it is much less likely that brain damage, such as stroke, would completely abolish procedural learning. There is some agreement among researchers concerning which stage of sleep is important for the consolidation of a certain memory types; however, several discrepancies persist. Two different theories explain the

role of the various sleep stages on the consolidation of different memory traces. These are the dualprocess theory and the sequential hypothesis, with recent studies56,57 showing increased support for the latter. According to the dual-process theory, a single sleep stage (ie, REM sleep or SWS) acts on and, therefore, is necessary to form distinct memory traces (ie, procedural versus declarative), depending on which memory system that trace is from.6 According to the sequential hypothesis, memories are consolidated through the ordered sequence of non-REM sleep followed by REM sleep, so that both stages of sleep are necessary for consolidation.58 In reality, these 2 theories are not mutually exclusive in that both non-REM and REM sleep stages are important for memory consolidation, but some memory traces may require more SWS (ie, declarative memory), whereas other memory traces may require more stage 2 non-REM or REM sleep (ie, procedural memory).6 Although some conflict remains, current consensus indicates that SWS is important for declarative memory consolidation. For example, declarative memory of word list recall59,60 was facilitated by periods of early nocturnal sleep, which corresponds to SWS. Other research demonstrates that REM sleep is important for consolidating declarative memories, such as for the learning of a

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Sleep and Motor Learning foreign language.61 The discrepancy of which stage of sleep is important for the consolidation of declarative memory may result from differences in the type of memory being formed. Episodic memory (memory of events) and semantic memory (memory of facts), both types of declarative memory, appear to require different stages of sleep for consolidation; semantic memory may require REM sleep to consolidate, whereas episodic memory may require anywhere from one to all stages of sleep.6 Wagner et al62 suggested that REM sleep is important for the consolidation of declarative memory that has an emotional content, but emotionally neutral declarative memory does not seemingly benefit significantly from sleep. Procedural memory likely requires stage 2 non-REM sleep,59,60,63,64 REM sleep,59,60,65 or both for consolidation. Overnight improvement in the performance of a finger-tapping task was found to correlate with the amount of stage 2 non-REM sleep,19 whereas overnight improvement in a similar sequential finger-to-thumb opposition task correlated with the amount of REM sleep.22 Another factor to consider is the cognitive requirement of the skill being learned, with less cognitively taxing procedural skills benefiting from stage 2 non-REM sleep and more cognitively involved procedural tasks benefiting from REM sleep for consolidation.66 Another interesting caveat in the determination of which stage of sleep is important for procedural memory consolidation is the initial skill level of the learner; REM sleep is important when the motor skill to be learned is entirely novel, whereas stage 2 non-REM sleep is beneficial for learning if some degree of ability is already present and the motor skill is being refined.67 Another explanation for discrepancies regarding which sleep cycle is important for consolidation of partic374

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ular types of memories centers on the need for an ordered sleep cycle (sequential hypothesis58). Stickgold et al56 and Gais et al57 demonstrated that performance of a visual discrimination task was enhanced following the ordered sequence of SWS followed by REM sleep. These behavioral data provide support for the sequential hypothesis of ordered non-REM sleep followed by REM sleep to stimulate memory consolidation. In summary, memories are likely consolidated through the repeated pattern of non-REM sleep followed by REM sleep, with SWS being more important for declarative memory consolidation and stage 2 non-REM sleep, REM sleep, or both being more important for procedural memory consolidation. However, many other variables such as the emotional content of the memory, the cognitive load of the task, and the initial skill level of the learner appear to affect which stage of sleep is critical for declarative and procedural memory consolidation. Future studies should seek to clarify the role of the various sleep stages in procedural and declarative memory consolidation. Type of Instruction Another factor to consider when examining the role of sleep in off-line procedural motor learning and memory consolidation is the type of instruction a person receives prior to practicing a skill. Explicit learning occurs when the individual is aware of the regularities of the skill being learned. Explicit instruction can be provided prior to task practice (ie, when a therapist informs a patient of the steps required to stand up from a chair), or a patient can gain explicit awareness during physical task practice (ie, when the patient becomes consciously aware of the steps needed to stand up from a chair through practice without instruction). Implicit learning occurs without the awareness of the task regu-

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larities (ie, the patient “figures out” how to stand up from a chair without being consciously aware of each of the steps involved). When the influence of sleep is not considered, explicit instruction either may aid68 –70 or may inhibit71–73 procedural learning in people who are healthy, depending on the nature of the instruction74,75 and the task.71,76 The type of instruction delivered to young people who are healthy appears to influence whether off-line motor learning is related to sleep or simply the passage of time. In a study by Robertson et al,77 young participants who were healthy and who practiced a sequential motor task implicitly (ie, had no awareness of the sequence being practiced) demonstrated performance improvements both following sleep and after a similar length of time being awake. In contrast, if participants were provided explicit instruction regarding the practiced sequence, off-line motor skill enhancement occurred only following a period of sleep. These findings indicate that for young people who are healthy, implicit motor memory consolidation occurs off-line simply with the passage of time (whether or not this time includes sleep), whereas explicit motor memory consolidation occurs off-line only during sleep.77 Concurrent evidence supports the hypothesis that explicit memories and awareness are preferentially enhanced off-line during sleep.78 – 80 It is possible that the implicit and explicit memory systems interact or compete with one another during learning and memory consolidation. In a study by Wagner et al,81 participants who slept between practicing a sequence and undergoing retention testing demonstrated an improved ability to detect a hidden rule compared with participants who did not sleep during the intervening interval. However, sleep resulted in a significant decrease in reaction time April 2009

Sleep and Motor Learning only in those participants who did not discover the hidden rule. These findings suggest that explicit memory is enhanced at the expense of implicit memory for this particular task,82 which would support the theory that different memory systems interact during formation.83 It is possible that off-line implicit motor skill learning appears to be timedependent because sleep enhances only certain aspects of an implicit motor task (ie, motor, spatial, or temporal parameters), which may be masked when overall off-line skill learning is considered. Evidence, however, does support this contention. Off-line enhancement of the spatial regularities of an implicit motor task were shown to be dependent on sleep following practice, whereas learning of the motor pattern was enhanced off-line through the passage of time without sleep.84 These findings demonstrate that particular components of an implicit motor memory may be enhanced offline through different mechanisms; some components may require sleep for off-line enhancement, whereas other components simply rely on the passage of time.85 In summary, mounting evidence demonstrates that explicit learning and memory are enhanced off-line by sleep. Discrepancies persist regarding whether sleep or the passage of time produces off-line consolidation of an implicit motor task. However, the lack of apparent sleep-dependent off-line learning of implicit motor tasks may be due to the fact that only certain components of an implicit motor skill are enhanced by sleep, and the enhancement of certain components may be masked by a lack of overall task improvement. Type of Task The beneficial effect of sleep on motor learning and memory consolidaApril 2009

tion also may be reliant on the type of procedural task being considered. Two important classifications for motor tasks are discrete and continuous skills. Discrete skills are movements with an obvious beginning and end, such as throwing a ball or reaching for a cup, whereas continuous skills, such as walking or knitting, do not have an obvious start or finish.86 Although the distinction between discrete and continuous tasks is useful to classify research tasks, these classifications frequently are less defined in the clinic, where more-complicated, “real-life” tasks are utilized. Studies to date examining the influence of sleep in off-line motor performance enhancement in young people who are healthy have used only discrete tasks during practice, including a finger-to-thumb opposition task,19 –22,78,87 a sequential finger-tapping task,77,86,88,89 and the SRT task.70,71,90 –92 Recent evidence demonstrates that although sleep enhances performance of a number of simple discrete tasks, sleep may not benefit all kinds of discrete tasks; a probabilistic version of the SRT task was not enhanced off-line by a night of sleep.93 Due to the variations in task requirements, continuous and discrete tasks utilize different mechanisms of motor control. Because discrete tasks often are performed rapidly and without time for feedback, these types of skills likely rely on a motor program, whereas continuous tasks, which are performed for a longer period of time, likely depend on feedback to make corrective movements as necessary online.86 Furthermore, continuous tasks often are more complex than discrete tasks. A review by Wulf and Shea94 concluded that the factors influencing learning of simple motor skills do not automatically apply to complex motor skill learning due to the additional degrees of freedom. Therefore, although evidence strongly

supports sleep-dependent off-line learning of discrete tasks, it remains to be determined whether the beneficial influence of sleep on off-line skill enhancement will generalize to a continuous task in young people who are healthy. One study demonstrated that more-complex motor tasks produced greater sleepdependent off-line motor learning.95 Perhaps “real-life” complex motor tasks, such as those conducted during rehabilitation following brain injury, may benefit even more from sleep to produce off-line motor skill enhancement. This supposition remains to be determined by future research.

Neuroimaging and Sleep-Dependent Off-line Learning Neuroimaging techniques have determined that the same areas of the brain activated during acquisition of a motor skill are reactivated during REM sleep.96,97 Reactivation during sleep may lead to changes in functional couplings of neural circuits and the modification of synaptic connections that were established during acquisition of the motor skill, both of which may lead to sleepdependent off-line learning.97,98 However, none of these studies examined whether reactivation occurred during non-REM sleep, leaving it unclear whether the pattern of REM sleep followed by non-REM sleep works to shift brain activity. Functional magnetic resonance imaging has been used to elucidate changes in the representation of motor memory following sleep in young people who are healthy, with certain areas of the brain demonstrating increased activity following sleep and other areas demonstrating reduced activity.87,99 These studies provide insight into the widespread changes in brain activity associated with offline sleep-dependent motor memory

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Sleep and Motor Learning consolidation in young adults who are healthy.

Neural Mechanisms of Sleep-Dependent Memory Consolidation Sleep is thought to provide a permissive environment that promotes various cellular and molecular mechanisms that enable the consolidation of memories. The various mechanisms include activity of neuroendocrine molecules, gene transcription, and protein synthesis.47,100,101 An increase in acetylcholine and a decrease in serotonin during REM sleep in rodents have been shown to facilitate protein synthesis and longterm potentiation (LTP) in the hippocampus.102 Furthermore, the unique electrophysiological events of both REM sleep (ie, ponto-geniculo-occipital spikes) and non-REM sleep (ie, sleep spindles) are thought to play a role in long-term synaptic potentiation.5,101 In particular, sleep spindles, which are characteristic of stage-2 non-REM sleep, have been demonstrated to play an important role in sleepdependent memory improvement.23,66,103 Sleep spindles are hypothesized to depolarize the postsynaptic membrane, resulting in a large influx of calcium ions that leads to a cascade of cellular events; these events result in gene expression and protein synthesis necessary for LTP of the postsynaptic membrane.46,101 The “replaying” of a memory during sleep is thought to result in a functional coupling of the synapses, leading to LTP of the neural circuit responsible for that memory trace. Ribeiro and Nicolelis104 proposed that reactivation of the neural circuits associated with a memory trace occurs during SWS, whereas the expression of genes necessary for remodeling of the circuit, and thus

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memory storage, occurs during REM sleep. The “synaptic homeostasis hypothesis”105 proposes a very different role for SWS. This hypothesis suggests that the purpose of SWS is to downscale the synaptic connections formed during awake learning, making neural connections more efficient. Studies using in vivo recordings of neural activity frequently are conducted in animals because of obvious limitations in the ability to conduct these studies in humans. Furthermore, many animal studies examining the role of sleep or sleep deprivation in learning utilize “hippocampus-dependent” learning paradigms in rats; these learning paradigms may be very different from procedural learning in humans, which is not thought to rely on the integrity of the hippocampus. Therefore, although the animal studies provide very important insight into the cellular and molecular underpinnings of sleep-dependent memory consolidation, there currently is a void between the physiological findings from the animal studies and the behavioral findings in humans.106

Sleep-Dependent Off-line Learning in Older Adults Who Are Healthy The majority of studies to date examining sleep-dependent off-line performance enhancement have been conducted using young people who are healthy. Furthermore, the variables affecting the beneficial role of sleep (ie, the type of instruction provided) have largely been examined with young participants who are healthy. In recent years, emerging work demonstrates that older people who are healthy do not benefit from sleep to enhance motor learning. Older adults failed to demonstrate sleep-dependent off-line enhancement of both explicit and implicit versions of a procedural sequence

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learning task,25 a declarative memory word-pair association task,26 or explicit and implicit versions of a continuous tracking task.27,33 We examined whether specific components of movement on a continuous tracking task (ie, spatial component, temporal component, or both) were differentially enhanced by sleep but perhaps masked by an overall lack of off-line performance enhancement. However, this does not appear to be the case; in our work, older people who were healthy failed to demonstrate off-line sleep-dependent improvements of either spatial tracking accuracy (Fig. 1A) or time lag of tracking (a measure of temporal accuracy; Fig. 1B) of a continuous tracking task.107 Therefore, older adults who are healthy fail to benefit from sleep to promote off-line memory enhancement, regardless of the type of memory examined (procedural or declarative), the type of instruction provided (implicit or explicit), or the type of task utilized (discrete SRT task or continuous tracking task). We propose that the changes in sleep architecture often demonstrated by older individuals limit the potential benefits of sleep. With normal aging, people typically experience a reduction in the total time spent in a sleep state as well as a reduction in the time spent in REM sleep and SWS,28,29 whereas time spent in stage 2 non-REM sleep appears to remain consistent (Tab. 1).28 Older individuals also frequently experience a reduction in the number of sleep spindles.30,31 Evidence suggests that stage 2 non-REM sleep,19 REM sleep,22 or both are associated with consolidation of simple motor tasks off-line for young people who are healthy. In particular, sleep spindles, which are a characteristic component of stage 2 non-REM sleep, are thought to be an important mechanism of sleep-dependent off-line memory improvement.23,66,103 We April 2009


Figure 1. Older adults who were healthy failed to demonstrate significant off-line learning between the last practice block and the retention block of either (A) spatial tracking accuracy (a negative score indicates less spatial tracking error at retention compared with the last block of practice) or (B) time lag of tracking (a positive score indicates improved time lag of tracking at retention [less lag] compared with the last block of practice) of the continuous tracking task. Error bars are standard error of measurement. (Reprinted with permission of Sage Journals from: Siengsukon CF, Boyd LA. Sleep enhances off-line spatial and temporal motor learning after stroke. Neurorehabil Neural Repair. In press.)

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Sleep and Motor Learning hypothesize that older adults fail to demonstrate sleep-dependent offline motor learning because they experience a reduction in both the time spent in REM sleep and the number of sleep spindles. If the hypothesis that older adults who are healthy do not demonstrate sleep-dependent off-line motor learning due to changes in their sleep characteristics is correct, it would follow that altering the sleep characteristics of older adults may enable these individuals to benefit from sleep to enhance off-line motor learning; indeed, this has been demonstrated to be true. Increased time spent in REM sleep, greater REM density, and decreased REM latency through the use of sleep-aid medication were correlated with enhanced performance of older adults on a word-recall task.108 If REM sleep is important for promoting off-line motor learning, as suggested by the findings of Fischer and colleagues’ study of young people who were healthy,22 the findings of the study by Schredl et al108 suggest that older individuals may benefit from sleep to enhance off-line learning if underlying changes in sleep architecture are addressed. No apparent attempts were made by Schredl et al to relate other sleep stages or characteristics such as stage 2 non-REM sleep or sleep spindle activity with performance improvement; therefore, potential benefits of modifying these sleep parameters in older adults via medication or other means remain to be determined.

Sleep-Dependent Off-line Learning After Stroke There is little doubt that individuals following stroke are able to learn new motor skills.109 –113 People were able to learn an implicit motor skill following a lesion in the middle cerebral artery distribution affecting the sensorimotor cortex69 and the basal ganglia,70 but providing them with explicit instruction disrupted 378

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implicit learning. However, the role of sleep in off-line motor learning or the sleep characteristics of study participants had never been directly considered until recently.27,33,107 Emerging evidence has demonstrated that people with brain injury benefit from sleep to enhance offline motor learning. In a recent study by Gomez Beldarrain et al,32 individuals with damage to the prefrontal cortex due to stroke, tumor, or trauma demonstrated sleep-dependent offline learning of a finger sequencing task. Our research suggests that people with chronic stroke benefit from sleep to enhance motor skill learning of both implicit and explicit versions of a continuous tracking task.27,33 We also have demonstrated that sleep promotes off-line motor learning through both improved spatial tracking accuracy (Fig. 2A) and anticipation of upcoming movements (a measure of temporal tracking error; Fig. 2B) in people with chronic stroke.107 Therefore, the few studies to date examining the importance of sleep in promoting off-line motor skill learning suggest that individuals with damage to the brain benefit from sleep to enhance off-line learning of both discrete motor tasks32 and continuous motor tasks,27,33 regardless of type of instruction provided (ie, sleep enhanced both implicit and explicit versions of a continuous tracking task),27,33 and learning of both the spatial and temporal components of a tracking task.107 Because the studies that demonstrate sleep-dependent off-line motor learning in people with chronic stroke were not conducted in a sleep laboratory, we can only hypothesize what mechanisms enabled these individuals to benefit from sleep. One hypothesis is that individuals with stroke are able to capitalize on changes in sleep architecture that occur following chronic stroke to promote off-line motor learning

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(Tab. 1). However, little is known regarding sleep architecture in people with chronic stroke. One study34 demonstrated that more than half of the participants with chronic stroke experienced alterations in sleep architecture compared with normative data.28 Individuals with chronic stroke spent about the same amount of time in REM sleep but more time in stage 2 non-REM sleep34 compared with published norms.28 Furthermore, the number of sleep spindles increases from acute to chronic stroke.35 We propose that the alterations in sleep architecture demonstrated by people with chronic stroke (the ability to maintain adequate amounts of REM sleep, increase stage 2 non-REM sleep,34 and increase sleep spindle activity35) enables them to demonstrate sleep-dependent skill enhancement. Much work utilizing sleep laboratories is needed to evaluate EEG data and better understand the potential alterations in sleep architecture demonstrated by individuals with chronic stroke to support our suppositions. Another potential explanation for why people with chronic stroke demonstrate sleep-dependent offline motor skill learning is that study participants performed the tracking task using their less-affected upper extremity.27,33,107 Using the lessaffected upper extremity would correspond primarily with neuronal activity in the nonlesioned hemisphere of the brain. Studies using transcranial magnetic stimulation demonstrated that transcollosal inhibition present in a healthy brain is reduced following stroke,114,115 which can result in hyperexcitability of the nonlesioned hemisphere.116,117 This, we hypothesize, may create a permissive environment for sleepdependent off-line memory consolidation in the stroke-damaged brain. Future work is needed to confirm this contention. Regardless of the mechanism, it appears that people April 2009


Figure 2. Participants with stroke demonstrated sleep-dependent off-line learning between the last practice block and the retention block for both (A) spatial tracking accuracy (a negative score indicates less spatial tracking error at retention compared with the last block of practice) and (B) time lag of tracking (a positive score indicates improved time lag of tracking at retention [less lag] compared with the last block of practice) of the continuous tracking task. Error bars are standard error of measurement. Asterisk indicates significance. (Reprinted with permission of Sage Journals from: Siengsukon CF, Boyd LA. Sleep enhances off-line spatial and temporal motor learning after stroke. Neurorehabil Neural Repair. In press.)

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Sleep and Motor Learning after a stroke benefit from sleepdependent off-line motor learning to further enhance skill acquisition. This offers a promising and novel opportunity that may be exploited by rehabilitation specialists to speed or enhance recovery of function after stroke. Studies demonstrating sleepdependent off-line motor learning in individuals with chronic stroke who used their less-affected upper extremity to perform the task raise the following question: Would sleepdependent off-line motor learning be observed if the more-affected upper extremity is used for practice? At this point, it is unclear whether altered hemispheric excitability affects the patterns of sleep or its effect on motor learning. Because motor practice increases hemispheric excitability,118,119 it may be that the effects of motor practice would prepare the lesioned hemisphere to benefit from sleep. Alternately, because studies using transcranial magnetic stimulation have demonstrated that stroke increases the threshold for motor excitability in the lesioned hemisphere,120 –125 it is possible that the benefits of sleep would be negated by the high motor threshold. These 2 competing theories should be addressed in future studies.

Clinical Applications Because stroke is a leading cause of long-term adult disability in the United States and Canada, it is imperative that any factor that could potentially improve recovery and enhance function for this group of people should be explored. In addition, because of the large number of people with stroke who have sleep alterations, understanding the role of sleep in off-line motor learning and memory consolidation in the damaged brain has tremendous implications for rehabilitation.

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Evidence to date suggests that people with chronic stroke demonstrate sleep-dependent off-line motor learning of both implicit and explicit versions of a continuous sequencing task.27,33 Furthermore, sleep enhances both spatial and temporal movement components of a continuous tracking task after stroke.107 This effect is unique to stroke; age- and sex-matched controls who were healthy did not experience sleep- or time-dependent off-line motor learning on either version of the tracking task and did not show off-line learning of the spatial or temporal movement components of the task.27,33,107 To exploit these findings for the benefit of individuals with stroke, sleep should be encouraged between therapy sessions to promote off-line learning of the skill practiced during therapy. Therapy may need to be conducted later in the day or in the evening prior to sleeping, or a nap following a therapy session may need to be encouraged. Furthermore, adequate sleep following stroke may need to be ensured by providing a quiet environment to sleep while in the hospital, reducing sleep disturbances and addressing potential sleep-limiting conditions that frequently occur following stroke, such as sleep apnea, depression, and medication side effects. The findings that sleep enhances offline learning of a continuous tracking task following chronic stroke27,33 provide the first evidence that sleep affects off-line learning of a continuous task; until recently, only the role of sleep in discrete tasks had been considered. These findings have important clinical implications, considering many of the movements performed during daily life and activities being learned or re-learned following stroke include movements that are continuous in nature, such as walking.

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Evidence that sleep enhances both the spatial and temporal components of a movement following chronic stroke107 suggests that therapists should incorporate activities that practice both of these components with these individuals. For example, practicing placing a cup on a cupboard of differing heights would emphasize the spatial component of this arm reaching task, whereas practicing the task in various sequences (ie, taking the cup out of the dishwasher and placing it on the cupboard versus washing the cup, drying the cup, and then placing it on the cupboard) would allow patients to anticipate the upcoming cup placing to emphasize the temporal component of the task. Although recent studies have demonstrated sleep-dependent off-line motor learning following damage to the brain,32 including chronic stroke,27,33,107 many questions remain unanswered. Future studies should assess whether these findings will generalize to a clinically relevant activity, such as walking or bed mobility. Research is needed to determine the neural mechanisms that allow individuals following stroke to benefit from sleep to promote offline motor learning. Additional evidence is needed to determine why older adults who are healthy fail to demonstrate sleep-dependent off-line motor learning and whether normalizing sleep parameters through mechanisms such as medications can induce sleep-dependent skill enhancement. Despite these unanswered questions, therapists should consider encouraging sleep following therapy sessions as well as promoting healthy sleep in their patients with chronic stroke to promote off-line motor learning of the skills practiced during rehabilitation. Both authors provided concept/idea/research design, writing, data collection, data analysis, project management, fund procurement, subjects, and facilities/equip-

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Sleep and Motor Learning ment. Dr Boyd provided institutional liaisons, clerical/secretarial support, and consultation (including review of manuscript before submission). This work was supported by funds awarded to Dr Siengsukon from the Foundation for Physical Therapy and funds awarded to Dr Boyd from the North Growth Foundation, the Vancouver Coastal Health Research Institute and Foundation, and the Heart and Stroke Foundation of British Columbia. This article was submitted October 1, 2008, and was accepted December 29, 2008. DOI: 10.2522/ptj.20080310

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14 Siegel JM. The REM sleep-memory consolidation hypothesis. Science. 2001; 294(5544):1058 –1063. 15 Vertes RP, Siegel JM. Time for the sleep community to take a critical look at the purported role of sleep in memory processing. Sleep. 2005;28:1228 –1229; discussion 1230 –1223. 16 Keisler A, Ashe J, Willingham DT. Time of day accounts for overnight improvement in sequence learning. Learn Mem. 2007;14:669 – 672. 17 Rickard TC, Cai DJ, Rieth CA, et al. Sleep does not enhance motor sequence learning. J Exp Psychol Learn Mem Cogn. 2008;34:834 – 842. 18 Korman M, Raz N, Flash T, Karni A. Multiple shifts in the representation of a motor sequence during the acquisition of skilled performance. Proc Natl Acad Sci USA. 2003;100:12492–12497. 19 Walker MP, Brakefield T, Morgan A, et al. Practice with sleep makes perfect: sleepdependent motor skill learning. Neuron. 2002;35:205–211. 20 Walker MP, Brakefield T, Seidman J, et al. Sleep and the time course of motor skill learning. Learn Mem. 2003;10:275–284. 21 Walker MP, Brakefield T, Hobson JA, Stickgold R. Dissociable stages of human memory consolidation and reconsolidation. Nature. 2003;425(6958):616 – 620. 22 Fischer S, Hallschmid M, Elsner AL, Born J. Sleep forms memory for finger skills. Proc Natl Acad Sci USA. 2002;99: 11987–11991. 23 Nishida M, Walker MP. Daytime naps, motor memory consolidation and regionally specific sleep spindles. PLoS ONE. 2007;2:e341. 24 Backhaus J, Junghanns K. Daytime naps improve procedural motor memory. Sleep Med. 2006;7:508 –512. 25 Spencer RM, Gouw AM, Ivry RB. Agerelated decline of sleep-dependent consolidation. Learn Mem. 2007;14: 480 – 484. 26 Backhaus J, Born J, Hoeckesfeld R, et al. Midlife decline in declarative memory consolidation is correlated with a decline in slow wave sleep. Learn Mem. 2007;14:336 –341. 27 Siengsukon CF, Boyd LA. Sleep to learn after stroke: implicit and explicit off-line motor learning. Neurosci Lett. 2009;451:1–5. 28 Danker-Hopfe H, Schafer M, Dorn H, et al. Percentile reference charts for selected sleep parameters for 20- to 80year-old healthy subjects from the SIESTA database. Somnolgie. 2005;9:3–14. 29 Buckley TM, Schatzberg AF. Aging and the role of the HPA axis and rhythm in sleep and memory-consolidation. Am J Geriatr Psychiatry. 2005;13:344 –352. 30 Crowley K, Trinder J, Kim Y, et al. The effects of normal aging on sleep spindle and K-complex production. Clin Neurophysiol. 2002;113:1615–1622.

31 Nicolas A, Petit D, Rompre S, Montplaisir J. Sleep spindle characteristics in healthy subjects of different age groups. Clin Neurophysiol. 2001;112:521–527. 32 Gomez Beldarrain M, Astorgano AG, Gonzalez AB, Garcia-Monco JC. Sleep improves sequential motor learning and performance in patients with prefrontal lobe lesions. Clin Neurol Neurosurg. 2008;110:245–252. 33 Siengsukon CF, Boyd LA. Sleep enhances implicit motor skill learning in individuals poststroke. Top Stroke Rehabil. 2008;15:1–12. 34 Vock J, Achermann P, Bischof M, et al. Evolution of sleep and sleep EEG after hemispheric stroke. J Sleep Res. 2002;11: 331–338. 35 Gottselig JM, Bassetti CL, Achermann P. Power and coherence of sleep spindle frequency activity following hemispheric stroke. Brain. 2002;125(pt 2):373–383. 36 Rechtschaffen A, Siegel J. Sleep and dreaming. In: Kandel ER, Schwartz JH, Jessell TM, eds. Principles of Neural Science. 4th ed. New York, NY: McGrawHill; 2000:936 –947. 37 Huether SE, McCance KL. Understanding Pathophysiology. 3rd ed. St Louis, MO: CV Mosby Inc; 2004. 38 De Gennaro L, Ferrara M. Sleep spindles: an overview. Sleep Med Rev. 2003;7: 423– 440. 39 Jankel WR, Niedermeyer E. Sleep spindles. J Clin Neurophysiol. 1985;2:1–35. 40 Leppavuori A, Pohjasvaara T, Vataja R, et al. Insomnia in ischemic stroke patients. Cerebrovasc Dis. 2002;14:90 –97. 41 Bassetti CL. Sleep and stroke. Semin Neurol. 2005;25:19 –32. 42 Bassetti CL, Aldrich MS. Sleep electroencephalogram changes in acute hemispheric stroke. Sleep Med. 2001;2: 185–194. 43 Muller C, Achermann P, Bischof M, et al. Visual and spectral analysis of sleep EEG in acute hemispheric stroke. Eur Neurol. 2002;48:164 –171. 44 Giubilei F, Iannilli M, Vitale A, et al. Sleep patterns in acute ischemic stroke. Acta Neurol Scand. 1992;86:567–571. 45 Kandel ER, Kupfermann I, Iversen S. Learning and memory. In: Kandel ER, Schwartz JH, Jessell TM, eds. Principles of Neural Science. 4th ed. New York, NY: McGraw-Hill; 2000:1227–1246. 46 Walker MP. A refined model of sleep and the time course of memory formation. Behav Brain Sci. 2005;28:51– 64; discussion 64 –104. 47 Alberini CM. Mechanisms of memory stabilization: are consolidation and reconsolidation similar or distinct processes? Trends Neurosci. 2005;28:51–56. 48 Stickgold R, Walker MP. Sleep-dependent memory consolidation and reconsolidation. Sleep Med. 2007;8:331–343. 49 Squire LR. Mechanisms of memory. Science. 1986;232(4758):1612–1619.

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Sleep and Motor Learning 50 Squire LR. Memory systems of the brain: a brief history and current perspective. Neurobiol Learn Mem. 2004;82: 171–177. 51 Squire LR, Stark CE, Clark RE. The medial temporal lobe. Annu Rev Neurosci. 2004;27:279 –306. 52 Squire LR, Zola SM. Structure and function of declarative and nondeclarative memory systems. Proc Natl Acad Sci USA. 1996;93:13515–13522. 53 Doyon J, Penhune V, Ungerleider LG. Distinct contribution of the corticostriatal and cortico-cerebellar systems to motor skill learning. Neuropsychologia. 2003;41:252–262. 54 Hikosaka O, Nakamura K, Sakai K, Nakahara H. Central mechanisms of motor skill learning. Curr Opin Neurobiol. 2002;12:217–222. 55 Hikosaka O, Nakahara H, Rand MK, et al. Parallel neural networks for learning sequential procedures. Trends Neurosci. 1999;22:464 – 471. 56 Stickgold R, Whidbee D, Schirmer B, et al. Visual discrimination task improvement: A multi-step process occurring during sleep. J Cogn Neurosci. 2000;12: 246 –254. 57 Gais S, Plihal W, Wagner U, Born J. Early sleep triggers memory for early visual discrimination skills. Nat Neurosci. 2000; 3:1335–1339. 58 Giuditta A, Ambrosini MV, Montagnese P, et al. The sequential hypothesis of the function of sleep. Behav Brain Res. 1995;69:157–166. 59 Plihal WB, Born J. Effects of early and late noctural sleep on declarative and procedural memory. J Cogn Neurosci. 1997;9: 534 –547. 60 Plihal WB, Pietrowsky R, Born J. Dexamethasone blocks sleep induced improvement of declarative memory. Psychoneuroendocrinology. 1999;24:313–331. 61 De Koninck J, Lorrain D, Christ G, et al. Intensive language learning and increases in rapid eye movement sleep: evidence of a performance factor. Int J Psychophysiol. 1989;8:43– 47. 62 Wagner U, Gais S, Born J. Emotional memory formation is enhanced across sleep intervals with high amounts of rapid eye movement sleep. Learn Mem. 2001;8:112–119. 63 Smith C. Sleep states and memory processes. Behav Brain Res. 1995;69: 137–145. 64 Smith C, MacNeill C. Impaired motor memory for a pursuit rotor task following Stage 2 sleep loss in college students. J Sleep Res. 1994;3:206 –213. 65 Karni A, Tanne D, Rubenstein BS, et al. Dependence on REM sleep of overnight improvement of a perceptual skill. Science. 1994;265(5172):679 – 682. 66 Fogel SM, Smith CT, Cote KA. Dissociable learning-dependent changes in REM and non-REM sleep in declarative and procedural memory systems. Behav Brain Res. 2007;180:48 – 61.

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67 Peters KR, Smith V, Smith CT. Changes in sleep architecture following motor learning depend on initial skill level. J Cogn Neurosci. 2007;19:817– 829. 68 Willingham DB, Goedert-Eschmann K. The relation between implicit and explicit learning: Evidence for parallel development. Psychological Science. 1999;10:531–534. 69 Boyd LA, Winstein CJ. Impact of explicit information on implicit motor-sequence learning following middle cerebral artery stroke. Phys Ther. 2003;83:976 –989. 70 Boyd LA, Winstein CJ. Providing explicit information disrupts implicit motor learning after basal ganglia stroke. Learn Mem. 2004;11:388 –396. 71 Shea CH, Wulf G, Whitacre CA, Park JH. Surfing the implicit wave. Q J Exp Psychol A. 2001;54:841– 862. 72 Green TD, Flowers JH. Comparison of implicit and explicit learning processes in a probabilistic task. Percept Mot Skills. 2003;97:299 –314. 73 Green TD, Flowers JH. Implicit versus explicit learning processes in a probabilistic, continuous fine-motor catching task. J Mot Behav. 1991;23:293–300. 74 Magill RA. 1997 C. H. McCloy Research Lecture: Knowledge is more than we can talk about: implicit learning in motor skill acquisition. Res Q Exerc Sport. 1998; 69:104 –110. 75 Reber AS, Kassin SM, Lewis S, Cantor G. On the relationship between implicit and explicit modes in the learning of a complex rule structure. J Exp Psychol Hum Learn Mem. 1980;6:492–502. 76 Boyd LA, Quaney BM, Pohl PS, Winstein CJ. Learning implicitly: effects of task and severity after stroke. Neurorehabil Neural Repair. 2007;21:444 – 454. 77 Robertson EM, Pascual-Leone A, Press DZ. Awareness modifies the skill-learning benefits of sleep. Curr Biol. 2004; 14:208 –212. 78 Fischer S, Drosopoulos S, Tsen J, Born J. Implicit learning: explicit knowing: a role for sleep in memory system interaction. J Cogn Neurosci. 2006;18:311–319. 79 Drosopoulos S, Wagner U, Born J. Sleep enhances explicit recollection in recognition memory. Learn Mem. 2005;12: 44 –51. 80 Spencer RM, Sunm M, Ivry RB. Sleepdependent consolidation of contextual learning. Curr Biol. 2006;16:1001–1005. 81 Wagner U, Gais S, Haider H, et al. Sleep inspires insight. Nature. 2004; 427(6972):352–355. 82 Born J, Wagner U. Awareness in memory: being explicit about the role of sleep. Trends Cogn Sci. 2004;8:242–244. 83 Poldrack RA, Packard MG. Competition among multiple memory systems: converging evidence from animal and human brain studies. Neuropsychologia. 2003;41:245–251.

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84 Cohen DA, Pascual-Leone A, Press DZ, Robertson EM. Off-line learning of motor skill memory: a double dissociation of goal and movement. Proc Natl Acad Sci USA. 2005;102:18237–18241. 85 Robertson EM, Cohen DA. Understanding consolidation through the architecture of memories. Neuroscientist. 2006; 12:261–271. 86 Schmidt RA, Lee TD. Motor Control and Learning: A Behavioral Emphasis. 3rd ed. Champaign, IL: Human Kinetics Inc; 1999. 87 Walker MP, Stickgold R, Alsop D, et al. Sleep-dependent motor memory plasticity in the human brain. Neuroscience. 2005;133:911–917. 88 Maquet P, Schwartz S, Passingham R, Frith C. Sleep-related consolidation of a visuomotor skill: brain mechanisms as assessed by functional magnetic resonance imaging. J Neurosci. 2003;23: 1432–1440. 89 Pew RW. Levels of analysis in motor control. Brain Res. 1974;71:393– 400. 90 Wulf G, Schmidt RA. Variability of practice and implicit motor learning. J Exp Psychol Learn Mem Cogn. 1997;23: 987–1006. 91 Boyd LA, Winstein CJ. Explicit information interferes with implicit motor learning of both continuous and discrete movement tasks after stroke. J Neurol Phys Ther. 2006;30:46 –57. 92 Boyd LA, Winstein CJ. Cerebellar stroke impairs temporal but not spatial accuracy during implicit motor learning. Neurorehabil Neural Repair. 2004;18:134 –143. 93 Song S, Howard JH Jr, Howard DV. Sleep does not benefit probabilistic motor sequence learning. J Neurosci. 2007;27: 12475–12483. 94 Wulf G, Shea CH. Principles derived from the study of simple skills do not generalize to complex skill learning. Psychon Bull Rev. 2002;9:185–211. 95 Kuriyama K, Stickgold R, Walker MP. Sleep-dependent learning and motor-skill complexity. Learn Mem. 2004;11: 705–713. 96 Maquet P, Laureys S, Peigneux P, et al. Experience-dependent changes in cerebral activation during human REM sleep. Nat Neurosci. 2000;3:831– 836. 97 Peigneux P, Laureys S, Fuchs S, et al. Learned material content and acquisition level modulate cerebral reactivation during posttraining rapid-eye-movements sleep. NeuroImage. 2003;20:125–134. 98 Laureys S, Peigneux P, Phillips C, et al. Experience-dependent changes in cerebral functional connectivity during human rapid eye movement sleep. Neuroscience. 2001;105:521–525. 99 Fischer S, Nitschke MF, Melchert UH, et al. Motor memory consolidation in sleep shapes more effective neuronal representations. J Neurosci. 2005;25: 11248 –11255. 100 Dang-Vu TT, Desseilles M, Peigneux P, Maquet P. A role for sleep in brain plasticity. Pediatr Rehabil. 2006;9:98 –118.

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Sleep and Motor Learning 101 Benington JH, Frank MG. Cellular and molecular connections between sleep and synaptic plasticity. Prog Neurobiol. 2003;69:71–101. 102 Graves L, Pack A, Abel T. Sleep and memory: a molecular perspective. Trends Neurosci. 2001;24:237–243. 103 Fogel SM, Smith CT. Learning-dependent changes in sleep spindles and Stage 2 sleep. J Sleep Res. 2006;15:250 –255. 104 Ribeiro S, Nicolelis MA. Reverberation, storage, and postsynaptic propagation of memories during sleep. Learn Mem. 2004;11:686 – 696. 105 Tononi G, Cirelli C. Sleep function and synaptic homeostasis. Sleep Med Rev. 2006;10:49 – 62. 106 Frank MG, Benington JH. The role of sleep in memory consolidation and brain plasticity: dream or reality? Neuroscientist. 2006;12:477– 488. 107 Siengsukon CF, Boyd LA. Sleep enhances off-line spatial and temporal motor learning after stroke. Neurorehabil Neural Repair. In press. 108 Schredl M, Weber B, Leins ML, Heuser I. Donepezil-induced REM sleep augmentation enhances memory performance in elderly, healthy persons. Exp Gerontol. 2001;36:353–361. 109 Pohl PS, McDowd JM, Filion DL, et al. Implicit learning of a perceptual-motor skill after stroke. Phys Ther. 2001;81: 1780 –1789. 110 Winstein CJ, Merians AS, Sullivan KJ. Motor learning after unilateral brain damage. Neuropsychologia. 1999;37:975–987.

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111 Platz T, Denzler P, Kaden B, Mauritz KH. Motor learning after recovery from hemiparesis. Neuropsychologia. 1994;32: 1209 –1223. 112 Hanlon RE. Motor learning following unilateral stroke. Arch Phys Med Rehabil. 1996;77:811– 815. 113 Pohl PS, McDowd JM, Filion D, et al. Implicit learning of a motor skill after mild and moderate stroke. Clin Rehabil. 2006;20:246 –253. 114 Shimizu T, Hosaki A, Hino T, et al. Motor cortical disinhibition in the unaffected hemisphere after unilateral cortical stroke. Brain. 2002;125(pt 8): 1896 –1907. 115 Liepert J, Hamzei F, Weiller C. Motor cortex disinhibition of the unaffected hemisphere after acute stroke. Muscle Nerve. 2000;23:1761–1763. 116 Traversa R, Cicinelli P, Pasqualetti P, et al. Follow-up of interhemispheric differences of motor evoked potentials from the “affected” and “unaffected” hemispheres in human stroke. Brain Res. 1998;803:1– 8. 117 Cicinelli P, Traversa R, Rossini PM. Poststroke reorganization of brain motor output to the hand: a 2– 4 month follow-up with focal magnetic transcranial stimulation. Electroencephalogr Clin Neurophysiol. 1997;105:438 – 450. 118 Sawaki L, Butler AJ, Xiaoyan L, et al. Constraint-induced movement therapy results in increased motor map area in subjects 3 to 9 months after stroke. Neurorehabil Neural Repair. 2008;22: 505–513.

119 Liepert J, Bauder H, Wolfgang HR, et al. Treatment-induced cortical reorganization after stroke in humans. Stroke. 2000;31:1210 –1216. 120 Catano A, Houa M, Caroyer JM, et al. Magnetic transcranial stimulation in acute stroke: early excitation threshold and functional prognosis. Electroencephalogr Clin Neurophysiol. 1996;101: 233–239. 121 Traversa R, Cicinelli P, Oliveri M, et al. Neurophysiological follow-up of motor cortical output in stroke patients. Clin Neurophysiol. 2000;111:1695–1703. 122 Koski L, Mernar TJ, Dobkin BH. Immediate and long-term changes in corticomotor output in response to rehabilitation: correlation with functional improvements in chronic stroke. Neurorehabil Neural Repair. 2004;18:230 –249. 123 Rossini PM, Pauri F. Neuromagnetic integrated methods tracking human brain mechanisms of sensorimotor areas “plastic” reorganisation. Brain Res Brain Res Rev. 2000;33:131–154. 124 Talelli P, Greenwood RJ, Rothwell JC. Arm function after stroke: neurophysiological correlates and recovery mechanisms assessed by transcranial magnetic stimulation. Clin Neurophysiol. 2006; 117:1641–1659. 125 Liepert J, Restemeyer C, Kucinski T, et al. Motor strokes: the lesion location determines motor excitability changes. Stroke. 2005;36:2648 –2653.

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Perspective

Delaying Mobility Disability in People With Parkinson Disease Using a Sensorimotor Agility Exercise Program Laurie A King, Fay B Horak LA King, PT, PhD, is Post-doctoral Fellow, Oregon Health and Sciences University, Portland, Oregon. FB Horak, PT, PhD, is Research Professor of Neurology and Adjunct Professor of Physiology and Biomedical Engineering, Department of Neurology, Oregon Health and Sciences University, West Campus, Building 1, 505 NW 185th Ave, Beaverton, OR 97006-3499 (USA). Address all correspondence to Dr Horak at: [email protected]. [King LA, Horak FB. Delaying mobility disability in people with Parkinson disease using a sensorimotor agility exercise program. Phys Ther. 2009;89:384 –393.]

This article introduces a new framework for therapists to develop an exercise program to delay mobility disability in people with Parkinson disease (PD). Mobility, or the ability to efficiently navigate and function in a variety of environments, requires balance, agility, and flexibility, all of which are affected by PD. This article summarizes recent research identifying how constraints on mobility specific to PD, such as rigidity, bradykinesia, freezing, poor sensory integration, inflexible program selection, and impaired cognitive processing, limit mobility in people with PD. Based on these constraints, a conceptual framework for exercises to maintain and improve mobility is presented. An example of a constraint-focused agility exercise program, incorporating movement principles from tai chi, kayaking, boxing, lunges, agility training, and Pilates exercises, is presented. This new constraint-focused agility exercise program is based on a strong scientific framework and includes progressive levels of sensorimotor, resistance, and coordination challenges that can be customized for each patient while maintaining fidelity. Principles for improving mobility presented here can be incorporated into an ongoing or long-term exercise program for people with PD.

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A Sensorimotor Agility Exercise Program for People With Parkinson Disease

M

ost people who are diagnosed with Parkinson disease (PD) do not consult with a physical therapist until they already have obvious mobility problems. However, it is possible that a rigorous exercise program that focuses on anticipated problems, which are inevitable with progression of the disease, may help patients who do not yet exhibit mobility problems. Although there are excellent guidelines for physical therapists to treat patients with PD who exhibit mobility problems in order to improve or maintain their mobility,1,2 there is little research on whether exercise may delay or reduce the eventual mobility disability in patients diagnosed with PD.

The major cause of disability in people with PD is impaired mobility.3 Mobility, the ability of a person to move safely in a variety of environments in order to accomplish functional tasks,4 requires dynamic neural control to quickly and effectively adapt locomotion, balance, and postural transitions to changing environmental and task conditions. Such dynamic control requires sensorimotor agility, which involves coordination of complex sequences of movements, ongoing evaluation of environmental cues and contexts, the ability to quickly switch motor programs when environmental conditions change, and the ability to maintain safe mobility during multiple motor and cognitive tasks.5,6 The types of mobility deficits inevitable with the progression of PD suggest


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that the basal ganglia are critical for sensorimotor agility.2 Critical aspects of mobility disability in people with PD, such as postural instability, are unresponsive to pharmacological and surgical therapies,7 making preventative exercise an attractive option. As yet, there is no known ongoing exercise program for people diagnosed with PD that focuses on maintaining or improving their agility to slow or reduce their decline in mobility. This article uses the known sensorimotor impairments of PD that affect balance, gait, and postural transitions to develop a conceptual framework to design exercises that aim to delay disability and maintain or improve mobility in people with PD. This framework is based on the current knowledge of the neurophysiology of PD and the inevitable constraints on mobility resulting from basal ganglia degeneration. The scientifically based principles presented here, which are focused on mobility disorders in people with PD, can be incorporated into an existing therapy program for people with PD. Based on this framework, this article also presents an example of a novel sensorimotor agility program that we are currently testing in a clinical trial. This program is unique in that it encourages a partnership among physical therapists, exercise trainers, and patients to set up, progress, and reevaluate an exercise program that ultimately can be carried out independently in the community. It is likely that a mobility program, such as the one presented here, would need to be sustained and modified throughout the course of the disease to maintain maximal benefit.

Why Exercise May Prevent or Delay Mobility Disability in People With PD Exciting new findings in neuroscience regarding the effects of exercise on neural plasticity and neuroprotection of the brain against neural degeneration suggest that an intense exercise program can improve brain function in patients with neurological disorders. Specifically, animal studies have demonstrated neurogenesis,8 an increase in dopamine synthesis and release,9 and increased dopamine in the striatum following acute bouts of exercise.10 Such changes in the brain may affect behavioral recovery as a result of neuroplasticity (the ability of the brain to make new synaptic connections), neuroprotection, and slowing of neural degeneration.11,12 Studies with parkinsonian rats have suggested that chronic exercise may help reverse motor deficits in animals by changing brain function. Specifically, rats that ran on a treadmill showed preservation of dopaminergic cell bodies and terminals11,13 associated with improved running distance and speed,12 indicating a neuroprotective effect of exercise. Conversely, nonuse of a limb induced by casting in parkinsonian rats increased motor deficits as well as loss of dopaminergic terminals.11 Aerobic exercise, such as treadmill training and walking programs, has been tested in individuals with PD and has been shown to improve gait parameters, quality of life, and levadopa efficacy.14 –16 However, it is not clear whether aerobic training, by itself, is the best approach to improving mobility, which depends upon dynamic balance, dual tasking, negotiating complex environments, quick changes in movement direction, and other sensorimotor skills affected by PD. It is possible that treadmill training, for example, could be even more effective for addressing complex mobility issues for people with

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A Sensorimotor Agility Exercise Program for People With Parkinson Disease PD if the therapist could incorporate tasks such as dual tasking, balance training, and set-switching into a treadmill program.

challenges into a comprehensive exercise program directed at delaying and reducing mobility problems in individuals with PD.

There currently are many untested exercise programs available for people with PD17–19 as well as several randomized controlled studies that test specific exercises, such as strength (force-generating capacity) training or gait training.20 –29 The approach presented in this article is focused on exercises that challenge sensorimotor control of dynamic balance and gait to improve mobility in people with PD. There are many other aspects of PD that also must be addressed in rehabilitation.

Reduce Mobility Constraints With Exercise

Drive Neuroplasticity With Task-Specific Agility Exercise Studies in rats have demonstrated that task-specific agility training (eg, acrobatic, environmental enrichmenttype, high-beam balance course) results in larger improvements in motor skills as well as larger changes in synaptic plasticity than simple, repetitive aerobic training such as running on treadmills.30 –35 Task-specific exercise also has been shown to be more effective than aerobic or general exercise to improve task performance in patients with stroke.36,37 Task-specific exercises targeted at a single, specific balance or gait impairment in patients with PD have been shown to be effective. For example, exercises targeted at improving small step size, poor axial mobility, difficulty with postural transitions, small movement amplitude, or slow speed of compensatory stepping have individually been shown to be effective in improving each particular aspect of mobility.18,22,38 – 42 We have borrowed singular techniques from several successful programs and combined them with task-specific components of mobility and systematic sensorimotor

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People with mild or newly diagnosed PD often do not have obvious muscle weakness or poor balance.43 Nevertheless, the literature suggests that muscle weakness, secondary to abnormal muscle activation associated with bradykinesia and rigidity, can be present at all stages of PD.44 – 47 Similarly, balance and mobility problems may be present in people with mild PD but only become apparent when more-complex coordination is required under challenging conditions.48,49 For example, mobility problems may only be apparent when an individual with PD is attempting to walk quickly in a cluttered environment while talking on a cell phone. As the disease progresses, balance problems become more apparent, just as patients begin to show impaired kinesthesia and inability to quickly change postural strategies.50,51 The basal ganglia affect balance and gait by contributing to automaticity, self-initiated gait and postural transitions, changing motor programs quickly, sequencing actions, and using proprioceptive information for kinesthesia and multisegmental coordination.52–54 During the progression of PD, mobility is progressively constrained by rigidity, bradykinesia, freezing, sensory integration, inflexible motor program selection, and attention and cognition.2 Table 1 summarizes constraints on mobility due to PD, the impact of these constraints on mobility, and the goals of exercises that could potentially reduce the impact of each constraint.

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Constraints Affecting Mobility in People With PD, With Implications for the Sensorimotor Agility Program Rigidity Parkinsonian rigidity is characterized by an increased resistance to passive movement throughout the entire range of motion, in both agonist and antagonist muscle groups.55–57 The functional outcomes of rigidity, in general, include a flexed posture,58 lack of trunk rotation,59,60 and reduced joint range of movement during postural transitions and gait.56,61 Electromyography studies have shown that people with PD have high tonic background activity, especially in the flexors, and cocontraction of muscles during movement, especially in the axial muscles.56,57 In addition, antagonist muscle activation is larger and earlier, resulting in coactivation of muscle groups during automatic postural responses.61 Another characteristic of parkinsonian rigidity is axial rigidity, which results in a loss of natural vertebral, pelvis/shoulder girdle, and femur/ pelvis flexibility and range of motion that accompanies efficient postural and locomotor activities.60,62 Wright et al55 found that rigidity in the neck, torso, and hips of standing subjects was 3 to 5 times greater in subjects with PD than in age-matched control subjects when measuring the torsional resistance to passive movement along the longitudinal axis during twisting movements. Levodopa medication did not improve their axial rigidity.55 The high axial tone (velocity-dependent resistance to stretch) in patients with PD contributes to their characteristic “en bloc” trunk motions, which make it difficult for them to perform activities such as rolling over in bed or turning while walking.62

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A Sensorimotor Agility Exercise Program for People With Parkinson Disease Table 1. Parkinsonian Constraints Affecting Mobility and Exercise Principles Designed to Reduce These Constraintsa Constraints

a

Impact on Mobility

Exercise Principles

I. Rigidity

Agonist/antagonist co-contraction Flexed alignment of trunk Reduced trunk rotation Reduced joint range of movement High axial tone (stiffness)

Trunk rotation Reciprocal movements Rhythmic movements Erect alignment Large CoM movements Increase limits of stability

II. Bradykinesia

Slow, small movements Narrow base of support Lack of arm swing

Fast, large steps CoM control Large arm swings

III. Freezing

Poor anticipatory postural adjustments Abnormal mapping of body and movement Abnormal visual-spatial maps Divided attention affects mobility

Improve weight shifting Understand role of external cues Exercise in small spaces Practice dual tasks

IV. Inflexible program selection (sequential coordination)

Poor rolling, sit-to-stand maneuvers, turns Difficult floor transfers Inability to change strategy quickly

Plan task in advance Quick change strategies Sequencing components of task

V. Impaired sensory integration

Inaccurate without vision Imbalance on unstable surface Poor alignment with environment

Kinesthetic awareness Decrease surface dependence Flexible orientation

VI. Reduced executive function and attention

Difficulty with dual tasks and sequences of actions

Practice gait and balance with secondary task and sequences of actions (ie; boxing, agility course)

CoM⫽center of mass.

Schenkman et al63 showed that exercise can increase trunk flexibility in people with PD. We propose an agility program that includes movements that minimize agonistantagonist muscle co-contraction (ie, reciprocal movements), promote axial rotation, lengthen the flexor muscles, and strengthen the extensor muscles to promote an erect posture. Rigidity can potentially be addressed with kayaking, an exercise in which the person counter-rotates the shoulder and pelvic girdle; tai chi, a set of exercises that focuses on the individual’s awareness of postural alignment during postural transitions; and pre-Pilates, a series of exercises aimed at increasing spinal mobility and lengthening flexor muscles groups. In addition, the program should include strategies for turning and transitioning from a standing position to sitting on the floor and back again that emphasize trunk and head rotation (Tabs. 2 and 3).18

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Bradykinesia Bradykinesia is most commonly defined as slowness of voluntary movement,43 but it also is associated with slow and weak postural responses to perturbations and anticipatory postural adjustments. Reactive postural responses to surface translations61,64 and anticipatory postural movements prior to rising onto toes65 and prior to step initiation66 are bradykinetic in patients with PD. Bradykinetic voluntary stepping and postural compensatory stepping are characterized by a delayed time to lift the swing limb, a weak push-off, reduced leg lift, a small stride length, and lack of arm swing.61,64,66,67 Bradykinesia also is apparent in reduced voluntary and reactive limits of stability, especially in the backward direction.64,68 The characteristic narrow stance of patients with PD may be compensatory for bradykinetic anticipatory postural adjustments prior to a step, at the expense of reduced lateral postural stability.67,69 Bradykinetic postural

responses in people with PD generally are not improved by antiparkinsonian medications, highlighting the need for an exercise approach to this constraint on mobility.6 Bradykinesia also is seen in postural transitions such as turning70 and the supine-to-stand manuever,59 as well as in single-joint movements71 and multi-joint reaching movements72 in people with PD. Bradykinesia is evident in slowed rate of increase and decrease of muscle activation patterns.73 Reduction in muscle strength in people with PD has been attributed primarily to reduced cortical drive to muscles because voluntary contraction, but not muscle response to nerve stimulation, is weak in these individuals.74,75 Electromyographic activity in bradykinetic muscles often is fractionated into multiple bursts and is not well scaled for changes in movement distance or velocity.71 Years of bradykinesia from abnormal, centrally driven muscle control and abnormal, inefficient pat-

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A Sensorimotor Agility Exercise Program for People With Parkinson Disease Table 2. Representative Agility Exercise Program, With Progressions Exercise

Actions

Progressions

I. Tai chi: Increase limits of stability, improve perception of posture and coordination of arms and legs and backward and lateral large steps

Prayer wheel: anterior-posterior slow, rhythmical weight shifts coordinated with large arm circles Cat walk: slow and purposeful steps, with diagonal weight shifts Cloud hands: slow lateral steps, with trunk vertical Part the wild horse’s mane: coordination of arms and legs while walking forward Repulsing the monkey: deliberate slow, backward walking, with diagonal weight shifts

Learn one action per week, starting with weight shifting and leg placement and progressing to coordinated arm, neck, and torso motion

II. Kayaking: Trunk rotation, segmental coordination, speed

Kayaking stroke: diagonal trunk rotation, with reciprocal forward arm extension and backward arm retraction

Speed, surface, resistance, vision, dual task

III. Agility course: Agility, multisegmental coordination, quick changes in direction, and mobility in tight spaces

High knees: high-amplitude stepping, with hand slapping knees Lateral shuffle: quick, lateral steps Tire course: wide-based, quick and high steps, with turns Grapevine cross: over coordinated steps

Speed, dual task, quick change in directions, tight and cluttered spaces, vision

IV. Boxing: Anticipatory postural adjustments, postural corrections, fast arm and foot motions, backward walking, timing, sequencing actions

Jab: short, straight punch from shoulder Cross: power punch, with trunk rotation, leading arm crosses midline Hook: short, lateral punch, with elbow bent and wrist twisted inward, trunk rotation Combinations: 2 or more punches delivered quickly after one another

Speed, dual task, walking forward, walking backward, turns, remembered sequences of action

V. Lunges: Big steps, stepping for postural correction, limits of stability, quick changes in direction, internal representation of body

Postural correction: lean until center of mass is outside base of support, requiring a step; all directions Single multidirectional steps (clock stepping) Dynamic multidirectional lunge walking

Surface (up and down stool), external cues, vision, resistance, dual task (add arm movements or cognitive task)

VI. Pre-Pilates: Improve trunk control, axial rotation and extension, functional transitions, sequencing actions

Cervical range of motion, sit-to-stand maneuver Floor transfer, supine (bridging) Rolling (prone lying, progress to spinal extension exercises) Quadruped (bird-dog, cat-camel, thread the needle) Half-kneeling to stand

Improve form and speed

terns of muscle recruitment limit functional mobility and eventually may result in focal muscle weakness. Because bradykinesia is due to impaired central neural drive, rehabilitation to reduce bradykinesia should focus on teaching patients to increase the speed, amplitude, and temporal pacing of their self-initiated and reactive limb and body centerof-mass (CoM) movements. Table 2 presents representative exercises aimed at reducing bradykinesia for mobility. These exercises may promote weight-shift control and postural adjustments in anticipation of voluntary movements such as 388

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lunges, kicks, and quick boxing movements. Patients also practice taking large, protective steps while tilting past their limits of stability and in response to external displacements associated with hitting or punching a boxing bag. To reduce bradykinesia, patients should be encouraged to “think big”42 while increasing the speed and amplitude of large arm and leg movements throughout agility courses and during multidirectional lunges and boxing (Tabs. 2 and 3). Walking sticks may help patients attend to the large, symmetrical arm swing that is coordinated with strides during gait.

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Freezing Freezing of gait manifests as a movement hesitation in which a delay or complete inability to initiate a step occurs.76 Freezing not only slows walking, but it also is a major contributor to falls in people with PD.77 It is a poorly understood phenomenon that is associated with executive disorders in people with PD.76,78 Freezing during gait occurs more often when a person is negotiating a crowded environment or narrow doorway, when making a turn, or when attention is diverted by a secondary task.77,79 Jacobs and Horak80 recently found that freezing or “start hesitation” in step initiation is assoApril 2009

A Sensorimotor Agility Exercise Program for People With Parkinson Disease Table 3. Progressions for Each Activity A. Kayaking: Kayaking focuses on counter-rotation of shoulder and pelvic girdle and axial trunk rotation. Level

Surface

Vision

Resistance

Normal, well-lit room

Holding pole

Dual Task

1

Sit on a chair

Counting

2

Sit on DynaDisca

Sunglasses

3-lb pole

Verbal: make a list

3

Stand on firm surface

No-body glasses

6-lb pole

Verbal/cognitive: math

B. Agility course: The agility course includes turns, doorways, hallways, and small areas. The tasks include high knees walking with hands touching knees, skipping, lateral shuffles, grapevine, and tire course. Advanced individuals may add agility on an inclined surface and bouncing or tossing a ball. Level

Speed/Agility

Arms and Trunk (High Knees and Tire Course Only)

Dual Task

1

Self-paced

Count steps out loud

Self-selected

2

Increase speed

Motor task: toss ball between hands

Reciprocal arms

3

Quick changes in direction, pace, stop and go

Cognitive task: math

Add head and trunk rotation

C. Boxing: The boxing task includes simple to complex combinations involving jabs, hooks, and crosses. Level

Plane of Movement

Speed

Dual Task

1

Lateral stance to the bag

Self-paced

Count punches

2

Pivot with back foot

Bursts of speed: combo punches for 15 s

Name punches (hook, jab, cross)

3

Walk backward around bag

Bursts of speed: combo punches for 30 s

Cognitive task while maintaining pattern

D. Lunges: Three types of lunges use these progressions: (1) lunges for postural correction, (2) clock stepping (multidirectional, in-place) lunges, and (3) dynamic lunges during locomotion.

Level

a

Surface

External Cue

Vision

Resistance

Arms and Trunk (Dynamic Lunges Only)

Dual Task

1

Firm surface

Rubber discs designate foot placement

Well-lit room

None

None

None

2

One foot on compliant surface (DynaDisc/ foam mat)

Decrease disc size or number

Sunglasses

Weight vest (start with 10% of body weight)

Motor task: trunk

Use arms reciprocally

3

Foam mat (both feet)

No discs

No-body glasses

Increase vest weight, 5% of body weight increments

Verbal or cognitive

Lift arms over head while holding ball

DynaDisk manufactured by Exertools Inc, 320 Professional Center Dr, #100, Rohnert Park, CA 94928.

ciated with repetitive, anticipatory, lateral weight shifts and that people who are healthy can be made to “freeze” when they do not have time to preplan which foot to use when initiating a compensatory or voluntary step. Therefore, freezing may be related to difficulties in shifts of attention, preplanning movement strategies, or quickly selecting a correct central motor program. To help people in the early stages of PD reduce their chances of being April 2009

affected by freezing, agility exercises should be performed in environments in which freezing typically occurs. As shown in Tables 2 and 3, exercises that involve high stepping, skipping, or taking large steps in different directions through doorways and over and around obstacles, such as between chairs placed shoulderwidth apart, could potentially reduce freezing episodes. Quick turns should be practiced in corners and near walls. Individuals with PD could perform these exercises in the home

or gym, where obstacle courses have been set up that require turning quickly, negotiating narrow and tight spaces such as corners, ducking under and stepping over obstacles, picking up objects while walking, and quickly changing directions and foot placement. Once a person successfully performs the agility exercises on an obstacle course, moreadvanced progressions could be introduced, such as performing dual cognitive tasks while maintaining form and speed on agility tasks.

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A Sensorimotor Agility Exercise Program for People With Parkinson Disease Inflexible Program Selection and Poor Sequential Coordination Research suggests that the basal ganglia play an important role in task switching, motor program selection, and suppression of irrelevant information before executing an action.52 The inability to quickly switch motor programs has been demonstrated in individuals with PD by an inability to change postural response synergies in the first perturbation trial after a change in support, change in instructions, or change in perturbation direction.51,81 Dopamine replacement does not improve inflexible program selection.82,83 The difficulty with switching motor programs manifests in difficulty maneuvering in new and challenging environments and in changes in postural transitions, such as turning, standing from a sitting position, and rolling over.84 In addition to difficulty switching motor programs, people with PD have difficulty sequencing motor actions.65,85,86 Patients with PD show a delay between their anticipatory postural adjustments and voluntary movements, such as rising onto toes65 or a voluntary step.66 These findings suggest that mobility in people with PD is constrained by poor coordination among body parts and between voluntary movements and their associated postural adjustments, as well as by difficulty in switching motor programs appropriate for changes in task constraints. Consequently, an exercise program should include complex, multisegmental, whole-body movements and should include tasks requiring quick selection and sequencing of motor programs such as practicing postural transitions (eg, moving from stance to the floor, rolling, and arising from the floor to stance). As shown in Table 2, one such exercise approach is tai chi, which helps patients to learn increasingly complex sequences of movement and to focus on smooth timing and synchroniza390

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tion of whole-body movements. Incorporating boxing actions into a remembered sequence is another way to practice the quick selection and sequencing of complex motor programs for mobility. To address problems of quick program selection, lunges and agility exercises also provide practice changing motor strategies during stopping, starting, changing direction, changing stepping limb, and changing the size and placement of steps. Sensory Integration There is strong evidence that the basal ganglia are critical for highlevel integration of somatosensory and visual information necessary to form an internal representation of the body and the environment.87,88 Despite clinical examinations of patients with PD revealing only inconsistent, subtle signs of abnormal sensory perception,89,90 an increasing number of studies are showing abnormal kinesthesia and use of proprioception in people with PD. For example, Wright et al55 and Horak et al64 found that individuals with PD have an impaired ability to detect the rotation of a surface or the passive rotation of the torso and that this poor kinesthesia is worsened by levodopa medication. Individuals with PD also show impaired perception of arm position and movement and decreased response to muscle vibration.91–93 The poor use of proprioceptive information and decreased perception of movement are associated with over-estimation of body motion (bradykinesia) and over-dependence on vision.50,94 To facilitate use of proprioceptive information and reduce overreliance on vision, an agility program should progress balancing and walking tasks by: (1) wearing dark sunglasses to reduce visual contrast sensitivity and (2) use of “no body” glasses to obscure the bottom half of the visual field so the body cannot be

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seen. In addition, many of the exercises can be performed on a variety of surfaces to require adaptation to altered somatosensory information from the surface. External feedback and sensory cues from the therapist regarding quality and size of the movements should be used initially and progressively decreased as patients develop a more accurate internal sense of body position. As shown in Table 3, the sensorimotor agility program used as an example in this article progresses with traditional progressive challenges95 (increasing resistance, speed of gait, endurance, and so on) and with sensorimotor challenges (dual tasking and changes in base of support, visual input, and surface conditions). Cognitive Constraints The inability to simultaneously carry out a cognitive task and a balance or walking task has been found to be a predictor of falls in elderly people.96 It is even more difficult for a person with PD than age-matched elderly people to perform multiple tasks,86 possibly because the basal ganglia are responsible for allowing automatic control of balance and gait and for switching attention between tasks.52,86 Postural sway increases most in individuals with PD who have a history of falls when a cognitive task is added to the task of quiet stance.97 These findings suggest that the ability to carry out a secondary cognitive or motor tasks while walking or balancing is a critical element of mobility that is a particular challenge in people with PD. An agility program could progress task difficulty by adding cognitive or motor tasks that teach patients with PD to maintain postural stability during performance of secondary tasks. Table 3 presents exercises in which it is safe and appropriate to add a dual cognitive or motor task. The exercises at level 1 have no dual tasks, level 2 has a motor task (eg, April 2009

A Sensorimotor Agility Exercise Program for People With Parkinson Disease bouncing a ball) added to the basic exercise such as an agility course, and level 3 has a cognitive task (eg, performing math or memory problems) added to the same basic exercise. The progression of adding secondary tasks to gait and balance tasks serves as a training device as well as a tool to help patients understand the relationship between safe mobility and secondary tasks in everyday life.

A Sensorimotor Agility Program for People With PD In this article, we propose a novel sensorimotor agility program targeted at constraints on mobility in people with PD. The expertise that contributed to the program includes an internationally recognized neurologist specializing in movement disorders for more 35 years and 5 physical therapists experienced in treating people with PD, including 3 with PhDs with a focus on PD. Six certified athletic trainers who regularly work with people with PD also were helpful in designing the program. We propose that the exercise program outlined in Table 2 could last 60 minutes, with about 10 minutes for each category of exercise. The exercises in the 6 categories were selected to target one or more of the constraints on mobility (Tab. 1). Although not all people with PD have all of the constraints addressed in this article, it may be that exercise should target all of these constraints, as each constraint generally is associated with the progression of PD and eventually has a marked effect on mobility. Addressing constraints early may delay the onset of related mobility deficits. Category I, “tai chi,” is a whole-body exercise that focuses on developing a sense of body kinesthesia, improving postural alignment, and sequencing of whole-body movements that move the CoM. Category II, “kayaking,” focuses on trunk and

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cervical rotation and speed, with large, coordinated arm movements. Category III, “agility course,” focuses on quickly changing motor programs such as quick turns, sequencing actions, and overcoming freezing. Category IV, “boxing,” focuses on building the patient’s agility and speed, backward walking, and components of anticipatory and reactive postural adjustments in response to a moving bag. Category V, “lunges,” helps patients with PD practice large CoM movements, multidirectional limits of stability, and steps for postural correction. Category VI, “pre-Pilates,” is a set of exercises that help patients with PD extend and strengthen the spine, as well as practice postural transitions such as sit-to-stand maneuvers, floor transfers, and rolling.18 The sensorimotor progressions of exercises II through V follow 3 levels of difficulty (Tab. 3). Progressions include: (1) reducing the base of support, (2) increasing surface compliance to reduce surface somatosensory information for postural orientation, (3) increasing speed or resistance with weights, (4) adding secondary cognitive tasks to automate posture and gait, and (5) limiting visual input of the body with “no body” glasses or of the environment with dark sunglasses to increase use of kinesthetic information. Category I (tai chi) and category Vl (prePilates) exercises progress by increasing the length of remembered sequences and improving the form of each subcomponent of the movements. All of these sensorimotor progressions were chosen specifically to target the predictable constraints on mobility due to PD, and testing of the program is currently under way.

Summary We present a progressive sensorimotor agility exercise program for prevention of mobility disability in people with PD. The program is based on the role of the basal ganglia in

posture and gait, the principles of neural plasticity, and the inevitable constraints of PD that ultimately affect dynamic balance and mobility. These principles of the program include a focus on self-initiated movements, big and quick movements, large and flexible CoM control, reciprocal and coordinated movements of arms and legs, and rotational movements of torso over pelvis and pelvis over legs. Flexible, rotational axial motion of trunk and neck are stressed to achieve erect postural alignment, strengthening of extensors, and lengthening of flexors. Our program is designed to facilitate sensory integration for balance, emphasizing the use of somatosensory information to move the body’s CoM quickly and effectively for balance and mobility. Secondary cognitive tasks are added to mobility tasks to automatize control of balance and gait. This sensorimotor agility approach to mobility training is intended for prevention of mobility disability but may be modified for patients at later stages of PD progression to improve their mobility. Both authors provided concept/idea/project design, writing, and project management. Dr Horak provided fund procurement, facilities/equipment, institutional liaisons, and consultation (including review of manuscript before submission). The exercise program developed out of brainstorming sessions with the following expert neurologists, scientists, physical therapists, and trainers: Fay B Horak, PT, PhD, Jay Nutt, MD, Laurie A King, PT, PhD, Sue Scott, CT, Andrea Serdar, PT, CNS, Chad Swanson, CT, Valerie Kelly, PT, PhD, Ashley Scott, CT, David Vecto, CT, Triana Nagel-Nelson, CT, Kimberly Berg, CT, Nandini Deshpande, PT, PhD, and Cristiane Zampieri, PT, PhD. Strawberry Gatts, PhD, provided expert advice to select and modify tai chi moves for people with Parkinson disease. This work was supported by a grant from the Kinetics Foundation and by a grant from the National Institute on Aging (AG006457). Dr Horak was a consultant for the Kinetics Foundation. This potential conflict of interest

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A Sensorimotor Agility Exercise Program for People With Parkinson Disease has been reviewed and managed by Oregon Health and Sciences University. This article was received July 11, 2008, and was accepted January 12, 2009. DOI: 10.2522/ptj.20080214

References 1 Keus SH, Bloem BR, Hendriks EJ, et al. Evidence-based analysis of physical therapy in Parkinson’s disease with recommendations for practice and research. Mov Disord. 2007;22:451– 460. 2 Morris ME. Movement disorders in people with Parkinson disease: a model for physical therapy. Phys Ther. 2000;80:578 –597. 3 Wood BH, Bilclough JA, Bowron A, Walker RW. Incidence and prediction of falls in Parkinson’s disease: a prospective multidisciplinary study. J Neurol Neurosurg Psychiatry. 2002;72:721–725. 4 Patla AE, Shumway-Cook A. Dimensions of mobility: defining the complexity and difficulty associated with community mobility. J Aging Phys Act. 1998;7:7–19. 5 Shumway-Cook A, Woollacott M. Motor Control: Theory and Practical Applications. Baltimore, MD: Williams & Wilkins; 1995. 6 Horak FB, Macphearson MJ. Postural orientation and equilibrium. In: Rowell LB, Shepherd JR, eds. Handbook of Physiology, Section 12: Exercise: Regulation and Integration of Multiple Systems. New York, NY: Oxford University Press; 1996: 255–292. 7 Bloem BR, van Vugt JP, Beckley DJ. Postural instability and falls in Parkinson’s disease. Adv Neurol. 2001;87:209 –223. 8 van Praag H, Kempermann G, Gage FH. Running increases cell proliferation and neurogenesis in the adult mouse dentate gyrus. Nat Neurosci. 1999;2:266 –270. 9 Heyes MP, Garnett ES, Coates G. Nigrostriatal dopaminergic activity is increased during exhaustive exercise stress in rats. Life Sci. 1988;42:1537–1542. 10 Meeusen R, De Meirleir K. Microdialysis as a method to measure central catecholamines during exercise. Med Sci Sports Exerc. 1994;26:S23. 11 Tillerson JL, Cohen AD, Caudle WM, et al. Forced nonuse in unilateral parkinsonian rats exacerbates injury. Neuroscience. 2002;22:6790 – 6799. 12 Fisher BE, Petzinger GM, Nixon K, et al. Exercise-induced behavioral recovery and neuroplasticity in the 1-methyl-4-phenyl1,2,3,6-tetrahydropyridine-lesioned mouse basal ganglia. J Neurosci Res. 2004; 77:378 –390. 13 Tillerson JL, Caudle WM, Reveron ME, Miller GW. Exercise induced behavioral recovery and attenuates neurochemical deficits in rodent models of Parkinson’s disease. Neuroscience. 2003;119:899 –911.

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14 Herman T, Giladi N, Gruendlinger L, Hausdorff JM. Six weeks of intensive treadmill training improves gait and quality of life in patients with Parkinson’s disease: a pilot study. Arch Phys Med Rehabil. 2007; 88:1154 –1158. 15 van Eijkeren FJ, Reijmers RS, Kleinveld MJ, et al. Nordic walking improves mobility in Parkinson’s disease. Mov Disord. 2008; 23:2239 –2243. 16 Muhlack S, Welnic J, Woitalla D, Muller T. Exercise improves efficacy of levodopa in patients with Parkinson’s disease. Mov Disord. 2007;22:427– 430. 17 Cianci H. Parkinson’s Disease: Fitness Counts. 3rd ed. Miami, FL: National Parkinson Foundation; 2006. 18 Argue J. Parkinson’s Disease and the Art of Moving. Oakland, CA: New Harbinger Publications; 2000. 19 Zid D. Delay the Disease: Exercise and Parkinson’s Disease. Columbus, OH: Columbus Health Works Production; 2007. 20 Palmer SS, Mortimer JA, Webster DD, et al. Exercise therapy for Parkinson’s disease. Arch Phys Med Rehabil. 1986;67: 741–745. 21 Comella CL, Stebbins GT, Brown-Toms N, Goetz CG. Physical therapy and Parkinson’s disease: a controlled clinical trial. Neurology. 1994;44(3 pt 1):376 –378. 22 Schenkman M, Cutson TM, Kuchibhatla M, et al. Exercise to improve spinal flexibility and function for people with Parkinson’s disease: a randomized controlled trial. J Am Geriatr Soc. 1998;46:1207–1216. 23 Hirsch MA, Toole T, Maitland CG, Rider RA. The effects of balance training and high-intensity resistance training on persons with idiopathic Parkinson’s disease. Arch Phys Med Rehabil. 2003;84: 1109 –1117. 24 Ellis T, de Goede CJ, Feldman RG, et al. Efficacy of physical therapy program in patients with Parkinson’s disease: a randomized controlled trial. Arch Phys Med Rehabil. 2005;86:626 – 632. 25 Protas EJ, Mitchell K, Williams A, et al. Gait and step training to reduce falls in Parkinson’s disease. NeuroRehabilitation. 2005; 20:183–190. 26 Burini D, Farabollini B, Iacucci S, et al. A randomised controlled cross-over trial of aerobic training versus Qigong in advanced Parkinson’s disease. Eura Medicophys. 2006;42:231–238. 27 Dibble LE, Hale TF, Marcus RL, et al. Highintensity resistance training amplifies muscle hypertrophy and functional gains in persons with Parkinson’s disease. Mov Disord. 2006;21:1444 –1452. 28 Schmitz-Hubsch T, Pyfer D, Kielwein K, et al. Qigong exercise for the symptoms of Parkinson’s disease: a randomized, controlled pilot study. Mov Disord. 2006; 21:543–548. 29 Ashburn A, Fazakarley L, Ballinger C, et al. A randomised controlled trial of a home based exercise programme to reduce the risk of falling among people with Parkinson’s disease. J Neurol Neurosurg Psychiatry. 2007;78:678 – 684.

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30 Schmidt RA. Motor Control and Learning: A Behavioral Emphasis. Champaign, IL: Human Kinetics Inc; 1982. 31 Chu CJ, Jones TA. Experience-dependent structural plasticity in cortex heterotopic to focal sensorimotor cortical damage. Exp Neurol. 2000;166:403– 414. 32 Isaacs KR, Anderson BJ, Alcantara AA, et al. Exercise and the brain: angiogenesis in the adult rat cerebellum after vigorous physical activity and motor skill learning. J Cereb Blood Flow Metab. 1992;12:110 –119. 33 Colcombe S, Kramer AF. Fitness effects on the cognitive function of older adults: a meta-analytic study. Psychol Sci. 2003; 14:125–130. 34 Black JE, Isaacs KR, Anderson BJ, et al. Learning causes synaptogenesis, whereas motor activity causes angiogenesis, in cerebellar cortex of adult rats. Proc Natl Acad Sci USA. 1990;87:5568 –5572. 35 Anderson BJ, Alcantara AA, Greenough WT. Motor-skill learning: changes in synaptic organization of the rat cerebellar cortex. Neurobiol Learn Mem. 1996;66: 221–229. 36 Sullivan KJ, Brown DA, Klassen T, et al. Effects of task-specific locomotor and strength training in adults who were ambulatory after stroke: results of the STEPS randomized clinical trial. Phys Ther. 2007; 87:1580 –1602; discussion 1603–1587. 37 Wolf SL, Winstein CJ, Miller JP, et al. Retention of upper limb function in stroke survivors who have received constraintinduced movement therapy: the EXCITE randomised trial. Lancet Neurol. 2008; 7:33– 40. 38 Morris M, Iansek R, Matyas TA, Summers JJ. Stride length regulation in Parkinson’s disease normalization strategies and underlying mechanisms. Brain. 1996;119: 551–568. 39 Viliani T, Pasquetti P, Magnolfi S, et al. Effects of physical training on straighteningup processes in patients with Parkinson’s disease. Disabil Rehabil. 1999;21:68 –73. 40 Mak MK, Hui-Chan CW. Cued task-specific training is better than exercise in improving sit-to-stand in patients with Parkinson’s disease: a randomized controlled trial. Mov Disord. 2008;23:501–509. 41 Jobges M, Heuschkel G, Pretzel C, et al. Repetitive training of compensatory steps: a therapeutic approach for postural instability in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 2004;75:1682–1687. 42 Farley BG, Koshland GF. Training BIG to move faster: the application of the speedamplitude relation as a rehabilitation strategy for people with Parkinson’s disease. Exp Brain Res. 2005;167:462– 467. 43 Melnick M. Neurologic Rehabilitation. 3rd ed. St Louis, MO: Mosby; 1995. 44 Wierzbicka MM, Wiegner AW, Logigian EL, Young RR. Abnormal most-rapid isometric contractions in patients with Parkinson’s disease. J Neurol Neurosurg Psychiatry. 1991;54:210 –216. 45 Stelmach GE, Teasdale N, Phillips J, Worringham CJ. Force production characteristics in Parkinson’s disease. Exp Brain Res. 1989;76:165–172.

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A Sensorimotor Agility Exercise Program for People With Parkinson Disease 46 Corcos DM, Chen CM, Quinn NP, et al. Strength in Parkinson’s disease: relationship to rate of force generation and clinical status. Ann Neurol. 1996;39:79 – 88. 47 Inkster LM, Eng JJ, MacIntyre DL, Stoessl AJ. Leg muscle strength is reduced in Parkinson’s disease and relates to the ability to rise from a chair Mov Disord. 2003; 18:157–162. 48 Carpinella I, Crenna P, Calabrese E, et al. Locomotor function in the early stage of Parkinson’s disease. IEEE Trans Neural Syst Rehabil Eng. 2007;15:543–551. 49 Rochester L, Hetherington V, Jones D, et al. Attending to the task: interference effects of functional tasks on walking in Parkinson’s disease and the roles of cognition, depression, fatigue, and balance. Arch Phys Med Rehabil. 2004;85:1578 –1585. 50 Maschke M, Gomez CM, Tuite PJ, Konczak J. Dysfunction of the basal ganglia, but not the cerebellum, impairs kinaesthesia. Brain. 2003;126(pt 10):2312–2322. 51 Chong RK, Horak FB, Woollacott MH. Parkinson’s disease impairs the ability to change set quickly. J Neurol Sci. 2000; 175:57–70. 52 Yehene E, Meiran N, Soroker N. Basal ganglia play a unique role in task switching within the frontal-subcortical circuits: evidence from patients with focal lesions. J Cogn Neurosci. 2008; 20:1079 –1093. 53 Taniwaki T, Okayama A, Yoshiura T, et al. Reappraisal of the motor role of basal ganglia: a functional magnetic resonance image study. J Neurosci. 2003;23:3432–3438. 54 Brown P, Marsden CD. What do the basal ganglia do? Lancet. 1998;351(9118): 1801–1804. 55 Wright WG, Gurfinkel VS, Nutt JG, et al. Axial hypertonicity in Parkinson’s disease: direct measurements of trunk and hip torque. Exp Neurol. 2007;208:38 – 46. 56 Burleigh A, Horak FB, Nutt JG, Frank JS. Levodopa reduces muscle tone and lower extremity tremor in Parkinson’s disease. Can J Neurol Sci. 1995;22:280 –285. 57 Mak MK, Wong EC, Hui-Chan CW. Quantitative measurement of trunk rigidity in parkinsonian patients. J Neurol. 2007;254: 202–209. 58 Jacobs JV, Dimitrova DM, Nutt JG, Horak FB. Can stooped posture explain multidirectional postural instability in patients with Parkinson’s disease? Exp Brain Res. 2005;166:78 – 88. 59 Schenkman ML, Morey M, Kuchibhatla M. Spinal flexibility and balance control among community-dwelling adults with and without Parkinson’s disease. J Gerontol A Biol Sci Med Sci. 2000;55:M441–M445. 60 Schenkman ML, Clark K, Xie T, et al. Spinal movement and performance of a standing reach task in participants with and without Parkinson disease. Phys Ther. 2001;81:1400 –1411. 61 Dimitrova D, Horak FB, Nutt JG. Postural muscle responses to multidirectional translations in patients with Parkinson’s disease. J Neurophysiol. 2004;91:489 –501.

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62 Vaugoyeau M, Viallet F, Aurenty R, et al. Axial rotation in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 2006;77:815– 821. 63 Schenkman ML, Cutson TM, Kuchibhatla M, et al. Exercise to improve spinal flexibility and function for people with Parkinson’s disease: a randomized, controlled trial. J Am Geriatr Soc. 1998;46:1207–1216. 64 Horak FB, Dimitrova D, Nutt JG. Directionspecific postural instability in subjects with Parkinson’s disease. Exp Neurol. 2005;193:504 –521. 65 Frank JS, Horak FB, Nutt JG. Centrally initiated postural adjustments in parkinsonian patients on and off levodopa. J Neurophysiol. 2000;84:2440 –2448. 66 Burleigh-Jacobs A, Horak FB, Nutt JG, Obeso JA. Step initiation in Parkinson’s disease: influence of levodopa and external sensory triggers. Mov Disord. 1997; 12:206 –215. 67 King LA, Horak FB. Lateral stepping for postural correction in Parkinson’s disease. Arch Phys Med Rehabil. 2008;89: 492– 499. 68 Mancini M, Rocchi L, Horak FB, Chiari L. Effects of Parkinson’s disease and levodopa on functional limits of stability. Clin Biomech (Bristol, Avon). 2008;23:450 – 458. 69 Rocchi L, Chiari L, Mancini M, et al. Step initiation in Parkinson’s disease: influence of initial stance conditions. Neurosci Let. 2006;406:128 –132. 70 Mak MK, Patla A, Hui-Chan C. Sudden turn during walking is impaired in people with Parkinson’s disease. Exp Brain Res. 2008; 190:43–51. 71 Pfann KD, Buchman AS, Comella CL, Corcos DM. Control of movement distance in Parkinson’s disease. Mov Disord. 2001;16: 1048 –1065. 72 Farley BG, Sherman S, Koshland GF. Shoulder muscle activity in Parkinson’s disease during multijoint arm movements across a range of speeds. Exp Brain Res. 2004; 154:160 –175. 73 Glendinning DS, Enoka RM. Motor unit behavior in Parkinson’s disease. Phys Ther. 1994;74:61–70. 74 Salenius S, Avikainen S, Kaakkola S, et al. Defective cortical drive to muscles in Parkinson’s disease and its improvements with levadopa. Brain. 2002;125:491–500. 75 Yanagawa S, Shindo M, Yanagisawa N. Muscular Weakness in Parkinson’s Disease. Vol. 53. NewYork, NY: Raven Press; 1990. 76 Giladi N, Kao R, Fahn S. Freezing phenomenon in patients with parkinsonian syndromes. Mov Disord. 1997;12:302–305. 77 Bloem BR, Hausdorff JM, Visser JE, Giladi N. Falls and freezing of gait in Parkinson’s disease: a review of two interconnected, episodic phenomena. Mov Disord. 2004; 19:871– 884. 78 Giladi N, McDermott MP, Fahn S, et al. Freezing of gait in PD: prospective assessment in the DATATOP cohort. Neurology. 2001;56:1712–1721. 79 Giladi N, Hausdorff JM. The role of mental function in the pathogenesis of freezing of gait in Parkinson’s disease. J Neurol Sci. 2006;248:173–176.

80 Jacobs JV, Horak FB. External postural perturbations induce multiple anticipatory postural adjustments when subjects cannot pre-select their stepping foot. Exp Brain Res. 2007;179:29 – 42. 81 Chong RKY, Jones CL, Horak FB. Postural set for balance control is normal in Alzheimer’s but not in Parkinson’s Disease. J Gerontol A Biol Sci med Sci. 1999;54: M129 –M135. 82 Tunik E, Feldman AG, Poizner H. Dopamine replacement therapy does not restore the ability of Parkinsonian patients to make rapid adjustments in motor strategies according to changing sensorimotor contexts. Parkinsonism Relat Disord. 2007;13:425– 433. 83 Horak FB, Nutt JG, Nashner LM. Postural inflexibility in parkinsonian subjects. J Neurol Sci. 1992;111:46 –58. 84 Steiger MJ, Thompson PD, Marsden CD. Disordered axial movement in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 1996;61:645– 648. 85 Brown RG, Marsden CD. Dual-task performance and processing resources in normal subjects and patients with Parkinson’s disease. Brain. 1991;114(pt 1A):215–231. 86 Bloem BR, Grimbergen YA, van Dijk JG, Munneke M. The “posture second” strategy: a review of wrong priorities in Parkinson’s disease. J Neurol Sci. 2006;248:196 –204. 87 DeLong MR. The neurophysiologic basis of abnormal movement in basal ganglia disorders. Neurobehav Toxicol Teratol. 1983;5:811– 816. 88 Lidsky T, Manetto C, Schneider J. A consideration of sensory factors involved in motor functions of the basal ganglia. Brain Res. 1985;356:133–146. 89 Snider SR, Isgreen WP, Cote LJ. Primary sensory systems in Parkinsonism. Neurology. 1976;26:423– 429. 90 Diamond SG, Schneider JS, Markham CH. Oral sensorimotor defects in patients with Parkinson’s disease. Adv Neurol. 1986;45: 335–338. 91 Jobst EE, Melnick ME, Byl NN, et al. Sensory perception in Parkinson’s disease. Arch Neurol. 1997;54:450 – 454. 92 Zia S, Cody FWJ, O’Boyle DJ. Disturbance of human joint position sense in Parkinson’s disease. J Physiol. 1997;504:117–118. 93 Zia S, Cody FWJ, O’Boyle DJ. Impairment of discrimination of bilateral differences in the loci of tactile stimuli in Parkinson’s disease. J Physiol. 1998;509:180 –181. 94 Klockgether T, Borutta M, Rapp H, et al. A defect of kinesthesia in Parkinson’s disease. Mov Disord. 1995;10:460 – 465. 95 O’Sullivan SB, Schmitz TJ. Physical Rehabilitation: Assessment and Treatment. Philadelphia: FA Davis Company; 1994. 96 Lundin-Olsson L, Nyberg L, Gustafson Y. “Stops walking when talking” as a predictor of falls in elderly people. Lancet. 1997;349(9052):617. 97 Marchese R, Bove M, Abbruzzese G. Effect of cognitive and motor tasks on postural stability in Parkinson’s disease: a posturographic study. Mov Disord. 2003;18:652– 658.

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Letters to the Editor On “Clinical prediction rules for physical therapy interventions…” Beneciuk JM, et al. Phys Ther. 2009;89:114–124.

• derivation (level of evidence: 4),

We commend the authors for undertaking a systematic review on this topic,1 but we have serious reservations about their methods and conclusions.

• impact analysis (level of evidence: 1).2

Clinical prediction rules (CPRs) or clinical decision rules can be used to make a diagnosis, predict disease progression, predict prognosis, or select therapy. Benecuik et al reviewed CPRs that were developed to select therapy but then evaluated the quality of these CPRs using criteria designed for prognosis studies. This is unfortunate because the optimal design and analysis strategies for a prognosis study are not the same as for an intervention study. For example, randomization and concealed allocation are regarded as important design features of studies evaluating therapy but are not relevant in a prognosis study because there is no control group. Accordingly, the authors’ comments about the methodological quality of the studies they have reviewed are in doubt because they have used the wrong yardstick to judge quality. We also are concerned that the authors encourage the use of CPRs before their value has been clearly established. They confined their review to CPRs that were still in the derivation stage but then concluded that “several CPRs may be appropriate for clinical applications involving patients and clinical environments similar to those used in the CPR derivation process.”1(p118) This conclusion ignores guidelines for CPR development that recommend a 3-step process:

• validation (narrow—level of evidence: 3; broad—level of evidence: 2),

It is recommended that a CPR only be applied after there is at least level-3 evidence (narrow validation) and then only if the population being treated matches that of the population used to derive the CPR.2,3 We feel that CPRs for selecting therapy have the potential to greatly enhance patient management by physical therapists, but we would caution that premature promotion of inadequately evaluated CPRs is unwise. McGinn and colleagues2 provide 3 reasons why CPRs that have been derived but not validated are not ready to be applied clinically. First, CPRs may reflect associations that are primarily due to chance; second, predictors may be specific to the setting of the study; and third, clinicians may fail to implement a CPR successfully in the clinical setting.2 In any case, suggesting that a derivation-stage CPR is applicable in a clinical setting promotes improper use of research findings. Our patients deserve a more rigorous approach to physical therapist practice. Tasha R Stanton, Chris G Maher, and Mark Hancock TR Stanton, MScRS, is a PhD candidate, Musculoskeletal Division, The George Institute for International Health, The University of Sydney, Level 7, 341 George St, Sydney, New South Wales 2000, Australia. CG Maher, PhD, is Director, Musculoskeletal Division, The George Institute for International Health, The University of Sydney.


M Hancock, PhD, is Lecturer, Back Pain Research Group, Discipline of Physiotherapy, The University of Sydney. This letter was posted as a Rapid Response on February 3, 2009, at www.ptjournal.org.

References 1 Beneciuk JM, Bishop MD, George SZ. Clinical prediction rules for physical therapy interventions: a systematic review. Phys Ther. 2009;89:114–124. 2 McGinn TG, Guyatt GH, Wyer PC, et al. Users’ guides to the medical literature, XXII: how to use articles about clinical decision rules [reprinted]. JAMA. 2000;284:79–84. 3 Childs JD, Cleland JA. Development and application of clinical prediction rules to improve decision making in physical therapist practice. Phys Ther. 2006;86:122–131. [DOI: 10.2522/ptj.2009.89.4.394.1]

Author Response We thank Stanton et al1 for taking time to provide feedback on our recent publication in PTJ.2 The purpose of our systematic review was to provide quality ratings for physical therapy–specific clinical prediction rule (CPR) derivation studies. It was our suspicion that CPR derivation studies reported in the physical therapy literature frequently used cohort/prognostic study designs. This suspicion was confirmed when we found that 9 out of the 10 retrieved studies used cohort/prognostic designs. Therefore, we believe our “yardstick” was consistent with our original intent. It may become necessary to implement other quality assessment criteria as physical therapy CPRs evolve to include other methods, but the current tool was appropriate for the studies included in the review.3 Stanton et al1 selected a sentence from our article to indicate that we encouraged clinical use of CPRs prior to validation. Missing from their response letter were the parts of the article in which we indicated the role of validation studies

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Letters to the Editor On “Clinical prediction rules for physical therapy interventions…” Beneciuk JM, et al. Phys Ther. 2009;89:114–124.

• derivation (level of evidence: 4),

We commend the authors for undertaking a systematic review on this topic,1 but we have serious reservations about their methods and conclusions.

• impact analysis (level of evidence: 1).2

Clinical prediction rules (CPRs) or clinical decision rules can be used to make a diagnosis, predict disease progression, predict prognosis, or select therapy. Benecuik et al reviewed CPRs that were developed to select therapy but then evaluated the quality of these CPRs using criteria designed for prognosis studies. This is unfortunate because the optimal design and analysis strategies for a prognosis study are not the same as for an intervention study. For example, randomization and concealed allocation are regarded as important design features of studies evaluating therapy but are not relevant in a prognosis study because there is no control group. Accordingly, the authors’ comments about the methodological quality of the studies they have reviewed are in doubt because they have used the wrong yardstick to judge quality. We also are concerned that the authors encourage the use of CPRs before their value has been clearly established. They confined their review to CPRs that were still in the derivation stage but then concluded that “several CPRs may be appropriate for clinical applications involving patients and clinical environments similar to those used in the CPR derivation process.”1(p118) This conclusion ignores guidelines for CPR development that recommend a 3-step process:

• validation (narrow—level of evidence: 3; broad—level of evidence: 2),

It is recommended that a CPR only be applied after there is at least level-3 evidence (narrow validation) and then only if the population being treated matches that of the population used to derive the CPR.2,3 We feel that CPRs for selecting therapy have the potential to greatly enhance patient management by physical therapists, but we would caution that premature promotion of inadequately evaluated CPRs is unwise. McGinn and colleagues2 provide 3 reasons why CPRs that have been derived but not validated are not ready to be applied clinically. First, CPRs may reflect associations that are primarily due to chance; second, predictors may be specific to the setting of the study; and third, clinicians may fail to implement a CPR successfully in the clinical setting.2 In any case, suggesting that a derivation-stage CPR is applicable in a clinical setting promotes improper use of research findings. Our patients deserve a more rigorous approach to physical therapist practice. Tasha R Stanton, Chris G Maher, and Mark Hancock TR Stanton, MScRS, is a PhD candidate, Musculoskeletal Division, The George Institute for International Health, The University of Sydney, Level 7, 341 George St, Sydney, New South Wales 2000, Australia. CG Maher, PhD, is Director, Musculoskeletal Division, The George Institute for International Health, The University of Sydney.


M Hancock, PhD, is Lecturer, Back Pain Research Group, Discipline of Physiotherapy, The University of Sydney. This letter was posted as a Rapid Response on February 3, 2009, at www.ptjournal.org.

References 1 Beneciuk JM, Bishop MD, George SZ. Clinical prediction rules for physical therapy interventions: a systematic review. Phys Ther. 2009;89:114–124. 2 McGinn TG, Guyatt GH, Wyer PC, et al. Users’ guides to the medical literature, XXII: how to use articles about clinical decision rules [reprinted]. JAMA. 2000;284:79–84. 3 Childs JD, Cleland JA. Development and application of clinical prediction rules to improve decision making in physical therapist practice. Phys Ther. 2006;86:122–131. [DOI: 10.2522/ptj.2009.89.4.394.1]

Author Response We thank Stanton et al1 for taking time to provide feedback on our recent publication in PTJ.2 The purpose of our systematic review was to provide quality ratings for physical therapy–specific clinical prediction rule (CPR) derivation studies. It was our suspicion that CPR derivation studies reported in the physical therapy literature frequently used cohort/prognostic study designs. This suspicion was confirmed when we found that 9 out of the 10 retrieved studies used cohort/prognostic designs. Therefore, we believe our “yardstick” was consistent with our original intent. It may become necessary to implement other quality assessment criteria as physical therapy CPRs evolve to include other methods, but the current tool was appropriate for the studies included in the review.3 Stanton et al1 selected a sentence from our article to indicate that we encouraged clinical use of CPRs prior to validation. Missing from their response letter were the parts of the article in which we indicated the role of validation studies

April 2009

Letters to the Editor (ie, “…quality scores are not a substitute for CPR validation studies”2[p119]). Furthermore, we presented a balanced consideration of clinical application of derivation CPRs: …our findings should not be viewed as definitive. Our data provide complementary information on which CPRs to use in clinical practice, but the ultimate decision must be made in the context of a clinician’s experience and factors specific to the encounter with a patient.2(p120)

We agree with Stanton et al1 that practice recommendations ideally should be based on validation studies. However, there are practical limitations of such an approach, because very few validation studies have been reported in the physical therapy literature. The approach to clinical application described in our review is consistent with current models of evidence-based practice and previous discussion of derivation studies (“…clinicians can still extract clinically relevant messages from an article describing the development of a clinical decision rule”4[p81]). That is, clinical practice can be guided by lower levels of evidence when appropriate, especially when higher levels are not available. Clinicians are the final arbiter of whether a given CPR is applied, and the data from our review may be used to help with that decision— along with the risk-benefit ratio and other important contextual factors from the clinical encounter. Our systematic review used an appropriate search and quality assessment tool to conclude that the majority of physical therapy–specific CPR derivation studies have not been validated and that their quality varied greatly. Our review was the first to empirically consider this important issue, but similar concerns regarding methods of CPR derivation studies have been featured in

April 2009

recent editorials.5,6 We are hopeful that continued dialog on this topic will encourage physical therapists to design rigorous derivation studies and include an a priori plan for timely validation. Steven Z George, Jason M Beneciuk, Mark D Bishop SZ George, PT, PhD, is Assistant Professor, Department of Physical Therapy, Brooks Center for Rehabilitation Studies, Center for Pain Research and Behavioral Health, University of Florida, Gainesville, FL 326100154 (USA). JM Beneciuk, PT, DPT, FAAOMPT, is currently enrolled in the Rehabilitation Sciences Doctoral Program, Department of Physical Therapy, University of Florida. MD Bishop, PT, PhD, is Assistant Professor, Department of Physical Therapy, University of Florida. This letter was posted as a Rapid Response on February 17, 2009, at www.ptjournal.org.

References 1 Stanton TR, Maher CG, Hancock M. On “Clinical prediction rules for physical therapy interventions…” Phys Ther. 2009;89:394. 2 Beneciuk JM, Bishop MD, George SZ. Clinical prediction rules for physical therapy interventions: a systematic review. Phys Ther. 2009;89:114–124.

Get Hooked. Get Evidence for Your Practice. Patient clinical scenarios for conditions commonly seen in practice are now available to provide immediate access to evidence of effectiveness of physical therapy interventions. APTA members can search the clinical scenarios and search the database of more than 4,900 extractions of research articles at www.hookedonevidence.org.

www.hookedonevidence.org

3 Kuijpers T, van der Windt DA, van der Heijden GJ, Bouter LM. Systematic review of prognostic cohort studies on shoulder disorders. Pain. 2004;109:420–431. 4 McGinn TG, Guyatt GH, Wyer PC, et al. Users’ guides to the medical literature, XXII: how to use articles about clinical decision rules. Evidence-Based Medicine Working Group. JAMA. 2000;284:79–84. 5 Simoneau GG. Making use of published guidelines to assist with study design and research. J Orthop Sports Phys Ther. 2008;38:658–660. 6 Cook CE. Potential pitfalls of clinical prediction rules. J Man Manip Ther. 2008;16:69– 71. [DOI: 10.2522/ptj.2009.89.4.394.2]


Scholarships, Fellowships, and Grants News from the Foundation for Physical Therapy We Celebrate 30 Years The Foundation for Physical Therapy was incorporated as a charitable organization in 1979 and awarded its first research grants that same year. Over the past 30 years, the Foundation has provided more than $12 million in doctoral scholarships, fellowships, and research grants to 500 talented physical therapy researchers. Many of these researchers have gone on to receive much larger funding from the National Institutes of Health (NIH) and other noteworthy institutions, including the National Institute on Disability Rehabilitation and Research, the American Cancer Society, and the National Cancer Institute. The Foundation thanks all who support research, the profession, and the Foundation.

Recipients in the News Appearing in PTJ this month is a perspective article titled, “Does Sleep Promote Motor Learning? Implications for Physical Rehabilitation,” co-authored by Catherine Siengsukon, PT, PhD, and Lara A Boyd, PT, PhD. This work was supported by funds awarded to Siengsukon from the Foundation for Physical Therapy. Siengsukon was awarded a Promotion of Doctoral Studies (PODS) I scholarship in 2006 and a PODS II scholarship in 2007. Co-author Boyd previously received Foundation support in the form of a PODS I scholarship in 1998 and a PODS II scholarship in 2000.

April 2009

Foundation-Funded Research Presentation at CSM 2009 Four platform and four poster presentations reported findings from Foundation-funded research at CSM 2009. These presentations were made possible by donors’ financial commitment to physical therapy research and to the future of the profession.

Platform Geriatrics Early Neuromuscular Electrical Stimulation Improves Functional Performance After Total Knee Arthroplasty. Jennifer E Stevens, PT, MPT, PhD Orthopaedics Effect of Femoral Strapping on Medial Femoral Rotation, Patellofemoral Joint Alignment and Pain Response in Females With Patellofemoral Pain: Assessment Using Weightbearing MRI. Richard Souza, PT, MPT Sports Physical Therapy Timeline for Non-Copers to Return to Sport. Erin H Hartigan, PT, DPT Tibiofemoral and Patallofemoral Alignment During a Single Leg Squat: An MRI Study. Brian W Noehren, PT, MS

Poster Geriatrics Impact of Delayed Total Knee Arthroplasty Surgery on Postoperative Quadriceps Muscle Strength and Functional Performance: A Case Report. Jennifer E Stevens, PT, MPT, PhD Preoperative and Inpatient Measures Predict Physical Function Three Months After Total Knee Arthroplasty. Jennifer E Stevens, PT, MPT, PhD

Neurology Recovery of Finger Extension and Grasping Ability After Stroke. Stacey DeJong, PT, MPT Pediatrics Functional Electrical StimulationAssisted Cycling in Adolescents With Cerebral Palsy. Ann Tokay, PT, PhD

Save the Date: Thursday, June 11 Foundation Dinner Dance 30-Year Celebration Join the Foundation at the annual Dinner Dance as we celebrate 30 years of funding physical therapy research during PT 2009 in Baltimore. This event is graciously sponsored by HPSO/CNA for the 9th consecutive year. We will honor the accomplishments of past funding recipients. The evening begins with a reception at 6:30 pm, dinner at 7:30 pm, and program at 8:30 pm. New this year: winners of the Georgia State–Marquette Challenge will be announced during the reception. Tables for 8 are $1,600 and include a listing of your name and company or organization in the program. Individual tickets are $150 ($100 for students). Dinner dance tickets must be purchased before PT 2009. Purchase your tickets at www. FoundationforPhysicalTherapy. org, or call the APTA Service Center at 800/999-2782, ext 3395. For event information or to learn about corporate sponsorship opportunities, contact [email protected] or 800/875-1378, ext 8502.


Scholarships, Fellowships, and Grants

Last Call for Split Raffle— Deadline Approaches

Foundation’s Web site for complete Split Raffle rules.

The 21st Annual Split Raffle fundraiser supports doctoral scholarships for physical therapists who are emerging researchers. Through the purchase of a split raffle ticket, you will have the satisfaction of knowing you are investing in the strength and future of the physical therapy profession. You also have the chance to win one of nine $2,000 prizes or the $10,000 grand prize! Tickets must be purchased by 9:00 am (EDT) on May 13, 2009, to participate. Contact Barbara Malm at 800/875-1378, ext 8502, to learn how you can participate. Visit the

Nominations for Scientific Review Committee Due April 30 The Foundation is seeking recommendations for individuals to serve on its Scientific Review Committee (SRC). Well-qualified physical therapist researchers will review doctoral, fellowship, and research grant applications received by the Foundation. Three appointments will be made in June 2009 for terms that will begin in January 2010. To be considered, individuals must meet the criteria for SRC

membership posted on the Foundation’s Web site (www.Founda tionforPhysicalTherapy.org). Selfnominations are welcome. Please e-mail your recommendations by April 30 to [email protected]. [DOI: 10.2522/ptj.2009.89.4.397]

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.


April 2009

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

sports medicine Volume 39 Issue 4 April 2009

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

Israel Journal of Mathematics, Volume 4, Issue 4 (1966)

Manual Therapy Journal - Volume 14, Issue 4, Pages 353-460 (August 2009)

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

MyJalah, Edisi 4 - April 2009

International Journal of Powder Metallurgy Volume 45 Issue 4

Israel Journal of Mathematics, Volume 4, Issue 3 (1966)

Journal of Semantics, Volume 2, Issue 3-4, 1983

International Journal of Powder Metallurgy Volume 44 Issue 4

Israel Journal of Mathematics, Volume 4, Issue 1 (1966)

Israel Journal of Mathematics, Volume 2, Issue 4 (1964)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

sports medicine Volume 39 Issue 4 April 2009

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

Israel Journal of Mathematics, Volume 4, Issue 4 (1966)

Manual Therapy Journal - Volume 14, Issue 4, Pages 353-460 (August 2009)

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

MyJalah, Edisi 4 - April 2009

International Journal of Powder Metallurgy Volume 45 Issue 4

Israel Journal of Mathematics, Volume 4, Issue 3 (1966)

Journal of Semantics, Volume 2, Issue 3-4, 1983

International Journal of Powder Metallurgy Volume 44 Issue 4

Israel Journal of Mathematics, Volume 4, Issue 1 (1966)

Israel Journal of Mathematics, Volume 2, Issue 4 (1964)

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