A Comparative Review of Contemporary Participation Measures\' Psychometric Properties and Content Coverage

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A Comparative Review of Contemporary Participation Measures’ Psychometric Properties and Content Coverage Susan Magasi, PhD, Marcel W. Post, PhD ABSTRACT. Magasi S, Post MW. A comparative review of contemporary participation measures’ psychometric properties and content coverage. Arch Phys Med Rehabil 2010;91 (9 Suppl 1):S17-28. Objectives: To provide a review of contemporary participation measures’ conceptual foundations, psychometric properties and linkage to the International Classification of Functioning, Disability and Health (ICF). Data Sources: Major medical databases, including PubMed, Medline, PsychInfo, and CINAHL. Study Selection: Articles that described the psychometric properties of generic measures of adult participation published in English between 1998 and 2008 were included. Data Extraction: Two reviewers independently reviewed each measure using recognized quality criteria for health questionnaires. Individual items were linked to the ICF using established linking rules. Data Synthesis: Eight measures met the inclusion criteria: Impact on Participation and Autonomy, ICF Measure of Participation and Activities, Keele Assessment of Participation, Assessment of Life Habits, Participation Profile, Participation Survey/Mobility, Participation Scale, and the Participation Measure for Post-Acute Care. The selected measures were based primarily on the ICF and demonstrated moderate to good validity and reliability, but psychometric information was often incomplete. The most commonly addressed ICF domains were mobility; domestic life; social interactions; major life domains; and community, social, and civic life. Conclusions: This review provides tools—a detailed review of individual participation measures, a comparative table of the measures’ psychometric properties, and ICF linkages—and a set of 3 guiding questions to help users select appropriate participation measures. Key Words: Consumer participation; Outcome assessment (health care); Psychometrics; Rehabilitation; Review [publication type]. © 2010 by the American Congress of Rehabilitation Medicine

1949, THE WORLD HEALTH Organization adopted a IandNdefinition of health as “a state of complete physical, mental social well-being, and not merely the absence of disease or

infirmity.”1 While physical and mental health are by now commonly used terms, “social health” is not.2 Social health outcomes have not been clearly defined, and health researchers who use the term “social” might refer to interactions with other persons only, or to role functioning, or to anything that is done within a social context. A milestone in the conceptualization of social health was the publication in 1980 of the WHO’s International Classification of Impairments, Disability and Handicaps, which provided a unifying classification of social health outcomes.3 The negative connotation of the term “handicap” and the unidirectional medical perspective behind the International Classification of Impairments, Disability and Handicaps, however, raised serious criticisms. In the 1990s, WHO began a revision process that ultimately led to the ICF4 and introduced and defined the terms “activities” and “participation.” The ICF defines participation as “involvement in life situations”4(p10) and activities as “the execution of a task or action.”4(p10) In the ICF, the term “participation” is used as a neutral term to describe social health and functioning. Originally conceived of as 2 distinct categories, the final version of the ICF merges activities and participation into a single taxonomy and delineates 9 domains of activities and participation: learning and applying knowledge; general tasks and demands; communication; mobility; self-care; domestic life; interpersonal relationships, major life areas (education, work, economic); and community, civic, and social life. The ICF provides users with no

List of Abbreviations CI ICC ICF ICIDH-2 IMPACT-S

From the Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL (Magasi); Rudolf Magnus Institute for Neuroscience and Center of Excellence in Rehabilitation Medicine, University Medical Center Utrecht (Post); De Hoogstraat, Utrecht, The Netherlands (Post). Presented to the American Congress of Rehabilitation Medicine, October 15-19, 2008, Toronto, ON, Canada. Supported by an honorarium from the National Institute on Disability and Rehabilitation Research through the Rehabilitation Research and Training Center on Measuring Rehabilitation Outcomes and Effectiveness (grant no. H144B040032) awarded to the Rehabilitation Institute of Chicago. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated. Reprint requests to Susan Magasi, PhD, Dept of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, 625 N Michigan Ave, Ste 2700, Chicago, IL 60611, e-mail: [email protected]. 0003-9993/10/9109S-00553$36.00/0 doi:10.1016/j.apmr.2010.07.011

IPA IRT KAP LHS LIFE-H P-Scale PAR-PRO PARTS/M PM-PAC RNL ROC SF-36 SIP WHO

confidence interval interclass correlation coefficient International Classification of Functioning, Disability and Health International Classification of Impairment, Disability and Handicap II ICF Measure of Activity and Participation— Screener Impact on Autonomy and Participation item response theory Keele Assessment of Participation London Handicap Scale Assessment of Life Habits Participation Scale Participation Profile Participation Survey/Mobility Participation Measure for Post Acute Care Reintegration to Normal Living receiver operated characteristic Medical Outcomes Study 36-Item ShortForm Health Survey Sickness Impact Profile World Health Organization

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less than 4 ways to distinguish activities and participation; there is as yet no consensus on how best to distinguish the 2 concepts.5,6 This conceptual ambiguity has made the operationalization and measurement of participation a challenge.5 Despite this conceptual confusion, the ICF with its term “participation” has gained worldwide acceptance and boosted attention to participation outcomes in disability policy and research.7,8 The ICF and its predecessors have inspired many researchers to develop both generic and disease-specific participation measures. There is, however, a lack of consistency in how to define participation, and there are significant differences in item contexts, content, and response options. Consequently, there are myriad instruments purporting to measure participation from very different perspectives. Rehabilitation researchers and clinicians are confronted with the daunting task of selecting the appropriate instrument for their applications. Recently, a number of high-quality reviews of participation measures have been published.9-11 We build on these publications by providing a comparative review of contemporary participation measures and emphasizing each instrument’s conceptual foundations, psychometric properties, and item content. We link item content to the ICF framework to facilitate users’ instrument selection. METHODS We completed a comprehensive search of the rehabilitation literature using PubMed, Medline, PsychInfo, and CINAHL for articles with participation as the major outcome or that reported the development of participation instruments. Key search terms included “participation instruments,” “participation and rehabilitation,” “participation and outcomes,” and “participation and measurement.” We used PubMed’s related articles feature to find articles relevant to participation outcome measurement. We evaluated the abstracts of 438 research articles according to the following 5 inclusion criteria to identify generic adult measures of participation. 1. In order to capture the WHO’s evolving concept of participation, we selected instruments published since 1998. 2. We selected instruments designed to measure participation; we excluded instruments measuring health-related quality of life, functional status, and life satisfaction, including those in with participation subscales and items nested within a broader measure. 3. Only instruments developed for adult populations were included. There are distinct differences between how participation is conceptualized and how it ought to be measured in pediatric populations.12,13 An examination of the state of pediatric participation measurement warrants a nuanced and focused review in its own right. 4. We only included generic measures of participation. It was beyond the scope of this review to evaluate the generalizability of measures developed for a specific clinical group that have not yet been used in other clinical samples. 5. Complete versions of the instruments had to be available in English from public sources or the developers. These narrow inclusion criteria enabled us to conduct a detailed review. Data were abstracted from peer-reviewed sources on each instrument’s conceptual foundations, development process, and psychometric properties. Psychometric data were rated using established quality criteria for evaluating the measurement properties of health status questionnaires.14,15 Table 1 lists the rating criteria. To reflect contemporary measurement science, Arch Phys Med Rehabil Vol 91, Suppl 1, September 2010

we evaluated the developers’ use of IRT models. Fitting data to IRT models produces estimates of item difficulty, respondent ability, relevance of data to the conceptual model, and estimates of local independence.16 Finally, we linked individual items from each measure to ICF codes using the rules of Cieza et al.17 The 2 authors— both of whom have expertise in outcome measurement and participation research—reviewed each measure independently and reconciled discrepancies until consensus was achieved. RESULTS Eight participation instruments met the inclusion criteria, including the IMPACT-S,18 the IPA,19 the KAP,20 the LIFEH,21 the PAR-PRO,22 the PARTS/M,23 the P-Scale,24 and the PM-PAC.25 Except for the IPA and LIFE-H, psychometric evidence originated from the original validation studies conducted by the instruments’ developers. Table 1 provides a comparative rating of the instruments’ psychometric properties. Table 2 provides comparative information on the instruments’ content coverage by ICF chapter, and table 3 provides detailed linkages of items to the most relevant ICF code. Only primary linkages to the ICF are provided. The agreement between the 2 authors was 98.5%. Differences between reviewers were related primarily to level of specificity and interpretation of environmental factors embedded in participation items. Detailed instrument summaries are provided for each measure. Instrument Summaries The IMPACT-S18 was developed in The Netherlands as a generic self-report measure of activity limitations and participation restrictions for use in epidemiologic and outcomes research. The developers sought to describe all 9 ICF domains of activities and participation. Chapters 1 to 5 are designated as activities, and chapters 6 to 9 are designated as participation. Dutch and English versions are available. There are no published data on administration time. ●







Scoring: The 32-item IMPACT-S uses a 4-point limitation rating scale (No, no limitations whatsoever; Yes, some limitations; Yes, considerable limitations; Yes, I cannot do that at all). Nine scale scores (1 per ICF domain), 2 subtotal scores for activities and participation, and a total score can be computed. All summary scores are converted to a score on a 0 to 100 scale, with higher scores indicating higher levels of participation. Content validity was established based on correspondence to the ICF and pilot testing with a heterogeneous sample of motor vehicle collision survivors (n⫽11) and rehabilitation professionals (n⫽18). Validity and reliability statistics are based on postal surveys with a Dutch sample of 275 survivors of motor vehicle collisions. Validity and reliability statistics are reported for 9 domain scales, 2 subtotal scores for activities and participation, and a total score. Construct validity: Internal consistency was evaluated via the Cronbach alpha and ranged from .74 to .89 for the individual domain scores, was .92 for the activity and participation subtotal scales, and was .96 for the IMPACT-S total. Principal component analyses failed to support the hypothesized division between activity and participation domains. Convergent validity was established by stronger Spearman correlations between corresponding scales of the IMPACT-S and the World Health Organization Disability

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Assessment Schedule II (WHODAS II) (.64 –.78) than with noncorresponding scales. ● Test-retest reliability was evaluated in a subsample of 197 people over a 4-week period. The ICC ranged from .72 to .87 for individual domain scales, ranged from .90 to .93 for subtotal scores, and was .94 for the IMPACT-S total. ● Strengths: The IMPACT-S has promising measurement properties and was developed using rigorous application of psychometric standards. ● Limitations: Published psychometric data are incomplete, empirical testing failed to support the hypothesized distinction between activities and participation, and there was limited patient involvement in the instrument’s deve lopment. The IPA was developed in The Netherlands19 and is conceptually founded on the ICIDH-2 and includes the concept of decisional autonomy as an integral component of participation. The 32 items assess perceived participation across 5 subscales; 9 additional items assess perceived problems and are intended to facilitate clinical decision-making. Dutch,19 English,26,27 and Swedish28 versions are available. IPA is a self-report questionnaire with an average completion time of 19.3⫾4.7 minutes.26 ●



Scoring: Respondents use a 5-point scale indicating chance of participating when and how they want (very good to very poor). Perceived problem items are rated on a 3-point scale (0, no problem; 1, minor problem; 2, major problem). Content validity was established based on input from a multidisciplinary clinical research group, external experts, and a qualitative study with rehabilitation patients.19







Construct validity: Factor analysis (excluding the items on work and education because of many missing values) revealed a 4-factor structure: self-care and appearance, mobility, family role, and social relationships (Cronbach ␣⫽.84 –.87).19,29 Confirmatory factor analysis of the English IPA established construct validity (Normal Fit Index⫽.98; Comparative Fit Index⫽.99).30 Rasch analysis revealed 2 unidimensional subscales: perceived participation and perceived problems; the item hierarchy was consistent with expert expectations.28,31 IPA subscales and a 30-item scale (indoor autonomy removed because of differential item functioning) were invariant across 2 European countries and by sex.28 Internal consistency of the English IPA is similar (Cronbach ␣⫽.96 –.94).30 Convergent validity was evaluated with the LHS,32 the SIP,33 and the SF-36.34 IPA correlated –.42 to –.57 with the LHS domains of mobility, physical independence, occupation, and social integration.28 IPA’s autonomy outdoors correlated .29 with the SIP’s physical dimension.29 IPA’s family role, autonomy indoors, and autonomy outdoors correlated –.43 to –.53 with the SF-36’s physical dimensions.29 A subsequent study found strong expected correlations (.53–.74) but also some strong unexpected correlations between IPA subscale scores and scores on the LHS, SIP, and SF-36.30 Discriminant validity: The sensitivity of the perceived problem scale may only be sufficient to distinguish between people with and without disabilities.29,31 Test-retest reliability was evaluated with a heterogeneous disability sample over 15-days (␬ ranged .56 –.90 for the participation scales and .59 –.87 for the problem items).28

Table 1: Psychometric Characteristics of 8 Participation Measures Psychometric Property

Administration* Content validity† Construct validity‡ Internal consistency§ Convergent validity储 Divergent validity¶ Test/retest# IRT validity coefficients** Ceiling/floor†† Responsiveness‡‡

IMPACT-S

⫹/– ? ⫹/– ⫹ ⫹ 0 ⫹ 0 0 0

IPA

KAP

LIFE-H

PAR-PRO

PARTS/M

PM-PAC

P-Scale

⫹/– ⫹ ⫹ ⫹ ⫹/– ⫹ ⫹/– ⫹ – ⫹

⫹ ? Not applicable Not applicable ⫹ ⫹/– – 0 – 0

– ⫹ 0 ⫹ ⫹/– ⫹ ⫹ ⫹ ⫹/– 0

⫹ – ⫹/– ⫹ 0 ⫹ 0 ⫹/– ⫹/– 0

– ⫹ – ⫹ ? 0 ? 0 0 0

⫹/– ? ⫹ ⫹ 0 ⫹ ? ⫹ – ⫹

⫹/– ? ⫹ ⫹ 0 ⫹ ⫹ 0 0 0

NOTE. Criteria13,14: 0, no information found; ?, doubtful design or method AND/OR criteria-specific issues listed below. *Administration: ⫹, quick and easy to complete (not more than 20 items); ⫹/–, median size and burden (20 – 60 items); –, long (⬎60 items), burdensome, complicated. † Content validity: ⫹, clear description is provided of the measurement aim, the target population, the concepts that are being measured, and the item selection AND target population and (investigators OR experts) were involved in item selection; ?, a clear description of the above mentioned aspects is lacking OR only target population involved OR doubtful design or method; –, no target population involvement. ‡ Construct validity: ⫹, specific hypotheses were formulated AND at least 75% of the results are in accordance with these hypotheses; ?, doubtful design or method (eg, no hypotheses); –, less than 75% of hypotheses were confirmed, despite adequate design and methods. § Internal consistency: ⫹, factor analyses performed on adequate sample size (7ⴱ#items and ⱖ100) AND Cronbach ␣ (s) calculated per dimension AND Cronbach ␣ (s).70 to .95; ?, doubtful design or method OR no factor analysis; ⫺, Cronbach ␣ (s) ⬍.70 or ⬎.95 despite adequate design and method. 储 Convergent validity: ⫹, convincing arguments that criterion standard is “criterion” AND correlations ⱖ.70; ?, doubtful design or method OR no convincing argument that criterion standard is “criterion”; ⫺, correlation with criterion standard ⬍.70, despite adequate design and method. ¶ Divergent validity: ⫹, relevant and expected differences between subgroups of patients; ?, doubtful design or method; –, unable to distinguish between subgroups of patients. # Test–retest reliability: ⫹, ICC or weighted ␬ ⱖ.70 (scales); ?, doubtful design or method (eg, no time interval); –, ICC or weighted ␬ ⬍.70, despite adequate design and method. **IRT validity coefficients: ⫹, an IRT was used to evaluate the instrument and reported results supporting the instrument’s validity; ⫹/–, an IRT and/or Rasch model to evaluate the instrument and reported results that do not support the instrument’s validity; 0, no IRT and/or Rasch model. †† Floor and ceiling effects: ⫹, at most 15% of respondents achieved the highest or lowest possible score; ?, doubtful design or method; –, ⬎15% of the respondents achieved the highest or lowest possible scores, despite adequate design and methods. ‡‡ Responsiveness: ⫹, changes in follow-up study or trial significant and standardized response mean or effect size ⬎0.4.

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PARTICIPATION MEASURE REVIEW, Magasi Table 2: Percentage of Items Linked to Each of the 9 Activity and Participation Chapters of the ICF

Participation Measure

Learning & Applying Knowledge

General Tasks & Demands

Communication

Mobility

IMPACT-S, n (%) IPA, n (%) KAP, n (%) LIFE-H, n (%) PAR-PRO, n (%) PARTS/M, n (%) PM-PAC, n (%) P-Scale, n (%) Mean %

3 (9.4) 0 0 1 (1.2) 0 0 1 (2.1) 1 (5.6) 2.3

2 (6.3) 0 0 2 (2.6) 0 0 0 0 1.1

3 (9.4) 0 0 7 (9.1) 0 0 3 (5.9) 0 3.1

7 (21.9) 3 (9.3) 2 (18.2) 15 (19.5) 2 (10.0) 2 (10.0) 8 (15.7) 3 (16.7) 15.2

Self-Care

Domestic Life

Social Interactions

Major Life Domains

Community, Social, & Civic

Not Participation

3 (9.4) 4 (12.5) 1 (9.1) 12 (15.6) 0 5 (25.0) 1 (2.0) 1 (5.6) 9.9

4 (12.5) 7 (21.9) 3 (27.3) 9 (11.7) 6 (30.0) 2 (10.0) 2 (3.9) 2 (11.1) 16.1

4 (12.5) 7 (21.9) 1 (9.1) 8 (10.4) 1 (5.0) 2 (10.0) 6 (11.8) 1 (5.6) 10.8

2 (6.3) 6 (18.8) 3 (27.3) 10 (13.0) 4 (20.0) 3 (15.0) 15 (29.4) 3 (16.7) 18.3

4 (12.5) 4 (12.5) 1 (9.1) 8 (10.4) 7 (35.0) 6 (30.0) 12 (23.5) 4 (22.2) 15.7

0 1 (3.1) 0 5 (6.5) 0 0 3 (5.9) 1 (5.6) 2.6

NOTE. All percentages are row percentages.



Responsiveness was evaluated in a sample of rehabilitation outpatients (n⫽49). Changes were substantial for family roles, outdoor autonomy, and work and education (squared root method⫽0.8 –1.3) and small for social relationships and autonomy indoors (squared root method⫽ 0.1– 0.4).35 ● Floor and ceiling effects were found, because Rasch analysis showed that 20% of people were either above or below the range of item calibration values. ● Strengths: The IPA has well documented psychometric properties and conceptual strengths. The IPA recognizes the importance of decisional autonomy in the lives of people with disabilities as evidenced by the used of choice and control language. The IPA is gaining prominence as a participation outcome measure in rehabilitation research. Validation and reliability data are available for general disability and specific clinical groups. The IPA has emerged as a validation measure for other participation measures and as an outcome measure in rehabilitation research with diverse clinical populations.36-43 ● Limitations: The IPA has floor and ceiling effects, there is limited evidence of responsiveness, and it offers a profile of participation domains without a total score. The KAP was developed in England for use in population surveys.20 This 11-item self-report questionnaire uses a 5-point rating scale (all of the time/most of the time/some of the time/a little of the time/none of the time) to evaluate perceived participation restrictions. Four filter items are included to distinguish people who choose not to participate from those whose participation is restricted. The KAP covers the ICF domains of domestic life; major life areas; mobility; self-care; interpersonal relationships; and community, social, and civic life. Mean completion time is 3 minutes (range, 2– 4min). ●







Scoring: Responses are dichotomized for the presence or absence of participation restrictions in each domain. There is no total score except for a distinction between people with having 1 or more participation restrictions from people with no participation restrictions. Content validity was documented through correspondence to ICF domains and qualitatively via cognitive and semistructured thematic interviews. Construct validity is not applicable to the KAP because there is no total score. Convergent and divergent validity were evaluated using the IPA19 and RNL.44 Convergent validity was good, with mean agreement to corresponding items of the RNL and IPA of 79.3% (range, 72%– 84%) and 87.7% (range, 74%–97%), respectively.

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Divergent validity was poor with mean agreement to noncorresponding items of the RNL and IPA of 76.0% (range, 57%– 89%) and 82.8% (range, 66%–97%), respectively. ● Evaluation of test-retest reliability indicated that perceived participation restrictions as measured by the KAP are not stable over time. Mean observed agreement for the 5 response options to each participation item was 75.1% (range, 68%– 83%), and chance-corrected agreement ranged from slight (␬␻⫽.34; 95% CI, .09 –.59) to moderate (␬␻⫽.64; 95% CI, .54 –.74). Observed agreement improved when response options were dichotomized to “none” or “any” (mean agreement⫽90.4%; range, 85.3%– 94.4%), but chance-corrected agreement did not improve, ranging from slight (␬⫽.20; 95% CI, –.04 to .44) to substantial (␬⫽.71; 95% CI, .57–.85). Pilot testing in a clinical sample of people with arthritis revealed potential ceiling effects, with 53% of respondents reporting no participation restrictions.45 ● Strengths: The KAP is a short measure of perceived participation restrictions that closely matches 6 ICF domains. It is potentially useful for population or epidemiologic studies that require a brief overview of participation restrictions. ● Limitations: The KAP has ceiling effects and questionable test-retest reliability. The KAP evaluates the presence or absence of participation restrictions broadly without indicating overall severity or relative importance of participation restrictions. It may not be suitable for clinical or research applications that require detailed information of the nature and scope of participation restrictions and the ability to document change over time. The LIFE-H is based on the Disability Creation Process Model and was developed in Canada to assess quality of social participation.21 The LIFE-H assesses 12 categories of life habits corresponding to all ICF chapters. Respondents rate their level of difficulty in task performance, use of assistance or aids, and level of satisfaction. The LIFE-H consists of 77 items and can be used as a self-report or interviewer-administered measure. French, English, Spanish, German, Dutch, and Italian versions are available. Administration time ranges from 30 to 60 minutes. ●

Scoring: LIFE-H provides 12 category scores, 2 subtotal scores (daily activities and social roles), and a total score. Level of difficulty (4-point scale), assistance/aids (4-point scale), and level of satisfaction (5-point scale) are rated for each item. An accomplishment score is calculated for each

PARTICIPATION MEASURE REVIEW, Magasi

life habit as a combination of the difficulty and assistance type rating. ● Content validity was evaluated by an extensive development process involving consultation with international experts including researchers, services providers, and consumer representatives. The instrument was refined based on clinical evaluation.21 ● Construct validity: Multidimensionality was evident in a factor analysis of residuals.46 Rasch analysis showed satisfactory measurement properties (person reliability⫽.91), and agreement with expert opinion was high (items hierarchy r⫽.89). Item difficulty hierarchy obtained from spinal cord injury experts differed from hierarchy obtained from traumatic brain injury experts, suggesting that the construct varies across impairment groups.46 ● Internal consistency was reported based on data from a sample of adults and children with spinal cord injury for the Life-H (Cronbach ␣ⱖ.82). ● Convergent validity was demonstrated by correlations between grouped LIFE-H items and corresponding CHART dimensions. Values ranged from .14 for social integration, through .33 and .36 for mobility and occupation, to .76 for physical independence.47 Strong correlations were found between LIFE-H and the Functional Autonomy Measurement System (.70)48 and between LIFE-H and the IPA and LHS (.80 –.92).49 ● Discriminant validity: The LIFE-H distinguishes people based on level and completeness of spinal cord injury,50 among older adults based on both living situation51 and health status.49 ● Test-retest reliability was found to be good with ICC values of .83 to .95 in adults with spinal cord injury,51 .76 to .92 in adults with myotonic dystrophy,52 greater than or equal to .89 for total and daily activity scores, and .64 for social roles in elderly people.51 The Dutch LIFE-H showed good test-retest reliability (ICC⫽.80) for the overall score, but ICC values for subscale scores were lower, ranging from .21 for social relationships to .88 for personal care.49 ● Interrater reliability was good between patients with stroke and proxies for subtotal and total scores (ICC, .63–.87).53 ● Responsiveness has not been evaluated. ● Ceiling and floor effects: Floor effects are minimal, but ceiling effects are present on several subscores. ● Strengths: The LIFE-H has been validated in adult and pediatric and general and specific rehabilitation populations. It is comprehensive and flexible with a broad coverage of participation domains. The LIFE-H can be used to elicit performance and satisfaction ratings for participation domains.50 It has been used as an outcome measure in rehabilitation and epidemiologic research.54-60 ● Limitations: The LIFE-H uses a long, laborious, and complicated response format. Several of the subscales have ceiling effects. The use of assistance or aids lowers accomplishment scores. Use of LIFE-H as a self-report measure is not recommended for the elderly and people with cognitive impairments.49 Perhaps because of the response burden, there has been limited adoption of the LIFE-H. The P-Scale was developed by an international team of researchers to evaluate the impact of rehabilitation interventions on social participation in rural communities.24 The P-Scale addresses the ICF domains of community, social and civic life, mobility, major life domains, domestic life, learning and applying knowledge, self-care, and social interactions. It is

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designed as a generic, client-reported, and cross-culturally relevant measure of participation that is suitable for nonprofessional interviewers. The P-Scale uses peer comparison (albeit not consistently)61 as a means of eliciting culturally sensitive ratings of participation. It has been translated from English and field-tested in 6 languages in 3 countries (Nepal, Brazil, India). Median completion time is less than 20 minutes.62 ●

Scoring: The 18-item P-Scale uses a 5-point intensity rating scale (no restrictions; some restrictions, but no problem; small problem; medium problem; large problem). Items are summed to obtain a total score ranging from 0 to 90. Scores may be converted to grades of participation restrictions with 0 to 12 indicating no significant restriction, 13 to 22 indicating mild restriction, 23 to 32 indicating moderate restriction, 33 to 52 indicating severe restriction, and 53 to 90 indicating extreme restriction. The authors caution that this classification may vary by cultural and social context. ● Content validity was evaluated through expert ratings of participation restrictions based on client interviews. ● Construct validity was supported by factor analysis; the first factor explained 90% of the variance. Internal consistency was excellent (Cronbach ␣⫽.92). ● Convergent validity has not been evaluated; however, the instrument developers used 3 strategies to evaluate the P-Scale’s external validity. They correlated P-Scale scores with (1) expert ratings based on clinical interviews (R⫽.44); (2) Eyes Hands Feet score in a sample of people with leprosy (R⫽.39); and (3) subject ratings of “How life is now” on a 0 to 10 visual analog scale (P⫽.001; Kruskal-Wallis test). ● Interrater and intrainterviewer reliability had ICCs of .80 and .83, respectively. ● Strengths: The P-Scale was developed to assess participation restrictions in a culture-free manner that is applicable to rural and non-Western societies using a peer comparison model. It is brief and easy to score. ● Limitations: The authors refer to an unpublished document to substantiate the P-Scales’ psychometric properties. The concept of peers is not consistently applied and may be difficult for some subjects. The PAR-PRO was developed in the United States as a measure of home and community participation of people with and without disability.22 The 20-item measure was developed by experts in medical rehabilitation who had familiarity with the Commission for the Accreditation of Rehabilitation Facilities’ accreditation standards and outcomes assessment. The PAR-PRO covers the ICF domains of community, social and civic life, domestic life, major life areas, mobility, and interpersonal relationships. It was designed as a companion to the FIM.63 It is completed using an interview format with the patient or a proxy. Information on completion time is not available. ●



Scoring: The PAR-PRO uses a 5-point frequency rating to assess frequency of participation in life situations. The 5-frequency ratings are collapsed into 3 (0, activity did not occur; 1, activity occurred at least once a month but less than weekly; 2, activity occurred at least once a week) to yield a global participation score. Psychometric properties were evaluated in patients with diverse impairments who were admitted to 9 inpatient rehabilitation facilities (n⫽594; mean age, 74.0y) in 6 states. Content validity is based on item selection by experts who reviewed legacy instruments and reconciled content with the ICF. Arch Phys Med Rehabil Vol 91, Suppl 1, September 2010

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Construct validity was evaluated using Rasch analysis. The mean infit and outfit values were 1.01 and 1.03, respectively, close to the Rasch ideal of 1.00. Item infit and outfit values ranged from .56 to 1.80, indicating that most items fit the underlying model. Person separation was poor (1.64), while the item separation of 10.37 suggests that the respondents can distinguish a wide range of item difficulty. Exploratory factor analysis identified 4 factors (domestic management, socialization, physical vigor, generative activities) accounting for 44.4% of the variance. Internal consistency was adequate (Cronbach ␣⫽.77). The authors concluded that the PAR-PRO is essentially unidimensional with weaker subfactors. No data are published on reproducibility, responsiveness, interpretability, or convergent validity. ● Discriminant validity: The PAR-PRO’s ability to discriminate subsamples of patients with orthopedic (n⫽133) and neurologic conditions (n⫽149) was evaluated using 1-way analysis of variance and analysis of covariance (with age as a covariate; F2,281⫽6.098, P⬍.033 and F2,281⫽5.22, P⬍.006, respectively). ● Strengths: The PAR-PRO is a parsimonious measure of frequency of participation in a variety of life activities that provides a single participation score, with preliminary support for 4 subfactors. It offers the potential for withinperson comparisons over time, although reproducibility needs to be established. ● Limitations: There is no evidence of consumer input in the development process. The PAR-PRO measures objective performance with no indication of the importance that individual activities hold for the person or the person’s level of satisfaction with participation levels. The PARTS/M was developed in the United States as a selfreport measure of participation by people with mobility impairments.23 The ICIDH-2 provides the conceptual framework. This 135-item self-report questionnaire evaluates participation in 20 activities across the ICF domains of self-care, mobility, major life areas and community, domestic life, interpersonal relationships, and social and civic life. Each activity is evaluated on 4 participation components (temporal—frequency and time taken; evaluative— choice, satisfaction, importance; health-related; supportive— human and environmental). The PARTS/M is available in both paper-based and computeradministered formats. The PARTS/M is available in English, and there are no published data on administration time. ●







Scoring is based on principal component analysis results. It yields an overall score of participation, a participation score for each of the 6 domains, and 4 component scores (temporal, evaluative, health-related limitations, environmental support). Validity and reliability data are based on a sample of 604 people with mobility impairments. Reliability and validity statistics were better at the domain level than for individual activities. Content validity was evaluated with extensive consumer and expert involvement in instrument development as well as linking to the ICF. Construct validity: Factor analysis was conducted to evaluate construct validity. First-order principal component analysis yielded 4 participation component factors, and second-order principal component analysis supported the existence of 6 participation domains scores and 1 overall participation score. Data from these analyses are not included in the published literature.

Arch Phys Med Rehabil Vol 91, Suppl 1, September 2010



Internal consistency was calculated for participation domains, items, and components using the Cronbach alpha and ranged from .40 to .75 for the 20 activities, .71 to .92 for the 6 domains, and .64 to .94 for the participation components. ● Convergent validity was evaluated via canonic correlation between PARTS/M and the RNL44 and the Personal Independence Profile.64 A priori hypotheses are not stated, but the authors report that the canonic correlation between the PARTS/M satisfaction score and RNL was .71, and the canonic correlations between the RNL and the PARTS/M evaluative and environmental support component components were .99 and .59 (P⬍.001), respectively, for related Personal Independence Profile subscales. ● Test-retest reliability was evaluated in a subsample of 371 people after 6 to 8 weeks. Pearson correlations for participation domains were good for all participation domains (ranging from .71 for interpersonal interactions and relationships to .91 for self-care) and participation components (ranging from .75 for health-related limitations to .93 for amount of personal assistance). ● Strengths: The PARTS/M is based on extensive consumer input. It provides a detailed description of participation based on multiple ratings. ● Limitations: The PARTS/M is long and complex, although computer-administered formats include branching algorithms. Its scoring is complex. One quarter of the PARTS/M items are related to self-care. The PM-PAC was developed in the United States to measure participation outcomes in outpatient or home care settings.25 The 53-item PM-PAC is composed of 7 multi-item scales addressing 8 ICF domains including major life areas/economic life; community, social, and civic participation; mobility; interpersonal relationships; communication; domestic life; selfcare; and learning and applying knowledge. Average completion time is 13.6⫾4.5 minutes. A computerized adaptive test version of the participation measure for post-acute care (PMPAC-CAT) requires an average completion time of 5.7⫾2.4 minutes.65 ●





Scoring: The PM-PAC provides 7 domain scores and 2 overall scores (social and home; community). The scoring algorithm is not published. The psychometric properties of the PM-PAC were evaluated with a sample of patients receiving postacute care (n⫽395). Content validity: The PM-PAC was guided by the ICIDH-2 and was subsequently reconciled with the ICF. The authors developed definitions to distinguish activity and participation; separate scales were developed to measure each aspect. Seventeen items were selected from extant measures, and an additional 34 items were written to address novel aspects of the ICF. Qualitative item review was based on focus groups with rehabilitation patients. The PM-PAC was pilot-tested with a sample of 8 people with disabilities. Feedback was also elicited from 8 rehabilitation researchers. Construct validity: Multitrait scaling analysis was used to verify domain structure. Item-scale correlations were calculated and met an a priori standard (ⱖ.40) for all items except exercise. Scaling success was defined as the percentage of items a domain that correlated most strongly with their expected scale; values ranged from 77.8% for interpersonal relationships to 100% for role functioning, domestic life, and economic life. Confirmatory factor analysis supported the 7-factor model, although some factors were highly correlated. A second-level principal

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PARTICIPATION MEASURE REVIEW, Magasi Table 3: ICF Linking of Participation Outcome Measures ICF Code

IMPACT-S

IPA

KAP

LIFE-H

Chapter 1—Learning and Applying Knowledge D1 Learning and applying knowledge

x

x

Chapter 2—General Tasks and Demands D2 General tasks and demands D2400 Handling responsibilities

x x

x

Chapter 3—Communication D3 Communicating with—receiving—spoken messages D325 Communication with—receiving—written messages D330 Speaking D345 Writing messages D350 Conversation D3503 Conversing with 1 person D3504 Conversing with many people D3600 Using telecommunication devices D3601 Using writing machines Chapter 4—Mobility D410 Changing body position D4200 Transferring oneself while sitting D4201 Transferring oneself while lying D435 Moving objects with the lower extremities D440 Fine hand use D445 Hand and arm use D450 Walking D460 Moving around in different locations D4600 Moving around within the home D4601 Moving around within buildings other than home D4602 Moving around outside the home and other buildings D465 Moving around using equipment D470 Using transportation D4701 Using private motorized transportation D4702 Using public motorized transportation D475 Driving D4750 Driving human-powered transportation Chapter 5—Self-Care D5 Self-care D510 Washing oneself D5101 Washing whole body D520 Caring for body parts D530 Toileting Chapter 5—Self-Care (continued) D5300 Regulating urination D5301 Regulating defecation D540 Dressing D550 Eating D560 Drinking D570 Looking after one’s health D5701 Managing diet and fitness D5702 Maintaining one’s health D5708 Looking after one’s health, other specified Chapter 6—Domestic Life D6 Domestic life D610 Acquiring a place to live D620 Acquisition of goods and services D6200 Shopping D630 Preparing meals D6300 Preparing simple meals D640 Doing housework D6400 Washing and drying clothes and garments D6401 Cleaning cooking area and utensils

PAR-PRO

PM-PAC

P-Scale

PARTS/M

x x

x

x

x x

x x x x

x x

x x

x x

x

x x x x x x x

x x x

x x x x

x x x

x

x x

x

x

x

x

x x

x

x x

x

x

x x

x x

x

x

x

x

x x

x

x

x x

x

x x x

x x x x

x x

x x x x x

x x x

x x x

x

x

x

x x

x

x

x x x

x

x x x

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PARTICIPATION MEASURE REVIEW, Magasi Table 3 (Cont’d): ICF Linking of Participation Outcome Measures

ICF Code

D6402 D6403 D650 D6501 D6505 D6506 D660

IMPACT-S

Cleaning living area Using household appliances Caring for household objects Maintaining dwelling and furnishings Taking care of plants, indoors and outdoors Taking care of animals Assisting others

Chapter 7—Interpersonal Relationships D7 Interpersonal interactions and relationships D710 Basic interpersonal relationships D7200 Forming relationships D730 Relating with strangers D740 Formal relationships D7400 Relating with persons in authority D7401 Relating with subordinates D750 Informal social relationships D7500 Informal relationships with friends D7501 Informal relationships with neighbors D7502 Informal relationships with acquaintances D760 Family relationships D7600 Parent-child relationships D7601 Child-parent relationships D7602 Sibling relationships D7603 Extended family relationships D770 Intimate relationships D7701 Spousal relationships D7702 Sexual relationships Chapter 8—Major Life Areas D8 Major life areas D820 School education D825 Vocational education D830 Higher education D845 Acquiring, keeping, and terminating a job D8450 Seeking employment D8451 Maintaining employment D850 Remunerative employment D855 Nonremunerative employment D860 Basic economic transactions D865 Complex economic transactions D870 Economic self-sufficiency D8700 Personal economic resources D8701 Public economic entitlements Chapter 9—Community, Social, and Civic Life D9 Community, social, and civic life D910 Community life D9102 Ceremonies D920 Recreation and leisure D9200 Play D9201 Sports D9202 Arts and culture D9203 Crafts D9204 Hobbies D9205 Socializing D9300 Organized religion D930 Religion and spirituality D9301 Spirituality D950 Political life and citizenship

Arch Phys Med Rehabil Vol 91, Suppl 1, September 2010

IPA

KAP

LIFE-H

PAR-PRO

PM-PAC

P-Scale

PARTS/M

x x

x x x

x x

x

x

x

x

x

x

x x

x

x

x

x

x x x x

x x x

x x x x x

x

x x

x

x

x x

x x

x x x

x x x x x

x

x x

x

x

x x x x x x x x x x x

x x x

x x x x x

x x

x x x x x x

x x x

x x x x x

x x x x

x

x

x x x

x

x x x x x

x x x

x x

x

x

x

x x x x x x

x x

x x

x

x x x

x x

x x

x x x

x

x x x

x x x x x x x

x x

x

x

PARTICIPATION MEASURE REVIEW, Magasi







● ●

component analysis of the scale scores supported the extraction of 2 factors. Internal consistency as measured by the Cronbach alpha ranged from .72 to .89. Test-retest reliability was evaluated in a subsample of 36 people 1 to 15 days after their initial interview (ICCs ranged from .61 for role functioning to .86 for community, social, and civic participation). IRT analysis was used to verify the distinctiveness of response options, and generalized partial-credit IRT models were used to fit item response models. Role functioning items tended to misfit. Floor and ceiling effects: Most items are targeted at lowerfunctioning individuals and the most informative items vary by the severity of disability. Sensitivity and responsiveness to change of the 3 PMPAC domains associated with factor 1 were evaluated in a sample of adults with neurologic, orthopedic, and medically complex conditions (n⫽94) 2 weeks after discharge from inpatient rehabilitation and again 3 months later.65 Sensitivity was evaluated using paired t tests, standard response means, and effect size. Responsiveness to patient-reported changes was examined using area under paired ROC curves for each domain. Only the mobility score reached the threshold ROC curves greater than .70. The PM-PAC-CAT correlated highly with the PM-PAC (ICC, .71–.81) with only mild decrements in sensitivity and responsiveness.65 Strengths: The PM-PAC is psychometrically robust. The PM-PAC-CAT reduces respondent burden. Limitations: The PM-PAC combines objective and subjective ratings as a single construct and has uneven content coverage across domains. The PM-PAC is complex, using 12 rating scales. It may be inappropriate for people with cognitive impairments. No scoring algorithm is publicly available.

DISCUSSION This review revealed a robust set of measures with strong conceptual foundations (primarily the ICF) and promising psychometric properties. Except for the IPA and LIFE-H, psychometric testing is incomplete and relies on the efforts of the instruments’ developers. Use of the contemporary measures of participation included in this review has yet to be documented in the rehabilitation literature, with the notable exception of the IPA and LIFE-H. Use of the IPA and the LIFE-H has been reported widely in the research literature in a variety of clinical populations, yet these measures have not been universally endorsed and remain limited to their particular geographic regions. For example, the IPA has enjoyed widespread adoption in Europe for varied clinical populations,36-43 but there is no evidence of its use in the Americas, Asia, and Africa. The LIFE-H is the most widely cited participation instrument in the rehabilitation literature, yet most of the research using the LIFE-H has been reported by a prolific group of researchers from Quebec involved in the LIFE-H’s development. While their publication record is impressive, the LIFE-H has not been widely adopted. Given the relatively nascent state of participation measurement and in the absence of a criterion measure of participation, researchers and clinicians have a daunting task of selecting the optimal measure for their work. Our review of contemporary participation measures indicates that their psychometric properties are relatively robust, albeit incompletely reported in the published literature. We contend, therefore, that what truly distinguish measures of participation are conceptual and logistic considerations. We propose 3 guiding questions to help users select the most appropriate measure for their purpose. We outline the rationale for

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these questions and then illustrate how they can be used to prioritize the instruments included in this review. How Do I Define or Conceptualize Participation? The ICF defines participation as “involvement in life situations” and activities as “the execution of a task or action.” Yet in the final ICF taxonomy, the 2 concepts are merged with no clear delineation. The ICF provides 4 possible strategies for distinguishing activities from participation. Leaders in the field of disability research and measurement have called for greater conceptual clarity and proposed theoretic distinctions. To date, none of these distinctions has been supported empirically. Instrument developers made decisions about which of the ICF activity and participation domains to include in their instruments. For example, the PAR-PRO includes only ICF domains 6 to 9 because the other chapters were covered by the FIM and were associated with activities.22 The KAP excludes ICF domains 1 to 3 because the authors believe that these activities are not influenced by environmental factors.20 The IMPACT-S is unique among the measures in this review in testing its proposed division.18 Testing the distinction between activities and participation is not straightforward. If, for example, inability to speak is strongly associated with restrictions in social relations and both end up in the same component in a principal component analysis, we cannot conclude that the conceptual distinction between activities and participation is refuted. A careful interpretation might be that “involvement in life situations” is, in part, determined by underlying “task accomplishments.” Whiteneck and Dijkers5 explore these issues in detail. Until the field codifies the distinction between activities and participation, instrument users must decide what domains of participation they are interested in measuring. All the measures we reviewed include items reflecting the ICF domains of mobility; domestic life; social relationships; major life areas; and community, social, and civic life; only the PAR-PRO excludes self-care. The ICF rules can be applied to distinguish activities and participation, thus narrowing the choices of participation measures, as follows (see fig 1 for ICF chapters). ● ● ● ●

Designation of only chapters 4 and 6 to 9 as participation, with no overlap: PAR-PRO Designation of only chapters 4 to 9 as participation, with no overlap: IPA, KAP, PARTS/M Designation of chapters 4 to 9 as participation, with partial overlap: addition of P-Scale, PM-PAC Designation of all domains as both activities and participation: IMPACT-S, LIFE-H

Fig 1. ICF domains of activities and participation.

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PARTICIPATION MEASURE REVIEW, Magasi

The ICF domains represent broad categories with divergent content that require instrument users to select the specific item content they need to ensure that instruments are consistent with their target outcomes. Tables 2 and 3 provide a guide to determine the relative weight that each measure places on a domain and detailed linking to specific ICF codes. For example, both the IMPACT-S and LIFE-H assess all 9 domains. However, items in the IMPACT-S are evenly distributed across domains, while the LIFE-H content emphasizes domains 4 to 9. Similarly, the IPA, KAP, and PARTS/M cover domains 4 to 9; however, the distribution of items across domains varies greatly.

and computer-adaptive testing. For example, the PM-PACCAT halves the number of questions administered while maintaining good measurement properties.65 Other options are the use of gate questions to channel respondents to the most relevant items, and global questions with free field specifications for clinical applications. In the absence of a widely accepted criterion measure of participation, it is incumbent on users of participation instruments to consider carefully which instrument will best meet their needs. These guiding questions and the information contained in tables 1 to 3 can help researchers and clinicians make informed decisions about participation instruments.

What Aspect of Participation Am I Most Interested in Measuring? The participation measures evaluated in this review varied greatly in the aspects of participation that they address, as evidenced in the developers’ choice of item contexts and response options. These differences are not trivial, but serve to define and bound what aspects of participation are evaluated. For example, empirical evidence indicates that objective and subjective participation are only weakly correlated, with subjective performance more closely associated with quality of life or subjective well being.66 Furthermore, different rehabilitation stakeholders have different priorities vis-à-vis participation outcomes.67 For example, funders of rehabilitation services want objective measures of participation in paid work and level of assistance, whereas rehabilitation consumers are more interested in subjective appraisals about the abilities and opportunities to participate in activities of their choice. Instrument users should select instruments based on their measurement purpose. Figure 2 links aspects of participation with relevant candidate measures. Given the diversity of stakeholder needs and multifaceted nature of participation, a combined approach that offers multiple ratings may be the best direction for participation measurement.68,69

Study Limitations This review has several limitations. First, in order to focus on a contemporary definition of participation, we limited our review to generic measures of participation developed since 1998. It was beyond the scope of this work to evaluate the generalizability of measures to other impairment groups. Setting strict inclusion criteria enabled us to examine a select set of measures in detail. We also limited our search to instruments available in English and consequently may have missed relevant measures. Many of the instruments are just starting to appear in the peer-reviewed literature, and therefore, the data on instruments’ psychometric properties and utility are incomplete. Our intent was to provide a comparative review of contemporary participation measures before consensus has been established on conceptual models. Finally, while this comparative review was conducted using standard quality criteria for outcome measures,14,15 the complex nature of participation defies simple application of these criteria. For example, classical and contemporary measurement theories are based on assumptions of unidimensionality and a hierarchic latent trait, yet the existence of a single construct of “participatoriness” remains controversial.

What Level of Specificity Do I Need to Measure? Participation instruments vary widely in the level of detail they assess. Users must consider the response burden and complexity. Brief instruments allow routine outcome measurement and are useful in studies that use a broader battery of measures. Detailed measures like the LIFE-H and PARTS/M are best suited to clinical assessment and interventions. Instruments that offer a profile of participation with a small number of items like IMPACT-S, IPA, or PM-PAC may be the best choice in other situations. Before more specific recommendations for clinical applications can be made, additional data on sensitivity and responsiveness to change are required. Alternative methods should be considered to improve measurement precision and responsiveness, including the use of item banks

CONCLUSIONS This review provides a detailed comparison of 8 participation instruments, a table of the instruments’ psychometric properties, and ICF linkages to help researchers and clinicians select the most appropriate participation measure for their work. Participation instruments are not equivalent because, even when linked to a single ICF code, items represent different aspects of a dimension. We recommend careful examination of items to ensure that the selected instrument is aligned with the users’ conceptual definition and the outcomes of interest for clinical or research applications. We propose 3 questions to help guide that process: (1) What domains of participation do it want to measure? (2) What aspect of particpaition do I want to measure? (3) What level of specificity do I need to measure? Continuing development of participation measures should be based on sound conceptual models, empirical comparisons with existing measures, and state-of-the-art measurement technologies to revise robust and parsimonious measures of participation. Clinicians and researchers must carefully evaluate the pool of participation measures to ensure that they select the measure that best suits their intended research and outcome focus. Acknowledgments: We thank Allen Heinemann, PhD, ABPP (RP), FACRM for his editorial assistance with several early drafts of this article.

Fig 2. Aspects of participation candidate measures.

Arch Phys Med Rehabil Vol 91, Suppl 1, September 2010

References 1. Preamble to the Constitution of the World Health Organization as adopted by the International Health Conference, New York, 19-22

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2.

3.

4.

5.

6.

7. 8.

9.

10.

11.

12.

13.

14.

15.

16. 17.

18.

19.

20.

June, 1946; signed on 22 July 1946 by the representations of 61 States (Official Records of the World Health Organization, no.2, p. 100) and entered into force on 7 April 1948. The Definition has not been amended since 1948. Dijkers MP, Whiteneck G, El Jaroudi R. Measures of social outcomes in disability research. Arch Phys Med Rehabil 2000; 81(suppl 2):S63-80. World Health Organization. International classification of impairments, disabilities, and handicaps: a manual of classification relating to the consequences of disease. Geneva: World Health Organization; 1980. World Health Organization. International Classification of Functioning, Disability and Health (ICF). Geneva: World Health Organization; 2001. Whiteneck G, Dijkers MP. Difficult to measure constructs: conceptual and methodological issues concerning participation and environmental factors. Arch Phys Med Rehabil 2009;90:S22-35. Badley EM. Enhancing the conceptual clarity of the activty and participation components of the International Classification of Functioning, Disability and Health in clinical settings. Soc Sci Med 2007;44:113-22. Americans with Disabilities Act of 1990, P.L. 101-336. 42 U.S.C.A. §12132 (1990). United States Department of Health and Human Services. The New Freedom Initiative. February 1, 2001. Available at: http:// www.cms.hhs.gov/NewFreedomInitiative. Accessed: March 17, 2009. Resnik L, Plow MA. Measuring participation as defined by the International Classification of Functioning, Disability and Health: an evaluation of existing measures. Arch Phys Med Rehabil 2009;90:856-66. Noonan VK, Kopec JA, Noreau L, Singer J, Dvorak MF. A review of participation instruments based on the International Classification of Functioning, Disability and Health. Disabil Rehabil 2009; 31:1883-901. Noonan V, Kopec J, Noreau L, Singer J, Chan A, Masse L, Dvorak M. Comparing the content of participation instruments using the International Classification of Functioning, Disability and Health. Health Qual Life Outcomes 2009;7:93. Coster W, Khetani MA. Measuring participation of children with disabilities: issues and challenges. Disabil Rehabil 2008;30: 639-48. McConachie H, Colver AF, Forsyth RJ, Jarvis SN, Parkinson KN. Participation of disabled children: how should it be characterised and measured? Disabil Rehabil 2006;28:1157-64. Terwee CB, Bot SD, de Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol 2007;60:34-42. Visser-Meily JM, Post MW, Riphagen II, Lindeman E. Measures used to assess burden among caregivers of stroke patients: a review. Clin Rehabil 2004;18:601-23. Wright BD, Masters GN. Rating scale analysis: Rasch measurement. Chicago: MESA Pr; 1982. Cieza A, Geyh S, Chatterji S, Kostanjsek N, Ustun B, Stucki G. ICF linking rules: an update based on lessons learned. J Rehabil Med 2005;37:212-8. Post MW, de Witte LP, Reichrath E, Verdonschot MM, Wijlhuizen GJ, Perenboom RJ. Development and validation of IMPACT-S, an ICF-based questionnaire to measure activities and participation. J Rehabil Med 2008;40:620-7. Cardol M, de Haan RJ, van den Bos GA, De Jong BA, de Groot IJ. The development of a handicap assessment questionnaire: the Impact on Participation and Autonomy (IPA). Clin Rehabil 1999; 13:411-9. Wilkie R, Peat G, Thomas E, Hooper H, Croft PR. The Keele Assessment of Participation: a new instrument to measure partic-

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

32.

33.

34.

35.

36.

37. 38.

39.

S27

ipation restriction in population studies. Combined qualitative and quantitative examination of its psychometric properties. Qual Life Res 2005;14:1889-99. Fougeyrollas P, Noreau L, Bergeron H, Cloutier R, Dion SA, St Michel G. Social consequences of long term impairments and disabilities: conceptual approach and assessment of handicap. Int J Rehabil Res 1998;21:127-41. Ostir GV, Granger CV, Black T, et al. Preliminary results for the PAR-PRO: a measure of home and community participation. Arch Phys Med Rehabil 2006;87:1043-51. Gray DB, Hollingsworth HH, Stark SL, Morgan KA. Participation survey/mobility: psychometric properties of a measure of participation for people with mobility impairments and limitations. Arch Phys Med Rehabil 2006;87:189-97. van Brakel WH, Anderson AM, Mutatkar RK, et al. The Participation Scale: measuring a key concept in public health. Disabil Rehabil 2006;28:193-203. Gandek B, Sinclair SJ, Jette AM, Ware JE, Jr.Development and initial psychometric evaluation of the participation measure for post-acute care (PM-PAC). Am J Phys Med Rehabil 2007;86: 57-71. Vazirinejad R, Lilley JM, Ward CD. The “Impact on Participation and Autonomy”: acceptability of the English version in a multiple sclerosis outpatient setting. Mult Scler 2003;9:612-5. Kersten P, Cardol M, George S, Ward C, Sibley A, White B. Validity of the impact on participation and autonomy questionnaire: a comparison between two countries. Disabil Rehabil 2007; 29:1502-9. Lund ML, Fisher AG, Lexell J, Bernspang B. Impact on participation and autonomy questionnaire: internal scale validity of the Swedish version for use in people with spinal cord injury. J Rehabil Med 2007;39:156-62. Cardol M, de Haan RJ, De Jong BA, van den Bos GA, de Groot IJ. Psychometric properties of the Impact on Participation and Autonomy Questionnaire. Arch Phys Med Rehabil 2001;82:210-6. Sibley A, Kersten P, Ward CD, White B, Mehta R, George S. Measuring autonomy in disabled people: validation of a new scale in a UK population. Clin Rehabil 2006;20:793-803. Franchignoni F, Ferriero G, Giordano A, Guglielmi V, Picco D. Rasch psychometric validation of the Impact on Participation and Autonomy questionnaire in people with Parkinson’s disease. Eura Medicophys 2007;43:451-61. Harwood RH, Rogers A, Dickinson E, Ebrahim S. Measuring handicap: the London Handicap Scale, a new outcome measure for chronic disease. Qual Health Care 1994;3:11-6. Post MW, De Bruin AF, De Witte L, Schrijvers A. The SIP68: a measure of health-related hunctional status in rehabilitation medicine. Arch Phys Med Rehabil 1996;77:440-5. Ware JE, Snow KK, Kosinski M, Gandek B. SF-36 health survey: manual and interpretation guide. Boston: The Health Institute, New England Medical Center; 1993. Cardol M, Beelen A, van den Bos GA, De Jong BA, de Groot IJ, de Haan RJ. Responsiveness of the Impact on Participation and Autonomy questionnaire. Arch Phys Med Rehabil 2002;83: 1524-9. Lund ML, Lexell J. Associations between perceptions of environmental barriers and participation in persons with late effects of polio. Scand J Occup Ther 2009:16:194-204. Lund ML, Lexell J. Perceived participation in life situations in persons with late effects of polio. J Rehabil Med 2008;40:659-64. Nieuwenhuijsen C, van der LY, Donkervoort M, Nieuwstraten W, Roebroeck ME, Stam HJ. Unmet needs and health care utilization in young adults with cerebral palsy. Disabil Rehabil 2008;30: 1254-62. van de Port IG, van den Bos GA, Voorendt M, Kwakkel G, Lindeman E. Identification of risk factors related to perceived Arch Phys Med Rehabil Vol 91, Suppl 1, September 2010

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40.

41.

42.

43.

44.

45.

46.

47.

48.

49.

50. 51.

52.

53. 54.

PARTICIPATION MEASURE REVIEW, Magasi

unmet demands in patients with chronic stroke. Disabil Rehabil 2007;29:1841-6. Lund ML, Nordlund A, Bernspang B, Lexell J. Perceived participation and problems in participation are determinants of life satisfaction in people with spinal cord injury. Disabil Rehabil 2007;29:1417-22. Larsson LM, Nordlund A, Nygard L, Lexell J, Bernspang B. Perceptions of participation and predictors of perceived problems with participation in persons with spinal cord injury. J Rehabil Med 2005;37:3-8. Kos D, Duportail M, D’Hooghe M, Nagels G, Kerckhofs E. Multidisciplinary fatigue management programme in multiple sclerosis: a randomized clinical trial. Mult Scler 2007;13:9961003. Middelkamp W, Moulaert VR, Verbunt JA, van Heugten CM, Bakx WG, Wade DT. Life after survival: long-term daily life functioning and quality of life of patients with hypoxic brain injury as a result of a cardiac arrest. Clin Rehabil 2007;21:425-31. Wood-Dauphinee SL, Opzoomer MA, Williams JI, Marchand B, Spitzer WO. Assessment of global function: the Reintegration to Normal Living Index. Arch Phys Med Rehabil 1988;69:583-90. Wilkie R, Peat G, Thomas E, Croft P. Factors associated with participation restriction in community-dwelling adults aged 50 years and ver. Qual Life Res 2007;16:1147-56. Dumont C, Bertrand R, Fougeyrollas P, Gervais M. Rasch modeling and the measurement of social participation. J Appl Meas 2003;4:309-25. Noreau L, Fougeyrollas P, Labbe A, Laramee MT. Comparison of two measurement tools addressing the concept of handicap: CHART and LIFE-H. J Spinal Cord Med 1998;21:151. Noreau L, Fougeyrollas P. Long-term consequences of spinal cord injury on social participation: the occurrence of handicap situations. Disabil Rehabil 2000;22:170-80. Lemmens J, van Engelen ISM, Post MW, Beurskens AJ, Wolters PM, de Witte LP. Reproducibility and validity of the Dutch Life Habits Questionnaire (LIFE-H 3.0) in older adults. Clin Rehabil 2007;21:853-62. Noreau L, Fougeyrollas P, Vincent C. The LIFE-H: assessment of the quality of social participation. Technol Disabil 2002;14:113-8. Noreau L, Desrosiers J, Robichaud L, Fougeyrollas P, Rochette A, Viscogliosi C. Measuring social participation: reliability of the LIFE-H in older adults with disabilities. Disabil Rehabil 2004;26: 346-52. Gagnon C, Mathieu J, Noreau L. Measurement of participation in myotonic dystrophy: reliability of the LIFE-H. Neuromuscul Disord 2006;16:262-8. Poulin V, Desrosiers J. Participation after stroke: comparing proxies’ and patients’ perceptions. J Rehabil Med 2008;40:28-35. Michelsen SI, Flachs EM, Uldall P, et al. Frequency of participation of 8-12-year-old children with cerebral palsy: a multi-centre

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55.

56.

57.

58. 59.

60.

61. 62. 63.

64.

65.

66.

67.

68.

69.

cross-sectional European study. Eur J Paediatr Neurol 2009;13:165-77. van Meeteren J, Roebroeck ME, Celen E, Donkervoort M, Stam HJ. Functional activities of the upper extremity of young adults with cerebral palsy: a limiting factor for participation? Disabil Rehabil 2008;30:387-95. Desrosiers J, Noreau L, Rochette A, Bravo G, Boutin C. Predictors of handicap situations following post-stroke rehabilitation. Disabil Rehabil 2002;24:774-85. Desrosiers J, Rochette A, Noreau L, Bravo G, Hebert R, Boutin C. Comparison of two functional independence scales with a participation measure in post-stroke rehabilitation. Arch Gerontol Geriatr 2003;37:157-72. Rochette A, Desrosiers J. Coping with the consequences of a stroke. Int J Rehabil Res 2002;25:17-24. Desrosiers J, Robichaud L, Demers L, Gelinas I, Noreau L, Durand D. Comparison and correlates of participation in older adults without disabilities. Arch Gerontol Geriatr 2009;49:397403. Demers L, Fuhrer MJ, Jutai JW, Scherer MJ, Pervieux I, DeRuyter F. Tracking mobility-related assistive technology in an outcomes study. Assist Technol 2008;20:73-83. Dijkers MP. Comments on van Brakel et al.’s Participation Scale. Disabil Rehabil 2006;28:1360-2. van Brakel WH. Participation Scale users manual v. 5.2. Amsterdam: KIT Leprosy Unit; 2008. Granger CV, Hamilton BB, Linacre JM, Heinemann AW, Wright BD. Performance profiles of the functional independence measure. Am J Phys Med Rehabil 1993;72:84-9. Nosek MA, Fuhrer MJ, Howland CA. Independence among people with disabilities, II: personal independence profile. Rehabil Counseling Bull 1992;36:21-36. Haley SM, Gandek B, Siebens H, et al. Computerized adaptive testing for follow-up after discharge from inpatient rehabilitation, II: participation outcomes. Arch Phys Med Rehabil 2008;89: 275-83. Dijkers M. “What’s in a name?” The indiscriminate use of the “quality of life” label, and the need to bring about clarity in conceptualizations. Int J Nurs Stud 2007;44:153-5. Magasi S, Hammel J, Heinemann AW, Whiteneck GG, Bogner J. Participation: a comparative analysis of multiple rehabilitation stakeholders’ perspectives. J Rehabil Med 2009;41:936-44. Magasi S, Heinemann AW. Integrating stakeholder perspectives in outcome measurement. J Neuropsychol Rehabil 2009;19: 928-40. Brown M, Dijkers MP, Gordon WA, Ashman T, Charatz H, Cheng Z. Participation objective, participation subjective: a measure of participation combining outsider and insider perspectives. J Head Trauma Rehabil 2004;19:459-81.

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