Association of Environmental Factors With Levels of Home and Community Participation in an Adult Rehabilitation Cohort

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ORIGINAL ARTICLE

Association of Environmental Factors With Levels of Home and Community Participation in an Adult Rehabilitation Cohort Julie J. Keysor, PhD, PT, Alan M. Jette, PhD, PT, Wendy Coster, PhD, OTR, Janet Prvu Bettger, ScD, TRS, Stephen M. Haley, PhD, PT ABSTRACT. Keysor JJ, Jette AM, Coster W, Bettger JP, Haley SM. Association of environmental factors with levels of home and community participation in an adult rehabilitation cohort. Arch Phys Med Rehabil 2006;87:1566-75. Objective: To examine whether home and community environmental barriers and facilitators are predictors of social and home participation and community participation at 1 and 6 months after discharge from an acute care or inpatient rehabilitation hospital. Design: Cohort study. Setting: Postacute care. Participants: Adults (N⫽342) age 18 years or older with a diagnosis of complex medical, orthopedic, or neurologic condition recruited from acute care and inpatient rehabilitation facilities. The mean age ⫾ standard deviation of participants was 68⫾14 years; 49% were women and 92% were white. Interventions: Not applicable. Main Outcome Measures: Participation in social, home and community affairs as assessed with the Participation Measure for Post-Acute Care. Results: Adjusting for covariates, 1 month after discharge a greater presence of home mobility barriers (P⬍.01) was associated with less social and home participation; whereas greater community mobility barriers (P⬍.01) and more social support (P⬍.001) were associated with greater participation. At 6 months, social support was the only environmental factor associated with participation after adjusting for covariates. Conclusions: This study provides new empirical evidence that environmental barriers and facilitators do influence participation in a general rehabilitation cohort, at least in the short term. Key Words: Disabled persons; Environment; Outcome assessment (health care); Rehabilitation. © 2006 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

From the Departments of Physical Therapy and Athletic Training (Keysor) and Occupational Therapy and Rehabilitation Counseling (Coster) and ScD Program in Rehabilitation Science (Prvu Bettger), Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA; and Health and Disability Research Institute, Boston University School of Public Health, Boston, MA (Jette, Haley). Presented in part to the American Congress of Rehabilitation Medicine, September 28⫺October 2, 2005, Chicago, IL. Supported by the National Institute of Disability and Rehabilitation Research, U.S. Department of Education (grant no. H133B990005), the National Institute of Child Health and Human Development (grant no. 5 K12 HD043444-02), and the Arthritis Foundation (arthritis investigator award). No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the author(s) or upon any organization with which the author(s) is/are associated. Reprint requests to Julie J. Keysor, PhD, PT, Sargent College of Health and Rehabilitation Services, Boston University, 635 Commonwealth Ave, Rm 521, Boston, MA 02215, e-mail: [email protected]. 0003-9993/06/8712-10803$32.00/0 doi:10.1016/j.apmr.2006.08.347

Arch Phys Med Rehabil Vol 87, December 2006

NVIRONMENTAL FACTORS ARE hypothesized to be E crucial determinants of people’s participation in daily life activities, yet there is little empirical evidence to support this 1-7

notion. Mobility barriers in a home (eg, stairs or doors) may limit one’s ability to function in that home, whereas mobility barriers in the community (eg, uneven sidewalks or curbs without curb-cuts) may limit one’s involvement in community activities. Conversely, mobility adaptive technologies (eg, walkers or wheelchairs) may enhance a person’s participation in daily life by providing some physical assistance with performance of specific tasks, while transportation facilitators (eg, availability of a car or public transportation) could result in greater involvement in community activities. Gaining a clearer perspective on how the environment is related to participation has important clinical and policy implications. First, the impact of environmental barriers and facilitators on participation could explain the apparent paradox often seen in clinical care: people who have the same severity of disease and level of impairment often function differently in daily life. For example, a person with knee osteoarthritis who has limited functional mobility may live in a community that has many architectural and physical barriers and few transportation facilitators may be quite limited in community activities, while another person with a similar clinical profile may be heavily engaged in community activities. Also, if environmental factors are indeed central to a person’s ability to participate in life role activities, health care providers could focus patient education on overcoming barriers that pose threats to involvement in life activities. Third, policy changes could be enacted to minimize barriers and enhance facilitators through changes in regulations, insurance, and modifications to the environment. The International Classification of Functioning, Disabilities and Health (ICF)7 framework explicitly states that participation is influenced by the environmental context in which people live. In the ICF model, the environmental context is described as the social and physical circumstances in which a person lives,7 with the 5 environmental domains specified: (1) products and technology; (2) natural environment and human-made changes; (3) support and relationships; (4) attitudes; and (5) services, systems, and policies.7 The ICF environmental framework is similar to frameworks that have been advocated by other investigators.2,8 Reports in the literature have shown that people with mobility limitations report that certain social, technologic, and environmental barriers affect their participation, but the impact may not be as large as once thought.9-13 Whiteneck et al9 reported that environmental barriers explained a modest amount of variance in participation restriction (⬎5% variance) among a population of 2726 people with spinal cord injury. When demographic, impairment, and activity variables were included in the models, environmental barriers generally did not contribute significantly to the variance explained in participation restriction. Similar findings were reported in other

ENVIRONMENT AND PARTICIPATION OUTCOMES, Keysor

studies, with environmental factors explaining 6%14 and 8%15 of the variance in participation. Badley et al,15 in a crosssectional population-based study of 16,017 persons with selfreported arthritis-associated disability, reported that modifications to a kitchen were associated with less dependence in external household activities and domestic activities of daily living (ADLs). In contrast, a modified bathroom, a cane, and other mobility aids were associated with more disability in domestic and personal care ADLs. This finding may indicate a greater need for mobility assistive technologies among people with disabilities, but does not support the belief that facilitative environments contribute significantly to greater participation. A randomized controlled trial16 involving 104 communitydwelling frail elderly people who received adaptive technologies and modifications to home environments showed that there was no beneficial effect on participation after 18 months. There were, however, slower declines of functional loss and less use of health care services, including institutional care, among subjects who received adaptive technologies and environmental modifications. We undertook this study to further our understanding of whether and how environmental barriers and facilitators were related to participation in a cohort of adults receiving rehabilitation services. We examined participation in 2 areas: (1) social and home participation, which is related to self-care and domestic functioning, financial functioning, social relationships, and communication; and (2) community participation, which reflects participation related to a person’s mobility, functioning in work, and other ADLs. The cohort was assessed 1 and 6 months after discharge from a hospital. Using the ICF,7 we sought to understand the participation-environment relationship. Specifically, we addressed the following hypotheses: (1) mobility barriers at home would be associated with less social and home participation; (2) community mobility barriers would be associated with less community participation; (3) mobility technology facilitators would be associated with greater community and social and home participation; (4) communication technology facilitators would be associated with greater social and home participation; (5) transportation facilitators would be associated with more community participation; and (6) social support would be associated with greater social and home participation. METHODS Sample Selection and Recruitment The Rehabilitation Outcomes Study (ROS) was a prospective cohort study of 516 adults age 18 years old and older who were recruited on discharge from a large acute care hospital, or on admission to 1 of 2 rehabilitation hospitals after discharge from an acute care hospital in the greater Boston region. Participants in the ROS were interviewed at 1, 6, and 12 months after discharge from the acute care or rehabilitation hospital, regardless of where they were living (eg, in the community or in a nursing home). Inclusion criteria for the ROS included a primary diagnosis of neurologic disorder, lower-extremity orthopedic trauma, or medically complex conditions; currently receiving, or about to be referred to, skilled rehabilitation services (physical therapy, occupational therapy, or speech and language pathology); able to speak and understand English; and a prognosis for survival of 1 year, as determined by the participant’s primary care physician or a facility recruiter through review of medical records. Exclusion criteria included inability to give informed consent, as indicated by information in the medical record and/or discussions with treating clinicians, any orientation deficit, difficulty re-

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membering the day’s events, and receptive or expressive communication deficits that precluded the patient from communicating responses reliably (verbally or nonverbally). Details of the recruitment strategy have been previously described.17 Participation and environmental surveys were administered to the 342 participants (of the original cohort of 516) who were living in the community at the 1-month follow-up. Participants who were in a hospital, rehabilitation center, or nursing home at this follow-up were not administered these 2 surveys. Of the 174 participants not completing participation and environment 1-month follow-up interviews, 74 (43%) were not living in the community, 15 (9%) were deceased, and 85 (49%) dropped out or refused the interview because they were too sick, could not be located, or cited other reasons. These 342 communitydwelling subjects comprise this study’s cohort. Of the 342 subjects who completed the surveys, 23 were missing data on educational attainment, functional status, applied cognitive status, or social support. An additional 23 participants were missing data on community mobility barriers or reported they “did not know” about the barrier (“did not know” was coded to missing), total home barriers, basic mobility devices, or communication devices. Much of the missing environment data pertained to community mobility barriers. Observations with missing data were omitted from multivariate regression analyses. Analyses with and without missing data showed that there were no differences regarding age, sex, race, educational attainment, or disease severity. Of the 342 participants, 283 (83%) completed the participation component of the 6-month follow-up. Of the 59 who did not, 9 (15%) were in a hospital, rehabilitation center, or nursing home and were not included in the participation assessment, 10 (17%) had died, 17 (29%) had dropped from the study, and 23 (39%) were lost to follow-up. Characteristics of those lost to follow-up at 6 months did not differ from those of participants with respect to age, education, disease severity, and 1-month participation levels. There were, however, differences in baseline functional status (P⫽.04) and race (P⫽.03), with patients with worse physical functioning or who were not white being more likely to be lost to follow-up. Data Collection A trained data collector conducted the 45- to 60-minute interviews with each patient at 1 and 6 months at the subjects’ current living location or at a mutually convenient location. Data collected at baseline and at the 2 later interviews included demographic factors, disease impairment groups, cognitive status, and severity of illness. Data were collected at 1- and 6-month interviews on functional activity (applied cognition and physical and mobility activity), environmental barriers and facilitators, and participation. Demographic variables. The data collector abstracted information on a patient’s age, sex, and race from the medical record. Age was scored as a continuous variable in years; sex was coded as 1 for male and 2 for female; and race was coded as 1 for white and 2 for nonwhite. Impairment groups. Patients’ medical records were abstracted to identify the primary condition for which the patient was receiving rehabilitation services: neurologic, lower-extremity orthopedic, or complex medical. Neurologic impairment was defined as a central nervous system impairment affecting mobility (cerebrovascular accident, Guillain-Barré syndrome, Parkinson’s disease, multiple sclerosis, traumatic brain injury). A lower-extremity orthopedic condition was defined as a traumatic (as contrasted with degenerative) impairment of a lower extremity, including pelvis (hip fracture, hip replacement, femur fracture, or lower-extremity amputation). Arch Phys Med Rehabil Vol 87, December 2006

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ENVIRONMENT AND PARTICIPATION OUTCOMES, Keysor Table 1: Descriptive Statistics of Home and Community Environment Subscale Items by Major Diagnostic Group* Home and Community Environment

Home mobility barriers Type of home Single family Assisted living Steps at main entrance of home (several) Railing at steps (% yes) Steps inside main living area (% none) Community mobility barriers Uneven sidewalks or other walking areas (some or many⫽barrier present) Parks and walking areas that are easy to get to and easy to use (none⫽barrier present) Curbs with curb cuts (none⫽barrier present) Mobility technology facilitators Manual wheelchair (% yes) Electric wheelchair or scooter (% yes) Walker (% yes) Cane or crutch (% yes) Bedside commode, raised toilet seat or grab bars near commode (% yes) Grab bars or bench in tub or shower (% yes) Reachers (% yes) Communication technology facilitators Communicate aids Computer Transportation facilitators Car available at home Do you drive Public transportation close to home (some or a lot)

Overall

Major Neurologic

Lower Extremity Orthopedic

Complex Medical

55 3 56 66 53

60 4 64 68 46

54 5 52 63 58

53 2 55 68 54

74

80

80

67

9

4

10

10

5

4

5

5

37 3 61 75 65

26 4 42 71 45

50 1 72 88 83

34 4 63 68 62

76

78

76

75

51

34

68

47

4 52

10 60

3 56

3 44

81 32 75

82 32 78

85 21 74

78 38 73

NOTE. Values are percent. *Not all subscale items are shown.

Complex medical impairments were defined as conditions that were not (immediately) life threatening, but that placed the subject at risk for debility and/or functional limitations (eg, chronic obstructive pulmonary disease, various cardiovascular conditions including myocardial infarction and heart surgery, and postsurgical debility). Severity of illness. We used the adjusted diagnosis groups (ADGs), a diagnosis-based case-mix severity measure based on International Classification of Diseases, 9th revision, codes, sex, and age, to assess severity of illness. The ADG system assigns patients to 1 of 32 diagnostic groups based on clinical dimensions such as duration and severity.18 The ADG system is based on the premise that a patient’s illness burden, or “clustering of morbidity,” characterizes the need for health services better than does the presence of specific diseases.19,20 The ADG system has good predictive ability for explaining variation in utilization of health care services.21 Home and Community Environment. The Home and Community Environment (HACE)22 is a 36-item instrument that assesses environmental barriers and facilitators in 6 domains: (1) home mobility, (2) community mobility, (3) basic mobility devices, (4) communication devices, (5) transportation factors, and (6) attitudes. Five subscales— home mobility barriers, community mobility barriers, mobility adaptive technologies, communication technologies, and transportation facilitators—were used for these analyses (see table 1 for examples of survey items). The home mobility domain consists of 9 Arch Phys Med Rehabil Vol 87, December 2006

items that assess the degree to which architectural barriers are present in a subject’s home. The scale ranges from 0 to 10 points, with higher scores indicating more barriers. The community mobility domain consists of 5 items scored to reflect the presence of architectural barriers in the community. Scores range from 0 to 5, with higher scores indicating more barriers. The basic mobility devices domain consists of 9 items summed to represent the number of mobility assistive technologies in one’s environment. Scores range from 0 to 9, with higher scores indicating more devices. In similar fashion, the communication devices score consists of 4 items that are summed to reflect the number of such devices in one’s environment. Scores range from 0 to 4, with higher scores indicating the availability of more communication technologies. The transportation-domain consists of 2 items pertaining to driving, 2 items pertaining to public transportation, and 1 item pertaining to handicapped parking availability. Scoring is from 0 to 5, with higher scores indicating more transportation opportunities. Social support. We used the Medical Outcomes Study (MOS) Social Support Survey23 to assess the social aspects of one’s environment. It assesses the level of emotional, tangible, affectionate, and positive social interaction support. We used the total summary scale for these analyses, with scores ranging from 0 to 100, with a high score reflecting more social support. Activity outcomes. Data on activity outcomes were collected using the short-form version of the Activity Measure

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ENVIRONMENT AND PARTICIPATION OUTCOMES, Keysor

for Post Acute Care (AM-PAC).24 We used 2 subscales of the AM-PAC for these analyses: physical and mobility and applied cognitive.25 Each scale consists of 10 items that ask about either the difficulty in (5-point rating), or the use of, assistance (6-point rating) to perform specified activities in that domain (eg, move from bed to chair, communicate with family, walk in the community). Raw summary scores for the 2 versions in each activity domain were transformed to interval-level scores along the same difficulty continuum (for that dimension), which were established using Rasch partial-credit methods. Scores range from 0 to 100, with higher scores reflecting greater function (less difficulty, less use of assistance). Test-retest reliability estimates for the longer AM-PAC versions from which these short forms were derived ranged from .91 to .97.26 Participation outcomes. We collected data on participation using the Participation Measure for Post-Acute Care (PMPAC),27 a 48-item self-report instrument designed to measure participation outcomes based on the ICF.17 The short-form PM-PAC asks patients to rate their participation restrictions across 7 domains: mobility; community, social and civic life; role functioning; self-care/domestic life; home management and finances; social relationships; and communication. The PM-PAC was initially tested on 395 rehabilitation patients 18 to 100 years of age (mean, 60y). Test-retest scale scores were in the acceptable range for aggregate comparisons (intraclass correlation coefficient range, .61⫺.86). The 7 participation domains are organized into 7 subscales. The mobility functioning subscale assesses the extent to which people are limited in about their homes and communities (eg, “How much are you currently limited in getting around your home? How much are you currently limited in getting around offices, stores, or public buildings?”). The community, civic and social functioning subscale assesses the extent to which people are limited in community activities (eg, doing recreational or leisure activities or going to movies, plays and concerts, sporting events, museums or similar activities). The role functioning subscale assesses limitations in work-related activities (eg, “How much of the time have you accomplished less than you would like?”). The self-care/domestic life subscale assesses the extent to which people are limited in maintaining their homes and in personal care (eg, keeping your home clean and fixed up, providing personal care to others). The home management and finances subscale assesses the extent to which people are limited in taking care of their finances (eg, “How much are you currently limited in managing your own money?”). The social relationship subscale assesses the extent to which people are limited in having relationships with other people (eg, “How satisfied are you with the general quality of your relationships with family and friends?”). The communication subscale assesses the extent to which people are limited in communicating with others (eg, “How much are you currently limited in reading books, magazines and newspapers, or listening to recordings on tape?”). Further factor analysis of the PM-PAC subscales identified 2 summary scales. The first, social and home participation, reflects participation as it relates to a person’s self-care and domestic, financial, social relationship, and communication functioning. The second scale, community participation, reflects a person’s mobility, community, civic and social, and role functioning. These summary scores were based on z transformations of 7 subscale scores that were weighted using factor score coefficients and then transformed to a T scale with a mean of 50 and standard deviation (SD) of 10.17

Table 2: Characteristics of Participants (Nⴝ342) Characteristics

Sex Female Race White Nonwhite Education High school or more Less than high school Impairment group Complex medical Lower extremity Orthopedic Major neurologic Continuous Variables Age (y) Disease severity score Mobility and physical function (range, 0⫺100) Applied cognition (range, 0⫺100)

Frequency (%)

169 (49) 314 (92) 28 (8.1) 297 (91) 31 (9) 152 (44) 112 (33) 78 (23) Mean ⫾ SD 68⫾14 5⫾6 57⫾9 81⫾16

Statistical Analysis We generated descriptive statistics for independent, dependent, and covariate variables. Bivariate analyses using Pearson correlation coefficients were performed to examine whether each HACE environmental domain and social support were associated with the social and home participation and community participation summary scales. Adjusted multivariable regression models were used to examine whether the HACE domains and social support were associated with 1-month participation after adjusting for age, sex, race, educational attainment, disease severity, functional activity, and applied cognition. For longitudinal analyses, we used adjusted multiple regression models to examine whether the HACE domains and social support were associated with 6-month social and home participation and community participation after adjusting for age, sex, race, educational attainment, disease severity, functional activity, applied cognition, and 1-month participation. We used unadjusted and adjusted multivariate regression models to examine whether environmental factors were associated with each of the 7 subscales of the PM-PAC at the 1-month time-point. The HACE environmental domains and social support were entered simultaneously into the models with 1 of the 7 subscales of the PM-PAC. Adjusted models included age, sex, race, educational attainment, disease severity, functional activity, and applied cognition. For longitudinal analyses, we entered the HACE environmental domains and social support simultaneously into the models with 1 of the 7 subscales of the PM-PAC survey completed at the 6-month time-point. Adjusted models included age, sex, race, educational attainment, disease severity, functional activity, and applied cognition. The HACE and PM-PAC summary subscales were used in all analytical procedures as continuous variables. Descriptive statistics of these variables supported parametric statistics, with the exception of community barriers, which was skewed. Age, disease severity, functional activity, and applied cognition were used as continuous variables and educational attainment, race, and sex were categorical. SASa was used for all analyses. RESULTS The mean age of participants was 68 years (range, 19⫺100y); 49% were women and 92% were white (table 2). Arch Phys Med Rehabil Vol 87, December 2006

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ENVIRONMENT AND PARTICIPATION OUTCOMES, Keysor Table 3: Descriptive Statistics of Environment and Participation at 1 Month and 6 Months Environment and Participation

1 Month (N⫽342)

6 Months (n⫽283)

Community participation* Mobility functioning Community, civic & social functioning Role functioning Social and home participation* Self-care & domestic functioning Financial functioning Social relations functioning Communication functioning Environmental factor Home mobility barriers (range, 0⫺9) Community mobility barriers (range, 0⫺4) Mobility technology facilitators (range, 0⫺9) Communication technology facilitators (range, 0⫺4) Transportation facilitators (range, 0⫺5) Social support*

48.1⫾12.2 49.3⫾10.7 48.3⫾0.7 48.4⫾0.7 57.0⫾6.7 55.9⫾7.5 52.8⫾3.1 51.4⫾6.9 53.7⫾6.1

58.3⫾11.8 56.3⫾9.5 55.0⫾9.2 56.0⫾10.0 55.7⫾5.7 57.2⫾6.3 52.9⫾4.0 52.7⫾1.19 54.9⫾5.4

3.0⫾2.1 0.7⫾0.9 3.9⫾2.0 1.0⫾1.0 3.2⫾1.2 83⫾19

NR NR NR NR NR NR

NOTE. Values are mean ⫾ SD. Abbreviation: NR, data at 6 months for environmental factors not reported because only baseline scores were used as a predictor. *Scale scores range 0 to 100.

The most frequent primary rehabilitation diagnosis was “complex medical,” followed by hip fracture or multitrauma orthopedic, and then neurologic. Participants reported on average 3 home barriers and less than 1 barrier in their community (table 3). Table 1 summarizes the types of barriers and facilitators in the cohort’s environment. The majority of participants lived in single-family homes or apartments or condominiums and reported that there were several steps with railing at the entrance to their homes. Approximately one half of the participants reported stairs inside their main living area. Approximately 75% of the participants reported uneven sidewalks or other walking areas, and 10% reported that there were no places to sit and rest in their community. An average of 4 mobility technology facilitators was reported whereas, on average, 1 communication facilitator were reported. Walkers, canes (or crutch), commode adaptations, and shower adaptations were the most frequently reported mobility technologies. Access to a computer was the most frequently reported communication facilitator. With the exception of mobility technology facilitators, reports of the environmental barriers and facilitators were generally similar among subjects in the 3 major diagnostic groups (ie, major neurologic, lower-extremity orthopedic, and complex medical). The mean levels of community participation increased significantly from 1 to 6 months (1-mo mean, 48.1; 6-mo mean,

58.3). The mean for social and home participation remained relatively stable, however (see table 3). Results of the association with environmental factors and participation are presented in this section for the unadjusted and adjusted analyses using the 2 PM-PAC summary scales. Because the findings from the analyses of the 7 PM-PAC subscales were similar to those for the summary scales, they are presented in appendixes 1 through 4. At the 1-month follow-up, unadjusted analysis revealed that home mobility barriers were not associated with social and home participation or community participation (table 4). A greater number of community mobility barriers was weakly associated with more social and home participation and community participation (P⬍.05). A greater number of mobility technology facilitators was associated with more social and home participation (P⬍.001) and less community participation (P⬍.001). Communication technology facilitators was not associated with social and home participation or community participation, whereas availability of transportation facilitators was associated with more community participation (P⬍.001). Greater social support was associated with greater social and home participation (P⬍.001) and community participation (P⬍.001). Multivariable 1-month cross-sectional analyses examining whether environmental factors were associated with participa-

Table 4: Pearson Correlation Coefficients of Home and Community Environment With 1- and 6-Month Community Participation and Social and Home Participation 1 Month (n⫽342) Home and Community Environment

Home mobility barriers Community mobility barriers Mobility technology facilitators Communication technology facilitators Transportation facilitators Social support Abbreviation: NS, not significant. *P⬍.05; †P⬍.01; ‡P⬍.001.

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6 Months (n⫽270)

Social and Home Participation

Community Participation

Social and Home Participation

Community Participation

NS .116* .170‡ NS NS .408‡

NS ⫺.127* ⫺.330‡ NS .279‡ .137†

NS NS NS NS NS .344‡

NS NS ⫺.283‡ .148† .134* .154†

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Table 5: Multivariate Associations of Home and Community Environment With 1-Month Community Participation and Social and Home Participation (nⴝ296) Variables

Environment variables Home mobility barriers Community mobility barriers Mobility technology facilitators Communication technology facilitators Transportation facilitators Social support Covariate variables Age Sex Education Race Disease severity Physical and mobility activity Applied cognition Adjusted R2

Social and Home Participation ␤

Community Participation ␤

⫺0.40† 0.88* 0.47† ⫺0.72* ⫺0.16 0.15‡

⫺0.44† 1.00† 0.34 ⫺0.66 ⫺0.10 0.15‡

⫺0.38 ⫺1.05 ⫺1.80‡ ⫺0.20 1.97‡ 0.06

⫺0.25 ⫺1.37* 0.15 ⫺0.20 0.96§ 0.05

NI NI NI NI NI NI NI 0.23

⫺0.01 0.20 ⫺0.37 ⫺1.10 0.06 ⫺0.07 0.05* 0.23

NI NI NI NI NI NI NI 0.16

0.03 ⫺0.46 0.26 0.02 ⫺0.11 0.73‡ 0.08* 0.43

NOTE. Parameter estimates shown in table. Abbreviation: NI, not included in this particular model. *P⬍.05; †P⬍.01; ‡P⬍.001; §P⫽.06.

tion showed that after adjusting for demographic factors, disease severity, physical and mobility activity, and cognition, a greater number of home mobility barriers was associated with less social and home participation (P⬍.01) (table 5). A greater presence of community mobility barriers was associated with less community participation (P⬍.05) but greater social and home participation (P⬍.01). The availability of more transportation facilitators was associated with increased community participation (P⫽.06); whereas greater social support was associated with more social and home participation (P⬍.001). Mobility and communication technology facilitators, generally, were not associated with community participation. At 6 months, in both the unadjusted and adjusted models, there were fewer associations between environmental fac-

tors and participation (tables 4, 6). Multivariable longitudinal analyses showed that after adjusting for demographic factors, disease severity, physical and mobility activity, cognition, and 1-month participation, greater social support predicted more social and home participation (P⬍.001). Generally, none of the other environmental barriers and facilitators was predictive of community participation or social and home participation. DISCUSSION We found that a person’s home and community environments were related to one’s level of participation in ADLs, particularly in the period shortly after discharge from an acute care or inpatient rehabilitation hospital. Though this finding is

Table 6: Multivariate Associations of Home and Community Environment With 6-Month Community Participation and Social and Home Participation After Adjusting for 1-Month Participation (nⴝ247) Variables

Environment variables Home mobility barriers Community mobility barriers Mobility technology facilitators Communication technology facilitators Transportation facilitators Social support Covariate variables Age Sex Education Race (nonwhite) Disease severity Physical and mobility activity Applied cognition Adjusted R2

Social and Home Participation ␤

Community Participation ␤

⫺0.07 ⫺0.41 0.13 0.04 0.20 0.07‡

⫺0.14 ⫺0.09 ⫺0.04 0.28 0.29 0.08‡

0.01 ⫺0.21 ⫺0.71* 1.86† ⫺0.04 0.03

⫺0.03 ⫺0.40 ⫺0.22 1.40 ⫺0.05 0.03

NI NI NI NI NI NI NI 0.23

0.02 0.33 ⫺2.10 ⫺4.20‡ 0.12* ⫺0.08 0.04 0.28

NI NI NI NI NI NI NI 0.26

⫺0.05 ⫺0.05 ⫺0.35 ⫺2.02 ⫺0.19 0.19 0.06 0.28

NOTE. Parameter estimates shown in table. *P⬍.05; †P⬍.01; ‡P⬍.001.

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not surprising, it does provide empirical evidence that supports the commonly held belief that participation in life activities is associated, at least in part, with aspects of the environment in which a person lives.1-7 Interesting, however, was the finding that there were fewer associations between environment and participation found at the 6-month follow-up—a finding that suggests that people may adapt to, or modify, their environment. The relation between the environment and participation, however, is clearly complex. Mobility barriers in the home were associated with less social and home participation, but only in the short term, whereas mobility barriers in the community were associated with less community participation and more social and home participation in the short term but not over a longer period of time. Contrary to our hypotheses, mobility and community technology facilitators did not enhance community or social or home participation after adjusting for covariates. As hypothesized, subjects who reported more transportation facilitators had increased community participation, although the statistical association was marginal. Subjects with more social support, however, participated more, in both the short and long terms, particularly in the home participation domain. Our findings are similar to those reported by Levasseur et al,13 who found that more perceived facilitators and fewer perceived obstacles in the environment were associated with higher participation among adults with functional limitations. Our findings differ, however, from the findings of Whiteneck et al9 that environmental factors did not appear to contribute to participation, at least among subjects with chronic spinal cord injuries. The study population and environmental instrumental assessment might explain the discrepancy in findings between Whiteneck’s study and ours. First, Whiteneck included adults with spinal cord injuries who had been living with the condition for at least a year and as many as 25 years. Thus, it might be that participants had adapted to or modified their environment. In addition, Whiteneck’s sample included more young adults, which perhaps suggests that a younger age might be related to more resiliencies in overcoming barriers in the community and participating in ADLs. Another explanation of the difference in findings between Whiteneck’s study and ours is that different environmental and participation assessments were used. Whiteneck used the Craig Hospital Inventory of Environmental Factors (CHIEF),28 a measure that ascertains the impact that perceived environmental barriers have on a person’s participation. The HACE assesses barriers and facilitators in the environment but is focused on the physical environmental domain. In comparison, the CHIEF assesses a broad range of environmental domains recognized in the formulations of the ICF. Thus, summary scores of the CHIEF provide different perspectives of the environment. Furthermore, Whiteneck used the Craig Handicap Assessment and Reporting Technique,29 a self-report measure of participation in 6 domains: physical independence, cognitive independence, mobility, occupation, social integration, economic self-sufficiency, and an overall score. Our outcome instrument, the PM-PAC has 7 subscales that assess mobility functioning, community, civic and social functioning, role functioning, self-care and domestic functioning, financial functioning, social functioning, and communication functioning, as well as 2 subscales representing community participation and home and social participation. Similar to the findings of Whiteneck et al29 however, at 6 months we did not find environmental factors to be related to participation longer term. It may be that environmental factors pose problems with participation over the short term, but on a longer-term basis people adapt to the barriers and participate in ADLs regardless of the factors within their environment. Arch Phys Med Rehabil Vol 87, December 2006

Our findings suggest that assistive mobility aids are not associated with community or home participation, and they generally support the research of others that showed the acquisition of mobility assistive technologies and environmental modifications to the home did not appear to be related to one’s level of participation.16 It may be that changes to the home environment and the implementation of assistive mobility technologies alone are inadequate for enhancing participation in ADLs. Devices may be available but not used because of social stigmas or inconveniences, or the technology may be inadequate to foster involvement in ADLs. Interestingly, the environmental factor that seemed the most relevant to short- and longer-term levels of participation in one’s home and community was social support, which may be critical in helping rehabilitation patients adapt to their chronic conditions and life’s challenges. If this is accurate, clinical interventions could be designed to enhance the acquisition and use of the social support features of an environment to optimize participation. The finding that social support is important to participation has been shown in other studies.30-33 Study Limitations Our study does have some limitations. First, its generalizability is limited by the convenience nature of our sample. We cannot make inferences at the population level and comparing our findings with population-based studies must be done cautiously. Second, the instruments used for environmental assessment have some limitations. The community mobility barriers assessed with the HACE had more missing data than would be desirable. In part, this was because we recoded responses of “do not know” as missing, which indicated that assessing specific community mobility barriers was difficult for some participants. In addition, the MOS Social Support Survey23 was not developed to reflect the ICF framework and the types of social support recognized by the ICF are not differentiated with this instrument. Assessing social support by type of support (specifying peer, family, health, or other) may provide further insight into this potentially important social environmental factor. Third, the ICF’s conceptualization of the environment7 is also not fully represented by the HACE.22 The domains assessed by the HACE22 have a greater emphasis on the physical aspects, and the services, systems, and policy component of the ICF are not measured with this instrument. These aspects of the environment may be important areas to explore in a postacute community-dwelling population. Fourth, the measurement of community participation might be limited because of the age of the sample population. Employment of participants who were older adults was not collected. This clarification may have detracted from the measurement of community participation meant to capture, among other things, functioning at work. Finally, although 83% of our subjects completed the 6-month follow-up assessment, those lost to follow-up had worse physical functioning and could have had lower participation. This might have influenced the magnitude of association seen between environmental factors and participation. Further research in this area should examine whether the environment has an effect on participation to greater degrees among subjects with different conditions or injuries that require rehabilitation care. For example, does the environment affect survivors of strokes, spinal cord injury, low back pain, or arthritis differently? Second, new studies in this area of environment factors and participation could include measurement of policies, systems and services, device use, types of support, and other socioecologic and personal factors, including percep-

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tions of health and well-being, with an expanded assessment by diagnostic group to identify any alternate explanations. CONCLUSIONS This study provides new empirical evidence that environmental barriers and facilitators do influence participation in a general rehabilitation cohort, at least in the short term.

Factors within the environment, however, might not be as important in the long term, as people adapt to their situations. In this study, social support was associated with greater social and home participation 6 months after discharge from an acute or inpatient rehabilitation hospital, underscoring the importance of social support in rehabilitation outcomes.

APPENDIX 1: UNADJUSTED ASSOCIATIONS OF HOME AND COMMUNITY ENVIRONMENT WITH 1-MONTH PARTICIPATION (nⴝ296) Environment Domain

Self-Care/Domestic

Home mobility barriers Community mobility barriers Mobility technology facilitators Communication technology facilitators Transportation facilitators Social support Adjusted R2

ⴚ0.60† 0.28 ⫺0.29 0.21 0.61 0.12‡ 0.11

Social

Financial

Communication

Mobility

Community, Civic & Social

Role Functioning

ⴚ0.43† 0.11 0.07 ⴚ1.06† 0.17 0.13‡ 0.16

⫺0.13 0.21 ⫺0.07 0.18 0.10 0.04‡ 0.04

⫺0.05 0.63 0.16 ⴚ0.85† 0.22 0.08‡ 0.09

⫺0.40 ⫺0.81 ⴚ1.57‡ 0.28 1.82‡ 0.07ⴱ 0.17

⫺0.24 ⫺0.61 ⴚ1.42‡ ⫺0.54 1.03ⴱ 0.08† 0.14

⫺0.10 ⫺0.56 ⴚ0.60ⴱ ⫺0.67 1.09ⴱ ⫺0.00 0.03

NOTE. Parameter estimates (␤) shown in table. Boldface denotes statistical significance. *P⬍.05; †P⬍.01; ‡P⬍.001.

APPENDIX 2: MULTIVARIABLE ASSOCIATIONS OF HOME AND COMMUNITY ENVIRONMENT WITH 1MONTH PARTICIPATION ADJUSTED FOR AGE, SEX, EDUCATION, RACE, DISEASE SEVERITY, PHYSICAL AND MOBILITY ACTIVITY, AND APPLIED COGNITION (nⴝ296)

Environment Domain

Self-Care/Domestic

Home mobility barriers Community mobility barriers Mobility technology facilitators Communication technology facilitators Transportation facilitators Social support Adjusted R2

ⴚ0.57† 0.26 0.20 0.25 0.27 0.11‡ 0.15

Social

Financial

Communication

ⴚ0.37* 0.13 0.11 ⫺0.64 0.11 0.12‡ 0.17

⫺0.13 0.22 0.02 0.15 0.05 0.04‡ 0.06

⫺0.13 0.70§ 0.58† ⴚ1.14‡ 0.08 0.08‡ 0.19

Mobility

⫺0.27 ⴚ1.08§ ⫺0.04 0.34 1.06* 0.06* 0.40

Community, Civic & Social

Role Functioning

⫺0.18 ⫺0.84 ⫺0.00 ⫺0.69 0.31 0.07† 0.35

⫺0.06 ⫺0.66 0.46 ⫺0.60 0.52 ⫺0.00 0.18

NOTE. Parameter estimates (␤) shown in table. Boldface denotes statistical significance. *P⬍.05; †P⬍.01; ‡P⬍.001; §P⫽.06.

APPENDIX 3: UNADJUSTED ASSOCIATIONS OF HOME AND COMMUNITY ENVIRONMENT WITH 6-MONTH PARTICIPATION (nⴝ247)

Environment Domain

Self-Care/Domestic

Home mobility barriers Community mobility barriers Mobility technology facilitators Communication technology facilitators Transportation facilitators Social support Adjusted R2

⫺0.09 ⴚ1.34† ⫺0.19 0.40 ⫺0.04 0.06† 0.21

Social

Financial

Communication

Mobility

Community, Civic & Social

Role Functioning

ⴚ0.34* ⫺0.12 ⫺0.10 0.22 0.45 0.09‡ 0.23

0.09 ⫺0.12 0.04 0.16 ⫺0.02 0.03‡ 0.06

0.03 0.05 ⫺0.15 0.48 0.19 0.02 0.12

0.00 0.22 ⴚ0.88† 0.91 0.49 0.04 0.22

⫺0.00 0.19 ⴚ0.77† 1.10* 0.17 0.01 0.15

⫺0.07 ⫺0.80 ⫺0.15 2.06† ⫺0.27 ⫺0.05 0.17

NOTE. Parameter estimates (␤) shown in table. Boldface denotes statistical significance. *P⬍.05; †P⬍.01; ‡P⬍.001.

Arch Phys Med Rehabil Vol 87, December 2006

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APPENDIX 4: MULTIVARIABLE ASSOCIATIONS OF HOME AND COMMUNITY ENVIRONMENT WITH 6-MONTH PARTICIPATION ADJUSTED FOR AGE, SEX, EDUCATION, RACE, DISEASE SEVERITY, PHYSICAL AND MOBILITY ACTIVITY, AND APPLIED COGNITION (nⴝ247) Environment Domain

Self-Care/Domestic

Home mobility barriers Community mobility barriers Mobility technology facilitators Communication technology facilitators Transportation facilitators Social support Adjusted R2

⫺0.08 ⴚ1.27† ⫺0.12 0.47 0.01 0.06† 0.22

Social

Financial

Communication

Mobility

Community, Civic & Social

Role Functioning

ⴚ0.35* 0.03 ⫺0.14 0.52 0.48 0.09‡ 0.25

0.06 ⫺0.03 0.07 0.05 ⫺0.02 0.03‡ 0.07

⫺0.07 0.34 ⫺0.04 0.40 0.17 0.02 0.17

⫺0.09 0.21 ⫺0.51 0.34 0.46 0.04 0.23

0.07 ⫺0.02 ⫺0.36 1.18§ 0.14 0.01 0.18

⫺0.09 ⫺0.88 0.51 1.62* ⫺0.48 0.04 0.20

NOTE. Parameter estimates (␤) shown in table. Boldface denotes statistical significance. *P⬍.05; †P⬍.01; ‡P⬍.001; §P⫽.06.

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