Background Evidence suggests that frequent engagement in daily activities requiring physical activity may influence risk factors for recurrent stroke. The effects of nonpharmacological interventions on daily physical activity levels and sedentary behavior are unclear. Objective To describe the effects of interventions on levels of daily physical activity and sedentary behavior among people with stroke. Methods OVID/Medline, CINAHL, PsycINFO, and the Cochrane Database were searched using the following search terms: stroke, rehabilitation, intervention, sedentary, physical activity, lifestyle, self‐management, and exercise. Data extraction and risk of bias assessment were conducted by two authors. Results Thirty‐one interventions were identified that included exercise, behavior change techniques, and education components. These components were delivered alone and in varying combinations. At postintervention, between‐group effects on change scores (Cohen's d = 0.17–0.75, P < .05) or between‐group differences in odds of participating in daily physical activity (odds ratio [OR] = 2.07, P < .05) were detected in six studies, and within‐group effects in nine studies (Cohen's d = 0.21–3.97, P < .05). At follow‐up, between‐group differences in odds of participating in daily physical activity were detected in one study (OR = 2.64, P < .05), and within‐group effects in two studies (Cohen's d = 0.25, P < .05). No effects (P < .05) were detected in 17 studies. Conclusion It may be possible to modify daily physical activity levels and sedentary behavior poststroke; however, there is insufficient evidence to suggest the superiority of a particular intervention approach. Future studies should explore the unique contributions of individual intervention components to guide development of parsimonious multicomponent interventions that are effective for promoting daily physical activity and reducing sedentary behavior among people with stroke. Level of Evidence I.

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Objective: The purpose of this scoping review was to identify predictors of community integration for adults with traumatic brain injury. Data Sources: We searched the PubMed and PsycINFO databases and reviewed references of included studies. We selected studies exploring multiple components of community integration, including instrumental activities of daily living, leisure activities, and social activities. A total of 53 studies were included. Data Extraction: We extracted data on sample size and sample characteristics (stage of injury and recovery, severity) and examined predictor variables, outcome measures for community integration, and significant findings, reported as correlations. Data Synthesis: We found that the predictors of community integration fell into 4 categories: demographics, injury characteristics, disability and impairments, and environmental factors. There was large variability in reported relationships for demographics (r = 0.01-0.43), injury characteristics (r = 0.01-0.58), disability/functional impairments (r = 0.003-0.98) and environmental factors (r = 0.11-0.58). Cognition, disability, mobility/physical functioning, mood, social support, and length of posttraumatic amnesia had the strongest relationships with community integration outcomes. Conclusions: Strategies for the management of cognitive, physical, and emotional functioning, and building and training a strong support system, may facilitate community integration outcomes. Additional work is warranted to further explore the discrepancies found among studies.

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Objective: This study examined the construct validity of the Enfranchisement scale of the Community Participation Indicators. Design: We conducted a secondary analysis of data collected in a cross-sectional study of rehabilitation outcomes. Subjects: The parent study included 604 community-dwelling adults with chronic traumatic brain injury, stroke, or spinal cord injury. The sample had a mean age of 64.1 years, was two-thirds male, and included a high proportion of racial minorities ( n = 250, 41.4%). Main measures: The Enfranchisement scale contains two subscales: the Control subscale and the Importance subscale. We examined correlations between each Enfranchisement subscale and measures of participation, environment, and impairments. The current analyses included cases with at least 80% of items completed on each subscale (Control subscale: n = 391; Importance subscale: n = 219). Missing values were imputed using multiple imputation. Results: The sample demonstrated high scores, indicating poor enfranchisement (Control subscale: M = 51.7; Importance subscale: M = 43.0). Both subscales were most strongly associated with measures of participation (Control subscale: r = 0.56; Importance subscale: r = 0.52), and least strongly associated with measures of cognition (Control subscale: r = 0.03; Importance subscale: r = 0.03). The Importance subscale was closely associated with depression ( r = 0.54), and systems, services, and policies ( r = 0.50). Both subscales were associated with social attitudes (Control subscale: r = 0.44; Importance subscale: r = 0.44) and social support (Control subscale: r = 0.49; Importance subscale: r = 0.41). Conclusions: We found evidence of convergent validity between the Enfranchisement scale and measures of participation, and discriminant validity between the Enfranchisement scale and measures of disability-related impairments. The analyses also revealed the importance of the environment to enfranchisement outcomes.