Examining the relationships between environmental barriers and leisure in community-dwelling individuals living with stroke
Bibliographic record
Abstract
OBJECTIVE:: To characterize environmental barriers to leisure participation among individuals living with stroke; examine relationships between environmental barriers and leisure interest and satisfaction; and investigate participant factors associated with the perception of environmental barriers. DESIGN:: Survey. SETTING:: Community. PARTICIPANTS:: Convenience sample of 51 community-dwelling adults less than six months post stroke. INTERVENTIONS:: Not applicable. MAIN OUTCOME MEASURE(S):: Craig Hospital Inventory of Environmental Factors-Short Form. RESULTS:: Physical and structural environmental barriers were reported as the most frequent and large barrier to leisure participation ( n = 26 (51%) rated as "monthly or more," n = 12 (24%) rated as "big problem"). While attitude and support and policy barriers were not as commonly encountered, participants labeled these as "big problem(s)" (attitude and support n = 6 (12%), policy n = 7 (14%)). The presence of depressive symptoms was associated with the frequency in which attitudinal and support (rho = 0.50, P < 0.001), physical and structural (rho = 0.46, P < 0.001), and service and assistance (rho = 0.28, P = 0.04) barriers were reported, as well as magnitude of attitude and support barriers (rho = 0.48, P < 0.001). In multivariable regression analysis, depressive symptoms and walking capacity explained 21% of the variance of the frequency of attitude and support barriers ( P = 0.004), where depressive symptoms was an independent correlate ( P = 0.004). No other factors were associated with environmental barriers to leisure participation. CONCLUSION:: Individuals with stroke report frequent and large physical and structural environmental barriers to leisure participation, which may be associated with the presence of depressive symptoms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".