Determinants of Satisfaction With Community Reintegration in Older Adults With Chronic Stroke: Role of Balance Self-Efficacy
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Many people with stroke have a low level of satisfaction with community reintegration. Although previous studies focused on the effect of physical factors on community reintegration, the effect of psychological factors, such as balance self-efficacy, has been ignored. The purpose of this study was to determine the contribution of balance self-efficacy to satisfaction with community reintegration in older adults with chronic stroke. SUBJECTS: A sample of 63 community-dwelling older adults (50 years of age or older) with chronic stroke (onset of 1 year or more) participated in this study. METHODS: This study involved a secondary analysis of data collected from a stroke exercise clinical trial. Satisfaction with community reintegration was measured with the Reintegration to Normal Living (RNL) Index, and balance self-efficacy was measured with the Activities-specific Balance Confidence (ABC) Scale. RESULTS: Bivariate correlation analyses showed that the RNL Index scores were moderately correlated with the ABC Scale scores. In a multiple regression analysis, after adjusting for age, sex, depression, and other impairments after stroke, balance self-efficacy remained independently associated with the RNL Index scores, accounting for 6.5% of the variance in the RNL Index scores. DISCUSSION AND CONCLUSION: Balance self-efficacy is an independent predictor of satisfaction with community reintegration in older adults with chronic stroke. Improving balance self-efficacy may be instrumental in enhancing community reintegration in this population.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it