The feasibility of an exercise program 12 months post-stroke in a small urban community
Bibliographic record
Abstract
BACKGROUND: There are few community-based exercise programs catering to individuals post-stroke, despite an increasing need. The primary objective of this study was to assess the feasibility of running a community-based exercise program for individuals post-stroke, and to provide a framework for local communities to run similar programs. METHODS: Individuals who had a stroke within 12 months of the start of the program were eligible to participate in a 9-week community-based exercise program. Sit to stand, grip strength, arm curl, timed up-and-go, 6-minute walk, Berg Balance Scale, Stroke-Specific Quality of Life Questionnaire, and Exercise Self-Efficacy Scale were assessed pre- and post-program to determine the effectiveness of the program. Caregivers of participants were invited to participate in a focus group after the program (N.=5) to better understand program feasibility and areas for improvement. RESULTS: Individuals (9 males, 1 female) with stroke were recruited from a local rehabilitation program within 1 week (aged 72.7±9.3 years). The ratio of volunteers to participants was 1:2. All participants completed the exercise program and pre-post-testing. Significant improvements were observed for sit to stand (7.6±3.4 to 9.8±4.3 repetitions, P<0.01), grip strength of the non-affected side (29.7±8.9 to 32.6±8.3 lbs, P=0.04), arm curl (15.2±6.1 to 19.9±4.7 repetitions, P=0.04), and Exercise Self-Efficacy score (Z=2.50, P=0.01, r=0.79) from pre to post-program. Caregivers suggested increasing the frequency of the program. CONCLUSIONS: An effective community-based exercise program for individuals post-stroke can be run at community centers utilizing qualified volunteers.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".