Community-based exercise programs incorporating healthcare-community partnerships to improve function post-stroke: feasibility of a 2-group randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Despite the potential for community-based exercise programs supported through healthcare-community partnerships (CBEP-HCPs) to improve function post-stroke, insufficient trial evidence limits widespread program implementation and funding. We evaluated the feasibility and acceptability of a CBEP-HCP compared to a waitlist control group to improve everyday function among people post-stroke. METHODS: We conducted a 3-site, pilot randomized trial with blinded follow-up evaluations at 3, 6, and 10 months. Community-dwelling adults able to walk 10 m were stratified by site and gait speed and randomized (1:1) to a CBEP-HCP or waitlist control group. The CBEP-HCP involved a 1-h, group exercise class, with repetitive and progressive practice of functional balance and mobility tasks, twice a week for 12 weeks. We offered the exercise program to the waitlist group at 10 months. We interviewed 13 participants and 9 caregivers post-intervention and triangulated quantitative and qualitative results. Study outcomes included feasibility of recruitment, interventions, retention, and data collection, and potential effect on everyday function. RESULTS: Thirty-three people with stroke were randomized to the intervention (n = 16) or waitlist group (n = 17). We recruited 1-2 participants/month at each site. Participants preferred being recruited by a familiar healthcare professional. Participants described a 10- or 12-month wait in the control group as too long. The exercise program was implemented per protocol across sites. Five participants (31%) in the intervention group attended fewer than 50% of classes for health reasons. In the intervention and waitlist group, retention was 88% and 82%, respectively, and attendance at 10-month evaluations was 63% and 71%, respectively. Participants described inclement weather, availability of transportation, and long commutes as barriers to attending exercise classes and evaluations. Among participants in the CBEP-HCP who attended ≥ 50% of classes, quantitative and qualitative results suggested an immediate effect of the intervention on balance, balance self-efficacy, lower limb strength, everyday function, and overall health. CONCLUSION: The CBEP-HCP appears feasible and potentially beneficial. Findings will inform protocol revisions to optimize recruitment, and program and evaluation attendance in a future trial. TRIAL REGISTRATION: ClinicalTrials.gov , NCT03122626 . Registered April 21, 2017 - retrospectively registered.
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How this classification was reachedexpand
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 | 0.016 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".