Considerations for expanding community exercise programs incorporating a healthcare-recreation partnership for people with balance and mobility limitations: a mixed methods evaluation
Bibliographic record
Abstract
OBJECTIVE: To increase access to safe and appropriate exercise for people with balance and mobility limitations, community organizations have partnered with healthcare providers to deliver an evidence-based, task-oriented group exercise program in community centers in Canada. We aimed to understand challenges and solutions to implementing this program model to inform plans for expansion. RESULTS: At a 1-day meeting, 53 stakeholders (healthcare/recreation personnel, program participants/caregivers, researchers) identified challenges to program implementation that were captured by seven themes: Resources to deliver the exercise class (e.g., difficulty finding instructors with the skills to work with people with mobility limitations); Program marketing (e.g., to foster healthcare referrals); Transportation (e.g., particularly from rural areas); Program access (e.g., program full); Maintaining program integrity; Sustaining partnerships (i.e., with healthcare partners); and Funding (e.g., to deliver program or register). Stakeholders prioritized solutions to form an action plan. A survey of individuals supervising 28 programs revealed that people with stroke, acquired brain injury, multiple sclerosis, and Parkinson's disease register at 95-100% of centers. The most prevalent issues with program fidelity across centers were not requiring a minimum level of walking ability (32%), class sizes exceeding 12 (21%), and instructor-to-participant ratios exceeding 1:4 (19%). Findings provide considerations for program expansion.
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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 | 0.118 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".