‘On-the ground’ strategy matrix for fostering quality participation experiences among persons with disabilities in community-based exercise programs
Bibliographic record
Abstract
OBJECTIVE: The purposes of this paper are to (1) document the generation and refinement of a quality participation strategy list to ensure resonance and applicability within community-based exercise programs (CBEPs) for persons with physical and intellectual disabilities, and (2) identify theoretical links between strategies and the quality participation constructs. METHODS: To address purpose one, a list of strategies to foster quality participation among members was extracted from qualitative interviews with providers from nine CBEPs serving persons with physical disabilities. Next, providers from CBEPs serving persons with physical (n = 9) and intellectual disabilities (n = 6) were asked to identify the strategies used, and examples of their implementation, within their programs. Additional strategies noted by providers and in recent published syntheses were added to the preliminary list. A re-categorization and revision process was conducted. To address purpose two, 22 researchers with expertise in physical and/or intellectual disability, physical activity, participation and/or health behaviour change theory completed a closed-sort task to theoretically link each strategy to the constructs of quality participation. RESULTS: The final list of 85 strategies is presented in a matrix. Each strategy has explicit examples and proposed theoretical links to the constructs of quality participation. CONCLUSIONS: The strategy matrix offers a theoretically-meaningful representation of how quality participation-enhancing strategies can be practically implemented "on-the-ground" in CBEPs for persons with disabilities.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".