Investigating the Relationship Between Quality and Quantity of Participation in an Online Community-Based Exercise Program: A Mixed-Methods Study
Bibliographic record
Abstract
The Quality Participation Framework proposes that repeated quality experiences foster continued quality participation (i.e., participation quantity over time). This study explored the relationship between the quality and quantity of participation in an exercise setting. Individuals (n = 17) with a physical disability engaged in Revved Up @ Home, a 10-week online community-based exercise program designed to foster quality participation. Using a mixed-methods sequential explanatory design situated in critical realism, participants completed quality experience global questionnaires at baseline and 10 weeks, and acute questionnaires following each exercise session. Participant attendance was retrieved from program records. In semi-structured interviews at 10 weeks, participants were shown graphs of results derived from the acute questionnaires and asked about their quality and quantity of participation during the program. Correlations quantified the relationship between quality and quantity of participation, and thematic analysis facilitated an exploration of the contextual relationship. Qualitative and quantitative findings were integrated, highlighting important relationships between belongingness and quantity, meaning and quantity, as well as between challenge and mastery. Findings provide preliminary evidence that repeated quality experiences foster quality participation, and detail relationships between the aspects of quality participation and between quantity and quality participation. Findings can be used to enhance quality participation and attendance among individuals with physical disabilities who attend community-based exercise programs.
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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 | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".