Physical and Leisure Activity in Older Community-Dwelling Canadians Who Use Wheelchairs: A Population Study
Bibliographic record
Abstract
Background. Physical and leisure activities are proven health promotion modalities and have not been examined in older wheelchair users. Main Objectives. Examine physical and leisure activity in older wheelchair users and explore associations between wheelchair use and participation in physical and leisure activity, and wheelchair use, physical and leisure activity, and perceived health. Methods. 8301 Canadians ≥60 years of age were selected from the Canadian Community Health Survey. Sociodemographic, health-related, mobility-related, and physical and leisure activity variables were analysed using logistic regression to determine, the likelihood of participation in physical and leisure activity, and whether participation in physical and leisure activities mediates the relationship between wheelchair use and perceived health. Results. 8.3% and 41.3% older wheelchair users were physically and leisurely active. Wheelchair use was a risk factor for reduced participation in physical (OR = 44.71) and leisure activity (OR = 10.83). Wheelchair use was a risk factor for poor perceived health (OR = 10.56) and physical and leisure activity negatively mediated the relationship between wheelchair user and perceived health. Conclusion. There is a need for the development of suitable physical and leisure activity interventions for older wheelchair users. Participation in such interventions may have associations with health benefits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".