Fall Prevention Program Characteristics and Experiences of Older Adults and Program Providers in Canada: A Thematic Content Analysis
Bibliographic record
Abstract
Objectives: To document the characteristics of fall prevention programs in specific regions in two Canadian provinces and to explore older adults’ and program providers’ experiences with these programs. Methods: Semi-structured interviews were conducted with 16 program providers/managers from 12 different programs. Ten semi-structured focus groups were conducted with 59 older adults. Data were analyzed using thematic content analysis. Results: Older adults reported functional and social benefits. Program providers identified barriers to program success, including cognitive impairment, frailty, and lack of motivation. The need for general attitudinal changes toward older adults’ needs and broader community changes were identified as important by the older adults. Discussion: Easily accessible information about fall prevention programs for older adults and no-cost, ongoing initiatives were critical. Health care providers play keys roles in disseminating information, facilitating referrals, and advocating for initiatives that best meet the needs of older adults in their communities.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".