Older adults’ experience as peer educators in health promotion programs
Bibliographic record
Abstract
Introduction Peer-led health promotion programs rely on community members to promote health-enhancing changes among their peers. Such programs are growing in popularity and, as a useful and relevant strategy to promote older adults’ social participation, have shown benefit to participants’ physical and psychological health. Little is known, however, about the experience of older adults involved as peer educators in health promotion programs. Methods: Using an exploratory qualitative design, semi-structured interviews were conducted with 7 older adults, aged between 62 and 76 years, involved as peer educators in one or two health promotion programs. Qualitative analysis rested on a mixed (inductive and deductive) approach. The deductive analysis relied on the Do-Live-Well model—an occupation-based framework with roots in health promotion. Findings: Engaging as peer educators allowed participants to express their identity, develop their capabilities, experience pleasure, and contribute to society. They perceived their involvement in this occupation as beneficial for their physical, psychological, and cognitive health. Personal and social forces (e.g., skills acquired through previous work experiences, social support) were considered facilitators to enable older adults to engage as peer educators. Conclusion: Being facilitators in peer-led health promotion programs provides an opportunity for older adults to engage in a meaningful occupational experience that can lead to positive health outcomes, while advancing health promotion messages among their peers.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".