AN IMPLEMENTATION EVALUATION OF A PEER-LED HEALTH PROMOTION PROGRAM FOR SENIORS WITH FEAR OF FALLING
Bibliographic record
Abstract
The use of seniors as peer educators is gaining in popularity for promoting seniors’ health. However, the conditions under which peer-led health promotion programs (HPP) can be optimally implemented are not well understood. Based on an extensive literature review, we developed a theoretical framework to identify factors related to programs, participants, peer educators and the organizational/environmental context, which could impact implementation outcomes of peer-led HPP. Our study aimed to test this framework using implementation data collected in a pragmatic effectiveness study of a peer-led HPP targeting seniors who are afraid of falling. Peers delivered the program to groups of 12 participants in 6 retirement homes. Program fidelity (peers’ adherence to program principles and guidelines) and participants’ responsiveness to the program were monitored using peers’ logbooks, observation grids, attendance sheets and satisfaction questionnaires completed at program termination. Implementation factors were documented through individual interviews conducted among a subgroup of program participants (n=24), peer leaders (n=6) and program managers in each retirement home (n=6). Participants’ response to the program was excellent, as reflected by their high satisfaction level with the program and a 91% attendance rate. Peers closely followed the program principles and guidelines. Coherent with our framework, individual-related factors (e.g. participants’ health condition, peers’ experience) and program-related factors (e.g. quality of materials) emerged as important implementation factors during preliminary qualitative data analysis. Results from this study can help program practitioners and managers design effective strategies to achieve successful implementation of peer-led HPP for seniors.
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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 | 0.016 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".