Evaluation of a peer‐led self‐management education programme <scp>PEP</scp> Talk: Diabetes, Healthy Feet and You
Bibliographic record
Abstract
PEP (Peer Education Programme) Talk: Diabetes, Healthy Feet and You is a peer-led self-management programme developed to address the problems of growing prevalence of diabetes and its complications, and limited health care dollars. An evaluation of the programme, how it might be situated within a public health perspective and potential bridges for its implementation in communities throughout Canada and worldwide, are presented. The programme consisted of workshops that were conducted by volunteer peer leaders and health care professionals in 12 communities in 10 Canadian provinces; the volunteers were supported through monthly mentoring teleconferences, on-line tips and discussion board conversations. A web portal was developed to be used by the team, volunteers and community participants. Workshop curriculum was developed based on diabetes footcare and self-management best practise guidelines. Community participants answered pre-and post-workshop statements that indicated that learning occurred, as indicated by an increase in the number of statements answered correctly. Participants' feedback about the workshops was positive. In telephone follow-up interviews, 97% of respondents reported having changed their foot self-management behaviours. The portal was commonly used according to website visits, but not as much as expected for registration of community participants. It is recommended that this programme be made widely available and tailored to the specific needs of the communities and that further evaluation be conducted.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".