Improving the diagnosis and treatment of osteoporosis using a senior-friendly peer-led community education and mentoring model: a randomized controlled trial
Bibliographic record
Abstract
Background: This randomized controlled trial (RCT) evaluated a 6-month peer-led community education and mentorship program to improve the diagnosis and management of osteoporosis. Methods: Ten seniors (74–90 years of age) were trained to become peer educators and mentors and deliver the intervention. In the subsequent RCT, 105 seniors (mean age =80.5±6.9; 89% female) were randomly assigned to the peer-led education and mentorship program (n=53) or control group (n=52). Knowledge was assessed at baseline and 6 months. Success was defined as discussing osteoporosis risk with their family physician, obtaining a bone mineral density assessment, and returning to review their risk profile and receive advice and/or treatment. Results: Knowledge of osteoporosis did not change significantly. There was no difference in knowledge change between the two groups (mean difference =1.3, 95% confidence interval [CI] of difference −0.76 to 3.36). More participants in the intervention group achieved a successful outcome (odds ratio 0.16, 95% CI 0.06–0.42, P <0.001). Conclusion: Peer-led education and mentorship can promote positive health behavior in seniors. This model was effective for improving osteoporosis risk assessment, diagnosis, and treatment in a community setting. Keywords: prevention, seniors, mentor, bone mineral density, capacity building, community knowledge translation
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".