How patient educators help students to learn: An exploratory study
Bibliographic record
Abstract
INTRODUCTION: Benefits of the active involvement of patients in educating health professionals are well-recognized but little is known about how patient educators facilitate student learning. METHOD: This exploratory qualitative study investigated the teaching practices and experiences that prepared patient educators for their roles in a longitudinal interprofessional Health Mentors program. Semi-structured interviews were conducted with eleven experienced health mentors. Responses were coded and analyzed for themes related to teaching goals, methods, and prior experiences. RESULTS: Mentors used a rich variety of teaching methods to teach patient-centeredness and interprofessionalism, categorized as: telling my story, stimulating reflection, sharing perspectives, and problem-solving. As educators they drew on a variety of prior experiences with teaching, facilitation or public speaking and long-term interactions with the health-care system. CONCLUSIONS: Patient educators use diverse teaching methods, drawing on both individualistic and social perspectives on learning. A peer-support model of training and support would help maintain the authenticity of patients as educators. The study highlights inadequacies of current learning theories to explain how patients help students learn.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".