When medical students are autonomously motivated to mentor: a pilot study on confidence in clinical teaching and psychological well-being
Bibliographic record
Abstract
Introduction: Near peer mentorship (NPM) programs can help support medical students' well-being. Most studies, however, have not accounted for students' underlying motives to mentor, nor focused on clinical skills development and teaching. These limitations represent opportunities to better understand what motivates medical student mentors, and how to support their autonomous motivation, clinical development, and well-being. Methods: Informed by self-determination theory (SDT), we collected data from a group of medical student mentors involved in a NPM program at the University of Saskatchewan called PULSE. We then used correlation and regression to assess the relationship between students' autonomous motivation towards mentoring, perceived competence in teaching the clinical material, and psychological well-being. Results: In line with our hypotheses, autonomous motivation towards mentoring (identified motivation in particular) was associated with higher perceived competence in clinical teaching, which in turn was associated with greater psychological well-being. Conclusions: Why medical students choose to mentor in NPM programs appears to have important implications for their clinical confidence and overall well-being. Findings are discussed in terms of designing NPM programs that support student growth and wellness in Canadian medical education.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 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".