Towards an autonomy-supportive model of wellness in Canadian medical education
Bibliographic record
Abstract
Purpose: Learner distress is a huge problem in medicine today, and medical institutions have been called upon to help solve this issue. Unfortunately, the majority have responded not by addressing the system and culture that have long plagued the profession, but by creating individual-focused "wellness" interventions (IFWs). As a result, medical learners are routinely being forced to undergo training on resilience, mindfulness, and burnout. Approach: Grounded in well-supported theory and empirical evidence, my central argument in this commentary is that IFWs are inappropriate, insulting, and psychologically harmful to learners, and that they need to stop. Contribution: Extending prior work in this area, I first present three fundamental problems with IFWs. I then recommend a paradigm shift in how we are approaching "wellness" in medical education. Conclusion: Finally, I provide an evidence-based roadmap, in self-determination theory, for how system-level improvements could be made in a timely, sustainable, and socially responsible way, that would benefit everyone in medicine-from leaders, to educators, to learners, to patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.126 | 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".