63. Developing a program for resident wellness at the postgraduate medical education office, University of Torontos
Bibliographic record
Abstract
Prevalence of stress-related mental health problems in residents is equal to, or greater than, the general population. Medical training has been identified as the most significant negative influence on resident mental health. At the same time, residents possess inadequate stress management and general wellness skills and poor help-seeking behaviours. Unique barriers prevent residents from self-identifying and seeking assistance. Stress management programs in medical education have been shown to decrease subjective distress and increase wellness and coping skills. The University of Toronto operates the largest postgraduate medical training program in the country. The Director of Resident Wellness position was created in the Postgraduate Medical Education Office to develop a systemic approach to resident wellness that facilitates early detection and intervention of significant stress related problems and promote professionalism. Phase One of this new initiative has been to highlight its presence to residents and program directors by speaking to resident wellness issues at educational events. Resources on stress management, professional services, mental health, and financial management have been identified and posted on the postgraduate medical education website and circulated to program directors. Partnerships have been established with physician health professionals, the University of Toronto, and the Professional Association of Residents and Internes of Ontario. Research opportunities for determining prevalence and effective management strategies for stress related problems are being identified and ultimately programs/resources will be implemented to ensure that resident have readily accessible resources. The establishment of a Resident Wellness Strategy from its embryonic stags and the challenges faced are presented as a template for implementing similar programs at other medical schools. Earle L, Kelly L. Coping Strategies, Depression and Anxiety among Ontario Family Medicine Residents. Canadian Family Physician 2005; 51:242-3. Cohen J, Patten S. Well-being in residency training: a survey examining resident physician satisfaction both within and outside of residency training and mental health in Alberta. BMC Medical Education; 5(21). Levey RE. Sources of stress for residents and recommendations for programs to assist them. Academic Med 2001; 70(2):142-150.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.074 | 0.011 |
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".