The directors of resident support program: a program evaluation of a resident well-being and support innovation
Bibliographic record
Abstract
BACKGROUND: Medical training can be a challenging time for residents both professionally and personally. Resident support programs must be able to address a range of potential experiences, be accessible and easy to navigate, and consider the unique context of residency. Rigorous evaluation of resident support programs is needed to determine whether these programs are meeting these goals. METHODS: The Directors of Resident Support (DRS) program, launched in January 2021 at the Cumming School of Medicine at the University of Calgary, is a near-peer support model consisting of three faculty physicians, trained in peer support, who receive contacts from residents needing support for any issue. DRS physicians provide empathetic listening, referral to existing resources, and peer support for residents. A multisource evaluation of the DRS program, including field notes, data collection forms, and surveys, was guided by the Donabedian framework. RESULTS: There were 62 total contacts in the 2-year evaluation period which required a median 2 h to address (range 5 min to more than 40 h). The most common topic for contact was to discuss feedback or evaluation (n = 10, 24.4%) and the most common response was listening and support (n = 29, 70.7%). Residents also contacted DRS to discuss experiences of racism, physical assault, sexual harassment, and mental health crises. Residents (n = 13) rated a median score of 74 out of possible 100 for usefulness (interquartile range [IQR] 1-100, with higher scores suggesting greater usefulness). Free text survey responses suggested that residents felt validated by contact with the program though some residents felt that additional follow-up would have been helpful. CONCLUSION: The DRS program has been well-utilized by residents for a variety of issues. Postgraduate Medical Education offices seeking to create resident support programs may anticipate that about 3% of residents may use a similar program per year and that the typical interaction would last 2 h, with a wide range. Feedback suggested that similar programs should have a formal process for follow-up with residents to ensure their concern was addressed and that resident supporters should have diverse lived experiences.
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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 | 0.010 | 0.007 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".