Psychosocial and career outcomes of peer mentorship in medical resident education: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Many medical residents lack ready access to social and emotional supports that enable them to successfully cope with the challenges associated with medical residency. This absence of support has been shown to lead to high levels of burnout, decreased mental wellbeing, and difficulty mastering professional competencies in this population. While there is emerging evidence that peer mentoring can be an important source of psychosocial and career-related support for many individuals, the extent of the evidence regarding the benefits of peer mentorship in medical residency education has not yet been established. We describe a protocol for a systematic review to assess the effects of peer mentoring on medical residents' mental wellbeing, social connectedness, and professional competencies. METHODS: Studies included in this review will be those that report on peer-mentoring relationships among medical residents. Quantitative, qualitative, and mixed-methods studies will be eligible for inclusion. No date or language limits will be applied. We will search EMBASE, MEDLINE, PsychINFO, Web of Science, Scopus, ERIC, Education Research Complete, and Academic Research Complete databases to identify relevant studies. Two authors will independently assess all abstracts and full-text studies for inclusion and study quality and extract study data in duplicate. DISCUSSION: This is the first systematic review to explicitly explore the role of peer mentoring in the context of medical residency education. We anticipate that the findings from this review will raise awareness of the benefits and challenges associated with peer-mentoring relationships, further the development and implementation of formal peer-mentoring programs for medical residents, and, through identifying gaps in the existing literature, inform future research efforts. SYSTEMATIC REVIEW REGISTRATION: This protocol has not been registered in PROSPERO or any other publicly accessible registry.
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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 | 0.091 | 0.093 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.022 | 0.016 |
| Bibliometrics | 0.022 | 0.016 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.051 | 0.006 |
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".