Effects of Mentorship on Surgery Residents’ Burnout and Well-Being: A Scoping Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In surgical training, a mentor is a more senior and experienced surgeon who guides a surgical trainee to meet personal, professional, and educational goals. Although mentorship is widely assumed to positively affect surgical residents' professional development, a more nuanced understanding of mentorship's impact is lacking and urgently needed as burnout rates among residents increase. This study aims to summarize the current literature on the effects of mentorship on surgical residents' burnout and well-being. METHODS: A comprehensive literature review was performed with key terms related to "surgical resident" and "mentor" using Pubmed, Embase, and ProQuest databases for primary studies published in the United States or Canada from January 1, 2010 to December 9, 2022 that measured outcomes related to burnout and well-being. Multiple reviewers screened titles and abstracts for relevance, then full-text articles for eligibility. RESULTS: Initial search resulted in 1,468 unique articles, and 19 articles were included after review. Only one article was a randomized controlled trial. Twelve studies described a decrease in burnout rates or in outcomes related to burnout. In contrast, 4 studies identified negative outcomes related to burnout. Six studies showed improved well-being or related outcomes. One study was not able to show a change in self-valuation between coached and noncoached residents. CONCLUSION: High quality mentorship can be associated with improved well-being and decreased burnout in surgical residents, but the key elements of effective and helpful mentorship remain poorly characterized. This summary highlights the importance of making mentorship accessible to surgical residents, and training faculty to be effective mentors.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 it