Wellness interventions in surgery: a scoping review
Bibliographic record
Abstract
BACKGROUND: Wellness research has expanded in surgery owing to the high prevalence of burnout. In this scoping review, we aim to identify trends of wellness interventions for surgeons and surgical trainees. METHODS: We identified studies on wellness interventions across surgical specialties. We categorized interventions based on the targeted wellness domain, including physical, social, emotional, intellectual, and occupational domains. RESULTS: = 24). Interventions focused on ergonomics, mindfulness, stress reduction, work hours, and wellness programs. Since 2015, there has been a shift in the wellness domains addressed from physical and occupational, to mostly emotional. CONCLUSION: The prevalence of individual-level interventions targeting emotional wellness reflects a belief that surgeons are responsible for their own wellness. Studies to date have largely focused on surgical trainees, with a dearth of research on measures to improve staff surgeon wellness. Methodologically sound intervention studies with objective outcome measures are lacking and needed to facilitate a culture of shared organizational responsibility for surgeon well-being.
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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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".