Disordered eating behaviours, self-compassion, and psychological distress in Canadian general surgery residents
Bibliographic record
Abstract
BACKGROUND: Surgical residents experience higher levels of negative stress and helplessness compared to the general population. Studies have linked stress to negative eating habits. Despite the high stress and burnout among surgical residents, studies on their disordered eating behaviors remain limited. Understanding the factors contributing to these findings will help optimize mental health during residency training. METHODS: This study is a mixed-methods cross-sectional survey of all general surgery residents in Canada. The survey assessed disordered eating, quality of life, and self-compassion using the Eating Attitudes Test (EAT-26), Kessler Psychological Distress Scale (KPDS), and Self-Compassion short-form scale (SCSF). A qualitative component examined factors influencing eating habits in residency. Logistic regression was performed to identify factors associated with at-risk disordered eating behaviors. RESULTS: Out of 450 surgical residents, 128 residents completed the survey (28 %). Respondents were 23 % male and split evenly across all postgraduate levels. There were 68 % of respondents who identified as having psychological distress and 34 % exhibited high risk behaviors for disordered eating. High levels of psychological distress (OR 3.29; 95 % CI [1.39-7.76]) and elevated BMI (OR 3.99; 95 % CI [1.63-9.77]) were significantly associated with exhibiting at-risk disordered eating behaviors Positive factors influencing eating were having a partner at home and having non-residency related extracurriculars. Negative factors were overnight call shift frequency, call shift length, and volume of pages. CONCLUSION: This is the first nationwide survey examining eating behaviors among general surgery residents. This population was found to have elevated rates of high-risk behavior for disordered eating.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".