Satisfaction and attrition in Canadian surgical training program leadership: a survey of program directors
Bibliographic record
Abstract
BACKGROUND: Surgical program directors (PDs) play an integral role in the well-being and success of postgraduate trainees. Although studies about medical specialties have documented factors contributing to PD burnout, early attrition rates and contributory factors among surgical PDs have not yet been described. We aimed to evaluate Canadian surgical PD satisfaction, stressors in the role and areas institutions could target to improve PD support. METHODS: We administered a cross-sectional survey of postgraduate Canadian surgical PDs from all Royal College of Physicians and Surgeons of Canada accredited surgical specialties. Domains we assessed included PD demographics and compensation, availability of administrative support, satisfaction with the PD role and factors contributing to PD challenges and burnout. RESULTS: Sixty percent of eligible surgical PDs (81 out of 134) from all 12 surgical specialties responded to the survey. We found significant heterogeneity in PD tenure, compensation models and available administrative support. All respondents reported exceeding their weekly protected time for the PD position, and 66% received less than 0.8 full-time equivalent of administrative support. One-third of respondents were satisfied with overall compensation, whereas 43% were unhappy with compensatory models. Most respondents (70%) enjoyed many aspects of the PD role, including relationships with trainees and shaping the education of future surgeons. Significant stressors included insufficient administrative support, complexities in resident remediation and inadequate compensation, which contributed to 37% of PDs having considered leaving the post prematurely. INTERPRETATION: Most surgical PDs enjoyed the role. However, intersecting factors such as disproportionate time demands, lack of administrative support and inadequate compensation for the role contributed to significant stress and risk of early attrition.
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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 | 0.003 | 0.000 |
| 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 | 0.000 |
| 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 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".