Educational roles impact burnout in paediatric undergraduate medical educators
Bibliographic record
Abstract
BACKGROUND: Physician burnout impacts all levels of medical education and has a relatively unknown impact on those responsible for medical student education, particularly in paediatrics. This study examines the prevalence of burnout among paediatric undergraduate medical educators and explores the impact of roles in medical education on medical educator burnout. METHODS: This cross-sectional mixed-methods study utilised a binational survey of paediatricians involved in undergraduate medical education. Respondents answered demographics, standardised questions about burnout and attitudes towards students, and an open-ended probe about interactions between medical student education and wellness. FINDINGS: Of 445 possible, 120 (26.9%) responded to demographic and burnout questions. Of these, 23.3% endorsed burnout, 21.7% high emotional exhaustion (EE) and 10.8% high depersonalisation (DP). High levels of student-related burnout symptoms were reported by fewer than 5% of respondents and were correlated with overall EE and DP. Content analysis revealed four emergent themes: positive effect of student-related role, need to balance medical education and clinical roles, impact of protected time and medical education-related autonomy on educator well-being, and the burden of the administrative portion of educational roles. DISCUSSION: Participating paediatric educators had low rates of burnout compared with paediatricians as a whole in prior studies. The vast majority found working with students rewarding and described the overall positive impact of their medical education role on wellness. CONCLUSION: Physician involvement in rewarding non-clinical activities may improve their overall well-being. Providing dedicated time for these activities may ameliorate the difficulty that many medical educators described in balancing their clinical and educational roles. Future studies should continue to explore how we can better support medical educators and the impact of this support on burnout.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".