Global prevalence of burnout among postgraduate medical trainees: a systematic review and meta-regression
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: Burnout among postgraduate medical trainees (PMTs) is increasingly being recognized as a crisis in the medical profession. We aimed to establish the prevalence of burnout among PMTs, identify risk and protective factors, and assess whether burnout varied by country of training, year of study and specialty of practice. METHODS: We systematically searched MEDLINE, Embase, PsycINFO, the Cochrane Database of Systematic Reviews, Web of Science and Education Resources Information Center from their inception to Aug. 21, 2018, for studies of burnout among PMTs. The primary objective was to identify the global prevalence of burnout among PMTs. Our secondary objective was to evaluate the association between burnout and country of training, year of study, specialty of training and other sociodemographic factors commonly thought to be related to burnout. We employed random-effects meta-analysis and meta-regression techniques to estimate a pooled prevalence and conduct secondary analyses. RESULTS: In total, 8505 published studies were screened, 196 met eligibility and 114 were included in the meta-analysis. The pooled prevalence of burnout was 47.3% (95% confidence interval 43.1% to 51.5%), based on studies published over 20 years involving 31 210 PMTs from 47 countries. The prevalence of burnout remained unchanged over the past 2 decades. Burnout varied by region, with PMTs of European countries experiencing the lowest level. Burnout rates among medical and surgical PMTs were similar. INTERPRETATION: Current wellness efforts and policies have not changed the prevalence of burnout worldwide. Future research should focus on understanding systemic factors and leveraging these findings to design interventions to combat burnout. STUDY REGISTRATION: PROSPERO no. CRD42018108774.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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