Cross-sectional survey on physician burnout during the COVID-19 pandemic in Vancouver, Canada: the role of gender, ethnicity and sexual orientation
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of physician burnout during the pandemic and differences by gender, ethnicity or sexual orientation. DESIGN, SETTING AND PARTICIPANTS: We conducted a cross-sectional survey (August-October in 2020) of internal medicine physicians at two academic hospitals in Vancouver, Canada. PRIMARY AND SECONDARY OUTCOMES: Physician burnout and its components, emotional exhaustion, depersonalisation and personal accomplishment were measured using the Maslach Burnout Inventory. RESULTS: The response rate was 38% (n=302/803 respondents, 49% women,). The prevalence of burnout was 68% (emotional exhaustion 63%, depersonalisation 39%) and feeling low personal accomplishment 22%. In addition, 21% reported that they were considering quitting the profession or had quit a position. Women were more likely to report emotional exhaustion (OR 2.00, 95% CI: 1.07 to 3.73, p=0.03) and feeling low personal accomplishment (OR 2.26, 95% CI: 1.09 to 4.70, p=0.03) than men. Visible ethnic minority physicians were more likely to report feeling lower personal accomplishment than white physicians (OR 1.81, 95% CI: 1.28 to 2.55, p=0.001). There was no difference in emotional exhaustion or depersonalisation by ethnicity or sexual orientation. Physicians who reported that COVID-19 affected their burnout were more likely to report any burnout (OR: 3.74, 95% CI: 1.99 to 7.01, p<0.001) and consideration of quitting or quit (OR: 3.20, 95% CI: 1.34 to 7.66, p=0.009). CONCLUSION: Burnout affects 2 out of 3 internal medicine physicians during the pandemic. Women, ethnic minority physicians and those who feel that COVID-19 affects burnout were more likely to report components of burnout. Further understanding of factors driving feelings of low personal accomplishment in women and ethnic minority physicians is needed.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it