Comparing the Maslach Burnout Inventory to Other Well-Being Instruments in Emergency Medicine Residents
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Bibliographic record
Abstract
ABSTRACT Background The Maslach Burnout Inventory (MBI) is considered the “gold standard” for measuring burnout, encompassing 3 scales: emotional exhaustion, depersonalization, and personal accomplishment. Other well-being instruments have shown utility in various settings, and correlations between MBI and these instruments could provide evidence of relationships among key variables to guide well-being efforts. Objective We explored correlations between the MBI and other well-being instruments. Methods We fielded a multicenter survey of 9 emergency medicine (EM) residencies, administering the MBI and 4 published well-being instruments: a quality-of-life assessment, a work-life balance rating, an appraisal of career satisfaction, and the Primary Care Evaluation of Mental Disorders Patient Health Questionnaire 2 question screen. Consistent with the Maslach definition, burnout was defined by high emotional exhaustion (> 26) and high depersonalization (> 12). Results Of 334 residents, 261 (78%) responded. Residents who reported lower quality of life had higher emotional exhaustion (ρ = –0.437, P < .0001), higher depersonalization (ρ = –0.18, P < .005), and lower personal accomplishment (ρ = 0.347, P < .001). Residents who reported a negative work-life balance had emotional exhaustion (P < .001) and depersonalization (P < .009). Positive career satisfaction was associated with lower emotional exhaustion (P < .0001), lower depersonalization (P < .005), and higher personal accomplishment (P < .05). A positive depression screen was associated with higher emotional exhaustion, higher depersonalization, and lower personal achievement (all P < .0001). Conclusions Our multicenter study of EM residents demonstrated that assessments using the MBI correlate with other well-being instruments.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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