The Influence of the Big Five Personality Traits on Burnout in Medical Doctors
Bibliographic record
Abstract
The objective of present study was to investigate the relationship between the Big Five personality factors and burnout in medical doctors. The sample comprised of 100 doctors (50 males and 50 females). Results of the study revealed that personality factors explained significant amount of variance in both the males’ and females’ sample. In females’ sample, agreeableness explained the maximum variance of 26% (r=-.507**, p<.01) in depersonalization, extraversion explained 12% (r=-.355*, p<.05) of variance in emotional exhaustion, conscientiousness explained 11% (r=-.351*, p<.05) of variance in reduced personal accomplishment and neuroticism explained 9% (r=.098) of variance in reduced personal accomplishment. In males’ sample, extraversion turned out to be the best predictor of emotional exhaustion and explained 11% (r=-.385**, p<.01) of variance in the said variable and openness explained about 10% (r=-.319*, p<.05) of variance in depersonalization. Overall these personality factors have explained 58% of variance in females’ sample and 21% of variance in males’ sample.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".