Empathy Levels and Burnout in Medical Students: An Analytic Cross-Sectional Study in a Thai University Hospital
Bibliographic record
Abstract
Objective: In medical education, empathy is an essential element of professionalism; however, medical students are sometimes advised to limit empathy. Excessive empathy might be linked to burnout and trigger negative consequences such as low mood and quality of life. Due to limited data regarding the association between empathy and burnout, this study aimed to examine the relationship between levels of empathy and burnout with their respective subscales, among medical students.Material and Methods: This cross-sectional study was conducted at the clinical level of medical students currently undergoing medical training at the Faculty of Medicine, Prince of Songkla University, at the end of the 2020 academic year. Medical students aged more than 20 years who completed the questionnaires were included. The questionnaires comprised 1) demographic data, 2) The Toronto Empathy Questionnaire, 3) The Maslach Burnout Inventory (Thai version), and 4) The Thai Mental Health Indicator-15. Associations between empathy and burnout including emotional exhaustion, depersonalisation, and personal accomplishment subscales were investigated using linear regression analysis. Results: From the three-year clinical level, 91.9% (466 of 507) of medical students completed the questionnaires, with a mean age of 23.1±1.4 years. In the linear regression analyses, empathy scores were positively associated with emotional exhaustion and negatively associated with depersonalisation and low personal accomplishment (Adjusted coefficient 0.18 (0.02, 0.33), -0.09 (-0.18, -0.01), and -0.42 (-0.52, -0.31), respectively). Among the empathy subscales, altruism was significantly correlated with personal accomplishment (r=-0.41, p-value<0.001).Conclusion: The study revealed a negative correlation between empathy and overall burnout. While a high level of empathy was found to prevent depersonalisation and enhance personal accomplishment, it did not significantly hinder the emotional exhaustion associated with burnout. Empathy, particularly altruism, was related to personal accomplishments. Our findings suggest that empathy is a crucial determinant of burnout prevention; therefore, optimal levels of empathy should be taught to medical students during medical training to prevent emotional exhaustion. However, the evaluation of further causal explanations is recommended.
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How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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 teacher head, 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".