“Relationship of mental health and burnout with empathy among undergraduate medical students in Lahore, Pakistan: A cross-sectional study.”
Bibliographic record
Abstract
Background: Empathy, crucial for effective communication and patient care in medicine, can be influenced by stress, workload, burnout, and impaired mental well-being. Objectives: To assess burnout levels, mental health status and the factors associated with empathy among undergraduate medical students in Lahore, Pakistan. Methods: A descriptive cross-sectional study was carried out among MBBS students from the 3rd to final year at King Edward Medical University, Lahore, with ethical approval granted by the Institutional Review Board. The research employed four questionnaires: a personal and demographic survey, the Warwick-Edinburgh Mental Well-being Scale (WEMWBS), the Maslach Burnout Inventory (MBI) for self-assessment of burnout, and the Toronto Empathy Questionnaire (TEQ). Data analysis involved descriptive statistics, and factors influencing empathy were examined using the Chi-square test or Fisher’s exact test. Results: The study evaluated 164 Muslim participants with a mean age of 21.77 years (SD = 1.10); 45.1% were male and 54.9% female. Physical illness was reported by 4.9% of the participants, while 6.7% had psychiatric conditions. Almost all participants refrained from alcohol and substance use. No significant association was found between any of the socio-demographic factors (gender, illness, substance use, academic year and specialty preference) and empathy. Likewise, empathy was not significantly related to mental health, as measured by the WEMWBS, or burnout, as assessed by the MBI. The majority of participants (96.3%) had below-average empathy, with a median score of 31 (IQR: 28-35) according to the TEQ scale. Conclusion: Majority demonstrated below-average empathy, only a few reported above-average empathy levels. Although, mostly exhibited high depersonalization and low personal achievement, they had good mental health and low exhaustion levels. No statistically significant relationship was found between any of the factors and empathy. Keywords: Empathy, Mental health, Burnout, Warwick-Edinburgh Mental Well-being Scale, Maslach Burnout Inventory, Toronto Empathy Questionnaire.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".