Restoring Empathy in Medical Education: The Measurable Impact of a Humanities-Based Course on Empathy
Bibliographic record
Abstract
Objective: To evaluate the effects of an educational intervention, the elective course "Humanistic Values and Contemporary Medicine," on medical students' empathy levels and to examine the predictive value of demographic and educational variables. Methods: A cross-sectional survey was conducted among 112 medical students using a modified Toronto Empathy Questionnaire assessing empathy in both personal and clinical contexts. Demographic and educational data were collected and analyzed for associations with empathy scores. Results: Most students recognized the importance of empathy, but only a subset had received formal education on the topic. Enrollment in the elective course was significantly associated with higher empathy scores. Gender showed a nearly significant effect, with female students tending to score higher. Other factors, including clinical training, living arrangements, and personal experience with chronic illness, were not significant predictors of empathy. Conclusion: Empathy is amenable to structured educational interventions and should be intentionally cultivated during medical training to support future physicians' interpersonal competencies and emotional resilience.
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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 | 0.005 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".