Impact of a longitudinal course on medical professionalism on the empathy of medical students
Bibliographic record
Abstract
OBJECTIVE: Medical education should enhance empathy. We examined, using self-assessment instruments and standardized patients (SPs), the impact on empathy, of a multi-year intervention (years 4-6 of medical training) that uses reflective learning approaches. METHODS: 241 final-year medical students participated; 110 from the 2018 graduation class (non-intervention group) and 131 from the 2019 graduation class (intervention group). Participants completed two self-reported empathy questionnaires - the Jefferson Scale of Empathy-Students (JSE-S) and the Interpersonal Reactivity Index (IRI) - and a personality questionnaire, the NEO Five-Factor Inventory. Additionally, SPs in a simulated station assessed participants' empathy with two patient-reported instruments: the Consultation and Relational Empathy (CARE) scale and the Jefferson Scale of Patient Perceptions of Physician Empathy (JSPPPE). RESULTS: Empathy scores were significantly higher in the intervention group compared to the non-intervention group when assessed by the SP (p < 0.001). No differences were found in self-reported questionnaires between the two groups. CONCLUSION: A longitudinal, multi-year reflection-based intervention enhanced empathy amongst medical students as assessed by SPs, but not when assessed by student self-reported measures. PRACTICE IMPLICATIONS: Multi-year reflective learning interventions during clinical training nurture empathy in medical students. Assessments completed by SPs or patients may enhance the evaluation of empathy.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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 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".