When patients teach students empathy: a systematic review of interventions for promoting medical student empathy
Bibliographic record
Abstract
Background: Despite growing emphasis on empathic care, numerous studies demonstrate diminishing empathy in medical students. Involving patient educators in medical curricula may be a solution. Therefore, we conducted a systematic review to evaluate patient-involved interventions that promote empathy among medical students. Method: A literature search of MEDLINE, Embase, PsycINFO, and ERIC databases was performed using the keywords "empathy," "medical student," and their synonyms. Results were independently screened in duplicate. Conflicts were resolved by group consensus. All English studies describing interventions that promote empathy in medical students engaging patient educators were included. Relevant data was extracted and summarized. Results: 1467 studies were screened. 14 studies were included, of which 10 were pilot studies. Studies included patient involved interventions such as storytelling (5/14), shadowing patients (3/14), recorded videos (3/14), or combinations of methods (3/14). Qualitative measurements of empathy included written feedback and group discussions. Quantitative measurements included validated scales measuring empathy. All studies demonstrated increase in empathy among medical students. Participants reported satisfaction with training and patients reported being proud of giving back by training future physicians. Conclusion: Interventions engaging patient educators were shown to have a positive impact on medical student empathy. Furthermore, patient-led education was shown to increase medical student understanding of subject and knowledge retention while empowering patients. Further implementation of patient-involved education is an important step forward in patient-partnered care and may identify additional advantages of patient engagement in medical education.
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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 | 0.009 | 0.153 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 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".