Simulating empathy: A qualitative experiential study of embedded resident learners in an empathy curriculum
Bibliographic record
Abstract
Objectives: Physician empathy and communication skills are crucial parts of a successful emergency department (ED) interaction. This study aimed to evaluate whether these skills can be improved through a novel curriculum where interns act as patients for their senior residents during simulated ED cases. Methods: Twenty-five residents participated in the curriculum. Prior to the cases, participants filled out the Toronto Empathy Questionnaire (TEQ). They then completed three simulated cases, with the 11 interns portraying the patients and the 14 seniors (postgraduate year [PGY]-2 and PGY-3 residents) in the physician role. Following the cases, the residents participated in a recorded, structured focus group. At the conclusion of the session participants again filled out the TEQ and answered a Likert questionnaire on their thoughts about the curriculum. Qualitative analysis was used to determine themes from the debriefs. Results: ). On qualitative analysis, we derived four major themes: empathy, communication, feedback, and physician experience. The most common subthemes discussed were empathy for the patient situation and the importance of communicating visit expectations. On a 5-point Likert survey related to the simulated cases, respondents rated comfort providing feedback to their peers (mean ± SD 4.41 ± 0.95) and gaining insight into the patient experience (mean ± SD 4.27 ± 0.83). Conclusions: The embedded intern exercise was rated well by resident participants, with no observed change in empathy scores. Qualitative analysis identified empathy and communication as major themes. Residents enjoyed this style of simulation and found it realistic.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".