Efficacy of a Short Role-Play Training on Breaking Bad News in the Emergency Department.
Bibliographic record
Abstract
INTRODUCTION: Breaking bad news (BBN) in the emergency department (ED) represents a challenging and stressful situation for physicians. Many medical students and residents feel stressed and uncomfortable with such situations because of insufficient training. Our randomized controlled study aimed to assess the efficacy of a four-hour BBN simulation-based training on perceived self-efficacy, the BBN process, and communication skills. METHODS: Medical students and residents were randomized into a 160-hour ED clinical rotation without a formal BBN curriculum (control group [CG], n = 31) or a 156-hour ED clinical rotation and a four-hour BBN simulation-based training (training group [TG], n = 37). Both groups were assessed twice: once at the beginning of the rotation (pre-test) and again four weeks later. Assessments included a BBN evaluation via a simulation with two actors playing family members and the completion of a questionnaire on self-efficacy. Two blinded raters assessed the BBN process with the SPIKES (a delivery protocol for delivering bad news) competence form and communication skills with the modified BBN Assessment Schedule. RESULTS: Group-by-time effects adjusted by study year revealed a significant improvement in TG as compared with CG on self-efficacy (P < 0.001), the BBN process (P < 0.001), and communication skills (P < 0.001). TG showed a significant gain regarding the BBN process (+33.3%, P < 0.001). After the training, students with limited clinical experience prior to the rotation showed BBN performance skills equal to that of students in the CG who had greater clinical experience. CONCLUSION: A short BBN simulation-based training can be added to standard clinical rotations. It has the potential to significantly improve self-efficacy, the BBN process, and communication skills.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".