The impact of a high fidelity simulation-based debriefing course on the Debriefing Assessment for Simulation in Healthcare (DASH)© score of novice instructors.
Bibliographic record
Abstract
INTRODUCTION: Experiential learning, followed by debriefing, is at the heart of Simulation-Based Medical Education (SBME) and has been proven effective to help master several medical skills. We investigated the impact of an educational intervention, based on high-fidelity SBME, on the debriefing competence of novice simulation instructors. METHODS: This is a prospective, randomized, quasi-experimental, pre- and post-test study. Sixty physicians without prior formal debriefing expertise attended a 5-day SBME seminar targeted on debriefing. Prior to the start of the seminar, 15 randomly chosen participants had to debrief a spaghetti and tape team exercise. Thereafter, the members of each team assessed their debriefer's performance using the Debriefing Assessment for Simulation in Healthcare (DASH)© score. The debriefing seminar that followed (intervention) consisted of 5 days of teaching that included theoretical and simulation training. Each scenario was followed by a Debriefing of the Debriefing (DOD) session conducted by the expert instructor. At the end of the course, 15 randomly chosen debriefers had to debrief a second tower building exercise and were re-evaluated with the DASH score by their respective team members. The Wilcoxon signed-rank test was used to compare pre- and post-test scores. Statistical tests were performed using GraphPad Prism 6.0c for Mac. RESULTS: A significant improvement in all items of the DASH score was noted following the seminar. The debriefers significantly improved their performance with regard to "maintaining an engaging learning environment" (Median [IQR]) (4[3-5] after the pre-test vs. 5.5[5-6] after the post-test, p<0.001); "structuring the debriefing in an organized way" (5[4-5] after the pre-test vs. 5[5-6] after the post-test, p=0.002); "provoking engaging discussion" (4[3-5.75] after the pre-test vs. 6[5-6] after the post-test, p<0.001); "identifying and exploring performance gaps" (5[4-6] after the pre-test vs. 6[5-6] after the post-test, p=0.014); and "helping trainees to achieve and sustain good future performance" (4[3-5] after the pre-test vs. 6[5-6] after the post-test, p<0.001). CONCLUSION: A simulation-based debriefing course, based mainly on DOD sessions, allowed novice simulation instructors to improve their overall debriefing skills including, more specifically, the ability to foster engagement in discussions and maintain an engaging learning environment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".