Effectiveness of a High-Fidelity Simulation-Based Training Program in Managing Cardiac Arrhythmias in Children
Bibliographic record
Abstract
OBJECTIVES: Pediatric cardiac arrest is a rare event. Its management requires technical (TSs) and nontechnical skills (NTSs). We assessed the effectiveness of a simulation-based training to improve these skills in managing life-threatening pediatric cardiac arrhythmias. METHODS: Four teams, each composed of 1 pediatric resident, 1 emergency medicine resident, and 2 pediatric nurses, were randomly assigned to the experimental group (EG) participating in 5 video-recorded simulation sessions with debriefing or to the control group (CG) assessed 2 times with video-recorded simulation sessions without debriefing at a 2-week interval. Questionnaires assessed self-reported changes in self-efficacy, stress, and satisfaction about skills. Blinded evaluators assessed changes in leaders' TSs and NTSs during the simulations and the time to initiate cardiopulmonary resuscitation. RESULTS: After training, stress decreased and satisfaction about skills increased in the EG, whereas it remained the same in the CG (P = 0.014 and P < 0.001, respectively). There was no significant change in self-efficacy. Analyses of video-recorded skills showed significant improvements in TSs and NTSs of the EG leaders after training, but not of the CG leaders (P = 0.026, P = 0.038, respectively). The comparison of the evolution of the 2 groups concerning time to initiate cardiopulmonary resuscitation was not significantly different between the first and last simulation sessions. CONCLUSIONS: A simulation-based training with debriefing had positive effects on stress and satisfaction about skills of pediatric residents and nurses and on observed TSs and NTSs of the leaders during simulation sessions. A future study should assess the effectiveness of this training in a larger sample and its impact on skills during actual emergencies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".