Simulation-Based Emergency Team Training in Pediatrics: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: The rare event of handling critically ill children often challenge the emergency care team. Several studies have investigated effects of simulation-based team training to prepare for such events, but the body of evidence remains to be compiled. We performed a systematic review of the effects of simulation-based team training on clinical performance and patient outcome. METHODS: From a search of MEDLINE, Embase, CINAHL, and Cochrane Library, we included studies of team training in emergency pediatric settings with reported clinical performance and patient outcomes. We extracted data using a predefined template and assessed risk of bias using the Cochrane risk-of-bias tool for randomized trials 2.0 and the Newcastle Ottawa Quality Assessment Scale. RESULTS: We screened 1926 abstracts and included 79 studies. We identified 15 studies reporting clinical health care professional performance or patient outcomes. Four studies reported survival data, 5 reported time-critical clinical events, 5 reported adherence to guidelines, checklists or tasks, and 2 reported on airway management. Randomized studies revealed improved team performance in simulated reevaluations 2 to 6 months after intervention. A meta-analysis was impossible because of heterogeneous interventions and outcomes. Most included studies had significant methodological limitations. CONCLUSIONS: Pediatric simulation-based team training improves clinical performance in time-critical tasks and adherence to guidelines. Improved survival was indicated but not concluded because of high risk of bias. Team performance and technical skills improved for at least 2 to 6 months. Future research should include longer-term measures of skill retention and patient outcomes or clinical measures of treatment quality whenever possible.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".