Effects of Simulation Fidelity on Health Care Providers on Team Training—A Systematic Review
Bibliographic record
Abstract
ABSTRACT: This systematic review, following PRISMA standards, aimed to assess the effectiveness of higher versus lower fidelity simulation on health care providers engaged in team training. A comprehensive search from January 1, 2011 to January 24, 2023 identified 1390 studies of which 14 randomized (n = 1530) and 5 case controlled (n = 257) studies met the inclusion criteria. The certainty of evidence was very low due to a high risk of bias and inconsistency. Heterogeneity prevented any metaanalysis. Limited evidence showed benefit for confidence, technical skills, and nontechnical skills. No significant difference was found in knowledge outcomes and teamwork abilities between lower and higher fidelity simulation. Participants reported higher satisfaction but also higher stress with higher fidelity materials. Both higher and lower fidelity simulation can be beneficial for team training, with higher fidelity simulation preferred by participants if resources allow. Standardizing definitions and outcomes, as well as conducting robust cost-comparative analyses, are important for future research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.144 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.013 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".