Evidence for simulation-based education in hyperbaric medicine: A systematic review
Bibliographic record
Abstract
INTRODUCTION: Evidence from many areas of healthcare suggests that skills learned during simulation transfer to clinical settings; however, this has not yet been investigated in hyperbaric medicine. This systematic review aimed to identify, summarize, and assess the impact of simulation-based education in hyperbaric medicine. METHODS: Eligible studies investigated the effect of simulation-based education for learning in hyperbaric medicine, used any design, and were published in English in a peer-reviewed journal. Learning outcomes across all Kirkpatrick levels were included. MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials were searched. Pairs of independent reviewers assessed references for study eligibility. RESULTS: We found no article assessing the impact of simulation-based education in hyperbaric medicine published in English. Only one potentially relevant paper published in German was found. CONCLUSIONS: More research is needed to determine how the hyperbaric medicine community and their patients may benefit from simulation-based education to optimize both practice and patient care.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 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 | 0.001 |
| 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".