Manikin physical realism for resuscitation education: A systematic review
Why this work is in the frame
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Bibliographic record
Abstract
To evaluate the impact of higher physical realism of manikins on educational and clinical outcomes during life support education. This systematic review was conducted as part of the continuous evidence evaluation process of the International Liaison Committee on Resuscitation (ILCOR). A search of PubMed, Embase, and Cochrane was conducted from January 1, 2005 until April 30, 2024. Studies comparing training with higher physical realism manikins and lower realism manikins were eligible for inclusion. Studies comparing manikins to other forms of training (e.g. screen-based, virtual reality) were excluded. Risk of bias was assessed using Cochrane Risk of Bias 2 (RoB 2) for randomized trials and Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) for observational studies. For outcomes reported by four or more randomized studies, random effects meta -analysis using standardized mean difference was performed. Of the 1276 articles identified and screened, 21 articles comprised the final review (19 randomized trials, 2 observational studies). Meta-analysis of eight RCTs reporting simulation skill performance in a simulated clinical scenario at course conclusion demonstrated a benefit from the use of higher- realism manikins compared with lower realism manikins (standardized mean difference 0.66, 95% CI 0.08 – 1.25). Meta-analysis of seven RCTs reporting knowledge at course conclusion showed no significant difference between the use of both types of manikins. Significant risk of bias and a high degree of heterogeneity were found among the included studies. This systematic review found that higher manikin realism during resuscitation training was associated with improved simulated clinical scenario performance at course conclusion; without an effect on knowledge at course conclusion. Future studies should examine the impact of resource requirements for high realism simulation on generalizability and implementation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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 it