Simulation-Based Summative Assessment of Neonatal Resuscitation Providers Using the RETAIN Serious Board Game—A Pilot Study
Bibliographic record
Abstract
Background Each year, 13-26 million newborn babies require help to breathe at birth. Healthcare professionals (HCPs) who provide neonatal resuscitative care must be frequently evaluated to maintain and improve the quality of healthcare delivered. While simulation-based competence assessment is preferred, resource constraints hinder uptake. We aimed to examine if the RETAIN simulation-based boardgame can be used to assess HCPs’ neonatal resuscitation knowledge. Method Twenty neonatal HCPs (19 females) from the Royal Alexandra Hospital (Edmonton, Canada) were recruited. First, they completed an open-answer written test of one neonatal resuscitation scenario. Then, they completed one neonatal resuscitation scenario of difficulty comparable to that of the open-answer written test, but this time using the RETAIN board game. In the RETAIN board game (https://playretain.com, RETAIN Labs Medical Inc, Edmonton, Canada), players perform simulated neonatal resuscitation scenarios based on real-life cases, using action cards and equipment pieces. Sessions were video-recorded and scored using Neonatal Resuscitation Program 2015 guidelines. Data are reported as mean (standard deviation) for normally distributed continuous variables, and as median (interquartile range) for non-normal continuous variables. Results Participants consisted of the following HCPs: 8 nurses, 4 respiratory therapists, 4 nurse practitioners, and 4 neonatal fellows with median(IQR) 10.5(3-17) years of clinical experience. Overall mean (SD) Open-answer test and Game Performance was 8.6(2.1) out of 16 possible points (53%) and 29(3.2) out of 40 possible points (74%), respectively. Out of the 10 actions shared between the open-answer test and game scenario, performance on the open-answer test was mean(SD) 7.2(1.3) (72%) and game performance was mean(SD) 8.8(1.4) (88%) (V=17, p<0.01). Conclusion RETAIN may provide an enjoyable and standardized alternative towards summative assessment of neonatal resuscitation providers. RETAIN may be used to improve more frequent and ubiquitous uptake of simulation-based competence assessment in healthcare settings.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".