Using the RETAIN Tabletop Simulator as a Summative Assessment Tool for Neonatal Resuscitation Healthcare Professionals: A Pilot Study
Bibliographic record
Abstract
Background Frequent and objective summative assessment of neonatal healthcare providers is important to ensure high quality care to patients during neonatal resuscitation. Currently, neonatal resuscitation providers are only individually assessed using an at-home online multiple-choice questionnaire. While simulation-based assessment is preferred, resource constraints limit its widespread uptake. An alternative approach to simulation-based summative assessment is needed. Simulation-based serious games may provide a solution. Objective The aim of this study was to examine if individual performance on the RETAIN (REsuscitation TrAINing for healthcare professionals) tabletop simulator can be used as a summative assessment of neonatal resuscitation providers, regardless of their prior board-game experience. Method Neonatal healthcare providers were recruited from a tertiary perinatal center to complete a 1) demographic pre-survey, 2) neonatal resuscitation scenario using an open-answer written pre-test, 3) neonatal resuscitation scenario using the RETAIN tabletop simulator, and 4) post-survey measuring usage and attitudes towards board games. Multiple linear regression analyses using the Johnson-Neyman technique were conducted in R to probe the moderation effect of Years of Board Game on the relationship between Pre-test and Game Performance. Results Twenty Neonatal Resuscitation Program-trained healthcare providers (nurses, nurse practitioners, respiratory therapists, and fellows) were recruited for this study (n=19 females). Participants’ mean(standard deviation) pre-test score was 8.35(1.81) out of a total 16 possible points (52%), and a score of 18(4.41) out of a total of 40 possible points (45%) using RETAIN. Overall board game experience was 22.5(12.6) years. Finally, Years of Board Game moderated significantly the relation between the Pre-test and Game Performance (B = -0.13, SE = 0.05, beta = -.48, t = -2.77, p < .05; 95% CI [-0.24, -0.03]). Thus, participants’ performance on the two tests (written and simulator) was significantly positively associated, but only for those who reported fewer than 21.5 years of board game experience. Conclusion This study reports preliminary results of a pilot study, indicating that the RETAIN tabletop simulator could be used as a simulation-based summative assessment, an enjoyable, low-cost alternative to traditional assessment approaches. RETAIN offers a solution to the need for more frequent and continued assessment of neonatal resuscitation providers.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".