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Record W4400293170 · doi:10.3390/children11070793

A Randomized Controlled Simulation Trial of a Neonatal Resuscitation Digital Game Simulator for Labour and Delivery Room Staff

2024· article· en· W4400293170 on OpenAlexafffund
Christiane Bilodeau, Georg M. Schmölzer, Maria Cutumisu

Bibliographic record

VenueChildren · 2024
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsMcGill UniversityUniversity of Alberta
FundersAlberta InnovatesWomen and Children's Health Research Institute
KeywordsSimulationRandomized controlled trialResuscitationNeonatal resuscitationComputer scienceMedicineAnesthesiaSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Healthcare providers (HCPs) working in labour and delivery rooms need to undergo regular refresher courses to maintain their neonatal resuscitation skills, which are shown to decline over time. However, due to their irregular schedules and limited time, HCPs encounter difficulties in readily accessing refresher programs. RETAIN is a digital game that simulates a delivery room to facilitate neonatal resuscitation training for HCPs. OBJECTIVE: This study aims to ascertain whether participants enjoyed the RETAIN digital game simulator and whether it was at least as good as a video lecture at refreshing and maintaining participants' neonatal resuscitation knowledge. METHODS: = 42 labour and delivery room HCPs were administered a pre-test of neonatal resuscitation knowledge using a manikin. Then, they were randomly assigned to a control or a treatment group. For 20-30 min, participants in the control group watched a neonatal resuscitation lecture video, while those in the treatment group played the RETAIN digital game simulator of neonatal resuscitation scenarios. Then, all participants were administered a post-test identical to the pre-test. Additionally, participants in the treatment group completed a survey of attitudes toward the RETAIN simulator that provided a measure of enjoyment of the RETAIN game simulator. After two months, participants were administered another post-test identical to the pre-test. RESULTS: For the primary outcome (neonatal resuscitation performance), an analysis of variance revealed that participants significantly improved their neonatal resuscitation performance over the first two time points, with a significant decline to the third time point, the same pattern of results across conditions, and no differences between conditions. For the secondary outcome (attitudes toward RETAIN), participants in the treatment condition also reported favourable attitudes toward RETAIN. CONCLUSIONS: Labour and delivery room healthcare providers in both groups (RETAIN simulator or video lecture) significantly improved their neonatal resuscitation performance immediately following the intervention, with no group differences. The findings suggest that participants enjoyed interacting with the RETAIN digital game simulator, which provided a similar boost in performance right after use to the more traditional intervention.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.332
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes2
Has abstractyes

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