Nrp Prompt: A Randomized Controlled Trial of a Mobile App for Neonatal Resuscitation Training
Bibliographic record
Abstract
Abstract BACKGROUND: There is poor adherence to the Neonatal Resuscitation Program (NRP) algorithm by all levels of providers in simulated and clinical settings. While audio- visual prompting improves adherence to cardiopulmonary resuscitation, visual prompting alone has not been effective in improving NRP compliance. For this study, an iOS mobile app, NRP Prompt, was designed to provide audio -visual prompts based on user responses at NRP decision points. OBJECTIVES: To determine if NRP Prompt improves the adherence of novice NRP providers to the NRP algorithm compared to visual- only prompting in simulated neonatal resuscitation. DESIGN/METHODS: First year residents attending NRP training were randomized into intervention and control groups. Resident pairs used standard visual aids with NRP Prompt (intervention) or visual aids only (control) in two low- fidelity neonatal resuscitation simulations, where each resident took turns as team leader. Pairs were then evaluated in a third simulated scenario that was video -recorded, where neither group used NRP Prompt nor visual aids. The primary outcome was comparing the median checklist score in NRP Prompt versus control. Tw o independent NRP providers evaluated the video recordings of each pair using a validated NRP checklist. Secondary outcomes were: time to positive pressure ventilation (PPV), time to chest compressions and time to intubation. Inter-observer variability was determined using a two- way mixed -effects intra -class correlation coefficient (ICC). Median NRP scores and time to interventions were compared between intervention and control using the Wilcoxon ranked- sum test. RESULTs: 39 residents participated, 8 pairs in intervention and 7 pairs (and 1 group of 3) in control. The ICC was 0.69, indicating good inter-rater agreement. Median NRP scores did not differ in intervention 21 (interquartile range (IQR): 1.5) vs. control 21 (IQR: 1.5), p=0.89. Median time in seconds did not differ for time to PPV (60.5 (IQR: 19.5) vs. 48 (IQR: 13.5) p=0.12), chest compressions (202.5 (IQR: 54) vs. 216 (IQR: 71) p=0.69), and intubation (234 (IQR: 145) vs. 264 (IQR: 94.5) p=0.25). CONCLUSION: Training using NRP Prompt did not improve performance in simulated neonatal resuscitation. Potential reasons include voice prompts being distracting and smaller than hypothesized effect size. Future development of prompting apps should have options for different degrees of prompting tailored to user preferences.
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 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".