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Record W2803525064 · doi:10.1093/pch/pxy054.074

Effect of Monitor Placement on Situational Awareness and Visual Attention in Simulated Neonatal Resuscitations

2018· article· en· W2803525064 on OpenAlexaff
Brenda Hiu Yan Law, Po‐Yin Cheung, Sylvia van Os, Caroline Fray, Georg M. Schmölzer

Bibliographic record

VenuePaediatrics & Child Health · 2018
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChecklistNeonatal resuscitationMedicineEye trackingPupillary responseIntubationNeonatal intensive care unitRandomized controlled trialMedical emergencyEmergency medicineResuscitationPediatricsPsychologyAnesthesiaPupilSurgeryComputer science

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Decision-making in neonatal resuscitation depends on clinical evaluation, oxygen saturation and heart-rate. However, the position of vital signs monitors varies between institutions and might lead to obstructed or difficult to see displays, which might affect Health Care Provider (HCP) performance. OBJECTIVES To compare Situation Awareness (SA), Neonatal Resuscitation (NRP) checklist score, Visual Attention (VA) and participant satisfaction during simulated neonatal resuscitations using two vital signs monitors locations. DESIGN/METHODS NRP-trained HCPs were recruited from a tertiary Neonatal Intensive Care Unit and randomized to either central (eye-level on the radiant warmer) or peripheral (left of the warmer) monitor placement. Following an orientation scenario, each HCP lead a resuscitation requiring intubation and chest compressions with a high-fidelity manikin (Newborn HAL, Gaumard Scientific, Miami, FL) and a standardized assistant. Each scenario was paused at 3 predetermined points and the HCP was asked 5 SA questions at each pause, per the Situation Awareness Global Assessment Tool (SAGAT) format. Simulations were video-recorded to analyze SAGAT responses and performance rating using a modified NRP checklist. VA was recorded using eye-tracking glasses (Tobii Pro, Tobii Technology Inc., Falls Church, VA) worn by participants. Statistical analysis was performed using Mann-Whitney U test. A post-simulation survey examined user preference. RESULTS We randomized 30 HCPs; all were analyzed for SA and NRP checklist scores. Twenty-two eye-tracking recordings were of sufficient quality and analyzed. SAGAT scores (median 11/15 vs. 12/15, p=0.52) and NRP Checklist Scores (median 46/50, p=0.75) were similar between groups. Distribution of VA was also similar in both groups. In the post-simulation survey, all HCPs found central monitor placement convenient, compared with only 8/15 in peripheral placement. CONCLUSION During simulated neonatal resuscitation, HCPs found central monitor placement more convenient. However, no differences in accuracy of situation awareness responses, NRP checklist scores, or visual attention were found. Hi-fidelity simulation, SAGAT, and eye-tracking can be used to evaluate physical ergonomics of neonatal resuscitation.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.399
Teacher spread0.383 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2018
Admission routes1
Has abstractyes

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