Analysis of neonatal resuscitation using eye tracking: a pilot study
Bibliographic record
Abstract
BACKGROUND: Visual attention (VA) is important for situation awareness and decision-making. Eye tracking can be used to analyse the VA of healthcare providers. No study has examined eye tracking during neonatal resuscitation. OBJECTIVE: To test the use of eye tracking to examine VA during neonatal resuscitation. METHODS: Six video recordings were obtained using eye tracking glasses worn by resuscitators during the first 5 min of neonatal resuscitation. Videos were analysed to obtain (i) areas of interest (AOIs), (ii) time spent on each AOI and (iii) frequency of saccades between AOIs. RESULTS: Five videos were of acceptable quality and analysed. Only 35% of VA was directed at the infant, with 33% at patient monitors and gauges. There were frequent saccades (0.45/s) and most involved patient monitors. CONCLUSION: During neonatal resuscitation, VA is often directed away from the infant towards patient monitors. Eye tracking can be used to analyse human performance during neonatal resuscitation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".