Assessment of Healthcare Provider Workload in Neonatal Resuscitation
Bibliographic record
Abstract
Objective: Human errors or protocol deviations during neonatal resuscitation are common. Excess workload has been proposed as a contributor to human error during medical tasks. We aim to characterize healthcare providers' perceived workload during neonatal resuscitation. Design: Perceived workload was measured using a multi-dimensional retrospective National Aeronautics and Space Administration Task Load Index (NASA TLX) survey. The NASA TLX collects data on mental, physical, and temporal demand, performance, effort, and frustration. Each section is rated independently by participants on a scale of 0–20 (0 being lowest and 20 being highest). The Raw-TLX score is a composite score of all dimensions and presented on a scale of 0–100. Healthcare providers complete a paper and pencil survey after attending delivery room resuscitations within 3 months. Setting: Level three neonatal intensive care unit at the Royal Alexandra Hospital, Edmonton, AB, Canada. Participants: All neonatal healthcare providers who attended deliveries. Exposure: Participation in the delivery room care of newborns. Measurement: Raw TLX scores as a measure of overall workload and scores for each dimension of workload. Main Results: During the study period, ~880 neonatal resuscitation events occurred, and a total of 204 surveys were completed. Healthcare providers completed one survey for 179 deliveries, two surveys for 20 deliveries, and three surveys for 5 deliveries. The mean (standard deviation) gestational age was 35 (5) weeks, and the median (interquartile range) birth weight was 2,690 (1,830–3,440) g. Interventions at delivery were (i) stimulation 149 (73%), suction 130 (64%), continuous positive airway pressure 120 (59%), positive pressure ventilation 105 (52%), intubation 33 (16%), chest compression 10 (5%), and epinephrine 4 (2%). The overall median (interquartile range) Raw-TLX was 34 (18–49). The scores varied by dimension with mental demand 10 (5–14), physical demand 4 (1–6), temporal demand 8 (3–14), performance 4 (2–6), effort 8 (4–13), and frustration 4 (1–10). Raw-TLX scores were higher when healthcare providers performed any intervention compared to no intervention [35 (22–49) vs. 8 (6–18), p = 0.0011]; intubation and no intubation was [55 (46–62) vs. 30 (17–46), p = 0.0001], and between performing chest compression vs. no chest compression [55 (49–64) vs. 33 (18–47), p = 0.001]. Conclusion: Perceived workload of neonatal healthcare providers increases during higher acuity deliveries. Healthcare providers' workload during neonatal resuscitation can be measured using NASATLX and was inversely associated with 5-min Apgar score. Future studies assessing healthcare providers' perceived workload during neonatal resuscitation in different settings are warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".