Paperdoi:10.1093/sleep/zsab146
Prediction of shiftworker alertness, sleep, and circadian phase using a model of arousal dynamics constrained by shift schedules and light exposure
SLEEP 44(11)
TL;DR
Field test of the arousal-dynamics model in 21 ICU nurses on rotating shifts, using shift times and light exposure. KSS predicted within ±1 point for 56–60% of ratings on day shifts and 48–52% on night shifts; sleep/wake overlap 81–87%. Accurate circadian phase needed individual light input.
Abstract
Study Objectives
The study aimed to, for the first time, (1) compare sleep, circadian phase, and alertness of intensive care unit (ICU) nurses working rotating shifts with those predicted by a model of arousal dynamics; and (2) investigate how different environmental constraints affect predictions and agreement with data.
Methods
The model was used to simulate individual sleep-wake cycles, urinary 6-sulphatoxymelatonin (aMT6s) profiles, subjective sleepiness on the Karolinska Sleepiness Scale (KSS), and performance on a Psychomotor Vigilance Task (PVT) of 21 ICU nurses working day, evening, and night shifts. Combinations of individual shift schedules, forced wake time before/after work and lighting, were used as inputs to the model. Predictions were compared to empirical data. Simulations with self-reported sleep as an input were performed for comparison.
Results
All input constraints produced similar prediction for KSS, with 56%–60% of KSS scores predicted within ±1 on a day and 48%–52% on a night shift. Accurate prediction of an individual’s circadian phase required individualized light input. Combinations including light information predicted aMT6s acrophase within ±1 h of the study data for 65% and 35%–47% of nurses on diurnal and nocturnal schedules. Minute-by-minute sleep-wake state overlap between the model and the data was between 81 ± 6% and 87 ± 5% depending on choice of input constraint.
Conclusions
The use of individualized environmental constraints in the model of arousal dynamics allowed for accurate prediction of alertness, circadian phase, and sleep for more than half of the nurses. Individual differences in physiological parameters will need to be accounted for in the future to further improve predictions.
Verbatim from the publisher's DOI record (opens in a new tab) · Publisher licence: https://creativecommons.org/licenses/by-nc-nd/4.0/
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Cite this paper
Knock, S. A., et al. (2021). Prediction of shiftworker alertness, sleep, and circadian phase using a model of arousal dynamics constrained by shift schedules and light exposure. SLEEP 44. https://doi.org/10.1093/sleep/zsab146
Knock, Stuart A., et al. 2021. "Prediction of shiftworker alertness, sleep, and circadian phase using a model of arousal dynamics constrained by shift schedules and light exposure." SLEEP 44. https://doi.org/10.1093/sleep/zsab146.
Knock, S. A. et al. (2021) 'Prediction of shiftworker alertness, sleep, and circadian phase using a model of arousal dynamics constrained by shift schedules and light exposure', SLEEP 44. doi: 10.1093/sleep/zsab146.
Knock, Stuart A., et al. "Prediction of shiftworker alertness, sleep, and circadian phase using a model of arousal dynamics constrained by shift schedules and light exposure." SLEEP 44, 2021. https://doi.org/10.1093/sleep/zsab146.
S. A. Knock et al., "Prediction of shiftworker alertness, sleep, and circadian phase using a model of arousal dynamics constrained by shift schedules and light exposure," SLEEP 44, 2021, doi: 10.1093/sleep/zsab146.
@article{knock2021prediction,
title = {{Prediction of shiftworker alertness, sleep, and circadian phase using a model of arousal dynamics constrained by shift schedules and light exposure}},
author = {Knock, Stuart A. and others},
year = {2021},
journal = {SLEEP 44},
doi = {10.1093/sleep/zsab146}
}Added to the ChatPPG research hub
