Pilot feasibility testing of biomathematical model recommendations for personalising sleep timing in shift workers

Sleep disturbances and circadian disruption play a central role in adverse health, safety, and performance outcomes in shift workers. While biomathematical models of sleep and alertness can be used to personalise interventions for shift workers, their practical implementation is undertested. This study tested the feasibility of implementing two biomathematical models-the Phillips-Robinson Model and the Model for Arousal Dynamics-in 28 shift-working nurses, 14 in each group. The study examined the overlap and adherence between model recommendations and sleep behaviours, and changes in sleep following the implementation of recommendations. For both groups combined, the mean (SD) percentage overlap between when a model recommended an individual to sleep and when sleep was obtained was 73.62% (10.24%). Adherence between model recommendations and sleep onset and offset times was significantly higher with the Model of Arousal Dynamics compared to the Phillips-Robinson Model. For the Phillips-Robinson model, 27% of sleep onset and 35% of sleep offset times were within ± 30 min of model recommendations. For the Model of Arousal Dynamics, 49% of sleep onset, and 35% of sleep offset times were within ± 30 min of model recommendations. Compared to pre-study, significant improvements were observed post-study for sleep disturbance (Phillips-Robinson Model), and insomnia severity and sleep-related impairments (Model of Arousal Dynamics). Participants reported that using a digital, automated format for the delivery of sleep recommendations would enable greater uptake. These findings provide a positive proof-of-concept for using biomathematical models to recommend sleep in operational contexts.

Prediction of shiftworker alertness, sleep, and circadian phase using a model of arousal dynamics constrained by shift schedules and light exposure

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.

Does the evidence support brief (≤30-mins), moderate (31-60-mins), or long duration naps (61+ mins) on the night shift? A systematic review

We performed a systematic review of four databases to determine if the evidence supports a short or long duration nap during night shifts to mitigate fatigue, and/or improve health, safety, or performance for emergency services and public safety personnel (PROSPERO CRD42020156780). We focused on experimental research and evaluated the quality of evidence with the grading of recommendations, assessment, development, and evaluation (GRADE) framework. We used the Cochrane Collaboration's risk of bias tool to assess bias and reported findings using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. Our search yielded n = 10,345 records and n = 44 were reviewed in full-text. Inter-rater agreement during screening was substantial (Kappa = 0.66). We retained n = 11 publications, reporting on n = 7 experimental studies with a cumulative sample size of n = 140. We identified wide variation in study design, napping interventions (i.e., timing, placement, and duration), and outcomes. We identified mixed findings comparing brief, moderate, and long duration naps on outcomes of interest. All seven studies presented serious risk of bias and the quality of evidence was rated as low. Based on the best available evidence, decisions regarding nap duration during night shift work should be based on time (post-nap) and outcome.

The prevalence of excessive sleepiness is higher in shift workers than in patients with obstructive sleep apnea

Excessive daytime sleepiness (EDS) is a common feature among shift workers as well as in obstructive sleep apnea (OSA) patients. There are several important accidents related to sleep disturbances causing EDS. The aim of this study was to evaluate EDS in a group of shift workers (regular rotating) from civil aviation and to compare them with OSA patients (n = 300) and with a group of regular workers (RW) (n = 140). Our sample was composed of 730 working-age individuals (aged 18-67 years). The regular rotating shift workers (SW) sample was composed of 290 aeronautical mechanics. EDS was evaluated with the Epworth Sleepiness Scale (ESS) and defined as a score ≥ 11. The prevalence value obtained for the EDS of RW was 37.1%, for SW it was 60.7% and for OSA patients it was 40.7%. A logistic regression model for EDS in a subsample composed of men and matched for age and BMI, controlling for self-reported sleep duration, showed an increased risk of EDS for SW (OR = 3.91, p = .001), with the RW group as reference. OSA patients did not differ from RW on EDS levels. This study emphasizes the presence of EDS in a shift work group of civil aviation professionals, which exceeded the EDS level of a positive control group of OSA patients. Sleep hygiene education for companies' workers and management is important and mitigation strategies should be implemented to reduce excessive sleepiness among workers.