Fatigue risk management based on self-reported fatigue: Expanding a biomathematical model of fatigue-related performance deficits to also predict subjective sleepiness

Biomathematical modeling of fatigue due to sleep inertia

Biomathematical models of fatigue capture the physiology of sleep/wake regulation and circadian rhythmicity to predict changes in neurobehavioral functioning over time. We used a biomathematical model of fatigue linked to the adenosinergic neuromodulator/receptor system in the brain as a framework to predict sleep inertia, that is, the transient neurobehavioral impairment experienced immediately after awakening. Based on evidence of an adenosinergic basis for sleep inertia, we expanded the biomathematical model with novel differential equations to predict the propensity for sleep inertia during sleep and its manifestation after awakening. Using datasets from large laboratory studies of sleep loss and circadian misalignment, we calibrated the model by fitting just two new parameters and then validated the model's predictions against independent data. The expanded model was found to predict the magnitude and time course of sleep inertia with generally high accuracy. Analysis of the model's dynamics revealed a bifurcation in the predicted manifestation of sleep inertia in sustained sleep restriction paradigms, which reflects the observed escalation of the magnitude of sleep inertia in scenarios with sleep restriction to less than ∼ 4 h per day. Another emergent property of the model involves a rapid increase in the predicted propensity for sleep inertia in the early part of sleep followed by a gradual decline in the later part of the sleep period, which matches what would be expected based on the adenosinergic regulation of non-rapid eye movement (NREM) sleep and its known influence on sleep inertia. These dynamic behaviors provide confidence in the validity of our approach and underscore the predictive potential of the model. The expanded model provides a useful tool for predicting sleep inertia and managing impairment in 24/7 settings where people may need to perform critical tasks immediately after awakening, such as on-demand operations in safety and security, emergency response, and health care.

Long-term influence of sleep/wake history on the dynamic neurobehavioural response to sustained sleep restriction

Chronic sleep restriction, common in today's 24/7 society, causes cumulative neurobehavioural impairment, but the dynamics of the build-up and dissipation of this impairment have not been fully elucidated. We addressed this knowledge gap in a laboratory study involving two, 5-day periods of sleep restriction to 4 hr per day, separated by a 1-day dose-response intervention sleep opportunity. We measured sleep physiological and waking neurobehavioural responses in 70 healthy adults, each randomized to one of seven dose-response intervention sleep doses ranging from 0 to 12 hr, or a non-sleep-restricted control group. As anticipated, sleep physiological markers showed homeostatic dynamics throughout the study, and waking neurobehavioural impairment accumulated across the two sleep restriction periods. Unexpectedly, there was only a slight and short-lived effect of the 1-day dose-response intervention sleep opportunity. Whether the dose-response intervention sleep opportunity involved extension, further restriction or total deprivation of sleep, neurobehavioural functioning during the subsequent second sleep restriction period was dominated by prior sleep-wake history. Our findings revealed a profound and enduring influence of long-term sleep-wake history as a fundamental aspect of the dynamic regulation of the neurobehavioural response to sleep loss.

Steps toward developing a comprehensive fatigue monitoring and mitigation solution: perspectives from a cohort of United States Naval Surface Force officers

Study Objectives

This study analyzed fatigue and its management in US Naval Surface Force warships, focusing on understanding current practices and barriers, and examining the influence of organizational and individual factors on managing chronic fatigue. Furthermore, this study explored the impact of organizational and individual factors on fatigue management.

Methods

As part of a larger study, 154 naval officers (mean ± standard deviation; 31.5 ± 7.0 years; 8.8 ± 6.8 years of service; 125 male, and 29 female) completed a fatigue survey. The survey addressed (1) self-reported fatigue, (2) fatigue observed in others, (3) fatigue monitoring strategies, (4) fatigue mitigation strategies, and (5) barriers to fatigue mitigation. Logistic and ordinal regressions were performed to examine the effect of individual (i.e. sleep quality and years in military service) and organizational (i.e. ship-class) factors on fatigue outcomes.

Results

Fatigue was frequently experienced and observed by 23% and 54% of officers, respectively. Of note, officers often monitored fatigue reactively (i.e. 65% observed others nodding off and 55% observed behavioral impairments). Still, officers did not frequently implement fatigue mitigation strategies, citing few operationally feasible mitigation strategies (62.3%), being too busy (61.7%), and not having clear thresholds for action (48.7%). Fatigue management varies across organizational factors, which must be considered when further developing fatigue management strategies.

Conclusions

Fatigue remains a critical concern aboard surface force ships and it may be better addressed through development of objective sleep and fatigue monitoring tools that could inform leadership decision-making.

Dawn of a New Dawn: Advances in Sleep Health to Optimize Performance

Optimal sleep health is a critical component to high-level performance. In populations such as the military, public service (eg, firefighters), and health care, achieving optimal sleep health is difficult and subsequently deficiencies in sleep health may lead to performance decrements. However, advances in sleep monitoring technologies and mitigation strategies for poor sleep health show promise for further ecological scientific investigation within these populations. The current review briefly outlines the relationship between sleep health and performance as well as current advances in behavioral and technological approaches to improving sleep health for performance.

Emerging applications of objective sleep assessments towards the improved management of insomnia

Self-reported sleep difficulties are the primary concern associated with diagnosis and treatment of chronic insomnia. This said, in-home sleep monitoring technology in combination with self-reported sleep outcomes may usefully assist with the management of insomnia. The rapid acceleration in consumer sleep technology capabilities together with their growing use by consumers means that the implementation of clinically useful techniques to more precisely diagnose and better treat insomnia are now possible. This review describes emerging techniques which may facilitate better identification and management of insomnia through objective sleep monitoring. Diagnostic techniques covered include insomnia phenotyping, better detection of comorbid sleep disorders, and identification of patients potentially at greatest risk of adverse outcomes. Treatment techniques reviewed include the administration of therapies (e.g., Intensive Sleep Retraining, digital treatment programs), methods to assess and improve treatment adherence, and sleep feedback to address concerns about sleep and sleep loss. Gaps in sleep device capabilities are also discussed, such as the practical assessment of circadian rhythms. Proof-of-concept studies remain needed to test these sleep monitoring-supported techniques in insomnia patient populations, with the goal to progress towards more precise diagnoses and efficacious treatments for individuals with insomnia.

Working around the Clock: Is a Person’s Endogenous Circadian Timing for Optimal Neurobehavioral Functioning Inherently Task-Dependent?

Neurobehavioral task performance is modulated by the circadian and homeostatic processes of sleep/wake regulation. Biomathematical modeling of the temporal dynamics of these processes and their interaction allows for prospective prediction of performance impairment in shift-workers and provides a basis for fatigue risk management in 24/7 operations. It has been reported, however, that the impact of the circadian rhythm—and in particular its timing—is inherently task-dependent, which would have profound implications for our understanding of the temporal dynamics of neurobehavioral functioning and the accuracy of biomathematical model predictions. We investigated this issue in a laboratory study designed to unambiguously dissociate the influences of the circadian and homeostatic processes on neurobehavioral performance, as measured during a constant routine protocol preceded by three days on either a simulated night shift or a simulated day shift schedule. Neurobehavioral functions were measured every 3 h using three functionally distinct assays: a digit symbol substitution test, a psychomotor vigilance test, and the Karolinska Sleepiness Scale. After dissociating the circadian and homeostatic influences and accounting for inter-individual variability, peak circadian performance occurred in the late biological afternoon (in the “wake maintenance zone”) for all three neurobehavioral assays. Our results are incongruent with the idea of inherent task-dependent differences in the endogenous circadian impact on performance. Rather, our results suggest that neurobehavioral functions are under top-down circadian control, consistent with the way they are accounted for in extant biomathematical models.