Occupational Safety & Sleep: Night and Shift Work
Night and Shift Work
Our research has been instrumental in understanding fatigue-related accidents and operational deficits in night and shift workers. Night shift workers experience significant challenges, including that workers sleeping during the day get substantially less total sleep and REM sleep compared to night sleep, leading to decrements in both psychomotor and cognitive performance. Workers also report feeling more tired, less happy, and less clear-thinking during night shifts. As a result, there are serious safety implications of sleep deprivation and circadian misalignment in operational settings.
Risks associated with fatigue that accumulates during work shifts have historically been managed through working time arrangements that specify fixed maximum durations of work shifts and minimum durations of time off. By themselves, such arrangements are not sufficient to curb risks to performance, safety, and health caused by misalignment between work schedules and the biological regulation of waking alertness and sleep. Science-based approaches for determining shift duration and mitigating associated risks, while addressing operational needs, require a recognition of the factors contributing to fatigue and fatigue-related risks; an understanding of evidence-based countermeasures that may reduce fatigue and/or fatigue-related risks; and an informed approach to selecting workplace-specific strategies for managing work hours.
Read more here: Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health (2021)
Over the past decade and a half, there have been considerable advances in technologies that objectively detect or predict operator fatigue, including onboard devices that monitor drivers' state or level of performance, as well as devices that predict fatigue in advance of a work cycle or trip. This paper discusses the challenges and opportunities for technological approaches to fatigue management.
Read more here: The challenges and opportunities of technological approaches to fatigue management (2011)
Inter-individual differences in performance impairment from sleep loss are substantial and consistent, as demonstrated and quantified here by means of the intraclass correlation coefficient (ICC) in two laboratory-based sleep deprivation studies. There is an urgent need, therefore, to consider inter-individual variability in biomathematical models of fatigue and performance, which currently treat individuals as being all the same. This paper demonstrates that inter-individual variability accounts for a large percentage of observed variance in neurobehavioral responses to sleep deprivation, and describes tools that model developers will need to produce a new generation of fatigue and performance models capable of incorporating inter-individual variability and useful for subject-specific prediction.
Read more here: Dealing with inter-individual differences in the temporal dynamics of fatigue and performance: Importance and techniques (2004)
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