Chapter 9 - Individual differences in cognitive vulnerability to fatigue in the laboratory and in the workplace
Section snippets
Trait individual differences in vulnerability to fatigue
Individual differences in tolerance for, adaptation to, and impairment from extended work hours and shift work have been documented across a range of operational settings (Gillberg and Åkerstedt, 1985, Härmä, 1995, Monk and Folkard, 1985). Evidence is accumulating that these individual differences may have a biological basis (Van Dongen, 2006), involving differences in vulnerability to fatigue (sleepiness, loss of alertness) due to sleep deprivation and circadian misalignment. Fatigue is
Individual differences in vulnerability to fatigue in operational settings
The existence of trait-like individual differences in vulnerability to fatigue may be crucially important for workers in 24/7 operational settings, such as medical personnel (Czeisler, 2009), first responders (Lammers-van der Holst et al., 2006), and aviators (Caldwell et al., 2008). However, it is not a priori evident that laboratory-based assessments of individual variability translate reliably to the workplace. In populations that are highly trained and also frequently exposed to extended
New research into distinct cognitive dimensions of vulnerability to fatigue
The curious finding that systematic individual differences in vulnerability to sleep loss depend on the outcome measure at hand, both in a highly controlled study of healthy young adults from the general population using laboratory measures of performance and fatigue (Van Dongen et al., 2004a) and in a simulator study of highly selected, active-duty jet fighter pilots using high-fidelity simulated flight performance measures (Van Dongen et al., 2006), suggests that there is much to learn yet
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State space model detection of driving fatigue considering individual differences and time cumulative effect
2024, International Journal of Transportation Science and TechnologyMental fatigue, anticipated effort, and subjective valuations of exercising predict choice to exercise or not: A mixed-methods study
2021, Psychology of Sport and ExerciseBeneficial effects of exercise training on cognitive performances during total sleep deprivation in healthy subjects
2020, Sleep MedicineCitation Excerpt :It has been demonstrated that both acute total sleep deprivation (TSD) and chronic sleep restriction impair the ability to maintain wakefulness, increase subjective sleepiness and sleep propensity, and, most critically, reduce various aspects of cognitive performance [1–3]. In studies conducted in our laboratory and by other teams, as well as in different professional situations inducing insufficient sleep, the most consistently and dramatically affected cognitive capacities were sustained attention accompanied by an increased occurrence of involuntary microsleeps [2,4,5]. In comparison, studies have highlighted a differential disruption of sustained attention and executive processes by TSD [6–9].
Effects of fatigue on teams and their role in 24/7 operations
2019, Sleep Medicine ReviewsCitation Excerpt :Conversely, aligning work schedules with the timing of the biological clock improves sleep [23] and, by extension, may help to mitigate fatigue and associated performance deficits. Importantly, the level of vulnerability to fatigue that each individual brings to the workplace depends on the task at hand [14]. A distinction can be made between tasks that predominantly 1) involve bottom-up processing of information generated by the task environment, as is the case in tasks that require continuous monitoring of systems and acutely detecting anomalies; versus 2) engage top-down attentional control to stay focused and facilitate decision making.
Vulnerability to mood degradation during sleep deprivation is influenced by white-matter compactness of the triple-network model
2019, NeuroImageCitation Excerpt :While cognitive and affective deficits have been well documented and reliably associated with SD, it is also true that lack of sleep does not affect all people to the same extent or in the same way (Tkachenko and Dinges, 2018). Work by Van Dongen and others has demonstrated that there are consistent trait-like differences in the magnitude of vulnerability/resistance that individuals show to cognitive declines during SD (Van Dongen et al., 2004, 2011, 2012; Van Dongen and Belenky, 2009; King et al., 2009; Patanaik et al., 2014; Rupp et al., 2012), and may involve networks such as the control-execution network (CEN). The specific cognitive or performance response to SD appears to be highly reproducible within a given individual even when assessed months or years apart (Dennis et al., 2017).
Drowsiness measures for commercial motor vehicle operations
2019, Accident Analysis and PreventionCitation Excerpt :They also vary with regard to their psychometric properties (e.g., reliability, validity, and predictive capability), their usability, and the extent to which they are susceptible to confounding factors (Dinges and Grace, 1998; Balkin et al., 2004; Abe et al., 2014; Kosmadopoulos et al., 2017; Sandström et al., 2017). Different drowsiness measures may show poor concurrent validity with each other (Leproult et al., 2003; Van Dongen et al., 2003a; Van Dongen et al., 2004; Van Dongen et al., 2011d); they are typically not simply interchangeable. The suitability for operational use of any measure of drowsiness is determined by many or all of these issues.