Chapter 9 - Individual differences in cognitive vulnerability to fatigue in the laboratory and in the workplace

https://doi.org/10.1016/B978-0-444-53817-8.00009-8Get rights and content

Abstract

Individual differences in cognitive functioning during extended work hours and shift work are of considerable magnitude, and observed both in the laboratory and in the workplace. These individual differences have a biological basis in trait-like, differential vulnerability to fatigue from sleep loss and circadian misalignment. Trait-like vulnerability is predicted in part by gene polymorphisms and other biological or psychological characteristics, but for the larger part it remains unexplained. A complicating factor is that whether individuals are vulnerable or resilient to sleep deprivation depends on the fatigue measure considered—subjective versus objective assessment, or one cognitive task versus another. Such dissociation has been observed in laboratory data published previously, and in data from a simulated operational setting first presented here. Discordance between subjective and objective measures of fatigue has been documented in various contexts, and may be one of the reasons why vulnerable individuals do not systematically opt out of professions involving high cognitive demands and exposure to fatigue. Discordance in vulnerability to fatigue among different measures of cognitive performance may be related to the “task impurity problem,” which implies that interrelated cognitive processes involved in task performance must be distinguished before overall performance outcomes can be fully understood. Experimental studies and cognitive and computational modeling approaches are currently being employed to address the task impurity problem and gain new insights into individual vulnerability to fatigue across a wide range of cognitive tasks. This ongoing research is driving progress in the management of risks to safety and productivity associated with vulnerability to cognitive impairment from fatigue 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

References (57)

  • J.R. Anderson et al.

    An integrated theory of the mind

    Psychological Review

    (2004)
  • J. Axelsson et al.

    Sleepiness and performance in response to repeated sleep restriction and subsequent recovery during semi-laboratory conditions

    Chronobiology International

    (2008)
  • S. Banks et al.

    Neurobehavioral dynamics following chronic sleep restriction: Dose-response effects of one night for recovery

    Sleep

    (2010)
  • G. Belenky et al.

    Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: A sleep dose-response study

    Journal of Sleep Research

    (2003)
  • B. Bjorvatn et al.

    Subjective and objective measures of adaptation and readaptation to night work on an oil rig in the North Sea

    Sleep

    (2006)
  • J.A. Caldwell et al.

    Are individual differences in fatigue vulnerability related to baseline differences in cortical activation?

    Behavioral Neuroscience

    (2005)
  • M.W.L. Chee et al.

    Functional neuroimaging insights into how sleep and sleep deprivation affect memory and cognition

    Current Opinion in Neurobiology

    (2008)
  • C.A. Czeisler

    Medical and genetic differences in the adverse impact of sleep loss on performance: Ethical considerations for the medical profession

    Transactions of the American Clinical and Climatological Association

    (2009)
  • S. Daan et al.

    Timing of human sleep: Recovery process gated by a circadian pacemaker

    The American Journal of Physiology

    (1984)
  • D.-J. Dijk et al.

    Integration of human sleep-wake regulation and circadian rhythmicity

    Journal of Applied Physiology

    (2002)
  • D.F. Dinges et al.

    Microcomputer analyses of performance on a portable, simple visual RT task during sustained operations

    Behavior Research Methods, Instruments, and Computers

    (1985)
  • S.M. Doran et al.

    Sustained attention performance during sleep deprivation: Evidence of state instability

    Archives of Italian Biology

    (2001)
  • M. Gillberg et al.

    Individual differences in susceptibility to sleep loss

  • G. Gunzelmann et al.

    Decreased arousal as a result of sleep deprivation: The unraveling of cognitive control

  • G. Gunzelmann et al.

    Individual differences in sustained vigilant attention: Insights from computational cognitive modeling

  • G. Gunzelmann et al.

    Examining sources of individual variation in sustained attention

  • M. Härmä

    Sleepiness and shiftwork: Individual differences

    Journal of Sleep Research

    (1995)
  • S.R. Hursh et al.

    Fatigue and performance modeling

  • Cited by (43)

    • Beneficial effects of exercise training on cognitive performances during total sleep deprivation in healthy subjects

      2020, Sleep Medicine
      Citation 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 Reviews
      Citation 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, NeuroImage
      Citation 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 Prevention
      Citation 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.

    View all citing articles on Scopus
    View full text