Current Approaches and Challenges to Development of an Individualized Sleep and Performance Prediction Model~!2009-03-22~!2010-05-11~!2010-07-15~!

Abstract

Workplace safety and productivity will be enhanced considerably with the development and application of individualized sleep and performance prediction models. These are models that predict an individual's operational performance based on his/her unique sleep schedule, individual sleep requirements, and individual pattern of responses to sleep loss across a variety of cognitive performance domains. Progress in the individualization of such models will occur as the result of integrated efforts based on (a) an expanding understanding of the relevant physiological processes underlying the sleep/circadian/performance interactions as well as (b) novel empirical and statistical approaches. In the present paper, an overview is presented of the state of the art of the individualization of sleep and performance models with sections on current efforts in model integration, the application of Bayesian forecasting techniques to the problem of model individualization, construction of Bayesian confidence intervals for predicted performance, and the problem of generalizability of individualized model predictions -i.e., the problem of using models constructed with performance data from one cognitive domain to predict performance in another cognitive domain. Success in model individualization will ultimately be facilitated by concerted, coordinated efforts involving multiple scientific entities and stakeholders.

Deconstructing and reconstructing cognitive performance in sleep deprivation

“…This makes it challenging, in general, to accurately predict the quantitative impact of sleep loss on performance for any specific job task. 12 …”

Performance Deficits during Sleep Loss

“…8,9 It has been proposed that the physiologic basis of this state instability may be a toggle switch (of the sort proposed by Saper and colleagues 10 ), in which sleeppromoting neurons within the ventral lateral preoptic nucleus and monoaminergic wake-promoting neurons inhibit each other, resulting in stable sleep when the former neurons are more active, stable wakefulness when the latter are more active, and relative instability as the activity levels and influence of these two cell groups on the toggle switch approaches parity. 11 Awareness of the deleterious effects of sleep loss have grown steadily over the past decade. Awareness has been bolstered by public educational campaigns by the National Sleep Foundation, the National Sleep Disorders Center at the National Institutes of Health (NIH), and other likeminded organizations; by publication of the Institute of Medicine's report Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem (2006) 1 ; and by findings from epidemiologic studies linking reduced average daily sleep duration with potential health consequences including obesity, diabetes, 2 and reduced longevity.…”

Naturalistic Field Studies of Sleep and Performance

“…Hursh and Van Dongen (2010) reviewed the role of mathematical models predicting performance from sleep wake history and time of day in fatigue risk management. Olofsen et al (2010) reviewed the development of individualized performance predictions to replace the one size fits all models currently available. Rangan et al (2010) review the integration of fatigue modeling in crew and rostering operations.…”