Modeling human neurobehavioral functions has the goal of identifying work-rest schedules that are safer and more productive. The models of Folkard et al. and of Jewett and Kronauer illustrate excellent progress toward this goal. Examination of these models reveals four additional areas that need to be addressed to facilitate continued development of accurate models of neurobehavioral functions. (1) The choice of neurobehavioral metrics may have a significant influence on model development. The lack of correlation among different neurobehavioral measures may make comparisons of models difficult. Many neurobehavioral measures are confounded by secondary and random error variance that can lead to model distortion. Although different models may ultimately be required for different neurobehavioral functions, measures that have been extensively validated to be sensitive to circadian variation and sleep loss should take priority in model development. (2) Because error variance in neurobehavioral outcomes can be substantial in uncontrolled environments, model validation should proceed from controlled laboratory protocols to real-world scenarios. Once validated, the ability of a model to predict field data can be tested. (3) While neurobehavioral models have been developed to predict behavior over time (i.e., within-subjects), to be useful in the real world, models will also ultimately have to provide estimates of between-subject variation in vulnerability to neurobehavioral dysfunction during night work or sleep loss (e.g., younger versus older workers). (4) Finally, to be theoretically accurate and practically useful, models of human neurobehavioral functions should be able to predict both cumulative effects (i.e., across days or weeks) and the influence of countermeasures (e.g., light, naps, caffeine).
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