Accession Number : ADA614085

Title :   Predicting Performance during Chronic Sleep Loss: Identification of Factors Sensitive to Individual Fatigue Resistance

Descriptive Note : Technical rept. Jan 2011-Mar 2015


Personal Author(s) : Hartzler, Beth M ; Chandler, Joseph F ; Levin, Chelsea B ; Turnmire, Ashley E

Full Text :

Report Date : 18 Mar 2015

Pagination or Media Count : 54

Abstract : Fatigue due to sleep loss has long been recognized as an insidious threat to military performance. In an effort to mitigate the detrimental effects of fatigue on Warfighter performance, generalized biomathematical models have been developed to estimate fatigue-related performance impairments for a given schedule. However, these models fail to account for individual differences in fatigue susceptibility. To address this shortcoming, the study described herein utilized a chronic sleep restriction paradigm (4 h time-in-bed for 4 nights) with the goal of identifying neurobehavioral measures sensitive to the effects of sleep restriction, and which thus might be beneficial in developing a predictive algorithm sensitive to individual differences. Group-level analyses revealed a number of measures which were sensitive to increasing fatigue across the duration of the study, such as the Psychomotor Vigilance Task (PVT), Profile of Mood States (POMS), and certain oculometric patterns. Individual-level analyses further revealed that several of these factors were also sensitive to differences in fatigue susceptibility. Moreover, the predictive value of the Fatigue Avoidance Scheduling Tool (FAST) was increased ten-fold by combining the performance estimates other assessments of the individual s present state. Successful improvement and subsequent use of these types of algorithms could help optimize both mission efficacy and safety by identifying personnel who are best able to maintain performance under fatigued operational conditions.


Subject Categories : Psychology
      Anatomy and Physiology
      Medicine and Medical Research
      Stress Physiology
      Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE