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Aviat Space Environ Med ; 80(5): 454-61, 2009 May.
Article in English | MEDLINE | ID: mdl-19456006

ABSTRACT

BACKGROUND: Remotely piloted aircraft (RPA) with long endurance allow near-continuous operations, necessitating the implementation of shift work for crewmembers to provide the necessary manning of ground control stations. Shift work has a well-known association with fatigue, degraded work performance, and an increased risk for errors and accidents. This study presents the results of a follow-up survey of a particular population of shift-working RPA crewmembers 1 yr after modification of their shift work schedule. METHODS: A cross-sectional survey of 66 RPA crewmembers was conducted using a collection of validated fatigue scales. This data was compared to survey data collected a year prior from the same population and from a reference group of non-shift-working aircrew. Shift system features and individual and situational differences associated with fatigue were explored. Additionally, several alternative types of shift schedules were assessed through modeling and simulation. RESULTS: The study found no significant reduction in reported fatigue despite prior modifications to the shift work schedule to increase opportunities for recovery. Months shift working, sleep quality, and disturbances in family and social activities were associated with overall fatigue scores. Approximately half of those surveyed met criteria for occupationally significant fatigue. Months shift working, use of on-duty napping, and fatigue scores were predictive of those with occupationally significant fatigue. Modeling of feasible variants of the current shift work schedule failed to reveal a significantly improved alternative schedule. CONCLUSIONS: Collectively, the results demonstrate a persistent problem with chronic fatigue in this study population, likely reflective of continued inadequate opportunities for recovery and restorative sleep.


Subject(s)
Aerospace Medicine , Fatigue , Work Schedule Tolerance , Adult , Cross-Sectional Studies , Female , Humans , Male , Robotics
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