Managing fatigue: It really is about sleep. (September 2015) - Darwent, David; Dawson, Drew; Paterson, Jessica L.; Roach, Gregory D.; Ferguson, Sally A.
Highlights: Insufficient sleep and circadian rhythm disturbances cause mental fatigue at work. Fatigue scores can be predicted and then classified into interval-level categories. On average, higher fatigue level intervals are associated with less observed sleep. Observed sleep amounts vary more within fatigue-level intervals than across them. Fatigue scores should be interpreted in the context of observed sleep distributions. Abstract: Biomathematical models of fatigue can assist organisations to estimate the fatigue consequences of a roster before operations commence. These estimates do not account for the diversity of sleep behaviours exhibited by employees. The purpose of this study was to develop sleep transfer functions describing the likely distributions of sleep around fatigue level estimates produced by a commercial biomathematical model of fatigue. Participants included 347 (18 females, 329 males) train drivers working commercial railway operations in Australia. They provided detailed information about their sleep behaviours using sleep diaries and wrist activity monitors. On average, drivers slept for 7.7 (±1.7) h in the 24 h before work and 15.1 (±2.5) h in the 48 h before work. The amount of sleep obtained by drivers before shifts differed only marginally across morning, afternoon and night shifts. Shifts were also classified into one of seven ranked categories using estimated fatigue level scores. Higher fatigue score categories were associated with significant reductions in the amount of sleep obtained before shifts, but there was substantial within-category variation. The study findings demonstrate that biomathematical models of fatigue have utility for designing round-the-clock rosters that provide sufficient sleep opportunities for the average employee. Robust variability in the amount of sleep obtained by drivers indicate that models are relatively poor tools for ensuring that all employees obtain sufficient sleep. These findings demonstrate the importance of developing approaches for managing the sleep behaviour of individual employees.