Fatigue and short-term unplanned absences among police officers

Purpose – The purpose of this paper is to assess whether shift work, sleep loss and fatigue are related to shortterm unplanned absences in policing. Design/methodology/approach – N 5 367 police officers from the Buffalo Police Department were studied. Day-by-day work and sick leave data were obtained from the payroll. Absenteeism was defined as taking a single sick day on a regularly scheduled workday. Biomathematical models of fatigue (BMMF) predicted officers’ sleep–wake behaviors and on-duty fatigue and sleepiness. Prior sleep, fatigue and sleepiness were tested as predictors of absenteeism during the next shift. Findings – A total of 513,666 shifts and 4,868 cases of absenteeism were studied. The odds of absenteeism increased as on-duty fatigue and sleepiness increased and prior sleep decreased. This was particularly evident for swing shift officers and night shift officers who were predicted by BMMF to obtain less sleep and have greater fatigue and sleepiness than day shift officers. The odds of absenteeism were higher for female officers than male officers; this finding was not due to a differential response to sleep loss, fatigue or sleepiness

Generalizability of a biomathematical model of fatigue’s sleep predictions

Introduction: Biomathematical models of fatigue (BMMF) predict fatigue during a work-rest schedule on the basis of sleep-wake histories. In the absence of actual sleep-wake histories, sleep-wake histories are predicted directly from work-rest schedules. The predicted sleep-wake histories are then used to predict fatigue. It remains to be determined whether workers organize their sleep similarly across operations and thus whether sleep predictions generalize. Methods: Officers (n = 173) enrolled in the Buffalo Cardio-Metabolic Occupational Police Stress study were studied. Officers’ sleep-wake behaviors were measured using wrist-actigraphy and predicted using a BMMF (FAID Quantum) parameterized in aviation and rail. Sleepiness (i.e. Karolinska Sleepiness Scale (KSS) ratings) was predicted using actual and predicted sleep-wake data. Data were analyzed using sensitivity analyses. Results: During officers’ 16.0 ± 1.9 days of study participation, they worked 8.6 ± 3.1 shifts and primarily worked day shifts and afternoon shifts. Across shifts, 7.0 h ± 1.9 h of actual sleep were obtained in the prior 24 h and associated peak KSS ratings were 5.7 ± 1.3. Across shifts, 7.2 h ± 1.1 h of sleep were predicted in the prior 24 h and associated peak KSS ratings were 5.5 ± 1.2. The minute-by-minute predicted and actual sleep-wake data demonstrated high sensitivity (80.4%). However, sleep was observed at all hours-of-the-day, but sleep was rarely predicted during the daytime hours. Discussion: The sleep-wake behaviors predicted by a BMMF parameterized in aviation and rail demonstrated high sensitivity with police officers’ actual sleep-wake behaviors. Additional night shift data are needed to conclude whether BMMF sleep predictions generalize across operations. © 2020, © 2020 Taylor & Francis Group, LLC