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Generalizability of a biomathematical model of fatigue’s sleep predictions

journal contribution
posted on 21.10.2020, 00:00 by SM Riedy, D Fekedulegn, M Andrew, B Vila, Drew Dawson, J Violanti
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.

Funding

Other

History

Volume

37

Issue

4

Start Page

564

End Page

572

Number of Pages

9

eISSN

1525-6073

ISSN

0742-0528

Publisher

Taylor & Francis

Peer Reviewed

Yes

Open Access

No

Acceptance Date

19/03/2020

External Author Affiliations

State University of New York, National Institute for Occupational Safety and Health Centers for Disease Control and Prevention, Washington State University, USA

Author Research Institute

Appleton Institute

Era Eligible

Yes

Journal

Chronobiology International

Exports

CQUniversity

Exports