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Generalizability of a biomathematical model of fatigue's sleep predictions.
Riedy, Samantha M; Fekedulegn, Desta; Andrew, Michael; Vila, Bryan; Dawson, Drew; Violanti, John.
Afiliación
  • Riedy SM; Sleep and Performance Research Center, Washington State University, Spokane, WA, USA.
  • Fekedulegn D; Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, USA.
  • Andrew M; Bioanalytics Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health Centers for Disease Control and Prevention, Morgantown, WV, USA.
  • Vila B; Bioanalytics Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health Centers for Disease Control and Prevention, Morgantown, WV, USA.
  • Dawson D; Sleep and Performance Research Center, Washington State University, Spokane, WA, USA.
  • Violanti J; Department of Criminal Justice and Criminology, Washington State University, Spokane, WA, USA.
Chronobiol Int ; 37(4): 564-572, 2020 04.
Article en En | MEDLINE | ID: mdl-32241186
ABSTRACT

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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Tolerancia al Trabajo Programado / Trastornos del Sueño del Ritmo Circadiano Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Chronobiol Int Asunto de la revista: FISIOLOGIA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Tolerancia al Trabajo Programado / Trastornos del Sueño del Ritmo Circadiano Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Chronobiol Int Asunto de la revista: FISIOLOGIA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos