Publication Cover
Chronobiology International
The Journal of Biological and Medical Rhythm Research
Volume 37, 2020 - Issue 4
335
Views
9
CrossRef citations to date
0
Altmetric
Original Articles

Generalizability of a biomathematical model of fatigue’s sleep predictions

, , , , ORCID Icon &
Pages 564-572 | Received 27 Nov 2019, Accepted 19 Mar 2020, Published online: 02 Apr 2020

Refere nces

  • Åkerstedt T, Anund A, Axelsson J, Kecklund G. 2014. Subjective sleepiness is a sensitive indicator of insufficient sleep and impaired waking function. J Sleep Res. 23(3):240–252.
  • Åkerstedt T, Connor J, Gray A, Kecklund G. 2008. Predicting road crashes from a mathematical model of alertness regulation–The sleep/wake predictor. Accid Anal Prev. 40(4):1480–1485.
  • Åkerstedt T, Folkard S, Portin C. 2004. Predictions from the three-process model of alertness. Aviat Space Environ Med. 75(3, Suppl):A75–A83.
  • Civil Aviation Safety Authority. 2014. Biomathematical Fatigue Models Guidance Document. Albert Park, Australia: Dédale Asia Pacific. Retrieved 28 Sep 2019 from https://www.icao.int/safety/fatiguemanagement/ArticlesPublications/biomathematical_fatigue_models.pdf.
  • Darwent D, Dawson D, Roach GD. 2010. Prediction of probabilistic sleep distributions following travel across multiple time zones. Sleep. 33(2):185–195.
  • Darwent D, Dawson D, Roach GD. 2012. A model of shift worker sleep/wake behaviour. Accid Anal Prev. 45S:6–10.
  • Dawson D, Darwent D, Roach GD. 2017. How should a bio-mathematical model be used within a fatigue risk management system to determine whether or not a working time arrangement is safe? Accid Anal Prev. 99(Pt B):469–473.
  • Dawson D, McCulloch K. 2005. Managing fatigue: it’s about sleep. Sleep Med Rev. 9(5):365–380.
  • Dawson D, Noy YI, Härma M, Åkerstedt T, Belenky G. 2011. Modelling fatigue and the use of fatigue models in work settings. Accid Anal Prev. 43:549–564.
  • Dean DA, Fletcher A, SR H, EB K. 2007. Developing mathematical models of neurobehavioral performance for the “real world”. J Biol Rhythms. 22(3):246–258.
  • Dorrian J, Darwent D, Dawson D, Roach GD. 2012. Predicting pilot's sleep during layovers using their own behaviour or data from colleagues: Implications for biomathematical models. Accident Analysis & Prevention. 45S 45:17–21.
  • Gabarino S, de Carli F, Nobili L, Mascialino B, Squarcia S, Penco MA, Beelke M, Ferrillo F. 2002. Sleepiness and sleep disorders in shift workers: A study on a group of Italian police officers. Sleep. 25(6):642–647.
  • Gabarino S, Guglielmi O, Puntoni M, Bragazzi NL, Magnavita N. 2019. Sleep quality among police officers: implications and insights from a systematic review and meta-analysis of the literature. Int J Environ Res Public Health. 16(5):885.
  • Gander PH. 2015. Evolving regulatory approaches for managing fatigue risk in transport operations. Rev Hum Ergon. 10(1):253–271.
  • Gander PH, Wu LJ, van den Berg M, Lamp A, Hoeg L, Belenky G. 2016. Fatigue risk management systems. In: Kryger MH, Roth T, Dement WC, editors. Principles and practice of sleep medicine. 6th ed. Philadelphia (PA): Elsevier; p. 697–707.
  • Gertler J, Hursh S, Fanzone RT 2012. Validation of FAST model sleep estimates with actigraph measured sleep in locomotive engineers; Baltimore, MD: Federal Railroad Administration. U.S. Department of Transportation. Report No. DOT/FRA/ORD-12/15.
  • Hobbs AN, Gregory KB, Parke BK, Pradhan SK, Caddick Z, Bathurst NG, Flynn-Evans EE San Francisco bar pilot fatigue study. Moffett Field (CA): NASA Ames Research Center. Report No. NASA/TM-2018-219934, ARC-E-DAA-TN58326.
  • Hursh SR, Balkin TJ, Van Dongen HPA. 2016. Sleep and performance prediction modeling. In: Kryger MH, Roth T, Dement WC, editors. Principles and practice of sleep medicine. 6th ed. Philadelphia (PA): Elsevier; p. 689–696.
  • Hursh SR, Raslear TG, Kaye AS, Fanzone JF 2008. Validation and calibration of a fatigue assessment tool for railroad work schedules, final report. Report No. DOT/FRA/ORD-08/04 Washington (D.C.): U.S. Department of Transportation.
  • Hursh SR, Waggoner LB 2017. Refining sleep predictions using actigraphy in operational environments: studies with pilots. 10th International Conference on Managing Fatigue Conference website Accessed September 28, 2019. San Diego, CA, USA. https://fatigueconference2017.com/materials/wednesday-am/modeling/Abstract_Hursh.pdf.
  • Ingre M, Van Leeuwen W, Klemets T, Ullvetter C, Hough S, Kecklund G, Karlsson ÅT. 2014. Validating and extending the three process model of alertness in airline operations. PLoS One. 9(10):e108679.
  • James FO, Mapp KJ, Greenwood P, Waggoner LB 2017. Applied fatigue risk management for transit: Biomathematical modeling in the analysis of recorded events. 10th International Conference on Managing Fatigue Conference website. Accessed February 9, 2020.
  • James FO, Waggoner LB, Weiss PM, PattersonDP, Higgins JS, Lang ES, Van Dongen HPA. 2018. Does implementation of biomathematical models mitigate fatigue and fatigue-related risks in emergency medical services operations? A systematic review. 22(sup1):69–80. doi:10.1080/10903127.2017.1384875
  • Jones CB, Dorrian J, Rajaratnam SMW, Dawson. 2005. Working Hours Regulations and Fatigue in Transportation: a Comparative Analysis. Safety Science. 43(4):225–252.
  • Kandelaars KJ, Dorrian J, Fletcher A, Roach GD, Dawson D 2005. A review of bio-mathematical fatigue models: where to from here? Paper presented at the 6th International Conference on Fatigue Management in Transportation, Seattle, WA.
  • Lamp A, Chen Jane M.C, McCullough DBelenky G. 2019. Equal to or better than: the application of statistical non-inferiority to fatigue risk management. Accident Analysis & Prevention. 126:184–190.
  • Mallis MM, Mejdal S, Nguyen TT, Dinges DF. 2004. Summary of the key features of seven biomathematical models of human fatigue and performance. Aviat Space Environ Med. 75(3, Suppl):A4–A14.
  • McDonald N. 1981. Safety and regulations restricting the hours of driving of goods vehicle drivers. Ergonomics. 24(6):475–485.
  • Pruchnicki SA, Wu LJ, Belenky G. 2011. An exploration of the utility of mathematical modeling predicting fatigue from sleep/wake history and circadian phase applied in accident analysis and prevention: the crash of comair flight 5191. Accid Anal Prev. 43(3):1056–1061. Doi: 10.1016/j.aap.2010.12.010
  • Quantum Version FAID 1.0. User Guide. 2017. InterDynamics.
  • Reaves BA. 2012. Hiring and retention of state and local law enforcement officers, 2008– statistical tables. October 2012. Washington (D.C.): Bureau of Justice Statistics. Report No.: NCJ238251 Accessed 2019 Nov 1 . https://www.bjs.gov/content/pub/pdf/hrslleo08st.pdf
  • Riedy SM, Dawson D, Vila B. 2019. U.S. police rosters: fatigue and public complaints. Sleep. 42(3):1–10. Doi:10.1093/sleep/zsy231
  • Sagherian K, Zhu S, Storr C, Hinds PS, Derickson D, Geiger-Brown J. 2018. Bio-mathematical fatigue models predict sickness absence in hospital nurses: an 18 months retrospective cohort study. Applied Ergonomics. 73:42–47.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.