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Cited by 217Sleep and Work-Related FatigueCircadian rhythm and melatoninHuman-Automation Interaction and Safety

The DOI matches its Crossref record; 101 of the 103 references it cites were found in a registry or an index.

Modelling fatigue and the use of fatigue models in work settings

Open access
Dawson, Drew, Ian Noy, Y., Härmä, Mikko, Åkerstedt, Torbjorn, Belenky, Gregory·2011·Accident Analysis & Prevention
DOI 10.1016/j.aap.2009.12.030
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Abstract

In recent years, theoretical models of the sleep and circadian system developed in laboratory settings have been adapted to predict fatigue and, by inference, performance. This is typically done using the timing of prior sleep and waking or working hours as the primary input and the time course of the predicted variables as the primary output. The aim of these models is to provide employers, unions and regulators with quantitative information on the likely average level of fatigue, or risk, associated with a given pattern of work and sleep with the goal of better managing the risk of fatigue-related errors and accidents/incidents. The first part of this review summarises the variables known to influence workplace fatigue and draws attention to the considerable variability attributable to individual and task variables not included in current models. The second part reviews the current fatigue models described in the scientific and technical literature and classifies them according to whether they predict fatigue directly by using the timing of prior sleep and wake (one-step models) or indirectly by using work schedules to infer an average sleep-wake pattern that is then used to predict fatigue (two-step models). The third part of the review looks at the current use of fatigue models in field settings by organizations and regulators. Given their limitations it is suggested that the current generation of models may be appropriate for use as one element in a fatigue risk management system. The final section of the review looks at the future of these models and recommends a standardised approach for their use as an element of the 'defenses-in-depth' approach to fatigue risk management.

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Crossref · 10.1016/j.aap.2009.12.030

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Citations

Cites

Research works printed but not linked: 2

  1. Kandelaars, K.J., 2006. Predicting the timing and duration of sleep in an operational setting using social factors. Ph.D. Thesis. University of South Australia. · DOI
  2. Thomas, 1998, PET imaging studies of sleep deprivation and sleep: implications for behavior and sleep function, J. Sleep Res., 7

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Metadata

Authors
Dawson, D., Ian Noy, Y., Härmä, M., Åkerstedt, T., & Belenky, G.
Affiliations
  • University of South Australia (AU)
  • Finnish Institute of Occupational Health (FI)
  • Washington State University (US)
ORCID
Venue
Accident Analysis & Prevention
Publisher
Elsevier BV
Published
2011-03
Volume
43
Issue
2
Pages
549-564
ISSN
0001-4575 (ISSN-L)
DOI
10.1016/j.aap.2009.12.030
OpenAlex
W2035641776
Cited by
217
References
103
Citations by year
2026: 10 · 2025: 9 · 2024: 16 · 2023: 11 · 2022: 14 · 2021: 25 · 2020: 21 · 2019: 16 · 2018: 15 · 2017: 14 · 2016: 9 · 2015: 11 · 2014: 10 · 2013: 11 · 2012: 5
FWCI
1.44
Type
journal article
Language
en
Open access
Licence
Locations
  • Accident Analysis & Prevention (publishedVersion)
  • PubMed (publishedVersion)
  • Acquire (CQUniversity) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and Work-Related Fatigue
  • Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
  • Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
Keywords
occupational fatigue, fatigue models, circadian rhythm, sleep timing, work schedules, fatigue risk management, fatigue-related accidents
MeSH terms
Accidents, Occupational, Fatigue, Humans, Models, Biological, Work Schedule Tolerance

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