Predicting pilot's sleep during layovers using their own behaviour or data from colleagues: implications for biomathematical models
Abstract
Biomathematical models are used in industry to estimate how much sleep people are likely to get on different work patterns, and how efficient and safe people are likely to be at work. Since there is evidence to suggest that individuals respond differently to sleep loss, there has been a recent focus on trying to account for individual differences. One possible approach could use past behaviour to predict future responses to similar working conditions. This study investigated the predictive value of sleep timing and duration data for a particular individual on a break between shifts relative to data from their colleagues. Sleep diaries and wrist actigraphy were collected from 306 international long-haul pilots for at least 2-weeks. Fifty layovers, equivalent in origin and destination, length and timing, were completed twice by individual pilots. Matched layovers done by other pilots (n=2311) were also identified. Layover periods were analysed for minute-by-minute correspondence of sleep or wake (yes/no), and total sleep time (TST). Using an individual's own data improved concordance by approximately 5% relative to using a large sample of different pilots, and by 10% relative to using a random sample of 50 different pilots. Using an individual's own TST to predict their TST on an equivalent layover yielded an r value of 0.83, compared to r=0.78 when data from a colleague was used, and r=0.73 using different pilots in a random sample of equivalent size. The mean difference in TST using pilots' own data was <20 min, compared to <40 min using data from colleagues. However, the confidence limits on these differences were large (up to 8h). Results suggest that for international pilots on specific layover patterns, knowing the past behaviour of an individual may only represent a modest improvement over knowing the length and timing of a colleague's sleep, when it comes to predicting their sleep behaviour.
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Sleep disorders screening in addition to circadian approaches and scheduled napping has shown effectiveness in improving safety.
“To address these concerns, sleep disorders screening in addition to circadian approaches and scheduled napping have shown effectiveness in improving safety.189–197”
From Sleep, Health, and Society (2017) · cites this paper as [190]
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- Authors
- Dorrian, J., Darwent, D., Dawson, D., & Roach, G. D.
- Affiliations
- University of South Australia (AU)
- Corresponding author
- Dorrian, Jillian
- Venue
- Accident Analysis & Prevention
- Publisher
- Elsevier BV
- Published
- 2012-03
- Volume
- 45
- Pages
- 17-21
- ISSN
- 0001-4575 (ISSN-L)
- OpenAlex
- W2095192731
- Cited by
- 18
- References
- 19
- Citations by year
- 2024: 1 · 2022: 4 · 2021: 3 · 2020: 4 · 2018: 2 · 2016: 2 · 2015: 1
- FWCI
- 0.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Accident Analysis & Prevention (publishedVersion)
- PubMed (publishedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Funders
- Australian Research Council
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and Work-Related Fatigue
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
- Keywords
- layover, total sleep time, sleep prediction, individual differences, biomathematical model, sleep diary, actigraphy, shift work, sleep deprivation
- MeSH terms
- Aerospace Medicine, Aviation, Fatigue, Humans, Individuality, Models, Theoretical, Neurobiology, Predictive Value of Tests, Sleep, Work Schedule Tolerance
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