ArticleChronobiology international
Prediction of individual differences in circadian adaptation to night work among older adults: application of a mathematical model using individual sleep-wake and light exposure data.
Article in Chronobiology international. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Afternoon to early evening bright light exposure reduces later melatonin production in adolescents.Npj biological timing and sleep · 2025Article
- Current Considerations in the Diagnosis and Treatment of Circadian Rhythm Sleep-Wake Disorders in Children.Seminars in pediatric neurology · 2023Article
- Circadian Rhythm Sleep-Wake Disorders in Older Adults.Sleep medicine clinics · 2022Review
- Predicting circadian phase across populations: a comparison of mathematical models and wearable devices.Sleep · 2021Article
- A classification approach to estimating human circadian phase under circadian alignment from actigraphy and photometry data.Journal of pineal research · 2021Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Circadian misalignment remains a distinct challenge for night shift workers. Variability in individual sleep-wake/light-dark patterns might contribute to individual differences in circadian alignment in night shift workers. In this simulation study, we compared the predicted phase shift from a mathematical model of the effect of light on the human circadian pacemaker to the observed melatonin phase shift among individuals who completed one of four interventions during simulated night shift work. Two inputs to the model were used to simulate circadian phase: sleep-wake/light-dark patterns measured from a wrist monitor (Simulation 1) and sleep-wake/light-dark patterns measured from a wrist monitor enhanced by known light levels measured at the level of the eye during simulated night shifts (Simulation 2). The estimated phase shift from the model was within 2 hours of the observed phase shift in ~80% of night shift workers for both simulations; none of the model-predicted phase shifts was more than ~3 hours from the observed phase shift. Overall, the root-mean-square error between observed and predicted phase shifts was better for Simulation 1. The light input from the wrist monitor informed by actual light level measured at the eye performed better in the sub-group exposed to bright light during their night shifts. The findings from this simulation study suggest that using a mathematical model combined with sleep-wake and light exposure data from a wrist monitor can facilitate the design of shift work schedules to enhance circadian alignment, which is expected to improve sleep, alertness, and performance.
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Registered trials
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