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Updated: Mar 18, 2026

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
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A global quantification of "normal" sleep schedules using smartphone data.

Olivia J Walch1, Amy Cochran1, Daniel B Forger2

  • 1Department of Mathematics, University of Michigan, Ann Arbor, MI 48109, USA.

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|July 8, 2016
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Social pressures delay bedtime and shorten sleep, overriding biological drives. This study used a smartphone app to quantify global sleep habits, revealing age as a key factor in sleep timing.

Keywords:
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Area of Science:

  • Chronobiology
  • Sleep Science
  • Sociology

Background:

  • Extensive laboratory research exists on circadian clock influence on sleep scheduling.
  • Societal effects on sleep patterns remain largely unquantified in real-world settings.

Purpose of the Study:

  • To quantify the impact of societal factors on global sleep habits.
  • To investigate the interplay between biological drives and social pressures in sleep timing.
  • To define and personalize "normal" sleep patterns and inform strategies against the global sleep crisis.

Main Methods:

  • Development and deployment of the ENTRAIN smartphone application for global sleep data collection.
  • Application of mathematical modeling and statistical analysis to analyze collected sleep data.
  • Comparison of real-world data with predictions from controlled laboratory models.

Main Results:

  • Social pressures were found to delay bedtime and reduce sleep duration, often masking biological influences.
  • Average bedtime, not wake time, significantly predicted sleep duration across populations.
  • Laboratory models accurately predicted environmental light trends but showed attenuated effects in real-world bedtime scenarios.
  • Women generally schedule more sleep than men.
  • Exposure to outdoor light correlated with earlier bedtimes and longer sleep durations compared to indoor light exposure.
  • Age was identified as the primary determinant of sleep timing and a significant factor in population-level sleep habit variability.

Conclusions:

  • Societal factors significantly influence sleep scheduling, often counteracting biological rhythms.
  • Individual sleep patterns are influenced by a complex interaction of age, light exposure, and social pressures.
  • The findings provide a foundation for personalized sleep recommendations and interventions to address widespread sleep issues.