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A global quantification of “normal” sleep schedules using smartphone data
The influence of the circadian clock on sleep scheduling has been studied extensively in the laboratory; however, the effects of society on sleep remain largely unquantified. We show how a smartphone app that we have developed, ENTRAIN, accurately collects data on sleep habits around the world. Thro...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4928979/ https://www.ncbi.nlm.nih.gov/pubmed/27386531 http://dx.doi.org/10.1126/sciadv.1501705 |
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author | Walch, Olivia J. Cochran, Amy Forger, Daniel B. |
author_facet | Walch, Olivia J. Cochran, Amy Forger, Daniel B. |
author_sort | Walch, Olivia J. |
collection | PubMed |
description | The influence of the circadian clock on sleep scheduling has been studied extensively in the laboratory; however, the effects of society on sleep remain largely unquantified. We show how a smartphone app that we have developed, ENTRAIN, accurately collects data on sleep habits around the world. Through mathematical modeling and statistics, we find that social pressures weaken and/or conceal biological drives in the evening, leading individuals to delay their bedtime and shorten their sleep. A country’s average bedtime, but not average wake time, predicts sleep duration. We further show that mathematical models based on controlled laboratory experiments predict qualitative trends in sunrise, sunset, and light level; however, these effects are attenuated in the real world around bedtime. Additionally, we find that women schedule more sleep than men and that users reporting that they are typically exposed to outdoor light go to sleep earlier and sleep more than those reporting indoor light. Finally, we find that age is the primary determinant of sleep timing, and that age plays an important role in the variability of population-level sleep habits. This work better defines and personalizes “normal” sleep, produces hypotheses for future testing in the laboratory, and suggests important ways to counteract the global sleep crisis. |
format | Online Article Text |
id | pubmed-4928979 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-49289792016-07-06 A global quantification of “normal” sleep schedules using smartphone data Walch, Olivia J. Cochran, Amy Forger, Daniel B. Sci Adv Research Articles The influence of the circadian clock on sleep scheduling has been studied extensively in the laboratory; however, the effects of society on sleep remain largely unquantified. We show how a smartphone app that we have developed, ENTRAIN, accurately collects data on sleep habits around the world. Through mathematical modeling and statistics, we find that social pressures weaken and/or conceal biological drives in the evening, leading individuals to delay their bedtime and shorten their sleep. A country’s average bedtime, but not average wake time, predicts sleep duration. We further show that mathematical models based on controlled laboratory experiments predict qualitative trends in sunrise, sunset, and light level; however, these effects are attenuated in the real world around bedtime. Additionally, we find that women schedule more sleep than men and that users reporting that they are typically exposed to outdoor light go to sleep earlier and sleep more than those reporting indoor light. Finally, we find that age is the primary determinant of sleep timing, and that age plays an important role in the variability of population-level sleep habits. This work better defines and personalizes “normal” sleep, produces hypotheses for future testing in the laboratory, and suggests important ways to counteract the global sleep crisis. American Association for the Advancement of Science 2016-05-06 /pmc/articles/PMC4928979/ /pubmed/27386531 http://dx.doi.org/10.1126/sciadv.1501705 Text en Copyright © 2016, The Authors http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Walch, Olivia J. Cochran, Amy Forger, Daniel B. A global quantification of “normal” sleep schedules using smartphone data |
title | A global quantification of “normal” sleep schedules using smartphone data |
title_full | A global quantification of “normal” sleep schedules using smartphone data |
title_fullStr | A global quantification of “normal” sleep schedules using smartphone data |
title_full_unstemmed | A global quantification of “normal” sleep schedules using smartphone data |
title_short | A global quantification of “normal” sleep schedules using smartphone data |
title_sort | global quantification of “normal” sleep schedules using smartphone data |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4928979/ https://www.ncbi.nlm.nih.gov/pubmed/27386531 http://dx.doi.org/10.1126/sciadv.1501705 |
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