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A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data
Night shift workers are often associated with circadian misalignment and physical discomfort, which may lead to burnout and decreased work performance. Moreover, the irregular work hours can lead to significant negative health outcomes such as poor eating habits, smoking, and being sedentary more of...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062546/ https://www.ncbi.nlm.nih.gov/pubmed/33888731 http://dx.doi.org/10.1038/s41598-021-87029-w |
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author | Feng, Tiantian Booth, Brandon M. Baldwin-Rodríguez, Brooke Osorno, Felipe Narayanan, Shrikanth |
author_facet | Feng, Tiantian Booth, Brandon M. Baldwin-Rodríguez, Brooke Osorno, Felipe Narayanan, Shrikanth |
author_sort | Feng, Tiantian |
collection | PubMed |
description | Night shift workers are often associated with circadian misalignment and physical discomfort, which may lead to burnout and decreased work performance. Moreover, the irregular work hours can lead to significant negative health outcomes such as poor eating habits, smoking, and being sedentary more often. This paper uses commercial wearable sensors to explore correlates and differences in the level of physical activity, sleep, and circadian misalignment indicators among day shift nurses and night shift nurses. We identify which self-reported assessments of affect, life satisfaction, and sleep quality, are associated with physiological and behavioral signals captured by wearable sensors. The results using data collected from 113 nurses in a large hospital setting, over a period of 10 weeks, indicate that night shift nurses are more sedentary, and report lower levels of life satisfaction than day-shift nurses. Moreover, night shift nurses report poorer sleep quality, which may be correlated with challenges in their attempts to fall asleep on off-days. |
format | Online Article Text |
id | pubmed-8062546 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80625462021-04-23 A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data Feng, Tiantian Booth, Brandon M. Baldwin-Rodríguez, Brooke Osorno, Felipe Narayanan, Shrikanth Sci Rep Article Night shift workers are often associated with circadian misalignment and physical discomfort, which may lead to burnout and decreased work performance. Moreover, the irregular work hours can lead to significant negative health outcomes such as poor eating habits, smoking, and being sedentary more often. This paper uses commercial wearable sensors to explore correlates and differences in the level of physical activity, sleep, and circadian misalignment indicators among day shift nurses and night shift nurses. We identify which self-reported assessments of affect, life satisfaction, and sleep quality, are associated with physiological and behavioral signals captured by wearable sensors. The results using data collected from 113 nurses in a large hospital setting, over a period of 10 weeks, indicate that night shift nurses are more sedentary, and report lower levels of life satisfaction than day-shift nurses. Moreover, night shift nurses report poorer sleep quality, which may be correlated with challenges in their attempts to fall asleep on off-days. Nature Publishing Group UK 2021-04-22 /pmc/articles/PMC8062546/ /pubmed/33888731 http://dx.doi.org/10.1038/s41598-021-87029-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Feng, Tiantian Booth, Brandon M. Baldwin-Rodríguez, Brooke Osorno, Felipe Narayanan, Shrikanth A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data |
title | A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data |
title_full | A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data |
title_fullStr | A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data |
title_full_unstemmed | A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data |
title_short | A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data |
title_sort | multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062546/ https://www.ncbi.nlm.nih.gov/pubmed/33888731 http://dx.doi.org/10.1038/s41598-021-87029-w |
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