A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data
Abstract 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 sedentar...
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Nature Portfolio
2021
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oai:doaj.org-article:1c88b5553556428999c9ce1d9e569fc12021-12-02T13:44:15ZA multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data10.1038/s41598-021-87029-w2045-2322https://doaj.org/article/1c88b5553556428999c9ce1d9e569fc12021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-87029-whttps://doaj.org/toc/2045-2322Abstract 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.Tiantian FengBrandon M. BoothBrooke Baldwin-RodríguezFelipe OsornoShrikanth NarayananNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021) |
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EN |
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Medicine R Science Q |
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Medicine R Science Q Tiantian Feng Brandon M. Booth Brooke Baldwin-Rodríguez Felipe Osorno Shrikanth Narayanan A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data |
| description |
Abstract 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 |
article |
| author |
Tiantian Feng Brandon M. Booth Brooke Baldwin-Rodríguez Felipe Osorno Shrikanth Narayanan |
| author_facet |
Tiantian Feng Brandon M. Booth Brooke Baldwin-Rodríguez Felipe Osorno Shrikanth Narayanan |
| author_sort |
Tiantian Feng |
| title |
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_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_sort |
multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/1c88b5553556428999c9ce1d9e569fc1 |
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