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Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study

With the outbreak of the COVID-19 pandemic in 2020, most colleges and universities move to restrict campus activities, reduce indoor gatherings and move instruction online. These changes required that students adapt and alter their daily routines accordingly. To investigate patterns associated with...

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Detalles Bibliográficos
Autores principales: Wu, Congyu, Fritz, Hagen, Miller, Melissa, Craddock, Cameron, Kinney, Kerry, Castelli, Darla, Schnyer, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8649714/
https://www.ncbi.nlm.nih.gov/pubmed/34888544
http://dx.doi.org/10.3389/fdgth.2021.765972
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author Wu, Congyu
Fritz, Hagen
Miller, Melissa
Craddock, Cameron
Kinney, Kerry
Castelli, Darla
Schnyer, David
author_facet Wu, Congyu
Fritz, Hagen
Miller, Melissa
Craddock, Cameron
Kinney, Kerry
Castelli, Darla
Schnyer, David
author_sort Wu, Congyu
collection PubMed
description With the outbreak of the COVID-19 pandemic in 2020, most colleges and universities move to restrict campus activities, reduce indoor gatherings and move instruction online. These changes required that students adapt and alter their daily routines accordingly. To investigate patterns associated with these behavioral changes, we collected smartphone sensing data using the Beiwe platform from two groups of undergraduate students at a major North American university, one from January to March of 2020 (74 participants), the other from May to August (52 participants), to observe the differences in students' daily life patterns before and after the start of the pandemic. In this paper, we focus on the mobility patterns evidenced by GPS signal tracking from the students' smartphones and report findings using several analytical methods including principal component analysis, circadian rhythm analysis, and predictive modeling of perceived sadness levels using mobility-based digital metrics. Our findings suggest that compared to the pre-COVID group, students in the mid-COVID group generally 1) registered a greater amount of midday movement than movement in the morning (8–10 a.m.) and in the evening (7–9 p.m.), as opposed to the other way around; 2) exhibited significantly less intradaily variability in their daily movement; 3) visited less places and stayed at home more everyday, and; 4) had a significant lower correlation between their mobility patterns and negative mood.
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spelling pubmed-86497142021-12-08 Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study Wu, Congyu Fritz, Hagen Miller, Melissa Craddock, Cameron Kinney, Kerry Castelli, Darla Schnyer, David Front Digit Health Digital Health With the outbreak of the COVID-19 pandemic in 2020, most colleges and universities move to restrict campus activities, reduce indoor gatherings and move instruction online. These changes required that students adapt and alter their daily routines accordingly. To investigate patterns associated with these behavioral changes, we collected smartphone sensing data using the Beiwe platform from two groups of undergraduate students at a major North American university, one from January to March of 2020 (74 participants), the other from May to August (52 participants), to observe the differences in students' daily life patterns before and after the start of the pandemic. In this paper, we focus on the mobility patterns evidenced by GPS signal tracking from the students' smartphones and report findings using several analytical methods including principal component analysis, circadian rhythm analysis, and predictive modeling of perceived sadness levels using mobility-based digital metrics. Our findings suggest that compared to the pre-COVID group, students in the mid-COVID group generally 1) registered a greater amount of midday movement than movement in the morning (8–10 a.m.) and in the evening (7–9 p.m.), as opposed to the other way around; 2) exhibited significantly less intradaily variability in their daily movement; 3) visited less places and stayed at home more everyday, and; 4) had a significant lower correlation between their mobility patterns and negative mood. Frontiers Media S.A. 2021-11-23 /pmc/articles/PMC8649714/ /pubmed/34888544 http://dx.doi.org/10.3389/fdgth.2021.765972 Text en Copyright © 2021 Wu, Fritz, Miller, Craddock, Kinney, Castelli and Schnyer. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Digital Health
Wu, Congyu
Fritz, Hagen
Miller, Melissa
Craddock, Cameron
Kinney, Kerry
Castelli, Darla
Schnyer, David
Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study
title Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study
title_full Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study
title_fullStr Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study
title_full_unstemmed Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study
title_short Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study
title_sort exploring post covid-19 outbreak intradaily mobility pattern change in college students: a gps-focused smartphone sensing study
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8649714/
https://www.ncbi.nlm.nih.gov/pubmed/34888544
http://dx.doi.org/10.3389/fdgth.2021.765972
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