| Autor: |
Mack, Dante L, DaSilva, Alex W, Rogers, Courtney, Hedlund, Elin, Murphy, Eilis I, Vojdanovski, Vlado, Plomp, Jane, Wang, Weichen, Nepal, Subigya K, Holtzheimer, Paul E, Wagner, Dylan D, Jacobson, Nicholas C, Meyer, Meghan L, Campbell, Andrew T, Huckins, Jeremy F |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Journal of Medical Internet Research, Vol 23, Iss 6, p e28892 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1438-8871 |
| DOI: |
10.2196/28892 |
| Popis: |
BackgroundSince late 2019, the lives of people across the globe have been disrupted by COVID-19. Millions of people have become infected with the disease, while billions of people have been continually asked or required by local and national governments to change their behavioral patterns. Previous research on the COVID-19 pandemic suggests that it is associated with large-scale behavioral and mental health changes; however, few studies have been able to track these changes with frequent, near real-time sampling or compare these changes to previous years of data for the same individuals. ObjectiveBy combining mobile phone sensing and self-reported mental health data in a cohort of college-aged students enrolled in a longitudinal study, we seek to understand the behavioral and mental health impacts associated with the COVID-19 pandemic, measured by interest across the United States in the search terms coronavirus and COVID fatigue. MethodsBehaviors such as the number of locations visited, distance traveled, duration of phone use, number of phone unlocks, sleep duration, and sedentary time were measured using the StudentLife mobile smartphone sensing app. Depression and anxiety were assessed using weekly self-reported ecological momentary assessments, including the Patient Health Questionnaire-4. The participants were 217 undergraduate students. Differences in behaviors and self-reported mental health collected during the Spring 2020 term, as compared to previous terms in the same cohort, were modeled using mixed linear models. ResultsLinear mixed models demonstrated differences in phone use, sleep, sedentary time and number of locations visited associated with the COVID-19 pandemic. In further models, these behaviors were strongly associated with increased interest in COVID fatigue. When mental health metrics (eg, depression and anxiety) were added to the previous measures (week of term, number of locations visited, phone use, sedentary time), both anxiety and depression (P |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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