Mental Health and Behavior of College Students During the Early Phases of the COVID-19 Pandemic: Longitudinal Smartphone and Ecological Momentary Assessment Study
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Abstract
Background: The vast majority of people worldwide have been impacted by coronavirus disease (COVID-19). In addition to the millions of individuals who have been infected with the disease, billions of individuals have been asked or required by local and national governments to change their behavioral patterns. Previous research on epidemics or traumatic events suggests that this can lead to profound behavioral and mental health changes; however, researchers are rarely able to track these changes with frequent, near-real-time sampling or compare their findings to previous years of data for the same individuals. Objective: By combining mobile phone sensing and self-reported mental health data among college students who have been participating in a longitudinal study for the past 2 years, we sought to answer two overarching questions. First, have the behaviors and mental health of the participants changed in response to the COVID-19 pandemic compared to previous time periods? Second, are these behavior and mental health changes associated with the relative news coverage of COVID-19 in the US media? Methods: Behaviors such as the number of locations visited, distance traveled, duration of phone usage, number of phone unlocks, sleep duration, and sedentary time were measured using the StudentLife smartphone sensing app. Depression and anxiety were assessed using weekly self-reported ecological momentary assessments of the Patient Health Questionnaire-4. The participants were 217 undergraduate students, with 178 (82.0%) students providing data during the Winter 2020 term. Differences in behaviors and self-reported mental health collected during the Winter 2020 term compared to previous terms in the same cohort were modeled using mixed linear models. Results: During the first academic term impacted by COVID-19 (Winter 2020), individuals were more sedentary and reported increased anxiety and depression symptoms (P<.001) relative to previous academic terms and subsequent academic breaks. Interactions between the Winter 2020 term and the week of the academic term (linear and quadratic) were significant. In a mixed linear model, phone usage, number of locations visited, and week of the term were strongly associated with increased amount of COVID-19–related news. When mental health metrics (eg, depression and anxiety) were added to the previous measures (week of term, number of locations visited, and phone usage), both anxiety (P<.001) and depression (P=.03) were significantly associated with COVID-19–related news. Conclusions: Compared with prior academic terms, individuals in the Winter 2020 term were more sedentary, anxious, and depressed. A wide variety of behaviors, including increased phone usage, decreased physical activity, and fewer locations visited, were associated with fluctuations in COVID-19 news reporting. While this large-scale shift in mental health and behavior is unsurprising, its characterization is particularly important to help guide the development of methods to reduce the impact of future catastrophic events on the mental health of the population.
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During the COVID-19 pandemic, the mental health of college students was negatively impacted by anxiety, depressive symptoms, and acute stress.
“During the pandemic, the mental health of college students was negatively impacted by anxiety, depressive symptoms, and acute stress, as shown by numerous studies (Bai et al. 2021; Huckins et al. 2020; Ma et al. 2020; Wu et al. 2021).”
From Changes in Mental Health and EEG Biomarkers of Undergraduates Under Different Patterns of Mindfulness (2024) · cites this paper as Huckins et al. 2020
The Results section, “Behavioral and Mental Health Changes Associated With the COVID-19 Pandemic” (page unavailable), reports that students’ depression and anxiety symptoms spiked and remained elevated relative to other terms. The paper discusses pandemic-related stress but does not report acute stress as a measured outcome in the passages reviewed, so that part of the claim is unsupported. (LLM, conf=0.88)
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- Authors
- Huckins, J. F., daSilva, A. W., Wang, W., Hedlund, E., Rogers, C., Nepal, S. K., Wu, J., Obuchi, M., Murphy, E. I., Meyer, M. L., Wagner, D. D., Holtzheimer, P. E., & Campbell, A. T.
- Affiliations
- Dartmouth College (US)
- The Ohio State University (US)
- Dartmouth–Hitchcock Medical Center (US)
- Corresponding author
- Huckins, Jeremy F
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2020-06-17
- Volume
- 22
- Issue
- 6
- Pages
- e20185
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC7301687
- OpenAlex
- W3033293557
- Cited by
- 759
- References
- 30
- Citations by year
- 2026: 25 · 2025: 44 · 2024: 82 · 2023: 126 · 2022: 217 · 2021: 206 · 2020: 59
- FWCI
- 60.73
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
- PsyArXiv (OSF Preprints) (submittedVersion)
- Funders
- National Institute of Mental Health (R01MH059282)
- Topics
- Social Sciences › Psychology › Clinical Psychology › COVID-19 and Mental Health
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Keywords
- COVID-19 pandemic, university students, mental health, depression, anxiety, sedentary behavior, smartphone sensing, ecological momentary assessment, COVID-19 news coverage, media exposure, location tracking, sleep duration
- MeSH terms
- Smartphone, Ecological Momentary Assessment, Betacoronavirus, COVID-19, SARS-CoV-2, Adolescent, Adult, Female, Humans, Longitudinal Studies, Male, Mental Health, Pneumonia, Viral, Students, Coronavirus Infections, Young Adult, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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