Document Type
Article
Publication Date
2-3-2023
Abstract
The COVID-19 pandemic has caused enormous societal upheaval globally. In the US, beyond the devastating toll on life and health, it triggered an economic shock unseen since the great depression and laid bare preexisting societal inequities. The full impacts of these personal, social, economic, and public-health challenges will not be known for years. To minimize societal costs and ensure future preparedness, it is critical to record the psychological and social experiences of individuals during such periods of high societal volatility. Here, we introduce, describe, and assess the COVID-Dynamic dataset, a within-participant longitudinal study conducted from April 2020 through January 2021, that captures the COVID-19 pandemic experiences of >1000 US residents. Each of 16 timepoints combines standard psychological assessments with novel surveys of emotion, social/political/moral attitudes, COVID-19-related behaviors, tasks assessing implicit attitudes and social decision-making, and external data to contextualize participants’ responses. This dataset is a resource for researchers interested in COVID-19-specific questions and basic psychological phenomena, as well as clinicians and policy-makers looking to mitigate the effects of future calamities.
Recommended Citation
Rusch, T., Han, Y., Liang, D. et al. COVID-Dynamic: A large-scale longitudinal study of socioemotional and behavioral change across the pandemic. Sci Data 10, 71 (2023). https://doi.org/10.1038/s41597-022-01901-6
Copyright
The authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Included in
Epidemiology Commons, Health Policy Commons, Inequality and Stratification Commons, Medical Humanities Commons, Medicine and Health Commons, Other Psychiatry and Psychology Commons, Other Sociology Commons, Politics and Social Change Commons, Social Psychology and Interaction Commons, Social Statistics Commons
Comments
This article was originally published in Scientific Data, volume 10, in 2023. https://doi.org/10.1038/s41597-022-01901-6
This scholarship is part of the Chapman University COVID-19 Archives.