COVID-Dynamic: A large-scale longitudinal study of socioemotional and behavioral change across the pandemic
Tessa Rusch, Yanting Han, Dehua Liang, Amber Hopkins, Caroline Lawrence, Uri Maoz, Lynn K. Paul, Damian Stanley, the COVID-Dynamic Team, Ralph Adolphs, Rubén Álvarez, Isabella Camplisson, Laura Harrison, Denise A. Hien, Tian Lan, Chujusn Lin, Teresa López‐Castro, Marie-Christine Nizzic, Allison Rabkin Golden, Iman Wahle, Gideon Yaffe
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.