COVID-Dynamic: A large-scale longitudinal study of socioemotional and behavioral change across the pandemic

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.

Alcohol, cannabis, and nicotine use have distinct associations with COVID-19 pandemic-related experiences: An exploratory Bayesian network analysis across two timepoints

“…We used data from the COVID-Dynamic project ( http://www.coviddynamic.caltech.edu ; Rusch et al, 2023 ; study preregistration http://osf.io/sb6qx ), a longitudinal U.S. dataset of self-report measures and behavioral data collected in 16 waves from April 2020 to January 2021. Participant (N=1797) recruitment began on April 4, 2020 via the online platform Prolific (prolific.co) according to the following criteria: aged 18–100, fluent in English, current resident of one of the 50 U.S. states, previous participation in a minimum of 5 Prolific studies, and Prolific approval rating ≥98%.…”

“…Participant (N=1797) recruitment began on April 4, 2020 via the online platform Prolific (prolific.co) according to the following criteria: aged 18–100, fluent in English, current resident of one of the 50 U.S. states, previous participation in a minimum of 5 Prolific studies, and Prolific approval rating ≥98%. To ensure geographic diversity, recruitment was spread equally across the U.S. East Coast, Middle U.S., and U.S. West Coast (see Rusch et al, 2023 for details). To ensure diversity in participant age, a portion of the recruitment targeted individuals between the ages of 40 and 100.…”

“…To ensure diversity in participant age, a portion of the recruitment targeted individuals between the ages of 40 and 100. Each wave, participants were given 140 minutes to complete an hour-long survey (survey measure composition varied from wave to wave; see Rusch et al, 2023 for details). Participants were compensated at a rate of $10 per estimated hour of survey time as well as with regular pseudo-randomly distributed bonuses.…”

“…Participants were compensated at a rate of $10 per estimated hour of survey time as well as with regular pseudo-randomly distributed bonuses. Participants were excluded from the longitudinal study based on performance and commitment metrics (see Rusch et al, 2023 for a detailed characterization of excluded participants).…”

COVID-19 Patterns in Araraquara, Brazil: A Multimodal Analysis

“…In order to identify and understand some of these disease patterns, researchers have demonstrated the association of COVID-19 cases with crowding and NPI implementation [ 8 , 9 , 33 , 34 , 35 ]. In this sense, COVID-19’s spread is regarded as a multifaceted sociopolitical problem, for which exploratory analysis and data comparison based on urban mobility and sociodemographic indicators can provide useful epidemiological information [ 36 , 37 , 38 , 39 , 40 ].…”