COVID-Dynamic: A Large-Scale Longitudinal Study of Socioemotional and Behavioral Change Across the Pandemic
Welcome to the GitHub repository for COVID-Dynamic, a large-scale longitudinal study that explores socioemotional and behavioral changes during the COVID-19 pandemic. This repository accompanies the paper: COVID-Dynamic: A large-scale longitudinal study of socioemotional and behavioral change across the pandemic Published in Scientific Data (Nature), 2022 Read the full article here: https://www.nature.com/articles/s41597-022-01901-6
Overview This repository provides access to the code associated with the study. The data is availbale for download on OSF: https://osf.io/nhm2v. Additional Public Resources: a) Web-based data explorer: http://coviddynamicdash.caltech.edu/shiny/coviddash/ b) Summary of COVID-19 Psychological Studies: https://coviddynamic.caltech.edu/resources/other-covid-studies c) 2020 Timeline: https://coviddynamic.caltech.edu/resources/timeline-2020-world-events.
Key Features of the study: Longitudinal data: Data was collected at 16 time points between April 2020 and Jannaury 2021 to track socioemotional/ behavioral changes across teh COVID pandemic. COVID-Dynamic test battery: The self-report questionnaire battery included commonly used, published psychological assessment instruments and race-related surveys. We also administered a variety of self-report questionnaires created specifically for this study to characterize experiences (e.g., direct exposure to COVID-19, COVID-19 illness amongst family and friends, more general COVID-19-related changes to daily life) and attitudes (e.g., towards masking, government-mandated restrictions, the killing of George Floyd, etc.) related to COVID-19 and the Black Lives Matter (BLM) protests, as well as demographic surveys and experimental questionnaires related to new and ongoing research (see Measures - Measures Created by COVID-Dynamic Team). Tasks: In addition to questionnaires, participants completed a series of computer-based tasks designed to assess implicit social attitudes towards race (specifically Black/White/Asian) and pro-sociality, as well as estimations of COVID-related trustworthiness, and social decisions related to pro-sociality, group-cohesion, and altruism. Demographic data: FOr each participant we provide detailed demographic information, as well as raking weights to weight the sample to match the demographics of the US population more closely. External measures: External measures In addition to data collected from participants, we aggregated data from a variety of external sources and linked the external data to the COVID-Dynamic data-collection-schedule, and participants’ individual wave-by-wave physical locations (US-state and county). See https://github.com/adolphslab/CVD-DYN_datarelease/tree/main/external_data for details on data-extraction and processing.