The RW3D: A multi-modal panel dataset to understand the psychological impact of the pandemic

TL;DR

The paper introduces RW3D, a comprehensive multi-modal dataset combining survey responses, demographic data, and open-ended texts collected over three years to study the psychological impact of COVID-19.

Contribution

It presents a new multi-modal, longitudinal dataset (RW3D) that integrates text, survey, and demographic data for pandemic-related psychological research.

Findings

Rich dataset with over 5,300 participants across three years.

Includes open-ended responses, emotions, life events, and stressors.

Enables multi-modal analysis of psychological impact over time.

Abstract

Besides far-reaching public health consequences, the COVID-19 pandemic had a significant psychological impact on people around the world. To gain further insight into this matter, we introduce the Real World Worry Waves Dataset (RW3D). The dataset combines rich open-ended free-text responses with survey data on emotions, significant life events, and psychological stressors in a repeated-measures design in the UK over three years (2020: n=2441, 2021: n=1716 and 2022: n=1152). This paper provides background information on the data collection procedure, the recorded variables, participants' demographics, and higher-order psychological and text-based derived variables that emerged from the data. The RW3D is a unique primary data resource that could inspire new research questions on the psychological impact of the pandemic, especially those that connect modalities (here: text data, psychological survey variables and demographics) over time.