Pandemic panic? Results of a 14-month longitudinal study on fear of COVID-19
Abstract
Background Fear is an evolutionary adaptive emotion that serves to protect the organism from harm. Once a threat diminishes, fear should also dissipate as otherwise fear may become chronic and pathological. While actual threat of the COVID-19 pandemic (i.e., number of infections, hospitalizations, and deaths) has substantially varied over the course of the pandemic, it remains unclear whether (subjective) fear has followed a similar pattern. Method To examine the development of fear of COVID-19 during the pandemic and investigate potential predictors of chronic fear, we conducted a large online longitudinal study (N = 2000) using the Prolific platform between April 2020 and June 2021. Participants were voluntary response samples and consisted of residents of 34 different countries. The Fear of the Coronavirus Questionnaire (FCQ) and several other demographic and psychological measures were completed monthly. Results Overall, we find that fear steadily decreased since April 2020. Additional analyses showed that elevated fear was predicted by region (i.e., North America > Europe), anxious traits, gender, risks for loved ones, general health, and media use. Limitations The interpretation of the results of this study is limited by the non-representativeness of the sample and the lack of data points between August 2020 and June 2021. Conclusions This study helps to characterize the trajectory of fear levels throughout the COVID-19 pandemic and establish several relevant predictors of increased fear.
Study specs
- Authors
- G Mertens,P Lodder,T Smeets,S Duijndam
- Institution
- Institute for Psychology,Biological Psychology and Cogntive Neuroscience,University of Bielefeld,Department of Methodology & Statistics,Tilburg University
- Discipline
- Psychology
- Year
- 2023
- Human Data Platform
- Prolific
- Source
- View Source Google Scholar
Peer Review & Critical Discussion
Potential Selection Bias in 2023 Cohort
The participant pool shows a concerning overrepresentation of users from high-income demographics. Looking at Table 3, we can see that 78% of respondents had annual incomes above $75k, which significantly limits the generalizability of these findings to broader populations.
Non-naive Participants Issue
I've noticed a methodological concern regarding participant naivety. Given that Prolific users often complete multiple studies, there's a real risk that participants had prior exposure to similar experimental paradigms, which could confound the results.
RLHF Applicability to This Study Design
The implications for RLHF training pipelines are understated. If we accept the authors' conclusions about preference stability, this has direct consequences for how we should structure reward model training. The temporal decay effect described in Section 4.2 is particularly relevant.
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