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Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Pavlović, Tomislav, Azevedo, Flavio, De, Koustav, Riaño-Moreno, Julián C, Maglić, Marina, Gkinopoulos, Theofilos, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Huang, Guanxiong, Kantorowicz, Jaroslaw, and others. (2022) Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning. PNAS Nexus, 1 (3). Article Number pgac093. ISSN 2752-6542. (doi:10.1093/pnasnexus/pgac093) (KAR id:104802)


At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

Item Type: Article
DOI/Identification number: 10.1093/pnasnexus/pgac093
Additional information: For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising.
Uncontrolled keywords: public health measures, COVID-19, social distancing, policy support, hygiene
Subjects: B Philosophy. Psychology. Religion
B Philosophy. Psychology. Religion > BF Psychology
Divisions: Divisions > Division of Human and Social Sciences > School of Psychology
Funders: Volkswagen Foundation (
Slovak Research and Development Agency (
Medical Research Council (
Carlsberg Foundation (
Dutch Research Council (
Ministry of Education, Science and Technological Development (
National Natural Science Foundation of China (
Ministry of Education of the People's Republic of China (
Croatian Science Foundation (
Institut Društvenih Znanosti Ivo Pilar (
National Scientific and Technical Research Council (
National Institutes of Health (
Coordenação de Aperfeicoamento de Pessoal de Nível Superior (
National Council for Scientific and Technological Development (
Australian Research Council (
John Templeton Foundation (
National Science Center (
The Research Council of Norway (
Social Sciences and Humanities Research Council (
Deutsche Forschungsgemeinschaft (
Biotechnology and Biological Sciences Research Council (
Jane and Aatos Erkko Foundation (
Research Council of Finland (
Universidad de Huelva (
University of Vienna (
FWF Austrian Science Fund (
Natural Sciences and Engineering Research Council (
Swedish Research Council for Environment Agricultural Sciences and Spatial Planning (
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 31 Jan 2024 16:14 UTC
Last Modified: 27 Feb 2024 11:57 UTC
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