Pavlović, Tomislav;
Azevedo, Flavio;
De, Koustav;
Riaño-Moreno, Julián C;
Maglić, Marina;
Gkinopoulos, Theofilos;
Donnelly-Kehoe, Patricio Andreas;
... Van Bavel, Jay Joseph; + view all
(2022)
Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning.
PNAS Nexus
, 1
(3)
, Article pgac093. 10.1093/pnasnexus/pgac093.
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Abstract
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.
| Type: | Article |
|---|---|
| Title: | Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/pnasnexus/pgac093 |
| Publisher version: | https://doi.org/10.1093/pnasnexus/pgac093 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | COVID-19, hygiene, policy support, public health measures, social distancing |
| UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Institute of Cognitive Neuroscience UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10154594 |
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