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

Tomislav Pavlović*, Flavio Azevedo, Koustav De, Julián C Riaño-Moreno, Marina Maglić, Theofilos Gkinopoulos, Patricio Andreas Donnelly-Kehoe, César Payán-Gómez, Guanxiong Huang, Jaroslaw Kantorowicz, Michèle D Birtel, Philipp Schönegger, Valerio Capraro, Hernando Santamaría-García, Meltem Yucel, Agustin Ibanez, Steve Rathje, Erik Wetter, Dragan Stanojević, Jan-Willem van ProoijenEugenia Hesse, Christian T Elbaek, Renata Franc, Zoran Pavlović, Panagiotis Mitkidis, Aleksandra Cichocka, Michele Gelfand, Mark Alfano, Robert M Ross, Hallgeir Sjåstad, John B Nezlek, Aleksandra Cislak, Patricia Lockwood, Koen Abts, Elena Agadullina, David M Amodio, Matthew A J Apps, John Jamir Benzon Aruta, Sahba Besharati, Alexander Bor, Becky Choma, William Cunningham, Waqas Ejaz, Harry Farmer, Andrej Findor, Biljana Gjoneska, Estrella Gualda, Toan L D Huynh, Mostak Ahamed Imran, Jacob Israelashvili, Elena Kantorowicz-Reznichenko, André Krouwel, Yordan Kutiyski, Michael Laakasuo, Claus Lamm, Jonathan Levy, Caroline Leygue, Ming-Jen Lin, Mohammad Sabbir Mansoor, Antoine Marie, Lewend Mayiwar, Honorata Mazepus, Cillian McHugh, Andreas Olsson, Tobias Otterbring, Dominic Packer, Jussi Palomäki, Anat Perry, Michael Bang Petersen, Arathy Puthillam, Tobias Rothmund, Petra C Schmid, David Stadelmann, Augustin Stoica, Drozdstoy Stoyanov, Kristina Stoyanova, Shruti Tewari, Bojan Todosijević, Benno Torgler, Manos Tsakiris, Hans H Tung, Radu Gabriel Umbreș, Edmunds Vanags, Madalina Vlasceanu, Andrew J Vonasch, Yucheng Zhang, Mohcine Abad, Eli Adler, Hamza Alaoui Mdarhri, Benedict Antazo, F Ceren Ay, Mouhamadou El Hady Ba, Sergio Barbosa, Brock Bastian, Anton Berg, Michał Białek, Ennio Bilancini, Natalia Bogatyreva, Leonardo Boncinelli, Jonathan E Booth, Sylvie Borau, Ondrej Buchel, Chrissie Ferreira de Carvalho, Tatiana Celadin, Chiara Cerami, Hom Nath Chalise, Xiaojun Cheng, Luca Cian, Kate Cockcroft, Jane Conway, Mateo A Córdoba-Delgado, Chiara Crespi, Marie Crouzevialle, Jo Cutler, Marzena Cypryańska, Justyna Dabrowska, Victoria H Davis, John Paul Minda, Pamala N Dayley, Sylvain Delouvée, Ognjan Denkovski, Guillaume Dezecache, Nathan A Dhaliwal, Alelie Diato, Roberto Di Paolo, Uwe Dulleck, Jānis Ekmanis, Tom W Etienne, Hapsa Hossain Farhana, Fahima Farkhari, Kristijan Fidanovski, Terry Flew, Shona Fraser, Raymond Boadi Frempong, Jonathan Fugelsang, Jessica Gale, E Begoña García-Navarro, Prasad Garladinne, Kurt Gray, Siobhán M Griffin, Bjarki Gronfeldt, June Gruber, Eran Halperin, Volo Herzon, Matej Hruška, Matthias F C Hudecek, Ozan Isler, Simon Jangard, Frederik Jørgensen, Oleksandra Keudel, Lina Koppel, Mika Koverola, Anton Kunnari, Josh Leota, Eva Lermer, Chunyun Li, Chiara Longoni, Darragh McCashin, Igor Mikloušić, Juliana Molina-Paredes, César Monroy-Fonseca, Elena Morales-Marente, David Moreau, Rafał Muda, Annalisa Myer, Kyle Nash, Jonas P Nitschke, Matthew S Nurse, Victoria Oldemburgo de Mello, Maria Soledad Palacios-Galvez, Yafeng Pan, Zsófia Papp, Philip Pärnamets, Mariola Paruzel-Czachura, Silva Perander, Michael Pitman, Ali Raza, Gabriel Gaudencio Rêgo, Claire Robertson, Iván Rodríguez-Pascual, Teemu Saikkonen, Octavio Salvador-Ginez, Waldir M Sampaio, Gaia Chiara Santi, David Schultner, Enid Schutte, Andy Scott, Ahmed Skali, Anna Stefaniak, Anni Sternisko, Brent Strickland, Jeffrey P Thomas, Gustav Tinghög, Iris J Traast, Raffaele Tucciarelli, Michael Tyrala, Nick D Ungson, Mete Sefa Uysal, Dirk Van Rooy, Daniel Västfjäll, Joana B Vieira, Christian von Sikorski, Alexander C Walker, Jennifer Watermeyer, Robin Willardt, Michael J A Wohl, Adrian Dominik Wójcik, Kaidi Wu, Yuki Yamada, Onurcan Yilmaz, Kumar Yogeeswaran, Carolin-Theresa Ziemer, Rolf A Zwaan, Paulo Sergio Boggio, Ashley Whillans, Paul A M Van Lange, Rajib Prasad, Michal Onderco, Cathal O'Madagain, Tarik Nesh-Nash, Oscar Moreda Laguna, Emily Kubin, Mert Gümren, Ali Fenwick, Arhan S Ertan, Michael J Bernstein, Hanane Amara, Jay Joseph Van Bavel

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

21 Citations (Scopus)
44 Downloads (Pure)

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.

Original languageEnglish
Article numberpgac093
Pages (from-to)pgac093
JournalPNAS Nexus
Volume1
Issue number3
DOIs
Publication statusPublished - Jul 2022

Bibliographical note

Publisher Copyright:
© The Author(s) 2022. Published by Oxford University Press on behalf of National Academy of Sciences.

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