학술논문
Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning
Document Type
Author
Maglić, Marina; Gkinopoulos, Theofilos; Donnelly-Kehoe, Patricio Andreas; Payán-Gómez, César; Huang, Guanxiong; Kantorowicz, Jaroslaw; Birtel, Michèle D; Schönegger, Philipp; Capraro, Valerio; Santamaría-García, Hernando; Yucel, Meltem; Ibanez, Agustin; Rathje, Steve; Wetter, Erik; Cislak, Aleksandra; Lockwood, Patricia; Abts, Koen; Agadullina, Elena; Amodio, David M; Mitkidis, Panagiotis; Cichocka, Aleksandra; Gelfand, Michele; Alfano, Mark; Ross, Robert M; Sjåstad, Hallgeir; Nezlek, John B; Lamm, Claus; Levy, Jonathan; Farmer, Harry; Findor, Andrej; Leygue, Caroline; Gjoneska, Biljana; Gualda, Estrella; Huynh, Toan L D; Bor, Alexander; Choma, Becky; Cunningham, William; Ejaz, Waqas; Kantorowicz-Reznichenko, Elena; Imran, Mostak Ahamed; Israelashvili, Jacob; Krouwel, André; Kutiyski, Yordan; Laakasuo, Michael; Lin, Ming-Jen; Mansoor, Mohammad Sabbir; Marie, Antoine; Mayiwar, Lewend; Todosijević, Bojan; Torgler, Benno; Tsakiris, Manos; Tung, Hans H; Umbreș, Radu Gabriel; Vanags, Edmunds; Vlasceanu, Madalina; Vonasch, Andrew J; Bogatyreva, Natalia; Boncinelli, Leonardo; Booth, Jonathan E; Białek, Michał; Bilancini, Ennio; Chalise, Hom Nath; Cheng, Xiaojun; Cian, Luca; Cockcroft, Kate; Antazo, Benedict; Ay, F Ceren; Ba, Mouhamadou El Hady; Barbosa, Sergio; Bastian, Brock; Berg, Anton; Borau, Sylvie; Buchel, Ondrej; de Carvalho, Chrissie Ferreira; Celadin, Tatiana; Cerami, Chiara; Zhang, Yucheng; Abad, Mohcine; Adler, Eli; Mdarhri, Hamza Alaoui; McHugh, Cillian; Olsson, Andreas; Otterbring, Tobias; Packer, Dominic; Palomäki, Jussi; Perry, Anat; Petersen, Michael Bang; Puthillam, Arathy; Rothmund, Tobias; Schmid, Petra C; Stadelmann, David; Stoica, Augustin; Stoyanov, Drozdstoy; Stoyanova, Kristina; Tewari, Shruti; Vieira, Joana B; von Sikorski, Christian; Walker, Alexander C; Watermeyer, Jennifer; Willardt, Robin; Di Paolo, Roberto; Dulleck, Uwe; Ekmanis, Jānis; Etienne, Tom W; Farhana, Hapsa Hossain; Wohl, Michael J A; Wójcik, Adrian Dominik; Wu, Kaidi; Yamada, Yuki; Farkhari, Fahima; Fidanovski, Kristijan; Flew, Terry; Fraser, Shona; Frempong, Raymond Boadi; Yilmaz, Onurcan; Yogeeswaran, Kumar; Ziemer, Carolin-Theresa; Zwaan, Rolf A; Boggio, Paulo Sergio; Fugelsang, Jonathan; Gale, Jessica; García-Navarro, E Begoña; Garladinne, Prasad; Gray, Kurt; Whillans, Ashley; Van Lange, Paul A M; Prasad, Rajib; Onderco, Michal; O'Madagain, Cathal; Nesh-Nash, Tarik; Gronfeldt, Bjarki; Gruber, June; Halperin, Eran; Herzon, Volo; Griffin, Siobhán M; Kubin, Emily; Gümren, Mert; Fenwick, Ali; Ertan, Arhan S; Bernstein, Michael J; Laguna, Oscar Moreda; Hruška, Matej; Hudecek, Matthias F C; Isler, Ozan; Jangard, Simon; Jørgensen, Frederik; Amara, Hanane; Van Bavel, Jay Joseph; Keudel, Oleksandra; Koppel, Lina; Koverola, Mika; Kunnari, Anton; Leota, Josh; Lermer, Eva; Li, Chunyun; Longoni, Chiara; McCashin, Darragh; Mikloušić, Igor; Molina-Paredes, Juliana; Monroy-Fonseca, César; Morales-Marente, Elena; Moreau, David; Muda, Rafał; Myer, Annalisa; Nash, Kyle; Nitschke, Jonas P; Nurse, Matthew S; de Mello, Victoria Oldemburgo; Palacios-Galvez, Maria Soledad; Pan, Yafeng; Papp, Zsófia; Pärnamets, Philip; Paruzel-Czachura, Mariola; Perander, Silva; Pitman, Michael; Raza, Ali; Rêgo, Gabriel Gaudencio; Robertson, Claire; Rodríguez-Pascual, Iván; Conway, Jane; Córdoba-Delgado, Mateo A; Crespi, Chiara; Crouzevialle, Marie; Cutler, Jo; Saikkonen, Teemu; Salvador-Ginez, Octavio; Sampaio, Waldir M; Santi, Gaia Chiara; Schultner, David; Cypryańska, Marzena; Dabrowska, Justyna; Davis, Victoria H; Minda, John Paul; Dayley, Pamala N; Schutte, Enid; Scott, Andy; Skali, Ahmed; Stefaniak, Anna; Sternisko, Anni; Strickland, Brent; Thomas, Jeffrey P; Tinghög, Gustav; Traast, Iris J; Tucciarelli, Raffaele; Delouvée, Sylvain; Denkovski, Ognjan; Dezecache, Guillaume; Dhaliwal, Nathan A; Diato, Alelie; Tyrala, Michael; Ungson, Nick D; Uysal, Mete Sefa; Van Rooy, Dirk; Västfjäll, Daniel; Mazepus, Honorata; Pavlović, Tomislav; Azevedo, Flavio; De, Koustav; Riaño-Moreno, Julián C; Stanojević, Dragan; van Prooijen, Jan-Willem; Hesse, Eugenia; Elbaek, Christian T; Franc, Renata; Pavlović, Zoran; Besharati, Sahba; Apps, Matthew A J; Aruta, John Jamir Benzon
Source
PNAS Nexus. 1(3)
Subject
Language
English
ISSN
2752-6542
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 ( = 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.