@article{Pavlovi_T-2022_93160,
title = {Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning},
author = {Pavlović, T. and Azevedo, F. and De, K. and Riaño-Moreno, J. and Maglić, M. and Gkinopoulos, T. and Donnelly-Kehoe, P. and Payán-Gómez, C. and Huang, G. and Kantorowicz, J. and Birtel, M. and Schönegger, P. and Capraro, V. and Santamaría-García, H. and Yucel, M. and Ibanez, A. and Rathje, S. and Wetter, E. and Stanojević, D. and van Prooijen, J. and Hesse, E. and Elbaek, C. and Franc, R. and Pavlović, Z. and Mitkidis, P. and Cichocka, A. and Gelfand, M. and Alfano, M. and Ross, R. and Sjåstad, H. and Nezlek, J. and Cislak, A. and Lockwood, P. and Abts, K. and Agadullina, E. and Amodio, D. and Apps, M. and Aruta, J. and Besharati, S. and Bor, A. and Choma, B. and Cunningham, W. and Ejaz, W. and Farmer, H. and Findor, A. and Gjoneska, B. and Gualda, E. and Huynh, T. and Imran, M. and Israelashvili, J. and Kantorowicz-Reznichenko, E. and Krouwel, A. and Kutiyski, Y. and Laakasuo, M. and Lamm, C. and Levy, J. and Leygue, C. and Lin, M. and Mansoor, M. and Marie, A. and Mayiwar, L. and Mazepus, H. and McHugh, C. and Olsson, A. and Otterbring, T. and Packer, D. and Palomäki, J. and Perry, A. and Petersen, M. and Puthillam, A. and Rothmund, T. and Schmid, P. and Stadelmann, D. and Stoica, A. and Stoyanov, D. and Stoyanova, K. and Tewari, S. and Todosijević, B. and Torgler, B. and Tsakiris, M. and Tung, H. and Umbreș, R. and Vanags, E. and Vlasceanu, M. and Vonasch, A. and Zhang, Y. and Abad, M. and Adler, E. and Mdarhri, H. and Antazo, B. and Ay, F. and Ba, M. and Barbosa, S. and Bastian, B. and Berg, A. and Białek, M. and Bilancini, E. and Bogatyreva, N. and Boncinelli, L. and Booth, J. and Borau, S. and Buchel, O. and de Carvalho, C. and Celadin, T. and Cerami, C. and Chalise, H. and Cheng, X. and Cian, L. and Cockcroft, K. and Conway, J. and Córdoba-Delgado, M. and Crespi, C. and Crouzevialle, M. and Cutler, J. and Cypryańska, M. and Dabrowska, J. and Davis, V. and Minda, J. and Dayley, P. and Delouvée, S. and Denkovski, O. and Dezecache, G. and Dhaliwal, N. and Diato, A. and Paolo, R. and Dulleck, U. and Ekmanis, J. and Etienne, T. and Farhana, H. and Farkhari, F. and Fidanovski, K. and Flew, T. and Fraser, S. and Frempong, R. and Fugelsang, J. and Gale, J. and García-Navarro, E. and Garladinne, P. and Gray, K. and Griffin, S. and Gronfeldt, B. and Gruber, J. and Halperin, E. and Herzon, V. and Hruška, M. and Hudecek, M. and Isler, O. and Jangard, S. and Jørgensen, F. and Keudel, O. and Koppel, L. and Koverola, M. and Kunnari, A. and Leota, J. and Lermer, E. and Li, C. and Longoni, C. and McCashin, D. and Mikloušić, I. and Molina-Paredes, J. and Monroy-Fonseca, C. and Morales-Marente, E. and Moreau, D. and Muda, R. and Myer, A. and Nash, K. and Nitschke, J. and Nurse, M. and de Mello, V. and Palacios-Galvez, M. and Palomäki, J. and Pan, Y. and Papp, Z. and Pärnamets, P. and Paruzel-Czachura, M. and Perander, S. and Pitman, M. and Raza, A. and Rêgo, G. and Robertson, C. and Rodríguez-Pascual, I. and Saikkonen, T. and Salvador-Ginez, O. and Sampaio, W. and Santi, G. and Schultner, D. and Schutte, E. and Scott, A. and Skali, A. and Stefaniak, A. and Sternisko, A. and Strickland, B. and Strickland, B. and Thomas, J. and Tinghög, G. and Traast, I. and Tucciarelli, R. and Tyrala, M. and Ungson, N. and Uysal, M. and Van Rooy, D. and Västfjäll, D. and Vieira, J. and von Sikorski, C. and Walker, A. and Watermeyer, J. and Willardt, R. and Wohl, M. and Wójcik, A. and Wu, K. and Yamada, Y. and Yilmaz, O. and Yogeeswaran, K. and Ziemer, C. and Zwaan, R. and Boggio, P. and Whillans, A. and Van Lange, P. and Prasad, R. and Onderco, M. and O'Madagain, C. and Nesh-Nash, T. and Laguna, O. and Kutiyski, Y. and Kubin, E. and Gümren, M. and Fenwick, A. and Ertan, A. and Bernstein, M. and Amara, H. and Van Bavel, J.},
month = {jul},
year = {2022},
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 multi-national 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 was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible 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.},
volume = {1},
issue = {3},
journal = {PNAS Nexus},
publisher = {Oxford University Press},
url = {https://doi.org/10.1093/pnasnexus/pgac093},
}
