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. 2022 Jul 5;1(3):pgac093.
doi: 10.1093/pnasnexus/pgac093. eCollection 2022 Jul.

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

Tomislav Pavlović  1 Flavio Azevedo  2 Koustav De  3 Julián C Riaño-Moreno  4 Marina Maglić  1 Theofilos Gkinopoulos  5 Patricio Andreas Donnelly-Kehoe  6 César Payán-Gómez  7 Guanxiong Huang  8 Jaroslaw Kantorowicz  9 Michèle D Birtel  10 Philipp Schönegger  11 Valerio Capraro  12 Hernando Santamaría-García  13 Meltem Yucel  14 Agustin Ibanez  15 Steve Rathje  16 Erik Wetter  17 Dragan Stanojević  18 Jan-Willem van Prooijen  19 Eugenia Hesse  20 Christian T Elbaek  21 Renata Franc  1 Zoran Pavlović  22 Panagiotis Mitkidis  21 Aleksandra Cichocka  23 Michele Gelfand  24 Mark Alfano  25 Robert M Ross  25 Hallgeir Sjåstad  26 John B Nezlek  27 Aleksandra Cislak  28 Patricia Lockwood  29 Koen Abts  30 Elena Agadullina  31 David M Amodio  32 Matthew A J Apps  29 John Jamir Benzon Aruta  33 Sahba Besharati  34 Alexander Bor  35 Becky Choma  36 William Cunningham  37 Waqas Ejaz  38 Harry Farmer  39 Andrej Findor  40 Biljana Gjoneska  41 Estrella Gualda  42 Toan L D Huynh  43 Mostak Ahamed Imran  44 Jacob Israelashvili  45 Elena Kantorowicz-Reznichenko  46 André Krouwel  47 Yordan Kutiyski  48 Michael Laakasuo  49 Claus Lamm  50 Jonathan Levy  51 Caroline Leygue  52 Ming-Jen Lin  53 Mohammad Sabbir Mansoor  54 Antoine Marie  35 Lewend Mayiwar  55 Honorata Mazepus  56 Cillian McHugh  57 Andreas Olsson  58 Tobias Otterbring  59 Dominic Packer  60 Jussi Palomäki  49 Anat Perry  45 Michael Bang Petersen  35 Arathy Puthillam  61 Tobias Rothmund  62 Petra C Schmid  63 David Stadelmann  64 Augustin Stoica  65 Drozdstoy Stoyanov  66 Kristina Stoyanova  67 Shruti Tewari  68 Bojan Todosijević  69 Benno Torgler  70 Manos Tsakiris  71 Hans H Tung  72 Radu Gabriel Umbreș  73 Edmunds Vanags  74 Madalina Vlasceanu  75 Andrew J Vonasch  76 Yucheng Zhang  77 Mohcine Abad  78 Eli Adler  45 Hamza Alaoui Mdarhri  78 Benedict Antazo  79 F Ceren Ay  80 Mouhamadou El Hady Ba  81 Sergio Barbosa  82 Brock Bastian  83 Anton Berg  49 Michał Białek  84 Ennio Bilancini  85 Natalia Bogatyreva  86 Leonardo Boncinelli  87 Jonathan E Booth  88 Sylvie Borau  89 Ondrej Buchel  90 Chrissie Ferreira de Carvalho  91 Tatiana Celadin  92 Chiara Cerami  93 Hom Nath Chalise  94 Xiaojun Cheng  95 Luca Cian  96 Kate Cockcroft  34 Jane Conway  97 Mateo A Córdoba-Delgado  98 Chiara Crespi  99 Marie Crouzevialle  63 Jo Cutler  100 Marzena Cypryańska  27 Justyna Dabrowska  101 Victoria H Davis  102 John Paul Minda  103 Pamala N Dayley  104 Sylvain Delouvée  105 Ognjan Denkovski  106 Guillaume Dezecache  107 Nathan A Dhaliwal  108 Alelie Diato  109 Roberto Di Paolo  85 Uwe Dulleck  110 Jānis Ekmanis  111 Tom W Etienne  112 Hapsa Hossain Farhana  113 Fahima Farkhari  114 Kristijan Fidanovski  115 Terry Flew  116 Shona Fraser  117 Raymond Boadi Frempong  64 Jonathan Fugelsang  118 Jessica Gale  76 E Begoña García-Navarro  119 Prasad Garladinne  68 Kurt Gray  120 Siobhán M Griffin  57 Bjarki Gronfeldt  23 June Gruber  121 Eran Halperin  45 Volo Herzon  49 Matej Hruška  40 Matthias F C Hudecek  122 Ozan Isler  110 Simon Jangard  58 Frederik Jørgensen  35 Oleksandra Keudel  123 Lina Koppel  124 Mika Koverola  49 Anton Kunnari  125 Josh Leota  126 Eva Lermer  127 Chunyun Li  88 Chiara Longoni  128 Darragh McCashin  129 Igor Mikloušić  1 Juliana Molina-Paredes  130 César Monroy-Fonseca  131 Elena Morales-Marente  132 David Moreau  133 Rafał Muda  134 Annalisa Myer  135 Kyle Nash  136 Jonas P Nitschke  50 Matthew S Nurse  137 Victoria Oldemburgo de Mello  37 Maria Soledad Palacios-Galvez  132 Yafeng Pan  138 Zsófia Papp  139 Philip Pärnamets  58 Mariola Paruzel-Czachura  140 Silva Perander  141 Michael Pitman  34 Ali Raza  142 Gabriel Gaudencio Rêgo  143 Claire Robertson  144 Iván Rodríguez-Pascual  132 Teemu Saikkonen  145 Octavio Salvador-Ginez  146 Waldir M Sampaio  143 Gaia Chiara Santi  147 David Schultner  148 Enid Schutte  34 Andy Scott  135 Ahmed Skali  149 Anna Stefaniak  150 Anni Sternisko  144 Brent Strickland  151 Jeffrey P Thomas  88 Gustav Tinghög  123 Iris J Traast  152 Raffaele Tucciarelli  153 Michael Tyrala  154 Nick D Ungson  155 Mete Sefa Uysal  156 Dirk Van Rooy  157 Daniel Västfjäll  158 Joana B Vieira  58 Christian von Sikorski  159 Alexander C Walker  117 Jennifer Watermeyer  160 Robin Willardt  63 Michael J A Wohl  150 Adrian Dominik Wójcik  161 Kaidi Wu  162 Yuki Yamada  163 Onurcan Yilmaz  164 Kumar Yogeeswaran  76 Carolin-Theresa Ziemer  165 Rolf A Zwaan  166 Paulo Sergio Boggio  143 Ashley Whillans  167 Paul A M Van Lange  19 Rajib Prasad  168 Michal Onderco  169 Cathal O'Madagain  78 Tarik Nesh-Nash  170 Oscar Moreda Laguna  48 Emily Kubin  159 Mert Gümren  171 Ali Fenwick  172 Arhan S Ertan  173 Michael J Bernstein  174 Hanane Amara  171 Jay Joseph Van Bavel  144
Affiliations

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

Tomislav Pavlović et al. PNAS Nexus. .

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.

Keywords: COVID-19; hygiene; policy support; public health measures; social distancing.

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Figures

Fig. 1.
Fig. 1.
Permutation variable importance calculated with respect to representativeness of the samples and stage of the pandemic.
Fig. 2.
Fig. 2.
Partial dependence plots depicting the relationships between our predictors and criteria based on the complete data. Note: red, blue, and green represent avoiding contact, maintaining hygiene, and policy support, respectively.
Fig. 3.
Fig. 3.
Partial dependence plots based on the data reflecting the early stage of pandemic. Note: red, blue, and green represent avoiding contact, maintaining hygiene, and policy support, respectively.
Fig. 4.
Fig. 4.
Partial dependence plots based on the data reflecting the advanced stage of pandemic. Note: red, blue, and green represent avoiding contact, maintaining hygiene, and policy support, respectively.

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