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

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dc.contributor.authorPavlović T
dc.contributor.authorAzevedo F
dc.contributor.authorDe K
dc.contributor.authorRiaño-Moreno JC
dc.contributor.authorMaglić M
dc.contributor.authorGkinopoulos T
dc.contributor.authorDonnelly-Kehoe PA
dc.contributor.authorPayán-Gómez C
dc.contributor.authorHuang G
dc.contributor.authorKantorowicz J
dc.contributor.authorBirtel MD
dc.contributor.authorSchönegger P
dc.contributor.authorCapraro V
dc.contributor.authorSantamaría-García H
dc.contributor.authorYucel M
dc.contributor.authorIbanez A
dc.contributor.authorRathje S
dc.contributor.authorWetter E
dc.contributor.authorStanojević D
dc.contributor.authorvan Prooijen J-W
dc.contributor.authorHesse E
dc.contributor.authorElbaek CT
dc.contributor.authorFranc R
dc.contributor.authorPavlović Z
dc.contributor.authorMitkidis P
dc.contributor.authorCichocka A
dc.contributor.authorGelfand M
dc.contributor.authorAlfano M
dc.contributor.authorRoss RM
dc.contributor.authorSjåstad H
dc.contributor.authorNezlek JB
dc.contributor.authorCislak A
dc.contributor.authorLockwood P
dc.contributor.authorAbts K
dc.contributor.authorAgadullina E
dc.contributor.authorAmodio DM
dc.contributor.authorApps MAJ
dc.contributor.authorAruta JJB
dc.contributor.authorBesharati S
dc.contributor.authorBor A
dc.contributor.authorChoma B
dc.contributor.authorCunningham W
dc.contributor.authorEjaz W
dc.contributor.authorFarmer H
dc.contributor.authorFindor A
dc.contributor.authorGjoneska B
dc.contributor.authorGualda E
dc.contributor.authorHuynh TLD
dc.contributor.authorImran MA
dc.contributor.authorIsraelashvili J
dc.contributor.authorKantorowicz-Reznichenko E
dc.contributor.authorKrouwel A
dc.contributor.authorKutiyski Y
dc.contributor.authorLaakasuo M
dc.contributor.authorLamm C
dc.contributor.authorLevy J
dc.contributor.authorLeygue C
dc.contributor.authorLin M-J
dc.contributor.authorMansoor MS
dc.contributor.authorMarie A
dc.contributor.authorMayiwar L
dc.contributor.authorMazepus H
dc.contributor.authorMcHugh C
dc.contributor.authorOlsson A
dc.contributor.authorOtterbring T
dc.contributor.authorPacker D
dc.contributor.authorPalomäki J
dc.contributor.authorPerry A
dc.contributor.authorPetersen MB
dc.contributor.authorPuthillam A
dc.contributor.authorRothmund T
dc.contributor.authorSchmid PC
dc.contributor.authorStadelmann D
dc.contributor.authorStoica A
dc.contributor.authorStoyanov D
dc.contributor.authorStoyanova K
dc.contributor.authorTewari S
dc.contributor.authorTodosijević B
dc.contributor.authorTorgler B
dc.contributor.authorTsakiris M
dc.contributor.authorTung HH
dc.contributor.authorUmbreș RG
dc.contributor.authorVanags E
dc.contributor.authorVlasceanu M
dc.contributor.authorZhang Y
dc.contributor.authorAbad M
dc.contributor.authorAdler E
dc.contributor.authorMdarhri HA
dc.contributor.authorAntazo B
dc.contributor.authorAy FC
dc.contributor.authorBa MEH
dc.contributor.authorBarbosa S
dc.contributor.authorBastian B
dc.contributor.authorBerg A
dc.contributor.authorBiałek M
dc.contributor.authorBilancini E
dc.contributor.authorBogatyreva N
dc.contributor.authorBoncinelli L
dc.contributor.authorBooth JE
dc.contributor.authorBorau S
dc.contributor.authorBuchel O
dc.contributor.authorde Carvalho CF
dc.contributor.authorCeladin T
dc.contributor.authorCerami C
dc.contributor.authorChalise HN
dc.contributor.authorCheng X
dc.contributor.authorCian L
dc.contributor.authorCockcroft K
dc.contributor.authorConway J
dc.contributor.authorCórdoba-Delgado MA
dc.contributor.authorCrespi C
dc.contributor.authorCrouzevialle M
dc.contributor.authorCutler J
dc.contributor.authorCypryańska M
dc.contributor.authorDabrowska J
dc.contributor.authorDavis VH
dc.contributor.authorMinda JP
dc.contributor.authorDayley PN
dc.contributor.authorDelouvée S
dc.contributor.authorDenkovski O
dc.contributor.authorDezecache G
dc.contributor.authorDhaliwal NA
dc.contributor.authorDiato A
dc.contributor.authorPaolo RD
dc.contributor.authorDulleck U
dc.contributor.authorEkmanis J
dc.contributor.authorEtienne TW
dc.contributor.authorFarhana HH
dc.contributor.authorFarkhari F
dc.contributor.authorFidanovski K
dc.contributor.authorFlew T
dc.contributor.authorFraser S
dc.contributor.authorFrempong RB
dc.contributor.authorFugelsang J
dc.contributor.authorGale J
dc.contributor.authorGarcía-Navarro EB
dc.contributor.authorGarladinne P
dc.contributor.authorGray K
dc.contributor.authorGriffin SM
dc.contributor.authorGronfeldt B
dc.contributor.authorGruber J
dc.contributor.authorHalperin E
dc.contributor.authorHerzon V
dc.contributor.authorHruška M
dc.contributor.authorHudecek MFC
dc.contributor.authorIsler O
dc.contributor.authorJangard S
dc.contributor.authorJørgensen F
dc.contributor.authorKeudel O
dc.contributor.authorKoppel L
dc.contributor.authorKoverola M
dc.contributor.authorKunnari A
dc.contributor.authorLeota J
dc.contributor.authorLermer E
dc.contributor.authorLi C
dc.contributor.authorLongoni C
dc.contributor.authorMcCashin D
dc.contributor.authorMikloušić I
dc.contributor.authorMolina-Paredes J
dc.contributor.authorMonroy-Fonseca C
dc.contributor.authorMorales-Marente E
dc.contributor.authorMoreau D
dc.contributor.authorMuda R
dc.contributor.authorMyer A
dc.contributor.authorNash K
dc.contributor.authorNitschke JP
dc.contributor.authorNurse MS
dc.contributor.authorde Mello VO
dc.contributor.authorPalacios-Galvez MS
dc.contributor.authorPalomäki J
dc.contributor.authorPan Y
dc.contributor.authorPapp Z
dc.contributor.authorPärnamets P
dc.contributor.authorParuzel-Czachura M
dc.contributor.authorPerander S
dc.contributor.authorPitman M
dc.contributor.authorRaza A
dc.contributor.authorRêgo GG
dc.contributor.authorRobertson C
dc.contributor.authorRodríguez-Pascual I
dc.contributor.authorSaikkonen T
dc.contributor.authorSalvador-Ginez O
dc.contributor.authorSampaio WM
dc.contributor.authorSanti GC
dc.contributor.authorSchultner D
dc.contributor.authorSchutte E
dc.contributor.authorScott A
dc.contributor.authorSkali A
dc.contributor.authorStefaniak A
dc.contributor.authorSternisko A
dc.contributor.authorStrickland B
dc.contributor.authorStrickland B
dc.contributor.authorThomas JP
dc.contributor.authorTinghög G
dc.contributor.authorTraast IJ
dc.contributor.authorTucciarelli R
dc.contributor.authorTyrala M
dc.contributor.authorUngson ND
dc.contributor.authorUysal MS
dc.contributor.authorVan Rooy D
dc.contributor.authorVästfjäll D
dc.contributor.authorVieira JB
dc.contributor.authorvon Sikorski C
dc.contributor.authorWalker AC
dc.contributor.authorWatermeyer J
dc.contributor.authorWillardt R
dc.contributor.authorWohl MJA
dc.contributor.authorWójcik AD
dc.contributor.authorWu K
dc.contributor.authorYamada Y
dc.contributor.authorYilmaz O
dc.contributor.authorYogeeswaran K
dc.contributor.authorZiemer C-T
dc.contributor.authorZwaan RA
dc.contributor.authorBoggio PS
dc.contributor.authorWhillans A
dc.contributor.authorVan Lange PAM
dc.contributor.authorPrasad R
dc.contributor.authorOnderco M
dc.contributor.authorO'Madagain C
dc.contributor.authorNesh-Nash T
dc.contributor.authorLaguna OM
dc.contributor.authorKutiyski Y
dc.contributor.authorKubin E
dc.contributor.authorGümren M
dc.contributor.authorFenwick A
dc.contributor.authorErtan AS
dc.contributor.authorBernstein MJ
dc.contributor.authorAmara H
dc.contributor.authorVan Bavel JJ
dc.contributor.authorVonasch, Andrew
dc.date.accessioned2023-01-08T22:35:48Z
dc.date.available2023-01-08T22:35:48Z
dc.date.issued2022en
dc.date.updated2022-07-24T06:56:57Z
dc.description.abstractAt 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.en
dc.identifier.citationPavlović T, Azevedo F, De K, Riaño-Moreno JC, Maglić M, Gkinopoulos T, Donnelly-Kehoe PA, Payán-Gómez C, Huang G, Kantorowicz J, Birtel MD, Schönegger P, Capraro V, Santamaría-García H, Yucel M, Ibanez A, Rathje S, Wetter E, Stanojević D, van Prooijen J-W, Hesse E, Elbaek CT, Franc R, Pavlović Z, Mitkidis P, Cichocka A, Gelfand M, Alfano M, Ross RM, Sjåstad H, Nezlek JB, Cislak A, Lockwood P, Abts K, Agadullina E, Amodio DM, Apps MAJ, Aruta JJB, Besharati S, Bor A, Choma B, Cunningham W, Ejaz W, Farmer H, Findor A, Gjoneska B, Gualda E, Huynh TLD, Imran MA, Israelashvili J, Kantorowicz-Reznichenko E, Krouwel A, Kutiyski Y, Laakasuo M, Lamm C, Levy J, Leygue C, Lin M-J, Mansoor MS, Marie A, Mayiwar L, Mazepus H, McHugh C, Olsson A, Otterbring T, Packer D, Palomäki J, Perry A, Petersen MB, Puthillam A, Rothmund T, Schmid PC, Stadelmann D, Stoica A, Stoyanov D, Stoyanova K, Tewari S, Todosijević B, Torgler B, Tsakiris M, Tung HH, Umbreș RG, Vanags E, Vlasceanu M, Vonasch AJ, Zhang Y, Abad M, Adler E, Mdarhri HA, Antazo B, Ay FC, Ba MEH, Barbosa S, Bastian B, Berg A, Białek M, Bilancini E, Bogatyreva N, Boncinelli L, Booth JE, Borau S, Buchel O, de Carvalho CF, Celadin T, Cerami C, Chalise HN, Cheng X, Cian L, Cockcroft K, Conway J, Córdoba-Delgado MA, Crespi C, Crouzevialle M, Cutler J, Cypryańska M, Dabrowska J, Davis VH, Minda JP, Dayley PN, Delouvée S, Denkovski O, Dezecache G, Dhaliwal NA, Diato A, Paolo RD, Dulleck U, Ekmanis J, Etienne TW, Farhana HH, Farkhari F, Fidanovski K, Flew T, Fraser S, Frempong RB, Fugelsang J, Gale J, García-Navarro EB, Garladinne P, Gray K, Griffin SM, Gronfeldt B, Gruber J, Halperin E, Herzon V, Hruška M, Hudecek MFC, Isler O, Jangard S, Jørgensen F, Keudel O, Koppel L, Koverola M, Kunnari A, Leota J, Lermer E, Li C, Longoni C, McCashin D, Mikloušić I, Molina-Paredes J, Monroy-Fonseca C, Morales-Marente E, Moreau D, Muda R, Myer A, Nash K, Nitschke JP, Nurse MS, de Mello VO, Palacios-Galvez MS, Palomäki J, Pan Y, Papp Z, Pärnamets P, Paruzel-Czachura M, Perander S, Pitman M, Raza A, Rêgo GG, Robertson C, Rodríguez-Pascual I, Saikkonen T, Salvador-Ginez O, Sampaio WM, Santi GC, Schultner D, Schutte E, Scott A, Skali A, Stefaniak A, Sternisko A, Strickland B, Strickland B, Thomas JP, Tinghög G, Traast IJ, Tucciarelli R, Tyrala M, Ungson ND, Uysal MS, Van Rooy D, Västfjäll D, Vieira JB, von Sikorski C, Walker AC, Watermeyer J, Willardt R, Wohl MJA, Wójcik AD, Wu K, Yamada Y, Yilmaz O, Yogeeswaran K, Ziemer C-T, Zwaan RA, Boggio PS, Whillans A, Van Lange PAM, Prasad R, Onderco M, O'Madagain C, Nesh-Nash T, Laguna OM, Kutiyski Y, Kubin E, Gümren M, Fenwick A, Ertan AS, Bernstein MJ, Amara H, Van Bavel JJ Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning. PNAS Nexus.en
dc.identifier.doihttp://doi.org/10.1093/pnasnexus/pgac093
dc.identifier.issn2752-6542
dc.identifier.urihttps://hdl.handle.net/10092/104936
dc.languageen
dc.language.isoenen
dc.publisherOxford University Press (OUP)en
dc.rightsAll rights reserved unless otherwise stateden
dc.rights.urihttp://hdl.handle.net/10092/17651en
dc.subjectCOVID-19en
dc.subjectsocial distancingen
dc.subjecthygieneen
dc.subjectpolicy supporten
dc.subjectpsychologyen
dc.subjectmachine learningen
dc.subjectpublic health measuresen
dc.subject.anzsrcFields of Research::52 - Psychologyen
dc.subject.anzsrcFields of Research::46 - Information and computing sciences::4611 - Machine learningen
dc.subject.anzsrcFields of Research::42 - Health sciencesen
dc.titlePredicting attitudinal and behavioral responses to COVID-19 pandemic using machine learningen
dc.typeJournal Articleen
uc.collegeFaculty of Science
uc.departmentSchool of Psychology, Speech and Hearing
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