Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning.
COVID-19
hygiene
policy support
public health measures
social distancing
Journal
PNAS nexus
ISSN: 2752-6542
Titre abrégé: PNAS Nexus
Pays: England
ID NLM: 9918367777906676
Informations de publication
Date de publication:
Jul 2022
Jul 2022
Historique:
received:
27
11
2021
accepted:
21
06
2022
entrez:
22
8
2022
pubmed:
23
8
2022
medline:
23
8
2022
Statut:
epublish
Résumé
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 (
Identifiants
pubmed: 35990802
doi: 10.1093/pnasnexus/pgac093
pii: pgac093
pmc: PMC9381137
doi:
Types de publication
Journal Article
Langues
eng
Pagination
pgac093Subventions
Organisme : Austrian Science Fund FWF
ID : I 3381
Pays : Austria
Organisme : Medical Research Council
ID : MR/P014097/2
Pays : United Kingdom
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of National Academy of Sciences.
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