COVID-19 Vaccine Acceptance in the US and UK in the Early Phase of the Pandemic: AI-Generated Vaccines Hesitancy for Minors, and the Role of Governments

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dc.contributor.author차지영ko
dc.contributor.author가브리엘 리마ko
dc.contributor.author차미영ko
dc.contributor.author황혜영ko
dc.date.accessioned2021-11-08T06:41:19Z-
dc.date.available2021-11-08T06:41:19Z-
dc.date.created2021-11-08-
dc.date.created2021-11-08-
dc.date.created2021-11-08-
dc.date.created2021-11-08-
dc.date.issued2021-06-
dc.identifier.citationJournal of The Korean Data Analysis Society, v.23, no.3, pp.1043 - 1062-
dc.identifier.issn1229-2354-
dc.identifier.urihttp://hdl.handle.net/10203/288918-
dc.description.abstractThis study presents survey results of the public’s willingness to get vaccinated against COVID-19 during an early phase of the pandemic and examines factors that could influence vaccine acceptance based on a between-subjects design. A representative quota sample of 572 adults in the US and UK participated in an online survey. First, the participants’ medical use tendencies and initial vaccine acceptance were assessed; then, short vignettes were provided to evaluate their changes in attitude towards COVID-19 vaccines. For data analysis, ANOVA and post hoc pairwise comparisons were used. The participants were more reluctant to vaccinate their children than themselves and the elderly. The use of artificial intelligence (AI) in vaccine development did not influence vaccine acceptance. Vignettes that explicitly stated the high effectiveness of vaccines led to an increase in vaccine acceptance. Our study suggests public policies emphasizing the vaccine effectiveness against the virus could lead to higher vaccination rates. We also discuss the public’s expectations of governments concerning vaccine safety and present a series of implications based on our findings.-
dc.languageEnglish-
dc.publisher한국자료분석학회-
dc.titleCOVID-19 Vaccine Acceptance in the US and UK in the Early Phase of the Pandemic: AI-Generated Vaccines Hesitancy for Minors, and the Role of Governments-
dc.typeArticle-
dc.type.rimsART-
dc.citation.volume23-
dc.citation.issue3-
dc.citation.beginningpage1043-
dc.citation.endingpage1062-
dc.citation.publicationnameJournal of The Korean Data Analysis Society-
dc.identifier.doi10.37727/jkdas.2021.23.3.1043-
dc.identifier.kciidART002730103-
dc.contributor.localauthor차미영-
dc.contributor.nonIdAuthor차지영-
dc.contributor.nonIdAuthor가브리엘 리마-
dc.contributor.nonIdAuthor황혜영-
dc.description.isOpenAccessN-
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