Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Nursing students' intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology

Full metadata record
DC Field Value Language
dc.contributor.authorKwak, Yeunhee-
dc.contributor.authorSeo, Y.H.-
dc.contributor.authorAhn, J.-W.-
dc.date.accessioned2022-11-18T08:40:10Z-
dc.date.available2022-11-18T08:40:10Z-
dc.date.issued2022-12-
dc.identifier.issn0260-6917-
dc.identifier.issn1532-2793-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/59096-
dc.description.abstractBackground: Marked advances in artificial intelligence (AI)-based technologies throughout industries, including healthcare, necessitate a broader understanding their use. Particularly, intent to use AI-based healthcare technologies and its predictors among nursing students, who are prospective healthcare professionals, is required to promote the utilization of AI. Objective: This study conducted a path analysis to predict nursing students' intent to use AI-based healthcare technologies based on the unified theory of acceptance and use of technology. Design: A cross-sectional survey was performed. Participants: The participants were 210 nursing students from two nursing schools in Korea. Methods: This study established hypothetical paths for the influence of performance expectancy, effort expectancy, social influence, facilitating conditions, self-efficacy, and anxiety on intent to use AI-based technologies. Mediation of positive and negative attitudes and facilitating conditions' direct effects on intent to use were examined. Results: Positive attitude toward AI (β = 0.485, p = .009) and facilitating conditions (β = 0.117, p = .045) predicted intent to use, whereas the path from negative attitude to intent to use was not significant. Performance expectancy, self-efficacy, and effort expectancy predicted positive attitude. Performance expectancy and self-efficacy had a negative effect on the path to negative attitude, whereas anxiety had a positive effect. Facilitating conditions did not significantly predict positive or negative attitude and only directly predicted intent to use. Social influence did not have a significant effect on intent to use. Conclusions: Intervention programs and other measures should be developed to provide education and information to boost performance expectancy, effort expectancy, facilitating conditions, and self-efficacy regarding the use of AI to lower anxiety and foster positive attitude toward AI-based health technologies. © 2022 Elsevier Ltd-
dc.language영어-
dc.language.isoENG-
dc.publisherChurchill Livingstone-
dc.titleNursing students' intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology-
dc.typeArticle-
dc.identifier.doi10.1016/j.nedt.2022.105541-
dc.identifier.bibliographicCitationNurse Education Today, v.119-
dc.description.isOpenAccessN-
dc.identifier.wosid000864471100010-
dc.identifier.scopusid2-s2.0-85139181869-
dc.citation.titleNurse Education Today-
dc.citation.volume119-
dc.type.docTypeArticle-
dc.publisher.location스코트랜드-
dc.subject.keywordAuthorAnxiety-
dc.subject.keywordAuthorArtificial intelligence-
dc.subject.keywordAuthorAttitude-
dc.subject.keywordAuthorHealth technology-
dc.subject.keywordAuthorHealthcare-
dc.subject.keywordAuthorNursing-
dc.subject.keywordAuthorSelf-efficacy-
dc.subject.keywordAuthorUTAUT model-
dc.subject.keywordPlusARTIFICIAL-INTELLIGENCE-
dc.subject.keywordPlusINFORMATION-TECHNOLOGY-
dc.subject.keywordPlusPERCEIVED EASE-
dc.subject.keywordPlusNURSES-
dc.relation.journalResearchAreaEducation & Educational Research-
dc.relation.journalResearchAreaNursing-
dc.relation.journalWebOfScienceCategoryEducation, Scientific Disciplines-
dc.relation.journalWebOfScienceCategoryNursing-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
Files in This Item
There are no files associated with this item.
Appears in
Collections
Red Cross College of Nursing > Department of Nursing > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kwak, Yeunhee photo

Kwak, Yeunhee
적십자간호대학 (간호학과)
Read more

Altmetrics

Total Views & Downloads

BROWSE