Nursing students' intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology
DC Field | Value | Language |
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dc.contributor.author | Kwak, Yeunhee | - |
dc.contributor.author | Seo, Y.H. | - |
dc.contributor.author | Ahn, J.-W. | - |
dc.date.accessioned | 2022-11-18T08:40:10Z | - |
dc.date.available | 2022-11-18T08:40:10Z | - |
dc.date.issued | 2022-12 | - |
dc.identifier.issn | 0260-6917 | - |
dc.identifier.issn | 1532-2793 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/59096 | - |
dc.description.abstract | Background: 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.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Churchill Livingstone | - |
dc.title | Nursing students' intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.nedt.2022.105541 | - |
dc.identifier.bibliographicCitation | Nurse Education Today, v.119 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000864471100010 | - |
dc.identifier.scopusid | 2-s2.0-85139181869 | - |
dc.citation.title | Nurse Education Today | - |
dc.citation.volume | 119 | - |
dc.type.docType | Article | - |
dc.publisher.location | 스코트랜드 | - |
dc.subject.keywordAuthor | Anxiety | - |
dc.subject.keywordAuthor | Artificial intelligence | - |
dc.subject.keywordAuthor | Attitude | - |
dc.subject.keywordAuthor | Health technology | - |
dc.subject.keywordAuthor | Healthcare | - |
dc.subject.keywordAuthor | Nursing | - |
dc.subject.keywordAuthor | Self-efficacy | - |
dc.subject.keywordAuthor | UTAUT model | - |
dc.subject.keywordPlus | ARTIFICIAL-INTELLIGENCE | - |
dc.subject.keywordPlus | INFORMATION-TECHNOLOGY | - |
dc.subject.keywordPlus | PERCEIVED EASE | - |
dc.subject.keywordPlus | NURSES | - |
dc.relation.journalResearchArea | Education & Educational Research | - |
dc.relation.journalResearchArea | Nursing | - |
dc.relation.journalWebOfScienceCategory | Education, Scientific Disciplines | - |
dc.relation.journalWebOfScienceCategory | Nursing | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
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