Publication:
Ethical decision-making and artificial intelligence in nursing education: an integrative review

dc.contributor.coauthorGul, Asiye
dc.contributor.departmentSchool of Nursing
dc.contributor.kuauthorFaculty Member, Şengül, Tuba
dc.contributor.kuauthorTeaching Faculty, Sarıköse, Seda
dc.contributor.schoolcollegeinstituteSCHOOL OF NURSING
dc.date.accessioned2025-09-10T04:55:30Z
dc.date.available2025-09-09
dc.date.issued2025
dc.description.abstractThe integration of artificial intelligence technologies is transforming healthcare and nursing education, offering significant benefits for patient care and professional development. However, as their use grows, it is crucial to address the ethical implications to ensure that fundamental principles like justice and integrity are maintained in both clinical and educational settings. The aim of this integrative review is to explore the ethical challenges, risks, and future perspectives of integrating artificial intelligence into nursing education. It examines how these tools influence ethical decision-making processes, identifies critical barriers, and proposes strategies for ethical implementation. Following an integrative review methodology, 184 articles were identified, with 124 remaining after duplicate removal. Fifteen peer-reviewed studies analyzed. The methodological quality of the included studies was assessed using appropriate Joanna Briggs Institute Critical Appraisal Checklists based on study design. Searches were conducted in the PubMed, Cochrane Library, MEDLINE (Ovid), Scopus, Web of Science, CINAHL, and ScienceDirect databases from 2014 to September 2024. Data was analysed using constant comparative analysis. The review is registered in the PROSPERO database (CRD42024609440). Guided by Rest's Four-Component Model of Moral Behavior, the synthesis was organized under four components. Moral Sensitivity included themes such as ethical and psychosocial effects, data privacy, equity in access, and cultural sensitivity. Moral Judgment covered ethical reasoning skills, AI accuracy, bias, and academic integrity. Moral Motivation addressed over-reliance on AI and the need for ethical frameworks. Moral Character highlighted educator roles and research priorities for ethical AI use. Artificial intelligence offers transformative opportunities for nursing education, but also presents significant ethical challenges. To ensure its responsible integration, nursing curricula must adopt clear ethical frameworks, equip educators with the skills to guide students and address disparities in access.
dc.description.fulltextYes
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.openaccessGold OA
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuN/A
dc.description.versionPublished Version
dc.identifier.doi10.1177/09697330251366600
dc.identifier.eissn1477-0989
dc.identifier.embargoNo
dc.identifier.filenameinventorynoIR06359
dc.identifier.issn0969-7330
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-105014453569
dc.identifier.urihttps://doi.org/10.1177/09697330251366600
dc.identifier.urihttps://hdl.handle.net/20.500.14288/30081
dc.identifier.wos001559182100001
dc.keywordsArtificial intelligence
dc.keywordsChatGPT
dc.keywordsEthical decision-making
dc.keywordsIntegrative review
dc.keywordsNursing education
dc.language.isoeng
dc.publisherSage Publications Ltd
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofNursing Ethics
dc.relation.openaccessYes
dc.rightsCC BY-NC (Attribution-NonCommercial)
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectEthics
dc.subjectNursing
dc.titleEthical decision-making and artificial intelligence in nursing education: an integrative review
dc.typeReview
dspace.entity.typePublication
relation.isOrgUnitOfPublicationcd883b5a-a59a-463b-9038-a0962a6b0749
relation.isOrgUnitOfPublication.latestForDiscoverycd883b5a-a59a-463b-9038-a0962a6b0749
relation.isParentOrgUnitOfPublication9781feb6-cb81-4c13-aeb3-97dae2048412
relation.isParentOrgUnitOfPublication.latestForDiscovery9781feb6-cb81-4c13-aeb3-97dae2048412

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