Artificial intelligence anxiety among nursing and midwifery students: the role of resistance to change - a cross-sectional study

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dc.contributor.authorGuner, Ozlem
dc.contributor.authorAydin, Melike Sena
dc.date.accessioned2026-04-25T14:20:17Z
dc.date.available2026-04-25T14:20:17Z
dc.date.issued2026
dc.departmentSinop Üniversitesi
dc.description.abstractObjective This study aimed to determine the levels of resistance to change and artificial intelligence (AI) anxiety among nursing and midwifery students and to examine the association between these variables. Methods This cross-sectional, descriptive-correlational study was conducted with 413 nursing and midwifery students enrolled at a state university during the 2024-2025 academic year. Data were collected using a Personal Information Form, the Resistance to Change Scale, and the Artificial Intelligence Anxiety Scale. Descriptive statistics, independent samples t-tests, one-way ANOVA, Pearson correlation analysis, and multiple linear regression analysis were performed. Results Students demonstrated moderate levels of resistance to change (Mean = 39.15 +/- 7.99) and moderate levels of AI anxiety (Mean = 44.62 +/- 11.04). Based on the recommended cut-off score of 48, 45.8% of participants (n = 189) were classified as experiencing high AI anxiety, while 54.2% (n = 224) had low-to-moderate levels of AI anxiety. Among AI anxiety subdimensions, the highest mean score was observed in sociotechnical blindness. Resistance to change was positively associated with AI anxiety (r = 0.296, p < 0.01). In the regression model, resistance to change showed the strongest association with AI anxiety (B = 0.47, p < 0.001), while gender and academic department were also significantly associated. The final model explained 14.1% of the variance in AI anxiety (R & sup2; = 0.141). Conclusion Higher levels of resistance to change are associated with increased AI anxiety among nursing and midwifery students. These findings suggest that resistance to change represents a modifiable psychological factor that may be addressed through educational interventions, alongside technical AI skill development, within digital transformation initiatives in health professions education.
dc.description.sponsorshipThe Scientific and Technological Research Council of Trkiye (TBIdot;TAK) under the 2209-A Research Projects Support Program for Undergraduate Students
dc.description.sponsorshipThis study was supported by the TUB & Idot;TAK 2209-A Undergraduate Research Project Support Program.
dc.identifier.doi10.1186/s12909-026-08754-2
dc.identifier.issn1472-6920
dc.identifier.issue1
dc.identifier.orcid0009-0004-7293-1346
dc.identifier.pmid41749216
dc.identifier.scopus2-s2.0-105034915826
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1186/s12909-026-08754-2
dc.identifier.urihttps://hdl.handle.net/11486/8489
dc.identifier.volume26
dc.identifier.wosWOS:001732106200005
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherBmc
dc.relation.ispartofBmc Medical Education
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20260420
dc.subjectArtificial intelligence anxiety
dc.subjectResistance to change
dc.subjectNursing and midwifery students
dc.subjectHealth education
dc.subjectDigital transformation
dc.titleArtificial intelligence anxiety among nursing and midwifery students: the role of resistance to change - a cross-sectional study
dc.typeArticle

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