ArticleJournal of advanced nursing2026
Understanding Nurses' Intention to Use Artificial Intelligence Technologies in Their Clinical Practice: A Survey-Based Configurational Analysis.
Article in Journal of advanced nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Nurse Practitioner Students' Perceptions of an Artificial Intelligence Differential Diagnosis Tool: A Pilot Study.Journal of clinical nursing · 2026Article
- The Association Between Perceived Ability to Use Artificial Intelligence, Self-Reported Nursing Productivity, and Self-Reported Practice Readiness Among Nurses in Saudi Arabia: A Multicentre Cross-Sectional Study.Healthcare (Basel, Switzerland) · 2026Article
- Understanding Nurses' Intention to Use Artificial Intelligence Technologies in Their Clinical Practice: A Survey-Based Configurational Analysis.Journal of advanced nursing · 2026Article
- The impact of innovativeness on Chinese nurses' attitudes toward artificial intelligence: a cross-sectional study based on the technology acceptance model.BMC nursing · 2026Article
- Generative artificial intelligence literacy profiles and workforce readiness among pre-professional nursing students: a latent profile analysis.Frontiers in public health · 2026Article
- The Mediating and Moderating Roles of Innovation Climate in the Relationship Between Nurses' Attitudes Toward Artificial Intelligence, Creative Self-Efficacy, and Clinical Competence.Journal of nursing management · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
aimsThe study focused on nurses' familiarity with, beliefs about, and attitudes towards artificial intelligence, aiming to identify configurations of necessary and sufficient conditions associated with strong intentions to use artificial intelligence-based health technologies in their clinical practice.
designCross-sectional survey conducted online from mid-October 2023 through early February 2024.
methodsThe fuzzy set qualitative comparative analysis method was employed to analyse the survey data. DATA SOURCE: 307 members of the professional order of nurses in Québec province, Canada.
resultsFindings from the qualitative comparative analysis show that strong intentions to use artificial intelligence are only observed when nurses perceive artificial intelligence to have a high impactfulness on their future clinical practice (necessary condition). Moreover, we observe three configurations of sufficient conditions, that is, three combinations (artificial intelligence profiles) of familiarity with, belief about, trust in, and perceived impactfulness of artificial intelligence.
conclusionCurrent curriculum efforts have centred on defining artificial intelligence competencies, yet competency alone does not guarantee a willingness to adopt artificial intelligence tools. Our findings indicate that a positive attitude towards artificial intelligence's potential impact is crucial, with various profiles supporting intentions to adopt artificial intelligence. IMPLICATIONS FOR THE PROFESSION: These findings suggest that nurses' preparation should go beyond developing artificial intelligence competencies and that nursing educators and trainers need to account for the different profiles associated with strong intentions to use artificial intelligence technologies. Training programmes and nursing curricula should prioritise shaping nurses' beliefs and attitudes about artificial intelligence rather than focusing solely on technical skills. IMPACT: We contribute to nursing research by showing that a positive attitude towards artificial intelligence's impactfulness on nurses' future clinical practice is a necessary condition for having high intentions to use artificial intelligence technologies. REPORTING
methodRelevant guidelines have been adhered to by employing recommended qualitative comparative analysis reporting methods. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.