Nursing Students' Perceptions and Attitudes on the Application of Artificial Intelligence in Nursing Education: A Mixed-Methods Systematic Review.
Journal:
Journal of advanced nursing
Published Date:
Nov 17, 2025
Abstract
BACKGROUND: The utilisation of artificial intelligence in the context of nursing education has become increasingly extensive. However, various studies show differing perspectives and attitudes among nursing students, and the findings have not been systematically synthesised. AIM: To systematically review the perceptions and attitudes of nursing students on the application of artificial intelligence in nursing education. DESIGN: Mixed-methods systematic review. METHOD: A comprehensive literature search was conducted across 10 databases, including PubMed, Cochrane, Embase, Web of Science, CINAHL, Scopus, China Science and Technology Journal Database, SinoMed, China National Knowledge Internet, and WanFang database, the inclusive years of articles searched were from 1969 to 2025. Two researchers independently screened the literature and extracted the data. The mixed methods assessment tool was used to evaluate the risk of bias in the included literature. The relevant data were extracted and synthesised according to the Joanna Briggs Institute's convergence synthesis method, ensuring the comprehensive integration of qualitative and quantitative results. These results were then integrated into the Technology Acceptance Model. RESULTS: A total of 28 articles were included, including 13 qualitative studies, 13 quantitative studies, and 2 mixed-method studies. According to the Technology Acceptance Model, the perceptions and attitudes of nursing students on the nursing education's adoption of artificial intelligence were integrated into 10 categories of three comprehensive themes: (i) Nursing students' perceptions and attitudes of the ease of use of artificial intelligence in nursing education, including 3 categories; (ii) nursing students' perceptions and attitudes on the usefulness of artificial intelligence in nursing education, including 4 categories; (iii) nursing students' behavioural intention, including 3 categories. CONCLUSIONS: Overall, our study demonstrated that nursing students had an active willingness to utilise artificial intelligence. However, they acknowledged that certain issues persist regarding the ease and practicality of artificial intelligence in nursing education. PATIENT OR PUBLIC CONTRIBUTION: No patients or members of the public were directly involved in this systematic review, as the study synthesised existing literature.
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