Beyond efficiency: A meta-synthesis of nursing students' experiences with generative AI in developing clinical judgment and ethical reasoning: A qualitative systematic review.
Abstract
Background
Generative AI (GenAI) is rapidly reshaping nursing education, yet its impact on students' clinical judgment and ethical reasoning remains multifaceted and complex.
Objectives
To synthesize qualitative evidence exploring nursing students' experiences with GenAI in developing core clinical and ethical competencies. REVIEW
Methods
A systematic meta-synthesis was conducted following ENTREQ guidelines. Five major databases (Cochrane, CINAHL, PubMed, Web of Science, and Embase) were searched up to February 2026. Data were synthesized using Thomas and Harden's thematic synthesis approach, and confidence in the findings was assessed with GRADE-CERQual.
Results
Eleven studies were included, yielding four meta-themes: (1) personalized support versus the risk of dependency, (2) developing clinical judgment through simulation and verification, (3) ethical reasoning and the human element, and (4) the need for institutional guidance and literacy.
Conclusions
Nursing students use GenAI for support, simulation, and feedback, but they also report risks of over-reliance, weak verification, and unclear ethical responsibility. Nursing programmes should teach students how to question AI outputs, protect patient data, and retain human clinical judgment when using GenAI. PROSPERO ID The review was registered on PROSPERO (registration number: CRD420261291252).