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Nursing students' experiences of interviewing artificial intelligence-simulated patients: A phenomenological study.

Jul 2026 · Nurse Education Today · Vol 166, pp. 107276 · 0 citations · 28 references
Medicine

TL;DR

This study shows that students experience enhanced clinical preparedness, strengthened professional identity, and improved communication skills through the use of AI-simulated patients in nursing education, and suggests that AI-based simulations can complement traditional teaching methods while boosting students' learning motivation.

Abstract

Background

The development of clinical skills is essential in nursing education, yet limited access to real practice areas restricts students' experience. AI-simulated patients offer a promising solution by providing safe interview opportunities, enhancing communication skills, and supporting professional role development.

Aim

To determine the experiences of nursing students who interviewed artificial intelligence-simulated patients.

Methods

This descriptive phenomenological study involved one-to-one interviews with 15 first-year nursing students who have experience of interviewing artificial intelligence-simulated patients. Data were analyzed using Giorgi's Phenomenological Method Analysis and reported according to the COREQ checklist.

Results

Five main themes emerged: Experiencing a Sense of Clinical Reality with AI-Based Education, Developing Reflective Communication Skills, Gaining Confidence for Future Clinical Practice, Emerging Professional Identity, and Increase in Learning Motivation. Students reported that their interviews with AI-simulated patients contributed positively to preparing them for real clinical settings, strengthening their communication skills, and enhancing their perception of professional identity.

Conclusion

This study shows that students experience enhanced clinical preparedness, strengthened professional identity, and improved communication skills through the use of AI-simulated patients in nursing education. The findings suggest that AI-based simulations can complement traditional teaching methods while boosting students' learning motivation.

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