Nursing Students’ Perceptions of a GPT-Based Virtual Patient Simulator for Clinical Skills Practice: A Descriptive Cross-Sectional Study

Background/Objectives: Generative artificial intelligence is gaining relevance in higher education, offering new possibilities for complementing practical training in the Health Sciences. This study aimed to assess nursing students’ perceptions of a GPT-based virtual patient simulator used during practical clinical skills sessions. Methods: A descriptive cross-sectional study was conducted with 79 undergraduate nursing students at the University of Extremadura, Spain. During a practical activity on diabetic foot assessment and care, students interacted with a GPT-based virtual patient that facilitated information-gathering, the request and interpretation of tests, clinical decision-making, and the formulation of nursing diagnoses and interventions. After the activity, students completed a questionnaire assessing their experiences and perceptions of the tool. Results: Overall, students reported favourable perceptions of the simulator. Among the 79 participants, 64.6% agreed and 29.1% strongly agreed that GPT facilitated the integration of theory and clinical practice. Regarding recommending GPT-based tools to support learning in nursing, 63.3% agreed and 32.9% strongly agreed. Concerning the perceived contribution of GPT to clinical reasoning, 51.9% agreed and 25.3% strongly agreed. Students also reported positive experiences regarding the clarity of the interaction, the usefulness of the tool for understanding clinical cases, and its potential to support autonomous learning. Conclusions: The GPT-based virtual patient simulator was favourably perceived by nursing students as a complementary resource for clinical skills practice.