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Enhancing Empathy in Nursing Students Through a Multimodal Artificial Intelligence-Supported Simulation: A
1Author Affiliations: College of Nursing, Keimyung University, Daegu, South Korea.
Background:
Empathic communication is a core competency in nursing practice, yet providing nursing students with realistic opportunities to develop this competency remains challenging. Recent advances in artificial intelligence (AI) have enabled the integration of behavioral and physiological data into simulation-based education.
Objective:
To evaluate the effectiveness of a multimodal AI-supported simulation in improving empathy, communication self-efficacy, and learning engagement among undergraduate nursing students.
Methods:
A quasi-experimental pretest-posttest study was conducted with 134 undergraduate nursing students (68 experimental and 66 control). The experimental group received multimodal AI-supported simulation integrating conversational AI, facial emotion recognition, speech analysis, and physiological monitoring, whereas the control group received conventional role-play-based simulation with faculty-led debriefing.
Results:
After adjustment for baseline scores, the experimental group showed significantly greater improvements in empathy, communication self-efficacy, and emotional, behavioral, and cognitive engagement than the control group (all P < .001). Heart rate variability and galvanic skin response showed significant group-by-time differences, indicating differential physiological responses during the simulation. Qualitative findings indicated enhanced empathy awareness, communication confidence, and reflective learning.
Conclusions:
Multimodal AI-supported simulation improved empathy, communication self-efficacy, and learning engagement by providing integrated behavioral and physiological feedback. This approach may serve as a complementary educational strategy to support empathic communication training in undergraduate nursing education.
