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AI-Powered Virtual Reality Simulation for Clinical Handover Training: A Development Framework.

Maggie Mee Kie Chan1, Daphne Sze Ki Cheung, Ken Hok Man Ho

  • 1Author Affiliations: School of Nursing, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China (Dr Chan); Centre for Quality and Patient Safety Research/Alfred Health Partnership, Institute for Health Transformation, Deakin University, Melbourne, VIC, Australia (Dr Cheung); Senior Research Fellow, School of Nursing and Midwifery, Faculty of Health, Deakin University, Melbourne, VIC, Australia (Dr Cheung); Associate Professor, School of Nursing & Midwifery, La Trobe University, Melbourne, VIC, Australia (Dr Ho); Teaching and Learning Innovation Centre, The University of Hong Kong, Hong Kong, China (Dr Hung, Mr Tai); and School of Nursing, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China (Mr Wan, Mr Wong, Mr Cheuk, Mr Lai, Mr Chan).

Nurse Educator
|October 27, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an AI-VR framework for nursing handover training, enhancing realism and feedback. The innovative approach improves clinical education through immersive virtual reality and adaptive artificial intelligence, boosting patient safety.

Keywords:
communication skillseducational technologyinterprofessional educationpatient safetyskills training

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Area of Science:

  • Nursing Education
  • Medical Simulation
  • Health Informatics

Background:

  • Clinical handover is vital for patient safety in nursing.
  • Traditional training methods lack immersion, realism, and personalized feedback.
  • Nurse educators face challenges integrating generative artificial intelligence (GenAI) and virtual reality (VR) into handover education.

Purpose of the Study:

  • To present a developmental framework for integrating GenAI and VR into nursing handover education.
  • To provide practical guidance for nurse educators implementing this technology.

Main Methods:

  • Developed a 3-layer architecture: system (ChatGPT for adaptive responses), interaction (gamification), and presentation (VR with AI avatars).
  • AI avatars were modeled after instructors, utilizing the Identification, Situation, Background, Assessment, Recommendation (ISBAR) framework.
  • Pilot tested with undergraduate nursing students.

Main Results:

  • Pilot testing demonstrated enhanced authenticity via real-person avatars and real-time ISBAR feedback.
  • Students reported improved training realism and engagement.
  • Identified nonverbal synchronization as an area for future improvement.

Conclusions:

  • The developmental framework and implementation checklist offer systematic guidance for deploying AI-VR in handover training.
  • This approach positions nursing education at the forefront of pedagogical innovation.
  • Enhances clinical handover competency and patient safety through advanced simulation.