Integration of Artificial Intelligence Into Extended Reality Debriefing in Healthcare Simulation: A Narrative Review

Area of Science:

• Healthcare Simulation
• Artificial Intelligence
• Extended Reality

Background:

• Extended reality (XR) is increasingly used in healthcare simulation for training.
• Debriefing in XR simulations presents unique challenges due to immersive and data-rich environments.

Purpose of the Study:

• To review how artificial intelligence (AI) can augment debriefing within XR/virtual reality (VR) healthcare simulations.
• To identify AI functions and assess the current evidence base for AI-enhanced debriefing.

Main Methods:

• Focused narrative review of peer-reviewed literature from 2015-2025.
• Searches in PubMed/MEDLINE and Google Scholar using terms for XR, simulation, and AI-enabled debriefing.
• Inclusion criteria focused on AI applied to debriefing processes or feedback within XR/VR healthcare simulations.

Main Results:

• Four recurring AI functions identified: automated performance analytics, natural language processing for discourse analysis, conversational agents/LLMs for reflective dialogue, and multimodal fusion for adaptive feedback.
• The evidence base is primarily composed of feasibility studies, pilots, and prototypes.
• Limited controlled comparisons, psychometric validation, or evidence of sustained behavior change were found.

Conclusions:

• AI offers significant potential to enhance debriefing in XR healthcare simulations.
• A hybrid model, where AI prepares data and human facilitators guide reflection, is a pragmatic near-term approach.
• Future research should focus on validation, bias/privacy safeguards, faculty development, and longitudinal outcomes.