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Generative AI in simulation debriefings: an exploratory study using the Team-FIRST framework and qualitative feedback
David W Tscholl1, Max Ebensperger2, Arend RahrischRahrisch1
1Institute for Anesthesiology and Perioperative Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Advances in Simulation (London, England)
|January 30, 2026
Summary
Generative artificial intelligence (AI) can aid medical simulation debriefings by analyzing team communication and providing feedback. However, human oversight is crucial due to AI
Area of Science:
- Medical Education Technology
- Artificial Intelligence in Healthcare
- Simulation-Based Training
Background:
- Simulation-based education requires effective debriefings for optimal learning.
- Facilitators face challenges in observing team interactions due to cognitive load and bias.
- Generative AI offers potential to analyze communication and support debriefing in medical simulations.
Purpose of the Study:
- To explore the utility of generative AI tools in observing teamwork during medical simulations.
- To assess the impact of AI-generated reports on simulation debriefing processes.
- To understand participants' and facilitators' experiences with AI in simulation.
Main Methods:
- Qualitative exploratory study involving thematic analysis of AI-generated reports and interviews.
- Forty-one participants in immersive medical simulations at University Hospital Zurich.
- AI-assisted transcription and analysis of verbal interactions using large language models (Isaac, ChatGPT-4o) based on the Team-FIRST framework.
Main Results:
- AI reports provided detailed transcripts and quotes, aiding structured feedback and capturing missed observations.
- Limitations included categorization inaccuracies, speaker misattribution, and lack of nonverbal context.
- Learners were optimistic about AI's efficiency and objectivity but concerned about transparency and errors; human oversight was deemed essential.
Conclusions:
- Generative AI can enhance simulation debriefings by structuring communication data and identifying teamwork patterns.
- Current AI limitations necessitate multimodal approaches and expert facilitation.
- AI should serve as a supportive tool, not a replacement, in simulation-based education.
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