Generative artificial intelligence in healthcare simulation-based education: A scoping review

<h2>Abstract</h2><h3>Aims</h3> This review aimed to explore the current state of generative artificial intelligence (GenAI) use in simulation-based healthcare education through a comprehensive examination of GenAI types, applications and reported outcomes. <h3>Methods</h3> A scoping review was conducted utilizing the Joanna Briggs Institute's methodological guidance. Six databases were searched from their inception until February 2025. <h3>Results</h3> We included 28 articles that were published between 2023 and 2025. Articles were mainly in the fields of medicine (<i>n</i> = 14) and nursing (<i>n</i> = 10). OpenAI's GPT models were most frequently used to portray simulated characters and deliver automated feedback. GenAI-enhanced simulation was generally perceived as accurate, realistic and feasible, with some evidence supporting its use as a supplement to conventional simulation and to enhance learning outcomes. Perspectives, ethical considerations and recommendations for GenAI-enhanced simulation were also highlighted. <h3>Conclusion</h3> GenAI-enhanced simulation is gaining popularity and is likely to evolve alongside human-facilitated simulation. Future developments should focus on building AI expertise among simulation educators and harnessing the synergy between human intelligence and GenAI. Further rigorous research is needed to establish best practices.

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Publication Details

Journal
Clinical Simulation in Nursing
Published
2025-10-04
DOI
https://doi.org/10.1016/j.ecns.2025.101819
Citations
4
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
2.62
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article

Generative artificial intelligence in healthcare simulation-based education: A scoping review

Wei Ling Chua, Tracy Levett‐Jones, Joko Gunawan, Eng Tat Khoo et al.
4 citations
Clinical Simulation in Nursing
Artificial Intelligence in Healthcare and Education
2.62
article

Generative artificial intelligence in healthcare simulation-based education: A scoping review

Wei Ling Chua, Tracy Levett‐Jones, Joko Gunawan, Eng Tat Khoo, Nicholas Wee Siong Neo, Sok Ying Liaw
article en
4 citations

Abstract

<h2>Abstract</h2><h3>Aims</h3> This review aimed to explore the current state of generative artificial intelligence (GenAI) use in simulation-based healthcare education through a comprehensive examination of GenAI types, applications and reported outcomes. <h3>Methods</h3> A scoping review was conducted utilizing the Joanna Briggs Institute's methodological guidance. Six databases were searched from their inception until February 2025. <h3>Results</h3> We included 28 articles that were published between 2023 and 2025. Articles were mainly in the fields of medicine (<i>n</i> = 14) and nursing (<i>n</i> = 10). OpenAI's GPT models were most frequently used to portray simulated characters and deliver automated feedback. GenAI-enhanced simulation was generally perceived as accurate, realistic and feasible, with some evidence supporting its use as a supplement to conventional simulation and to enhance learning outcomes. Perspectives, ethical considerations and recommendations for GenAI-enhanced simulation were also highlighted. <h3>Conclusion</h3> GenAI-enhanced simulation is gaining popularity and is likely to evolve alongside human-facilitated simulation. Future developments should focus on building AI expertise among simulation educators and harnessing the synergy between human intelligence and GenAI. Further rigorous research is needed to establish best practices.

Clinical Simulation in NursingVol. 108
University of Technology Sydney (AU), National University of Singapore (SG)
Openalex Percentile: Top 8%
Artificial Intelligence in Healthcare and Education
2.62
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Generative artificial intelligence in healthcare simulation-based education: A scoping review — Wei Ling Chua, Tracy Levett‐Jones, et al. · Clinical Simulation in Nursing (2025) | TGRS Research Map | TGRS