Generative AI in simulation-based SBIRT training: Enhancing content validity and educational impact

IF 2.5 3区医学 Q1 NURSING

Clinical Simulation in Nursing Pub Date : 2025-09-30 DOI:10.1016/j.ecns.2025.101811

Nicole Kroll PhD, APRN, ANP-C, FNP-BC, PMHNP-BC , Lauren Thai MEd, CHSOS , Jinsil Hwaryoung Seo PhD , Mihir Sunil Godbole , Cindy Weston DNP, APRN, FNP-BC, CHSE, FNAP, FAANP, FAAN , Elizabeth Wells-Beede PhD, RN, C-EFM, CHSE-A, CNE, ACUE, FSSH, FAAN

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引用次数: 0

Abstract

Background: Traditional SBIRT (Screening, Brief Intervention, and Referral to Treatment) training is limited by subjective assessments and resource constraints. Integrating generative AI into simulation offers scalable, consistent, and objective learning for addressing substance use disorders. Method: A web-based AI-enabled SBIRT simulation using large language models was piloted with content experts to evaluate usability, content validity, and educational impact via mixed-methods feedback and survey analysis. Results: Most evaluators rated the simulation as highly relevant and natural, with enhanced consistency and accessibility. The platform was easy to use and improved therapeutic communication skills. Conclusion(s): Generative AI in SBIRT simulation increases training reliability, scalability, and learner engagement for healthcare providers.

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基于模拟的SBIRT培训中的生成式人工智能：增强内容有效性和教育影响

背景：传统的SBIRT（筛查、短暂干预和转诊治疗）培训受到主观评估和资源限制的限制。将生成式人工智能集成到模拟中，为解决物质使用障碍提供了可扩展、一致和客观的学习。方法：在内容专家的指导下，使用大型语言模型进行基于web的人工智能SBIRT模拟，通过混合方法反馈和调查分析来评估可用性、内容有效性和教育影响。结果：大多数评估者认为模拟是高度相关和自然的，具有增强的一致性和可访问性。该平台易于使用，并提高了治疗沟通技巧。结论：SBIRT模拟中的生成式AI提高了医疗保健提供者的培训可靠性、可扩展性和学习者参与度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical Simulation in Nursing NURSING-

CiteScore

5.50

自引率

15.40%

发文量

107

期刊介绍： Clinical Simulation in Nursing is an international, peer reviewed journal published online monthly. Clinical Simulation in Nursing is the official journal of the International Nursing Association for Clinical Simulation & Learning (INACSL) and reflects its mission to advance the science of healthcare simulation. We will review and accept articles from other health provider disciplines, if they are determined to be of interest to our readership. The journal accepts manuscripts meeting one or more of the following criteria: Research articles and literature reviews (e.g. systematic, scoping, umbrella, integrative, etc.) about simulation Innovative teaching/learning strategies using simulation Articles updating guidelines, regulations, and legislative policies that impact simulation Leadership for simulation Simulation operations Clinical and academic uses of simulation.