Development of an artificial intelligence-based nursing simulation scenario evaluation tool: a methodological study using the Real-Time Delphi method in South Korea

基于人工智能的护理模拟场景评估工具的开发:一项在韩国采用实时德尔菲法的学科方法学研究

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Abstract

PURPOSE: Simulation-based education plays a critical role in nursing by allowing students to acquire clinical competencies in a safe and controlled environment. However, current evaluation tools for simulation scenarios often lack standardization, resulting in inconsistencies when assessing the effectiveness of such programs. METHODS: This study aimed to develop a comprehensive Nursing Simulation Scenario Evaluation Tool using the Real-Time Delphi method. A panel of 10 experts in nursing and simulation education participated in two rounds of surveys. The evaluation criteria were derived from the International Nursing Association for Clinical Simulation and Learning Standards of Best Practice and relevant literature. Survey items were refined through expert consensus using content validity ratios and coefficient of variation values. The finalized tool was further enhanced with artificial intelligence (AI)-based evaluation capabilities to support objective and systematic assessment. The tool was registered and patented in the Republic of Korea (Korean Intellectual Property Office Registration No. 10-2024-0051234) to acknowledge its innovation and technical merit. RESULTS: The process resulted in an evaluation tool comprising eight key domains and 36 items, covering scenario structure, learning objectives, preparation, script development, debriefing, facilitation, expected outcomes, and scenario validity. A Kendall's coefficient of concordance of 0.739 indicated strong agreement among the experts. CONCLUSION: This study successfully developed a standardized and validated tool to improve the reliability and effectiveness of simulation-based education in nursing. The tool addresses a key gap in current educational practices and enhances consistency in evaluating nursing simulation scenarios. Future studies should focus on validating its application across diverse educational environments.

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