Title: Integrating Metaverse Technologies in Medical Education: Examining Acceptance Factors Among Current and Future Healthcare Providers Show Chinese title

Title: 将元宇宙技术整合到医学教育中：考察当前和未来医疗保健提供者的接受因素

Abstract: This study investigates behavioral intention to use healthcare metaverse platforms among medical students and physicians in Turkey, where such technologies are in early stages of adoption. A multi-theoretical research model was developed by integrating constructs from the Innovation Diffusion Theory, Embodied Social Presence Theory, Interaction Equivalency Theorem and Technology Acceptance Model. Data from 718 participants were analyzed using partial least squares structural equation modeling. Results show that satisfaction, perceived usefulness, perceived ease of use, learner interactions, and technology readiness significantly enhance adoption, while technology anxiety and complexity have negative effects. Learner learner and learner teacher interactions strongly predict satisfaction, which subsequently increases behavioral intention. Perceived ease of use fully mediates the relationship between technology anxiety and perceived usefulness. However, technology anxiety does not significantly moderate the effects of perceived usefulness or ease of use on behavioral intention. The model explains 71.8% of the variance in behavioral intention, indicating strong explanatory power. The findings offer practical implications for educators, curriculum designers, and developers aiming to integrate metaverse platforms into healthcare training in digitally transitioning educational systems. Show Chinese abstract

Abstract: 本研究调查了土耳其医学生和医生对医疗元宇宙平台的使用行为意图，这些技术在该国尚处于采用的早期阶段。 通过整合创新扩散理论、具身社会存在理论、交互等价定理和技术接受模型中的构建，开发了一个多理论研究模型。 对718名参与者的数据显示，使用偏好的部分最小二乘结构方程建模进行了分析。 结果表明，满意度、感知有用性、感知易用性、学习者互动和技术准备度显著促进采用，而技术焦虑和技术复杂性则有负面影响。 学习者之间的互动和学习者与教师之间的互动强烈预测满意度，这随后增加了行为意图。 感知易用性完全中介了技术焦虑与感知有用性之间的关系。 然而，技术焦虑并不显著调节感知有用性或易用性对行为意图的影响。 该模型解释了行为意图71.8%的方差，表明其具有强大的解释力。 研究结果为教育工作者、课程设计者和开发者提供了实际意义，旨在将元宇宙平台整合到数字化转型教育系统中的医疗培训中。