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.

翻译：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向，该地区此类技术尚处于早期应用阶段。通过整合创新扩散理论、具身社会临场感理论、交互等价定理与技术接受模型中的构念，构建了一个多理论研究模型。采用偏最小二乘结构方程模型对718名参与者的数据进行分析。结果表明：满意度、感知有用性、感知易用性、学习者互动和技术就绪度显著促进技术采纳，而技术焦虑与复杂性则产生负面影响。学习者-学习者及学习者-教师互动能有效预测满意度，进而提升行为意向。感知易用性在技术焦虑与感知有用性之间起完全中介作用，但技术焦虑对感知有用性或易用性影响行为意向的调节效应不显著。该模型解释了行为意向71.8%的变异，具有强解释力。研究结果为教育工作者、课程设计者和开发者在数字化转型的教育体系中整合元宇宙平台进行医疗培训提供了实践启示。