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医学生医疗人工智能准备度量表汉化及信效度检验

Chinese version of Medical Artificial Intelligence Readiness Scale for Medical Students and its reliability and validity tests

摘要目的:本研究旨在汉化医学生医疗人工智能准备度量表,并检验其在医学生群体中的信效度,以此为评估中国医学生的医疗人工智能准备度提供可靠工具。方法:依据Brislin翻译模型进行量表汉化,过程包括翻译、回译和文化调适。采用便利抽样法选取267名医学生开展问卷调查,运用R 4.3.1软件进行统计分析以检验信效度。结果:中文版医学生医疗人工智能准备度量表包含基础知识、实践能力、态度和价值观3个维度,共14个条目,累计方差贡献率达54.03%。模型适配情况良好( χ2/ df=1.63,RMSEA=0.05,TLI=0.94,GFI=0.93,CFI=0.95)。量表各维度Cronbach’s α系数在0.71~0.78之间,量表整体Cronbach’s α系数为0.85,重测信度为0.67。 结论:汉化后的医学生医疗人工智能准备度量表信效度达标,可用于评估中国医学生的医疗人工智能准备度,能为医疗人工智能教育改革提供实证依据。

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abstractsObjective:To translate the Medical Artificial Intelligence Readiness Scale for Medical Students into Chinese, test its reliability and validity among medical students, and provide a reliable tool for assessing medical artificial intelligence readiness of medical students in China.Methods:The scale was translated following Brislin's translation model, which included translation, back-translation, and cultural adaptation. A total of 267 medical students were selected using convenience sampling to complete the questionnaire survey. R 4.3.1 software was used for statistical analysis to evaluate reliability and validity.Results:The Chinese version of the Medical Artificial Intelligence Readiness Scale for Medical Students consisted of 14 items across three dimensions: basic knowledge, practical ability, and attitude and values, with a cumulative variance contribution rate of 54.03%. The confirmatory factor analysis indicated a good model fit ( χ2/ df=1.63, root mean square error of approximation=0.05, Tucker-Lewis index=0.94, goodness-of-fit index=0.93, comparative fit index=0.95). The Cronbach's α coefficients for the three dimensions ranged from 0.71 to 0.78, and the overall Cronbach's α coefficient of the scale was 0.85. The test-retest reliability was 0.67. Conclusions:The Chinese version of the Medical Artificial Intelligence Readiness Scale for Medical Students demonstrated acceptable reliability and validity, and can be used to assess medical artificial intelligence readiness among Chinese medical students. These results provide an empirical basis for reforms in medical artificial intelligence education.

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作者 何登鑫 [1] 陈芳 赵梅村 学术成果认领
作者单位 湖北中医药大学护理学院实验教学中心,武汉 430065 [1]
DOI 10.3760/cma.j.cn116021-20250923-02197
发布时间 2026-01-13(万方平台首次上网日期,不代表论文的发表时间)
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