中华医学教育杂志

中华医学教育杂志 ›› 2026, Vol. 46 ›› Issue (3): 199-205.DOI: 10.3760/cma.j.cn115259-20250506-00503

• 教育技术 • 上一篇    下一篇

临床医学专业学生生成式人工智能使用行为影响因素研究

陈丽华1, 刘硕2, 信斯言3, 王雨4, 吴红斌5   

  1. 1北京大学公共卫生学院2023级卫生政策与管理学系专业硕士研究生, 北京 100191;
    2北京大学公共卫生学院2024级卫生政策与管理学系专业硕士研究生, 北京 100191;
    3首都医科大学附属北京朝阳医院教育处, 北京 100024;
    4北京大学教育学院2023级医学教育学系硕士研究生, 北京 100871;
    5北京大学医学教育研究所, 北京 100191
  • 收稿日期:2025-05-06 出版日期:2026-03-01 发布日期:2026-02-28
  • 通讯作者: 吴红斌, Email: wuhongbin@pku.edu.cn
  • 基金资助:
    2025年北京大学本科教学改革项目:“医学本科生GenAI素养及其影响研究”(JG2025170)

A study on the influencing factors of the use of generative artificial intelligence by clinical medicine students

Chen Lihua1, Liu Shuo2, Xin Siyan3, Wang Yu4, Wu Hongbin5   

  1. 1Master Degree Candidate, Department of Health Policy and Management, Enrolled in 2023, School of Public Health, Peking University, Beijing 100191, China;
    2Master Degree Candidate, Department of Health Policy and Management, Enrolled in 2024, School of Public Health, Peking University, Beijing 100191, China;
    3Education Department, Beijing CHAO-YANG Hospital, Capital Medical University, Beijing 100024, China;
    4Master Degree Candidate, Department of Medical Education, Enrolled in 2023, School of Education, Peking University, Beijing 100871;
    5Institute of Medical Education, Peking University, Beijing 100191, China
  • Received:2025-05-06 Online:2026-03-01 Published:2026-02-28
  • Contact: Wu Hongbin, Email: wuhongbin@pku.edu.cn
  • Supported by:
    Undergraduate Teaching Reform Project of Peking University in 2025(JG2025170)

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摘要： 目的 探讨临床医学专业学生(以下酌情简称医学生)生成式人工智能(generative artificial intelligence,GenAI)使用行为的影响因素。方法 依据2024年中国医学生培养与发展调查(China medical student survey,CMSS)结果,采用描述性统计、卡方检验和Logistic回归方法,分析个人、家庭和院校等因素对医学生生成式人工智能使用行为的影响。结果 参与调查的81 892名医学生中,34 715名(42.4%)医学生表示每周至少使用1次GenAI(如ChatGPT、文心一言等)。在医学生的GenAI使用上,个人因素方面,男生的GenAI使用率显著高于女生(OR=1.561,P<0.001);二年级医学生的GenAI使用率高于三年级、四年级和五年级医学生(OR=0.643、OR=0.406、OR=0.423,均P<0.001);独生子女医学生的GenAI使用率低于非独生子女医学生(OR=0.947,P=0.001)。家庭因素方面,父母从事医学相关职业的医学生的GenAI使用率高于父母非医学相关职业的医学生(OR=1.074,P<0.001);家庭年总收入15万元以上的医学生的GenAI使用率高于家庭年总收入15万元及以下的医学生(OR=1.155,P<0.001);家庭所在地为城市的医学生的GenAI使用率高于家庭所在地为农村的医学生(OR=1.058,P=0.001)。院校因素方面,双一流建设高校(universities under the double first-class initiative)的医学生的GenAI使用率高于普通高校的医学生(OR=1.194,P<0.001);位于西部地区高校医学生的GenAI使用率高于东部地区高校医学生(OR=1.071,P<0.001),位于中部地区高校医学生的GenAI使用率低于东部地区高校医学生(OR=0.905,P<0.001);开设AI课程院校的医学生的GenAI使用率高于未开设AI课程院校的医学生(OR=2.065,P<0.001)。结论 本研究结果显示,医学生高GenAI使用率的影响因素包括男性、二年级、城市、家庭年总收入15万元以上、双一流建设高校、院校开设AI课程等,院校应当通过建设医学GenAI课程改善医学生对GenAI的使用行为。

关键词: 生成式人工智能, 临床医学专业, 医学生, 使用行为, 影响因素

Abstract: Objective To explore the factors influencing the use of generative artificial intelligence (GenAI) among clinical medical students (Hereinafter referred to as medical students). Methods In 2024, the China medical student survey (CMSS) was used to investigate the use of GenAI among medical students. Descriptive statistics, chi-square tests, and logistic regression analysis were employed to examine the impact of personal, family, and institutional factors. Results Among the 81 892 medical students surveyed, 34 715 (42.4%) medical students reported using GenAI (ChatGPT, Ernie Bot, etc.) at least once a week. In terms of individual factors, male medical students had a significantly higher GenAI usage rate than females (OR=1.561, P<0.001); Second-year medical students demonstrated higher GenAI usage rate compared to their third-, fourth-, and fifth-year counterparts (OR=0.643, 0.406, and 0.423 respectively, all P<0.001; only child medical students showed a lower GenAI usage rate than their non-only child peers (OR=0.947, P=0.001). Regarding familial factors, medical students whose parents are engaged in medical-related professions show a higher GenAI usage rate than those whose parents are not (OR=1.074, P<0.001); medical students from households with an annual income exceeding 150 000 RMB show a higher GenAI usage rate than those from households with an annual income 150 000 RMB or less (OR=1.155, P<0.001); medical students from urban households exhibit a higher GenAI usage rate than those from rural households (OR=1.058, P=0.001). Regarding institutional factors, medical students from “Double First-Class”universities (DFC, a Chinese government initiative to build world-class universities and disciplines) demonstrated a higher GenAI usage rate than those from non-DFC universities (OR=1.194, P<0.001); medical students in universitial located in western China showed a significantily higher GenAI usage rate compared to those in universities in eastern China (OR=1.071, P<0.001), where is those in central China showed a significantily lower GenAI usage rate (OR=0.905,P<0.001); medical students from universities that offer AI courses show a significantly higher GenAI usage rate than those from universities without AI courses (OR=2.065, P<0.001). Conclusions The results of this study demonstrate that factors associated with a high usage rate of Generative AI (GenAI) among medical students include, but are not limited to, male gender, second-year standing, urban household background, an annual household income exceeding 150 000 RMB, enrollment in a Double First-Class university, and institutional offering of AI-related courses.Medical schools should consider integrating GenAI-focused medical courses to enhance medical students' adoption of these tools.

Key words: Generative artificial intelligence, Clinical medicine major, Medical student, Use behavior, Influencing factors

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