Chen Jinjuan, Hou Xiaorong, Lv Yalan, Liu Mimi, Yang Meijie, Zhou Xiaoyu, Du Fei, Yi Jia, Zhang Lingqin, Li Guangying
College of Artificial Intelligence Medicine, Chongqing Medical University, Chongqing 400016, China; Bishan Hospital of Chongqing Medical University, Bishan Hospital of Chongqing, Chongqing 402760, China.
College of Artificial Intelligence Medicine, Chongqing Medical University, Chongqing 400016, China.
Int J Med Inform. 2025 Nov;203:106043. doi: 10.1016/j.ijmedinf.2025.106043. Epub 2025 Jul 12.
With the advancement of the digital society and the extensive application of digital medical technologies, the demand for digital competencies among medical students is becoming increasingly critical. Digital competence of medical students refers to the ability of medical students to effectively select and use digital or intelligent technologies and applications to accomplish their studies, research, and future clinical practice. Currently in China, no digital competency framework for medical students has been established based on clinical practice requirements. Therefore, the study aimes to investigate digital competencies for medical students and provide recommendations for future digital competency training initiatives and framework development.
Focusing on competency theory, we reviewed and analyzed literature related to digital competency. Twenty experts participated in a two-round Delphi method to iteratively refine and correct the indicator items. Finally, the weights of indicators were calculated through the Analytic Hierarchy Process.
Twenty experts were invited to participate in two rounds of the Delphi survey, achievinga 100 % response rate in both rounds, with Expert Authority Coefficients of 0.81 and 0.82, indicating the credibility and professional expertise the panelists. Furthermore, Kendall's consistency coefficient (Kendall's W) ranged from 0.143 to 0.275 (p < 0.05), indicating that experts reached a consensus on the indicators. The final framework comprises 3 domains, 9 primary indicators, and 27 secondary indicators.
A digital competency framework for medical students was developed using the Delphi method. This framework facilitates the self-development of medical students and serves as a reference for the development of digital medical curricula.
随着数字社会的发展和数字医疗技术的广泛应用，医学生对数字能力的需求日益迫切。医学生的数字能力是指医学生有效选择和使用数字或智能技术及应用来完成学业、研究和未来临床实践的能力。目前在中国，尚未基于临床实践要求建立医学生数字能力框架。因此，本研究旨在调查医学生的数字能力，并为未来的数字能力培训举措和框架制定提供建议。
以能力理论为重点，我们对与数字能力相关的文献进行了回顾和分析。20位专家参与了两轮德尔菲法，以迭代方式完善和修正指标项目。最后，通过层次分析法计算指标权重。
邀请20位专家参与两轮德尔菲调查，两轮的回复率均达到100%，专家权威系数分别为0.81和0.82，表明专家小组的可信度和专业水平。此外，肯德尔一致性系数（Kendall's W）在0.143至0.275之间（p < 0.05），表明专家们在指标上达成了共识。最终框架包括3个领域、9个一级指标和27个二级指标。
采用德尔菲法制定了医学生数字能力框架。该框架有助于医学生的自我发展，并为数字医学课程的开发提供参考。
