Objective: 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.
Methods: 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.
Results: 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.
Conclusions: 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.
Keywords: Artificial intelligence; Delphi method; Digital competency; Medical education.
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