Digital literacy across disciplines scale for medical students: development, validation, and analysis

Abstract

Purpose: To develop and validate a Digital Literacy Across Disciplines (DLAD) scale for medical students, analyze its differential performance across gender and major groups, and provide insights for the digital transformation of medical education. Methods: Based on Zhou Xiaoli’s theoretical framework of DLAD, integrated with World Federation for Medical Education (WFME) standards and Accreditation Council for Graduate Medical Education (ACGME) guidelines, a scale was developed through literature analysis, expert review, student feedback, and formal testing (n = 675). Reliability and validity were assessed using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA), whereas differences across majors and genders were analyzed via the Kruskal‒Wallis H test and the Mann‒Whitney U test. Results: EFA revealed a four-factor structure (Technology, Competence, Attitude, Knowledge), accounting for 61.5% of the cumulative variance. CFA further validated the model with strong structural validity (CFI = 0.919, TLI = 0.906, RMSEA = 0.069, SRMR = 0.057) and high internal consistency (Cronbach’s α = 0.93). The finalized scale comprises four dimensions: Technology (3.71, IQR = 0.57), Attitude (3.75, IQR = 0.75), Knowledge (3.75, IQR = 1.00), and Competence (3.00, IQR = 0.89), with a total score of 3.42 (IQR = 0.67). Significant disparities were observed:Clinical Medicine students scored significantly lower in total score (3.08, IQR = 0.85) and subdimensions (Technology: 3.43, IQR = 1.00); Competence: 2.56, IQR = 1.11; Knowledge: 3.25, IQR = 1.25) compared with Preventive Medicine (3.69, IQR = 0.41, p < 0.001), Medical Imaging Technology (3.67, IQR = 0.79, p < 0.001), and Nursing (3.54, IQR = 0.50, p < 0.001).Female students outperformed males in the Attitude dimension (p = 0.008, r = 0.1). Conclusion: This study developed the first validated DLAD scale for medical education, revealing critical gaps in digital competence and interdisciplinary disparities. Embedding digital diagnosis–treatment simulations into curricula is recommended to enhance skill integration.