Knowledge, Attitudes, and Practices Related to AI in Learning and Research Among Medical Students in Vietnam: Cross-Sectional Study

Clinical Snapshot

Key Findings

• P Value: P<0.001 for both knowledge and attitudes associations with practices

• Effect Size: Attitudes POMP score: β=0.42 per unit increase in practices POMP score; Knowledge POMP score: β=0.12 per unit increase in practices POMP score. Age, gender, major, GPA classification, and AI seminar attendance were not independently associated with AI practices.

• Primary Outcome: AI practices POMP score: median 50.00 (IQR 46.88–71.88); primary use was information retrieval and literature research support

• Nnt Or Sensitivity: Not applicable (descriptive/associational cross-sectional study); no NNT, sensitivity, specificity, or hazard ratio reported. R² and model fit statistics not provided.

• Confidence Interval: Attitudes β: 95% CI 0.34–0.51; Knowledge β: 95% CI 0.08–0.16

Clinical Application

The study's recommendation to integrate AI fundamentals, applications, and ethics into medical curricula is feasible and already underway in many institutions globally. However, the evidence base from this single cross-sectional study is insufficient to drive specific curriculum design decisions without corroborating evidence from multi-institutional, longitudinal, or interventional studies. Australian medical schools operate under AMC accreditation standards that are increasingly incorporating digital health and health informatics competencies. The RACGP and RACP have published position statements on AI in clinical practice. The Medical Board of Australia's Good Medical Practice framework addresses practitioner responsibility for technology use. While this Vietnamese study cannot directly inform Australian curriculum policy, it contributes to the global evidence base suggesting that positive attitudes — more than formal knowledge — drive AI adoption among medical students, a finding relevant to Australian curriculum designers prioritising attitudinal and ethical AI education. The TGA's regulatory framework for AI-based medical devices (Software as a Medical Device) and the Australian Digital Health Agency's national strategy provide the governance context within which Australian medical graduates will practise. PBS and TGA considerations are not directly relevant to this educational study. Medical students in lower-middle-income Southeast Asian countries with emerging AI integration in medical curricula; findings have limited direct applicability to high-income country medical education contexts

Abstract

BACKGROUND: In recent years, artificial intelligence (AI) has ushered in a promising era in medicine, particularly in medical education. However, studies assessing the knowledge, attitudes, and practices related to AI among medical students in Vietnam remain limited. OBJECTIVE: This study aimed to evaluate AI knowledge, attitudes, and practices among Vietnamese medical students in learning and research, and to identify factors associated with their AI practices. METHODS: A cross-sectional study was conducted among medical students at Thai Binh University of Medicine and Pharmacy from November to December 2025. Data were collected using an online structured questionnaire covering demographic characteristics and AI knowledge, attitudes, and practices. The main outcome of interest was AI practices in learning and research. Descriptive statistics and multivariable linear regression were used to examine associated factors. Regression coefficients (β), 95% CIs, and P values are reported. RESULTS: A total of 1002 medical students (mean age 21.00, IQR 19.00-23.00 years; n=596, 59.5% female) were included. The median percentage of maximum possible (POMP) score of AI knowledge was 66.67 (IQR 33.33-83.33), with a high level of familiarity with common tools (n=798, 79.6%). AI attitudes were generally positive (median POMP score 70.00, IQR 53.33-76.67). AI-related practices were lower (median POMP score 50.00, IQR 46.88-71.88), with AI being used primarily for information retrieval and literature research support. In the multivariable analysis, knowledge POMP score (β=0.12, 95% CI 0.08-0.16) and attitudes POMP score (β=0.42, 95% CI 0.34-0.51) were significantly associated with AI practices POMP score (P<.001). Age, gender, major, grade point average classification, and having participated in an AI seminar or training were not associated with AI practices. CONCLUSIONS: Medical students showed favorable knowledge and positive attitudes, but their AI practices remained limited. Integrating AI into medical curricula, including fundamentals, applications, and ethical aspects, is essential to prepare future physicians for AI-driven health care.

References

1. 1.Bui, M. T., Le, H. M., Luong, T. K. H., Vu, H. A., Tran, T. A., Ngo, T. P. L., Bui, D. L., Bui, T. H., Nguyen, D. C., Ngo, T. B., Nguyen, T. K., & Dao, T. L. (2026). Knowledge, attitudes, and practices related to AI in learning and research among medical students in Vietnam: Cross-sectional study. JMIR Formative Research. https://doi.org/10.21608/erji.2023.306718