Application of Artificial Intelligence in Hypertension Health Education: A Scoping Review

Background: Hypertension is a major global health challenge, and effective health education is crucial for improving patients‘ self-management. Traditional health education methods have significant limitations in personalization, scalability, and continuous follow-up. Artificial intelligence (AI) technologies—including natural language processing (NLP), machine learning (ML), and large language models (LLM)—offer promising solutions to overcome these limitations. However, the current evidence regarding the application of AI in hypertension health education has not yet been comprehensively summarized. Objective: This scoping review aims to synthesize the published literature on the application of AI in health education for hypertension, with three specific objectives: (1) to identify the types of AI technologies employed and their application scenarios; (2) to characterize the methodological approaches or research designs adopted in this domain; and (3) to catalog the outcome measures used to evaluate AI-based hypertension health education.