Generative Artificial Intelligence in Health Education for Chronic Disease Patients: A Scoping Review

With the rapid iteration of Generative Artificial Intelligence (GenAI) technology and its deep integration with the healthcare field, its application potential in health education for patients with chronic diseases has become increasingly prominent. Chronic diseases are characterized by long duration, complex management, and high demand for patients' self-health management. Traditional health education models have pain points such as homogeneous content, insufficient personalization, limited communication efficiency, and unsustained follow-up interventions, making it difficult to fully meet the differentiated health knowledge needs and long-term health management demands of different patients with chronic diseases. This study adopts a scoping review method to systematically search domestic and foreign literatures on the application of generative artificial intelligence in health education for patients with chronic diseases, clarify the application scenarios, application models, and core technology types of generative artificial intelligence in this field, sort out the advantages and existing problems in the current application process, and analyze the key factors affecting its promotion and application. The purpose of the study is to comprehensively and systematically present the application status and research progress of generative artificial intelligence in the field of health education for patients with chronic diseases, fill the gap in the existing research on the overall application of this field, provide clear direction guidance for the subsequent related research, and at the same time provide theoretical reference and practical basis for clinical medical staff and health managers to formulate scientific and reasonable chronic disease health education strategies. The expected outcomes of this study include: clarifying the main application scenarios of generative artificial intelligence in health education for patients with chronic diseases (such as personalized health knowledge push, intelligent consultation and answering, customization of health management plans, rehabilitation training guidance, etc.) and corresponding application models; summarizing the current core technical bottlenecks, ethical risks, application limitations and improvement suggestions in application; forming a scoping review report on the application of generative artificial intelligence in health education for patients with chronic diseases; providing basic support for subsequent targeted empirical research, technical optimization research and policy formulation, promoting generative artificial intelligence technology to better empower health education for patients with chronic diseases, improving the pertinence, effectiveness and accessibility of health education, helping patients with chronic diseases improve their self-health management ability and improve health outcomes.