%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 27
%N 
%P e66032
%T Health Communication on the Internet: Promoting Public Health and Exploring Disparities in the Generative AI Era
%A Uddin,Jamal
%A Feng,Cheng
%A Xu,Junfang
%+ Department of Pharmacy, Second Affiliated Hospital, School of Public health, Zhejiang University School of Medicine, 866 Yuhangtang road, Xihu district, Hangzhou, 310058, China, 86 18801230482 ext 000, junfangxuhappy1987@163.com
%K internet
%K generative AI
%K artificial intelligence
%K ChatGPT
%K health communication
%K health promotion
%K health disparity
%K health
%K communication
%K internet
%K AI
%K generative
%K tool
%K genAI
%K gratification theory
%K gratification
%K public health
%K inequity
%K disparity
%D 2025
%7 6.3.2025
%9 Viewpoint
%J J Med Internet Res
%G English
%X Health communication and promotion on the internet have evolved over time, driven by the development of new technologies, including generative artificial intelligence (GenAI). These technological tools offer new opportunities for both the public and professionals. However, these advancements also pose risks of exacerbating health disparities. Limited research has focused on combining these health communication mediums, particularly those enabled by new technologies like GenAI, and their applications for health promotion and health disparities. Therefore, this viewpoint, adopting a conceptual approach, provides an updated overview of health communication mediums and their role in understanding health promotion and disparities in the GenAI era. Additionally, health promotion and health disparities associated with GenAI are briefly discussed through the lens of the Technology Acceptance Model 2, the uses and gratifications theory, and the knowledge gap hypothesis. This viewpoint discusses the limitations and barriers of previous internet-based communication mediums regarding real-time responses, personalized advice, and follow-up inquiries, highlighting the potential of new technology for public health promotion. It also discusses the health disparities caused by the limitations of GenAI, such as individuals’ inability to evaluate information, restricted access to services, and the lack of skill development. Overall, this study lays the groundwork for future research on how GenAI could be leveraged for public health promotion and how its challenges and barriers may exacerbate health inequities. It underscores the need for more empirical studies, as well as the importance of enhancing digital literacy and increasing access to technology for socially disadvantaged populations.
%M 40053755
%R 10.2196/66032
%U https://www.jmir.org/2025/1/e66032
%U https://doi.org/10.2196/66032
%U http://www.ncbi.nlm.nih.gov/pubmed/40053755