Artificial Intelligence in Public Health Communication Research

Artificial intelligence (AI) is transforming the ways health information is generated, disseminated, personalized, and evaluated. Advances in generative AI, large language models (LLMs), machine learning (ML), natural language processing, and computational analytics present unprecedented opportunities for public health researchers and practitioners to enhance health communication, promote healthy behaviors, support clinical and public health decision-making and care, and engage diverse populations at scale. AI-powered technologies also offer innovative approaches to developing tailored health messages, monitoring health behaviors, combating misinformation, improving participant recruitment, and reaching underserved communities.As AI technologies become increasingly integrated into communication ecosystems, it is essential that their development and application be grounded in rigorous scientific principles, behavioral theories, and evidence-based research methods. The responsible and ethical use of AI in public health communication requires multidisciplinary collaboration across communication science, behavioral medicine, public health, computer science, informatics, data science, and related disciplines. Rigorous and transparent research is critical to ensure that AI-driven interventions are effective, equitable, reproducible, and ethically implemented. This Research Topic invites original research and scholarly contributions examining the role of AI in advancing public health communication across diverse populations and settings. We welcome submissions addressing, but not limited to, the following questions:• How can AI, including generative AI, large language models (LLMs), and machine learning, advance public health communication research and practice?• How can AI be integrated with behavioral theories and communication science to design, deliver, and evaluate effective health communication?• How can AI facilitate ethical collection, analysis, and use of health data to improve how health promotion initiatives are communicated to at-risk populations? • How can AI improve the personalization, dissemination, and evaluation of health messages for diverse populations while promoting equity, transparency, and trust?We particularly encourage submissions on, but not limited to, the following topics:• AI-assisted development, personalization, and evaluation of health communication strategies• generative AI and large language models for health messaging and interventions• machine learning and computational methods for public health communication research• AI-enabled recruitment, participant engagement, and research data collection• AI-driven detection, monitoring, and mitigation of health misinformation• AI-supported public health surveillance and large-scale health communication analytics• digital phenotyping and AI-enabled monitoring using mobile devices, wearable sensors, and ecological momentary assessment• AI-assisted interventions using observational, experimental, and/or mixed methods• AI applications to improve health communication and engagement among underserved populations• ethical, equity, explainability, and trustworthiness considerations in AI-mediated health communication.We welcome submissions presenting original empirical research, methodological innovations, systematic reviews, meta-analyses, and visions that advance the science of AI in public health communication. We particularly encourage multidisciplinary contributions from communication, public health, behavioral medicine, health informatics, computer science, artificial intelligence, data science, population health, cancer prevention and control, addiction science, computational social science, and related disciplines. By bringing together researchers across these fields, this Research Topic aims to advance a rigorous scientific foundation for understanding how AI can be responsibly leveraged to improve public health communication, promote healthy behaviors, reduce health disparities, and strengthen population health outcomes.Information and Instructions for AuthorsAbstractsInitial abstracts (which Frontiers call 'manuscript summaries) of up to 300 words will be considered until February 15 2027. Abstracts should be structured under the following headings: Background, Objective, Methods, Results, and Conclusions.Article typesThis Research Topic accepts the following article types:Original Research: up to 8,000 wordsBrief Research Report: up to 4,000 wordsPerspective: up to 3,000 wordsAll word limits include the abstract, notes, references, tables, and figures. Topic editors: Sunny Jung Kim, Jeff Hancock, Viktor Clark Source: https://www.frontiersin.org/research-topics/84332/artificial-intelligence-in-public-health-communication-research