Exploring the Role of Artificial Intelligence in Enhancing Social Participation for Community-Based Health Promotion: A Qualitative Study

Abstract

Background: Artificial intelligence (AI) encompasses diverse technologies such as chatbots, predictive analytics, and mobile health platforms, which are increasingly recognized for their capacity to influence social systems and enhance community participation. In community-based health promotion, AI offers new opportunities to engage diverse populations, reduce disparities, and strengthen access to health services. Objectives: This study aimed to explore how specific AI applications can facilitate social participation to improve public and community health, and to identify practical and ethical strategies for their integration into health promotion initiatives. Methods: Using a conventional content analysis approach, 28 semi-structured interviews were conducted in Tehran, Iran, with a purposive sample of AI experts, social scientists, policymakers, and community members. Thematic saturation was reached. Data analysis followed Graneheim and Lundman’s method, involving systematic coding and theme development, with trustworthiness ensured through triangulation, member validation, and detailed documentation. Participant diversity was considered in sampling and analysis to capture a range of perspectives. Results: Eight interrelated themes emerged, including civic engagement, social innovation, health and well-being, technological infrastructure, crisis management, environmental sustainability, accessibility, and public awareness. Participants highlighted AI tools such as chatbots for communication, predictive analytics for crisis response, and mobile platforms for inclusive decision-making, emphasizing AI’s role in fostering equitable, responsive, and collaborative health promotion. Conclusions: Findings suggest AI has transformative potential to enhance social participation and community health. However, successful implementation requires ethical design, inclusivity, and alignment with local needs. While conducted in Tehran, results provide insights that may inform AI integration in similar urban contexts, with caution advised when generalizing to different cultural or technological settings.