Bibliometric Analysis: Mapping the AI ​​Research Landscape on a Case Study of Otitis Media in Pierre Bourdieu's Perspective

Abstract

This study integrates bibliometric analysis, systematic scoping reviews, and sociological analysis to map the landscape of AI research in otitis media (OM) with a focus on social, cultural, and structural dimensions that are often overlooked. Using the Social Construction of Illness theoretical framework, this study reveals that the majority of AI innovations in OM diagnosis are dominated by a biomedical perspective that ignores patients' life experiences and the social structures that shape their disease journey. Of the 47 articles analyzed, only four studies discussed conversation-based AI applications, and only one considered the perspective of patients or families. This gap reflects the dominance of the technocratic-medical paradigm and neglect of health equity. Based on the gap analysis, this study proposes the development of an AI chatbot (INFO-OM) designed with user participation, cultural sensitivity, and a deep understanding of the social determinants of health as a methodological foundation for creating socially valid and inclusive health technology. This study adopts Pierre Bourdieu's sociological perspective on social capital to analyze how the distribution of AI knowledge in OM diagnosis reflects power structures in the health field. The analysis shows that access to AI technology as symbolic capital is concentrated in research institutions in developed countries, while communities with limited economic and cultural models, especially in Low and Middle Income Countries (LMICs), experience double exclusion from access to health services and from participation in the development of health technology.