The Lyme Disease Controversy: An AI-Driven Discourse Analysis of a Quarter Century of Academic Debate and Divides

ABSTRACTThe scientific discourse surrounding Chronic Lyme Disease (CLD) and Post-Treatment Lyme Disease Syndrome (PTLDS) has evolved over the past twenty-five years into a complex and polarised debate, shaped by shifting research priorities, institutional influences, and competing explanatory models. This study presents the first large-scale, systematic examination of this discourse using an innovative hybrid AI-driven methodology, combining large language models with structured human validation to analyse thousands of scholarly abstracts spanning 25 years. By integrating computational techniques with expert oversight, we developed a quantitative framework for tracking epistemic shifts in contested medical fields, with applications to other content analysis domains. Our analysis revealed a progressive transition from infection-based models of Lyme disease to immune-mediated explanations for persistent symptoms, a shift that has been particularly pronounced in high-impact clinical and immunology journals. At the same time, research supporting CLD has remained largely confined to hypothesis-driven publications, indicating a persistent asymmetry in how competing perspectives are disseminated and legitimised. The investigation into thematic trends further highlighted the enduring complexity of Lyme disease diagnostics and evolving research focus on therapeutic controversies, even as institutional alignment with PTLDS perspectives continues to grow. This study offers new empirical insights into the structural and epistemic forces shaping Lyme disease research, providing a scalable and replicable methodology for analysing discourse. The findings have implications for policymakers, clinicians, and communication strategists, emphasising the need for more equitable research funding, standardised diagnostic criteria, and improved patientcentred care models. This research also underscores the value of AI-assisted methodologies in social science and medical research by systematically quantifying discourse evolution, offering a foundation for future studies examining other contested conditions and controversies.