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

TL;DR

This study tackles the long-standing Lyme disease controversy by applying a novel hybrid AI-driven discourse analysis to over 25 years of scholarly abstracts, framed by a Science and Technology Studies perspective. By combining large language models with structured human validation, the authors quantify epistemic shifts from infection-centric to immune-mediated explanations (PTLDS) and reveal substantial journal- and citation-level biases that shape the discourse. They identify eight emergent themes and demonstrate that Neutral stances dominate, with PTLDS gaining prominence in high-impact venues since 2010, while CLD remains comparatively marginal and diffusion-limited. The work offers a scalable, replicable methodology for analyzing contested medical knowledge and provides insights for policy, clinical practice, and health communication, with broad applicability to other areas of healthcare research.

Abstract

The 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 Large Language Models (LLMs) 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. 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, while underscoring the value of AI-assisted methodologies in social science and medical research.

Figures (11)

• Figure 1: A broad and consolidated outline of the discourse themes and tensions on the Lyme disease controversy in media and academia over time as reported in literature elliott2021valuestricker2008chronicwalker2021portrayallantos2011chronic.
• Figure 2: Overview of the steps comprising the proposed hybrid AI-driven content analysis methodology.
• Figure 3: Proportion of retrieved articles per database
• Figure 4: PRISMA flow diagram for new systematic reviews, which included searches of databases and registers only. 1This number includes 2088 abstracts with less than 300 characters in length which were rejected due to the information content being too low for analysis. 2Lyme, Borrelia*, burgdorferi, Ixodes, Erythema, migrans, tick-borne, tickborne, tick borne.
• Figure 5: Number of relevant studies by year (2000-2004) and their classification. Classifications consisted of Neutral (blue), Supports PTLDS (orange), and Supports CLD (green).