FIBROMYALGIA DIAGNOSIS: From Past Paradigms to Future Directions-The State of the Art and Ongoing Controversies

Fibromyalgia remains a contested clinical entity, characterized by persistent uncertainty regarding its definition, diagnostic boundaries, and underlying mechanisms. Over the past three decades, diagnostic frameworks have evolved from the 1990 American College of Rheumatology (ACR) classification criteria, based on widespread pain and tender point examination, to symptom-based models emphasizing patient-reported outcomes, such as the 2010 and 2016 ACR criteria. While these developments have improved feasibility and expanded clinical recognition, they have largely remained confined to biomedical and neuropsychological domains. This narrative review critically examines the historical evolution, conceptual foundations, and methodological limitations of fibromyalgia diagnostic criteria, integrating evidence from major classification systems, including ACR frameworks and the ACTTION-American Pain Society (APS) Pain Taxonomy (AAPT). Across these models, fibromyalgia is predominantly operationalized through symptom aggregation, with limited incorporation of social and contextual determinants of health. The analysis highlights persistent epistemological tensions, including diagnostic inflation, the continuum of polysymptomatic distress, and debates regarding disease legitimacy. In response, emerging proposals advocate for a biopsychosocial diagnostic framework that formally integrates biological, psychological, and social dimensions into the diagnostic core. This review also critically evaluates alternative dual-framework approaches that separate biological diagnosis from psychosocial severity assessment, emphasizing potential limitations such as fragmentation of patient experience and underestimation of psychosocial mechanisms in symptom generation. The findings suggest that future diagnostic models should move beyond static, symptom-based thresholds toward dynamic, integrative, and context-sensitive approaches. Such models may improve patient stratification, clinical decision-making, and research validity, while aligning diagnostic practice with contemporary understandings of chronic pain as a multidimensional and interactive condition.