Fibromyalgia and Depression: A Network Analysis Approach

Fibromyalgia (FM) is a complex disorder characterized by chronic and widespread musculoskeletal pain. FM and depression are highly comorbid; however, their relationship remains unclear. In line with the hypothesis that there are bidirectional relationships between symptoms of both disorders, a network analysis was conducted. This method is a graphical representation of a partial correlation matrix between individual symptoms, which enables an understanding of how these symptoms relate to one another. Data were pooled from three studies conducted on patients with FM (n = 219). Well-established network analyses methods were used to illustrate the network of FM and depressive symptoms, determine the centrality and bridge strength of each symptom, and identify clusters from within the data. Most clusters detected included both FM and depression symptoms. The most central symptoms that also exhibited high bridge strength were cognitive and psychological: (1) negative affect, and (2) memory problems. Surprisingly, pain did not emerge as central to this network. Utilizing a network analysis approach to examine symptom-to-symptom relationships yielded novel insight into the maintenance of this comorbidity. The research and clinical implications of the findings, such as developing treatments targeting the most central symptoms and avenues for further research, are discussed.