Online Discourse on Fibromyalgia: Text-Mining to Identify Clinical Distinction and Patient Concerns

Background: The purpose of this study was to evaluate the possibility of using text-mining to identify clinical distinctions and patient concerns in online memoires posted by patients with fibromyalgia (FM). Material/Methods: A total of 399 memoirs were collected from an FM group website. The unstructured data of memoirs associat-ed with FM were collected through a crawling process and converted into structured data with a concordance, parts of speech tagging, and word frequency. We also conducted a lexical analysis and phrase pattern identi-fication. After examining the data, a set of FM-related keywords were obtained and phrase net relationships were set through a web-based visualization tool. Results: The clinical distinction of FM was verified. Pain is the biggest issue to the FM patients. The pains were affect-ing body parts including ‘muscles, ’ ‘leg, ’ ‘neck, ’ ‘back, ’ ‘joints, ’ and ‘shoulders ’ with accompanying symptoms such as ‘spasms, ’ ‘stiffness, ’ and ‘aching, ’ and were described as ‘sever, ’ ‘chronic, ’ and ‘constant. ’ This study also demonstrated that it was possible to understand the interests and concerns of FM patients through text-mining. FM patients wanted to escape from the pain and symptoms, so they were interested in medical treat-ment and help. Also, they seemed to have interest in their work and occupation, and hope to continue to live life through the relationships with the people around them. Conclusions: This research shows the potential for extracting keywords to confirm the clinical distinction of a certain disease