Common-sense model of self-regulation to cluster fibromyalgia patients: results from a cross-sectional study in Italy.

ABSTRACT

OBJECTIVES: Fibromyalgia is a severe and disabling chronic pain syndrome affecting millions of people worldwide. Various patients' subgroups were identified using different atheoretical measures, hardly effective to tailor treatments. Previous literature findings showed the relevance of fibromyalgia patients' illness perceptions in adjusting to the disease. The present study aims to identify clusters of fibromyalgia patients based on their illness perceptions and investigate whether they can differ across pain, mood, physical functioning, catastrophising, and pain acceptance measures. METHODS: Fifty-three newly referred fibromyalgia patients completed clinical and psychological questionnaires. Patients' subgroups were created by applying hierarchical cluster analysis to their answers to Illness Perception Questionnaire-Revised subscales. Potential differences across subgroups in outcome variables were tested. RESULTS: Cluster analysis identified two patient groups. Group A (32 patients) had a higher representation of fibromyalgia as a chronic disease with severe consequences, lower beliefs in personal and treatment control, and a higher fibromyalgia-related emotional distress than group B (21 patients). Clusters did not differ on pain intensity and duration. Group A, compared to group B, showed worse physical functioning and overall impairment due to fibromyalgia, a poorer psychological condition, a higher tendency to catastrophise, and less pain acceptance. CONCLUSIONS: Study findings reveal two fibromyalgia subgroups differing in emotional suffering and impairment despite similar pain intensity and duration. Patients' illness perceptions and attitudes towards pain, like catastrophising and acceptance, might be critical in adjusting to the disease. A detailed assessment of such risk and protective factors is critical to differentiate patients' subgroups with different needs and thus offering tailored treatments.