Abstract
Background: Chronic Fatigue Syndrome (CFS) is a condition of unknown aetiology with a heterogeneous population. The variability in symptomatology produces difficulties in studying CFS, therefore this study aimed to establish symptom typology and sub-groups within a sample of participants by use of data reduction techniques. Methods: Two-hundred and forty-six participants completed two symptom measures (one of which evaluated CFS-specific symptoms and the other a general symptom checklist) which were subsequently combined and analysed. Symptom types were established with factor analysis, whereas sub-groups within the sample were determined by cluster analysis. Results: Five symptom types resulted from the factor analysis which were labelled FMS-like, depression/anxiety, fatigue/post-exertional malaise, cognitive/neurological and IBS-like symptoms, with the FMS-like accounting for the majority of the variance in the data. Cluster analysis illustrated that the sample could be divided into three sub-groups based upon the symptom reports. The clusters that emerged were formed of a low symptomatology sub-group (LSS-G), a medium symptomatology sub-group (MSS-G) and a high symptomatology sub-group (HSS-G), which, as the names suggests, signified symptom severity. Notably, these sub-groups did not differ in respect to age, sex, illness duration or time taken to gain a diagnosis which infers that the groupings were not influenced by demographic concerns. Conclusion: This study illustrated that symptomatology in CFS can be divided into distinct categories that concur with the most recent guidelines for the condition. Additionally, the illness can be separated into discrete sub-groups, although these groupings are linked to overall severity, rather than symptom types.