| Title | Symptom clusters in fibromyalgia: potential utility in patient assessment and treatment evaluation. | | Author(s) | Rutledge DN, Mouttapa M, Wood PB | | Institution | Department of Nursing, California State University, Fullerton, CA, USA. drutledge@fullerton.edu | | Source | Nurs Res 2009 Sep-Oct; 58(5):359-67. | | MeSH | Adaptation, Psychological
Adolescent
Adult
Aged
Analysis of Variance
Attitude to Health
California
Cluster Analysis
Cognition Disorders
Depression
Factor Analysis, Statistical
Fatigue
Female
Fibromyalgia
Humans
Male
Middle Aged
Nursing Assessment
Nursing Methodology Research
Pain
Questionnaires
Risk Assessment
Risk Factors
Severity of Illness Index
Sleep Disorders
Stress, Psychological
| | Abstract | BACKGROUND: Recent evidence points to the likelihood of heterogeneity in the presentation and, perhaps, etiology of fibromyalgia (FM). A clearer understanding of the symptomatology and consideration of potential FM subtypes could add insights regarding this condition.
OBJECTIVE: The aim of this study was to determine whether clusters could be identified among 20 symptoms that participants in a prior online study identified and to elucidate the underlying structure of resultant clusters.
METHODS: Factor analysis was used on data from a study sponsored by the National Fibromyalgia Association in which 2,569 persons with FM responded to an online survey during a 3-day period in 2005.
RESULTS: In this well-educated, primarily Caucasian sample, morning stiffness, fatigue, and not feeling rested in the morning were the symptoms with the highest severity scores. A series of exploratory factor analyses and subsequent confirmatory factor analysis with Cronbach's alpha testing led to a five-factor model with the following domains containing 17 symptoms: Somatic, Distress, Fibromyalgia Core, Dyscognition, and Sleep Problems.
DISCUSSION: The findings support the heterogeneity of the FM experience and the presence of symptom clusters within the greater spectrum of symptoms comprising the FM syndrome. These observations suggest the possibility of tailoring interventions based upon individual patient symptomatology. Further work is needed to develop symptom inventories that can be used in clinical trials as outcome metrics and by healthcare providers to describe clinical burden and effect of treatments. | | Language | eng | | Pub Type(s) | Journal Article
| | PubMed ID | 19752676 |
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