| Title |
Pain characteristics in fibromyalgia: understanding the multiple dimensions of pain
|
|---|---|
| Published in |
Clinical Rheumatology, July 2014
|
| DOI | 10.1007/s10067-014-2736-6 |
| Pubmed ID | |
| Authors |
Mark Plazier, Jan Ost, Gaëtane Stassijns, Dirk De Ridder, Sven Vanneste |
| Abstract |
Fibromyalgia is a common disease with a high economic burden. The etiology of this disease remains unclear, as there are no specific abnormalities on clinical or technical examinations. Evidence suggests that central pain sensitization at the brain pain matrix might be involved. Understanding the pain characteristics of this disease is of importance both for diagnosis and treatment. The authors present their findings of pain characteristics in a Belgium population of fibromyalgia patients. Data of 65 patients (57 male and 8 female patients) were analyzed in this study (mean age 46.86, SD = +8.79). Patients filled out the following questionnaires: visual analogue scale, fibromyalgia impact questionnaire, pain-catastrophizing scale, pain vigilance and awareness questionnaire, modified fatigue impact scale, the Beck depression inventory, the short form 36 and the Dutch shortened profile of mood states. Statistical analysis was performed making use of a factor analysis and a hierarchical cluster analysis. We were able to define pain characteristics in this group of patients. The reciprocal effects of mood and fatigue on pain experience could be identified within the data, catastrophizing scores show a high correlation with overall life quality and pain experience. We have performed a cluster analysis on the fibromyalgia patients, based on the four main principal components defining the overall disease burden. Mood explained most of the variance in symptoms, followed by mental health state, fatigue, and catastrophizing. Three clusters of patients could be revealed by these components. Clusters: 1 high scores on mood disorders, pain, and decreased mental health, 2 high scores on fatigue and physical health, and 3 a mixture of these two groups. This data suggest that different subgroups of fibromyalgia patients could be identified and based on that, treatment strategies and results might be adapted. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 1% |
| Italy | 1 | 1% |
| Unknown | 96 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 17 | 17% |
| Student > Postgraduate | 12 | 12% |
| Student > Ph. D. Student | 11 | 11% |
| Student > Doctoral Student | 10 | 10% |
| Student > Bachelor | 8 | 8% |
| Other | 18 | 18% |
| Unknown | 22 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 27 | 28% |
| Psychology | 14 | 14% |
| Nursing and Health Professions | 13 | 13% |
| Agricultural and Biological Sciences | 4 | 4% |
| Neuroscience | 4 | 4% |
| Other | 10 | 10% |
| Unknown | 26 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 March 2015.
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#18,375,064
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Outputs from Clinical Rheumatology
#2,310
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#163,262
of 228,546 outputs
Outputs of similar age from Clinical Rheumatology
#28
of 37 outputs
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