Network structure of functional somatic symptoms
Version
Published
Identifiers
10.1016/j.jpsychores.2024.111968
Date Issued
2025-01
Author(s)
Type
Article
Language
English
Abstract
Objective
The overlap among functional somatic syndromes (FSS) is substantial, which is why various empirical attempts at an improved understanding of related symptoms have been undertaken. Network analyses are particularly valuable from a clinical point of view, since they focus on the extent to which symptoms expression is co-dependent. The aim of this study was to provide the first estimation of the network structure of symptoms in 17 FSS.
Methods
N = 3054 young adults participated in an online survey. The Questionnaire on Functional Somatic Syndromes (FSSQ) was used to diagnose FSS and to assess related symptoms. The Patient Health Questionnaire (PHQ-9) was used to assess (comorbid) depression. Various R packages were used for network analysis, which yielded correlations between symptoms (edges), symptom groups (communities), and measures of centrality for individual symptoms (e.g., node strength).
Results
The final network had a relatively small number of edges, with small (46.5 %) or small- to medium-sized (47.1 %) correlations. Ten communities were identified: cognitive problems/fatigue/depression, sensory problems, facial pain, head/neck/upper back pain, dizziness/nausea, throat pain/problems with swallowing, chest pain, widespread pain, abdominal pain/problems with digestion, and genital pain. The highest node strength in the network was found for the symptoms “tired”, “down, depressed, or hopeless”, and “tired after minimal exertion”.
Conclusions
The network analyses pointed to ten distinct groups of moderately associated symptoms in individuals with FSS. Fatigue and depression emerged as important symptoms connecting groups. Future studies should test whether (transdiagnostic) interventions specifically targeting these symptoms are particularly potent in alleviating FSS.
The overlap among functional somatic syndromes (FSS) is substantial, which is why various empirical attempts at an improved understanding of related symptoms have been undertaken. Network analyses are particularly valuable from a clinical point of view, since they focus on the extent to which symptoms expression is co-dependent. The aim of this study was to provide the first estimation of the network structure of symptoms in 17 FSS.
Methods
N = 3054 young adults participated in an online survey. The Questionnaire on Functional Somatic Syndromes (FSSQ) was used to diagnose FSS and to assess related symptoms. The Patient Health Questionnaire (PHQ-9) was used to assess (comorbid) depression. Various R packages were used for network analysis, which yielded correlations between symptoms (edges), symptom groups (communities), and measures of centrality for individual symptoms (e.g., node strength).
Results
The final network had a relatively small number of edges, with small (46.5 %) or small- to medium-sized (47.1 %) correlations. Ten communities were identified: cognitive problems/fatigue/depression, sensory problems, facial pain, head/neck/upper back pain, dizziness/nausea, throat pain/problems with swallowing, chest pain, widespread pain, abdominal pain/problems with digestion, and genital pain. The highest node strength in the network was found for the symptoms “tired”, “down, depressed, or hopeless”, and “tired after minimal exertion”.
Conclusions
The network analyses pointed to ten distinct groups of moderately associated symptoms in individuals with FSS. Fatigue and depression emerged as important symptoms connecting groups. Future studies should test whether (transdiagnostic) interventions specifically targeting these symptoms are particularly potent in alleviating FSS.
Publisher DOI
Journal or Serie
Journal of Psychosomatic Research
ISSN
0022-3999
Organization
Volume
188
Publisher
Elsevier
Submitter
Hanusch, Kay
Citation apa
Litzenburger, A., Rothacher, Y., Hanusch, K., Ehlert, U., Nater, U. M., & Fischer, S. (2025). Network structure of functional somatic symptoms. In Journal of Psychosomatic Research (Vol. 188). Elsevier. https://doi.org/10.24451/arbor.12835
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