Network Analysis of Persistent Somatic Symptoms in Two Clinical Patient Samples
| Autor: | Katharina Senger, Matthias Sehlbrede, Maria Kleinstäuber, Jens Heider, Michael Witthöft, Annette Schröder |
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| Rok vydání: | 2021 |
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| Zdroj: | Psychosomatic Medicine. 84:74-85 |
| ISSN: | 1534-7796 0033-3174 |
| DOI: | 10.1097/psy.0000000000000999 |
| Popis: | OBJECTIVE Previous attempts to group persistent somatic symptoms (PSS) with factor-analytic approaches have obtained heterogeneous results. An alternative approach that seems to be more suitable is the network theory. Compared to factor analysis, which focuses on the underlying factor of symptoms, network analysis focuses on the dynamic relationships and interactions among different symptoms. The main aim of this study is to apply the network approach to examine the heterogeneous structure of PSS within two clinical samples. METHODS The first dataset consisted of N = 254 outpatients who were part of a multicentre study. The second dataset included N = 574 inpatients, both with somatoform disorders. Somatic symptom severity was assessed with the Screening of Somatoform Disorder (SOMS-7 T) (1). RESULTS Results indicate that there are five main symptom groups which were found in both samples: neurological, gastrointestinal, urogenital, cardiovascular, and musculoskeletal symptoms. While patterns of symptoms with high connection to each other look quite similar in both networks, the order of the most central symptoms (e.g. symptoms with a high connection to other symptoms in the network) differs. CONCLUSION This work is the first to estimate the structure of PSS using network analysis. A next step could be first to replicate our findings before translating them into clinical practice. Second, results may be useful for generating hypotheses to be tested in future studies and the results open new opportunities for a better understanding for aetiology, prevention, and intervention research. |
| Databáze: | OpenAIRE |
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