Network Analysis of Persistent Somatic Symptoms in Two Clinical Patient Samples

病因学 干预(咨询) 集合(抽象数据类型) 心理学 医学 临床心理学 精神科 计算机科学 程序设计语言
作者
Katharina Senger,Jens Heider,Maria Kleinstäuber,Matthias Sehlbrede,Michael Witthöft,Annette Schröder
出处
期刊:Psychosomatic Medicine [Lippincott Williams & Wilkins]
卷期号:84 (1): 74-85 被引量:10
标识
DOI:10.1097/psy.0000000000000999
摘要

Previous attempts to group persistent somatic symptoms (PSSs) with factor-analytic approaches have obtained heterogeneous results. An alternative approach that seems to be more suitable is the network theory. Compared with 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.The first data set consisted of n = 254 outpatients who were part of a multicenter study. The second data set included n = 574 inpatients, both with somatoform disorders. Somatic symptom severity was assessed with the Screening of Somatoform Disorder (SOMS-7T).Results indicate that there are five main symptom groups that were found in both samples: neurological, gastrointestinal, urogenital, cardiovascular, and musculoskeletal symptoms. Although 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.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 etiology, prevention, and intervention research.
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