Network Analysis of Persistent Somatic Symptoms in Two Clinical Patient Samples
- Publikationstyp:
- Zeitschriftenaufsatz
- Metadaten:
-
- Autoren
- Katharina Senger
- Jens Heider
- Maria Kleinstaeuber
- Matthias Sehlbrede
- Michael Witthoft
- Annette Schroeder
- Autoren-URL
- https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000730736200013&DestLinkType=FullRecord&DestApp=WOS_CPL
- DOI
- 10.1097/PSY.0000000000000999
- eISSN
- 1534-7796
- Externe Identifier
- Clarivate Analytics Document Solution ID: XP2YK
- PubMed Identifier: 34428004
- ISSN
- 0033-3174
- Ausgabe der Veröffentlichung
- 1
- Zeitschrift
- PSYCHOSOMATIC MEDICINE
- Schlüsselwörter
- network analyses
- persistent somatic symptoms
- somatic symptom disorder
- SOMS-7T
- clinical sample
- CI = confidence interval
- CS = correlation stability coefficients
- EBIC = extended Bayesian information criterion
- PSS = persistent physical symptoms
- SOMS-7T=Screening of Somatoform Disorder
- SSD = somatic symptom disorder
- Paginierung
- 74 - 85
- Datum der Veröffentlichung
- 2022
- Status
- Published
- Titel
- Network Analysis of Persistent Somatic Symptoms in Two Clinical Patient Samples
- Sub types
- Article
- Ausgabe der Zeitschrift
- 84
Datenquelle: Web of Science (Lite)
- Andere Metadatenquellen:
-
- Abstract
- <jats:title>ABSTRACT</jats:title> <jats:sec> <jats:title>Objective</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>The first data set consisted of <jats:italic toggle="yes">n</jats:italic> = 254 outpatients who were part of a multicenter study. The second data set included <jats:italic toggle="yes">n</jats:italic> = 574 inpatients, both with somatoform disorders. Somatic symptom severity was assessed with the Screening of Somatoform Disorder (SOMS-7T).</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>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.</jats:p> </jats:sec>
- Autoren
- Katharina Senger
- Jens Heider
- Maria Kleinstäuber
- Matthias Sehlbrede
- Michael Witthöft
- Annette Schröder
- DOI
- 10.1097/psy.0000000000000999
- eISSN
- 1534-7796
- ISSN
- 0033-3174
- Ausgabe der Veröffentlichung
- 1
- Zeitschrift
- Psychosomatic Medicine
- Sprache
- en
- Online publication date
- 2021
- Paginierung
- 74 - 85
- Datum der Veröffentlichung
- 2022
- Status
- Published
- Herausgeber
- Ovid Technologies (Wolters Kluwer Health)
- Herausgeber URL
- http://dx.doi.org/10.1097/psy.0000000000000999
- Datum der Datenerfassung
- 2023
- Titel
- Network Analysis of Persistent Somatic Symptoms in Two Clinical Patient Samples
- Ausgabe der Zeitschrift
- 84
Datenquelle: Crossref
- Abstract
- <h4>Objective</h4>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.<h4>Methods</h4>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).<h4>Results</h4>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.<h4>Conclusions</h4>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.
- Addresses
- From the Department of Psychology (Senger, Heider, Schröder), University of Koblenz-Landau, Landau, Germany; Department of Psychology (Kleinstäuber), Emma Eccles Jones College of Education and Health Services, Utah State University, Logan, Utah; Section of Health Care Research and Rehabilitation Research, Faculty of Medicine and Medical Centre (Sehlbrede), University of Freiburg, Freiburg im Breisgau; and Division of Clinical Psychology and Psychotherapy (Witthöft), Johannes Gutenberg University of Mainz, Mainz, Germany.
- Autoren
- Katharina Senger
- Jens Heider
- Maria Kleinstäuber
- Matthias Sehlbrede
- Michael Witthöft
- Annette Schröder
- DOI
- 10.1097/psy.0000000000000999
- eISSN
- 1534-7796
- Externe Identifier
- PubMed Identifier: 34428004
- Open access
- false
- ISSN
- 0033-3174
- Ausgabe der Veröffentlichung
- 1
- Zeitschrift
- Psychosomatic medicine
- Schlüsselwörter
- Humans
- Somatoform Disorders
- Medically Unexplained Symptoms
- Sprache
- eng
- Medium
- Paginierung
- 74 - 85
- Datum der Veröffentlichung
- 2022
- Status
- Published
- Datum der Datenerfassung
- 2021
- Titel
- Network Analysis of Persistent Somatic Symptoms in Two Clinical Patient Samples.
- Sub types
- Research Support, Non-U.S. Gov't
- Multicenter Study
- Journal Article
- Ausgabe der Zeitschrift
- 84
Datenquelle: Europe PubMed Central
- Abstract
- OBJECTIVE: 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. METHODS: 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: 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. CONCLUSIONS: 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.
- Autoren
- Katharina Senger
- Jens Heider
- Maria Kleinstäuber
- Matthias Sehlbrede
- Michael Witthöft
- Annette Schröder
- Autoren-URL
- https://www.ncbi.nlm.nih.gov/pubmed/34428004
- DOI
- 10.1097/PSY.0000000000000999
- eISSN
- 1534-7796
- Ausgabe der Veröffentlichung
- 1
- Zeitschrift
- Psychosom Med
- Schlüsselwörter
- Humans
- Medically Unexplained Symptoms
- Somatoform Disorders
- Sprache
- eng
- Country
- United States
- Paginierung
- 74 - 85
- PII
- 00006842-202201000-00009
- Datum der Veröffentlichung
- 2022
- Status
- Published
- Datum, an dem der Datensatz öffentlich gemacht wurde
- 2022
- Titel
- Network Analysis of Persistent Somatic Symptoms in Two Clinical Patient Samples.
- Sub types
- Journal Article
- Multicenter Study
- Research Support, Non-U.S. Gov't
- Ausgabe der Zeitschrift
- 84
Datenquelle: PubMed
- Beziehungen:
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