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Comparison of the symptom networks of long‐Covid and chronic fatigue syndrome

From modularity to connectionism

Dados Bibliográficos

ID21392015
AutoresMichael E Hyland (0000-0003-3879-0469, University of Plymouth Plymouth UK, autor correspondente), Yuri Antonacci (0000-0002-6956-6323, University of Palermo Palermo Italy), Anne-Marie Bacon (0000-0003-4279-3814, University of Plymouth Plymouth UK), Alison M Bacon (University of Plymouth Plymouth UK)
Ano2024
Volume65
Fascículo6
Páginas1132-1140
Data de publicação2024-12-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoScandinavian Journal of Psychology (JOURNAL)
Identificadores do periódicoISSN: 0036-5564 • E-ISSN: 1467-9450
EditoraWiley (PUBLISHER • GB)
DOI10.1111/sjop.13060
PMID39034480
OpenAlexW4400896457
IdiomaEN
Referências citadas58

The objective was to compare the symptom networks of long‐COVID and chronic fatigue syndrome (CFS) in conjunction with other theoretically relevant diagnoses in order to provide insight into the etiology of medically unexplained symptoms (MUS). This was a cross‐sectional comparison of questionnaire items between six groups identified by clinical diagnosis. All participants completed a 65‐item psychological and somatic symptom questionnaire (GSQ065). Diagnostically labelled groups were long‐COVID ( N = 107), CFS ( N = 254), irritable bowel syndrome (IBS, N = 369), fibromyalgia ( N = 1,127), severe asthma ( N = 100) and healthy group ( N = 207). The 22 symptoms that best discriminated between the six groups were selected for network analysis. Connectivity, fragmentation and number of symptom clusters (statistically related symptoms) were assessed. Compared to long‐COVID, the symptom networks of CFS, IBS and fibromyalgia had significantly lower connectivity, greater fragmentation and more symptom clusters. The number of clusters varied between 9 for CFS and 3 for severe asthma, and the content of clusters varied across all groups. Of the 33 symptom clusters identified over the six groups 30 clusters were unique. Although the symptom networks of long‐COVID and CFS differ, the variation of cluster content across the six groups is inconsistent with a modular causal structure but consistent with a connectionist (network, parallel distributed processing) biological basis of MUS. A connectionist structure would explain why symptoms overlap and merge between different functional somatic syndromes, the failure to discover a biological diagnostic test and how psychological and behavioral interventions are therapeutic

Arousal · Chronic fatigue syndrome · Comorbidity · Etiology · Fibromyalgia · Irritable bowel syndrome · Medical diagnosis · Psychiatry · Psychological intervention · Clinical Psychology · Fibromyalgia and Chronic Fatigue Syndrome Research · Medicine · Mental Health Research Topics · Neuroscience · Psychology · Psychosomatic Disorders and Their Treatments

  • The Psychology of Physical Symptoms

    Open Access•James W Pennebaker•Psychology of Physical Symptoms•1982

  • Maps of random walks on complex networks reveal community structure

    Open Access•Martin Rosvall, Carl T Bergstrom•Proceedings of the National…•2008

  • Functional Somatic Syndromes

    Open Access•Arthur J Barsky, Jonathan F Borus•Annals of Internal Medicine•1999

  • Fatigue and cognitive impairment in Post-Covid-19 Syndrome

    Open Access•Felicia Ceban, Susan Ling et al.•Brain, Behavior, and Immunity•2022

  • Exploratory graph analysis

    Open Access•Hudson F Golino, Hudson Golino et al.•PLoS ONE•2017

  • Computing Communities in Large Networks Using Random Walks

    Pascal Pons, Matthieu Latapy•Computer and Information Sciences…•2005

  • MGM

    Open Access•Jonas M B Haslbeck, Lourens Waldorp et al.•Journal of Statistical Software•2020

  • Functional somatic syndromes

    Open Access•Simon Wessely, Chaichana Nimnuan et al.•The Lancet•1999

  • Estimating psychological networks and their accuracy

    Open Access•Sacha Epskamp, Denny Borsboom et al.•Behavior Research Methods•2018

  • Network Analysis

    Denny Borsboom, Angélique O J Cramer•Annual Review of Clinical…•2013

  • An Exploratory Study of Subgrouping of Patients With Functional Somatic Syndrome Based on the Psychophysiological Stress Response

    Kenji Kanbara, Mikihiko Fukunaga et al.•Psychosomatic Medicine•2007

  • Network Analysis of Symptoms Co-Occurrence in Chronic Fatigue Syndrome

    Open Access•Sławomir Kujawski, Joanna Słomko et al.•International Journal of…•2021

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