The network structure of self-reported psychopathological dimensions in common mental disorders (CMDs)

• Manuel J. Cuesta ^[1] ; Juan I. Arrarás ^[1] ; Gustavo J. Gil-Berrozpe ^[1] ; Victor Peralta ^[1] ; Laura Barrado ^[2] ; Olga Correa ^[2] ; Rebeca Elorza ^[2] ; Lorea Fernández ^[3] ; Irma Garmendia ^[2] ; Lucía Janda ^[2] ; Patricia Macaya ^[2] ; Camino Núñez ^[2] ; Pablo Sabater ^[2] ; Aileen Torrejon ^[2]
  1. [1] Instituto de Investigación Sanitaria de Navarra

     Instituto de Investigación Sanitaria de Navarra

     Pamplona, España

     
  2. [2] Mental Health Department, Servicio Navarro de Salud – Osasunbidea, Pamplona, Spain
  3. [3] Navarrabiomed

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• Localización: European journal of psychiatry, ISSN 0213-6163, Vol. 37, Nº 2, 2023, págs. 100-108
• Idioma: inglés
• DOI: 10.1016/j.ejpsy.2022.11.003
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• Resumen

  • Background and objectives Common mental disorders (CMDs) in mental health settings show high rates of comorbidities. While semi-structured interviews are the gold standard to establish a diagnosis, there are self-report instruments such as the Psychiatric Diagnostic Screening Questionnaire (PDSQ) that aids clinicians in improving the diagnostic process in a time-efficient manner.

    Methods Network analysis of the 13 domains of the PDSQ was applied to a sample of 374 first-contact outpatients to identify domains of psychopathology acting as hubs and bridges of interconnections within the CMDs.

    Results A global network densely connected with positive connections among PDSQ domains was found. The global network has four main clusters: depression-anxiety, somatoform, psychosis and substance-related domains. This network allowed for the identification of main ‘nodes’ acting as hubs favoring interconnections between dimensions and main ‘bridges’ easing the connections between clusters.

    Conclusion The network structure of the PDSQ domains might provide a complementary explanation to the high rates of comorbidity among CMDs. Moreover, our results support the relevance of the self-administered PDSQ inventory to account for a deeper understanding of comorbidities among CMDs.