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[Network analysis of psychopathological symptoms in patients with schizophrenia as a model for studying the clinical presentation].

Created on 07 Aug 2026

Authors

E G Kornetova, S A Galkin, A N Kornetov, D A Petkun, S A Ivanova

Published in

Zhurnal nevrologii i psikhiatrii imeni S.S. Korsakova. Volume 126. Issue 7. Pages 63-68.

Abstract

To evaluate the validity of the six-factor model of the Positive and Negative Syndrome Scale (PANSS) using network analysis and to examine the relationships between depression, anxiety, and symptoms associated with schizophrenia.
The study included a cohort of 150 inpatients diagnosed with schizophrenia. The severity of psychopathological symptoms was assessed using the PANSS based on a six-factor model. The study also utilized the Hamilton Depression Rating Scale (HDRS) and the Hamilton Anxiety Rating Scale (HARS). Network analysis was performed using the R statnet package.
The findings revealed that the highest centrality rates were attributed to the disorganized, negative, and excitation factors within the PANSS scale. Anxiety scores derived from HARS were found to be significantly associated with G16 (active social avoidance), G6 (depression), N2 (emotional withdrawal), and G3 (guilt feelings), which correspond to elements within the negative, depressive, and disorganized factors. In addition, HDRS depression scores demonstrated associations with G6 and N2, representing the depressive and negative factors. A correlation was also observed between the scores from both assessment scales.
The network analysis indicated that depressive symptoms evaluated through the HDRS, alongside anxiety symptoms assessed via HARS, hold substantial significance among the psychopathological presentations observed in patients with schizophrenia. These symptoms exhibit a close interrelationship with components of the negative, depressive, and disorganized factors as identified within the PANSS model. In addition, the analysis substantiated the validity of the PANSS six-factor model.

PMID:
42565400
Bibliographic data and abstract were imported from PubMed on 07 Aug 2026.

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