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Published on: May 19, 2015
Rethinking the core symptom of schizophrenia: An exploration of disorganized thought centrality in psychosis
Jingjing Li1, Xiaoyun Zhang1, Fang Liu2
1Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Henan International Joint Laboratory of Biological Psychiatry, Zhengzhou, China; Henan Psychiatric Transformation Research Key Laboratory, Zhengzhou University, Zhengzhou, China.
Background And Hypothesis:
Schizophrenic symptoms are currently classified into several dimensions: positive symptoms, negative symptoms, disorganized thought, cognitive deficits, and general symptoms. This multi-dimensional categorization of symptoms has sparked an ongoing debate in the field: what is the core symptom of schizophrenia? This question remains central to our understanding of the disorder. In our previous research, we demonstrated the centrality of disorganized thought in schizophrenia. Building on this finding, we hypothesized that this centrality is not a feature of all psychotic disorders.
Study Design:
We analyzed Brief Psychiatric Rating Scale (BPRS) data from 17,414 outpatients using a Variational AutoEncoder (VAE) model. Clustering analysis was performed on the latent representations, followed by network analysis to examine symptom interactions within identified clusters. Analyses were further stratified by age and BPRS item types.
Study Results:
Clustering analysis revealed four distinct groups, in which one cluster exhibiting characteristics with more severe symptoms (mean BPRS score 99.73 [SD 9.46]), younger age (mean 19.48 [SD 9.31] years), and smaller sample size showed a unique centrality of thought disturbance among five subscale symptoms. This pattern persisted in both adult and adolescent subgroups and when analyzing only verbally reported items.
Conclusions:
Our findings support the specificity of disorganized thought centrality in one particular cluster, distinguishing it from other psychiatric presentations. This study demonstrates the value in analyzing large-scale clinical data to refine our understanding of complex psychiatric disorders, potentially informing future targeted interventions.
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