4.6 Article

A network analysis of anxiety, depressive, and psychotic symptoms and functioning in children and adolescents at clinical high risk for psychosis

Journal

FRONTIERS IN PSYCHIATRY
Volume 13, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fpsyt.2022.1016154

Keywords

clinical high risk for psychosis (CHR-P); comorbidity; network analysis; attenuated psychotic symptoms; depressive symptoms; anxiety symptoms; general functioning

Categories

Funding

  1. Department of Dynamic and Clinical Psychology, and Health Studies, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy

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This study aimed to analyze the network structure of symptom domains, depressive and anxiety symptoms, and general functioning in youths at clinical high risk for psychosis. The results showed a strong association between negative and disorganization symptoms, as well as dense connections among depressive and anxiety symptoms. Physical symptoms of anxiety played a bridging role. Positive symptoms were not associated with other nodes. The findings suggest the importance of targeting negative and disorganization symptoms, as well as depressive and anxiety symptoms, simultaneously.
ObjectiveYouths at clinical high risk for psychosis (CHR-P) are characterized by a high prevalence of anxiety and depressive disorders. The present study aimed at developing and analyzing a network structure of CHR-P symptom domains (i.e., positive, negative, disorganization, and general subclinical psychotic symptoms), depressive and anxiety symptoms, and general functioning. MethodsNetwork analysis was applied to data on 111 CHR-P children and adolescents (M-age = 14.1), who were assessed using the Structured Interview for Prodromal Syndromes, the Children's Depression Inventory, the Children's Global Assessment Scale, and the Multidimensional Anxiety Scale for Children. ResultsIn the network, negative and disorganization symptoms showed the strongest association (r = 0.71), and depressive and anxiety symptoms showed dense within-domain connections, with a main bridging role played by physical symptoms of anxiety. The positive symptom cluster was not associated with any other node. The network stability coefficient (CS) was slightly below 0.25, and observed correlations observed ranged from 0.35 to 0.71. ConclusionThe lack of association between subclinical positive symptoms and other network variables confirmed the independent nature of subclinical positive symptoms from comorbid symptoms, which were found to play a central role in the analyzed network. Complex interventions should be developed to target positive and comorbid symptoms, prioritizing those with the most significant impact on functioning and the most relevance for the young individual, through a shared decision-making process. Importantly, the results suggest that negative and disorganization symptoms, as well as depressive and anxiety symptoms, may be targeted simultaneously.

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