Network analysis has been used to explore the interplay between psychopathology and functioning in psychosis, but no study has used dedicated statistical techniques to focus on the bridge symptoms connecting these domains. The current study aims to estimate the network of depressive, negative, and positive symptoms, general psychopathology, and real-world functioning in people with first-episode schizophrenia or schizophreniform disorder, focusing on bridge nodes.

Baseline data from the OPTiMiSE trial were analyzed. The sample included 446 participants (age 40.0 ± 10.9 years, 70% males). The network was estimated with a Gaussian graphical model, using scores on individual items of the positive and negative syndrome scale (PANSS), the Calgary depression scale for schizophrenia, and the personal and social performance scale. Stability, strength centrality, expected influence (EI), predictability, and bridge centrality statistics were computed. The top 20% scoring nodes on bridge strength were selected as bridge nodes.

Nodes from different rating scales assessing similar psychopathological and functioning constructs tended to cluster together in the estimated network. The most central nodes (EI) were Delusions, Emotional Withdrawal, Depression, and Depressed Mood. Bridge nodes included Depression, Conceptual Disorganization, Active Social Avoidance, Delusions, Stereotyped Thinking, Poor Impulse Control, Guilty Feelings, Unusual Thought Content, and Hostility. Most of the bridge nodes belonged to the general psychopathology subscale of the PANSS. Depression (G6) was the bridge node with the highest value.

The current study provides novel insights for understanding the complex phenotype of psychotic disorders and the mechanisms underlying the development and maintenance of comorbidity and functional impairment after psychosis onset.

This study was performed to identify the predictive factors of functional capacity assessed by the Spanish University of California Performance Skills Assessment (Sp-UPSA) and real-world functioning assessed by the Spanish Personal and Social Performance scale (PSP) in outpatients with schizophrenia.

Naturalistic, 6-month follow-up, multicentre, validation study. Here, we report data on 139 patients with schizophrenia at their baseline visit. Assessment: Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression-Severity (CGI-S), Sp-UPSA and PSP. Statistics: Pearson's correlation coefficient (r) was used to determine the relationships between variables, and multivariable stepwise linear regression analyses to identify predictive variables of Sp-UPSA and PSP total scores.

Functional capacity: scores on the PSP and PANSS-GP entered first and second at P < 0.0001 and accounted for 21% of variance (R2 = 0.208, model df = 2, F = 15.724, P < 0.0001). Real-world functioning: scores on the CGI-S (B = −5.406), PANSS-N (B = −0.657) and Sp-UPSA (B = 0.230) entered first, second and third, and accounted for 51% of variance (model df = 3, F = 37.741, P < 0.0001).

In patients with schizophrenia, functional capacity and real-world functioning are two related but different constructs. Each one predicts the other along with other factors; general psychopathology for functional capacity, and severity of the illness and negative symptoms for real-world functioning. These findings have important clinical implications: (1) both types of functioning should be assessed in patients with schizophrenia and (2) strategies for improving them should be different.

Better understanding of interplay among symptoms, cognition and functioning in first-episode psychosis (FEP) is crucial to promoting functional recovery. Network analysis is a promising data-driven approach to elucidating complex interactions among psychopathological variables in psychosis, but has not been applied in FEP.

This study employed network analysis to examine inter-relationships among a wide array of variables encompassing psychopathology, premorbid and onset characteristics, cognition, subjective quality-of-life and psychosocial functioning in 323 adult FEP patients in Hong Kong. Graphical Least Absolute Shrinkage and Selection Operator (LASSO) combined with extended Bayesian information criterion (BIC) model selection was used for network construction. Importance of individual nodes in a generated network was quantified by centrality analyses.

Our results showed that amotivation played the most central role and had the strongest associations with other variables in the network, as indexed by node strength. Amotivation and diminished expression displayed differential relationships with other nodes, supporting the validity of two-factor negative symptom structure. Psychosocial functioning was most strongly connected with amotivation and was weakly linked to several other variables. Within cognitive domain, digit span demonstrated the highest centrality and was connected with most of the other cognitive variables. Exploratory analysis revealed no significant gender differences in network structure and global strength.

Our results suggest the pivotal role of amotivation in psychopathology network of FEP and indicate its critical association with psychosocial functioning. Further research is required to verify the clinical significance of diminished motivation on functional outcome in the early course of psychotic illness.