Network Analysis Demonstrates Importance of Early Interventions for Schizophrenia

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Connectivity was significantly higher in nonrecovered than recovered patients, and there were fewer connections in recovered patients compared with nonrecovered patients, indicating significant differences in network structure.

Network analysis showed that nonrecovered patients with schizophrenia had stronger connections between poor real-life functioning and psychopathology than recovered patients, according to a 4-year follow-up study published in World Psychiatry.1 The findings highlight the potential importance of early interventions for patients with schizophrenia.

The network approach to psychopathology attempts to explain mental illness as a network of interconnecting nodes that represent causally connected symptoms. Symptoms within networks may form feedback loops which allow the symptoms to become self-sustaining, and the stronger the connections in a network, the more likely it is symptoms will activate each other.2

The Italian Network for Research on Psychosis previously examined network connectivity in a multicenter study of 921 community-dwelling patients with schizophrenia.3 The networks consisted of 27 variables, including psychopathology, social context, resilience, internalized stigma, and real-life functioning. The Fruchterman-Reingold algorithm places highly associated nodes at the center and weakly associated nodes at the periphery. In the previous study, researchers found that functional capacity and real life functioning had the highest centrality and connectivity.3 To test network trajectories and the influence of recovery, the researchers performed a 4-year follow-up study assessing network connectivity in 618 subjects (mean age, 45.1 years; 69.1% men) from the original study.

Network structure did not significantly differ between patients in the baseline and follow-up studies (M-test = 0.13; P =.154). Connectivity between variables increased slightly but not significantly (S-test = 0.57; P =.196). At baseline and follow-up, functional capacity and everyday life skills and real-life functioning maintained high centrality and connectivity.

In the 4-year follow-up study, network connectivity was compared between recovered (n=124) and nonrecovered (n=494) patients based on symptomatic remission and functional recovery criteria. In nonrecovered patients, network connectivity did not differ from baseline but did differ from recovered patients. Connectivity was significantly higher in nonrecovered than recovered patients (S-test = 9.156; P <.001), and there were fewer connections in recovered patients compared with nonrecovered patients, indicating significant differences in network structure (M-test = 0.371; P =.002). Notably, the 3 domains of real-life functioning were disconnected and not interrelated in recovered patients, whereas everyday life skills and disorganization had stronger connections in nonrecovered patients.

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The results suggest a strongly interconnected network of symptoms and dysfunctions may be self-perpetuating in patients with schizophrenia. However, the conclusions are limited by the small number of recovered patients included in the analysis. “Early and integrated treatment plans, targeting variables with high centrality, might prevent the emergence of self-reinforcing networks of symptoms/dysfunctions in people with schizophrenia,” concluded the researchers.


1. Galderisi S, Rucci P, Mucci A, et al. The interplay among psychopathology, personal resources, context-related factors and real-life functioning in schizophrenia: stability in relationships after 4 years and differences in network structure between recovered and non-recovered patients. World Psychiatry. 2020;19(1):81-91.

2. Borsboom D. A network theory of mental disorders. World Psychiatry. 2017;16(1):5-13.

3. Galderisi S, Rucci P, Kirkpatrick B, et al. Interplay among psychopathologic variables, personal resources, context-related factors, and real-life functioning in individuals with schizophrenia: a network analysis. JAMA Psychiatry. 2018;75(4):396-404.