Diagnostic validity and clinical utility of the psychosis-risk state: A multidimensional network analysis

Introduction: The clinical high-risk for psychosis (CHR-P) paradigm was developed to identify individuals at substantial risk of developing full-blown psychotic disorders (Fusar-Poli et al., 2020; Nelson & McGorry, 2020). Despite the establishment of specialized clinics aimed at preventing psychosis and improving general functioning in CHR-P individuals, there are significant challenges to the relevance and utility of this paradigm in healthcare systems (van Os & Guloksuz, 2017). These include the small proportion of CHR-P individuals who transition to psychosis and the difficulty in distinguishing CHR-P from common mental disorders due to high comorbidity rates. This study aimed to evaluate the clinical specificities of CHR-P youth compared to general help-seekers and non-CHR-P youth. By employing network analyses (Borsboom, 2017), the study sought to identify unique clinical characteristics of CHR-P individuals that could guide the development of tailored interventions, thereby supporting the diagnostic validity and clinical utility of the CHR-P concept. Methods: A total of 146 CHR-P and 103 non-CHR-P help-seeking youth were recruited from a neuropsychiatric unit. Participants were assessed using the Structured Interview for Psychosis-Risk Syndromes (SIPS), Children’s Depression Inventory (CDI), Multidimensional Anxiety Scale for Children (MASC), Global Functioning: Social (GF: Social), Global Functioning: Role (GF: Role), and Wechsler Intelligence Scale for Children/Wechsler Adult Intelligence Scale (WISC/WAIS). Three network structures were analyzed: the entire help-seeking sample (help-seekers network), only CHR-P patients (CHR-P network), and only non-CHR-P patients (non-CHR-P network). Results: In the help-seekers network, each variable presented at least one edge, indicating interconnectedness among clinical variables. The CHR-P network revealed two isolated subgraphs: one including functioning, anxiety, depressive, negative, disorganization, and general symptoms; the other including positive symptoms and IQ. In the non-CHR-P network, positive symptoms were negatively connected to functioning, disorganization, and negative symptoms. Conclusion: The findings highlight specific clinical characteristics of CHR-P youth that support the need for tailored interventions addressing comorbid disorders alongside positivde psychotic symptoms. The isolation of positive symptoms in the CHR-P network suggests that these symptoms may not interact with other psychopathology domains, necessitating distinct treatment strategies. The study supports the diagnostic validity and clinical utility of the CHR-P concept, advocating for specialized clinical approaches for CHR-P individuals. This study underscores the importance of specific clinical strategies for CHR-P youth, reinforcing the need for specialized clinics and tailored interventions (Yung et al., 2021). The network analysis approach provides a comprehensive understanding of the complex interactions among clinical variables in CHR-P individuals, which can inform future research and clinical practices aimed at preventing psychosis and improving outcomes for at-risk youth.