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Introduction: Income inequality, a pivotal determinant of general and mental health, operates through intricate mechanisms at various geographical scales. While established at country or region levels, the impact of lower-level (municipal or neighborhood) inequality remains inconsistent. This study explores the influence of regional- and municipal-level income inequality on individual psychological distress during the COVID-19 pandemic in Italy, employing a multilevel data analysis., Materials and Methods: In a post hoc analysis of data from the first wave of the pandemic (March to April 2020), three hierarchical levels were considered: individual participants, municipalities, and regions. Depressive and anxiety symptoms were measured using the PHQ-9 and GAD-7 scales, while the Gini coefficient gauged income inequality at municipal and regional levels. The analysis incorporated demographic variables as potential confounders., Results: The study encompassed 21 regions, 3,900 municipalities, and 21,477 subjects. Income inequality at both regional and municipal levels exhibited associations with distress scores, suggesting independent effects. Notably, higher distress scores were identified in southern regions with elevated inequality, despite a more substantial COVID-19 impact in the north., Discussion: Findings contribute to existing literature by emphasizing the independent impact of lower-level (municipal) and higher-level (regional) income inequality on population psychopathology. The study supports theories suggesting diverse pathways through which inequality at different levels influences health, such as potential associations with healthcare system dysfunction at the regional level and welfare dysfunction at the municipal level. The observed north-south gradient in distress scores highlights the need for psychosocial interventions to alleviate income inequality, especially in historically disadvantaged southern regions. Future research should explore the nuanced interplay between income inequality and various ecological variables to provide a comprehensive understanding of its health impact.

Aim: Current diagnostic systems, DSM-5 and ICD-10, still adopt a categorical approach to classify psychotic disorders. The present study was aimed at investigating the structure of psychotic symptomatology in both affective and non-affective psychosis from a dimensional approach., Methods: Participants with a first episode psychosis (FEP) were recruited from a cluster-randomized controlled trial (GET-UP PIANO TRIAL), offered to all Community Mental Health Centres (CMHCs) located across two northern Italian regions. After clinical stabilization, patients were assessed with a comprehensive set of psychopathological measures including the Positive and Negative Syndrome Scale, the Hamilton Depression Rating Scale and the Bech-Rafaelsen Mania Rating Scale. A two-step cluster analysis was performed., Results: Overall, 257 FEP patients (male, n = 171, 66.5%; mean age = 24.96 ± 4.56) were included in the study. The cluster analysis revealed a robust four-cluster solution: delusional-persecutory (n = 82; 31.9%), depressed (n = 95; 37%), excited (n = 26; 10.1%) and negative-disorganized (n = 54; 21%), thus suggesting a quadripartite structure with both affective and non-affective dimensions. Among non-affective dimensions, negative and disorganization symptoms constituted a unique construct apart from positive symptoms., Conclusions: Symptom dimensions may represent a useful tool for dissecting the indistinct and non-specific psychopathology of FEP in order to better target specific interventions., (© 2019 John Wiley & Sons Australia, Ltd.)