Autism spectrum disorders (ASDs) and schizophrenia spectrum disorders (SSDs), although conceptualized as separate entities, may share some clinical and neurobiological features. ASD symptoms may have a relevant role in determining a more severe clinical presentation of schizophrenic disorder but their relationships with cognitive aspects and functional outcomes of the disease remain to be addressed in large samples of individuals.

To investigate the clinical, cognitive, and functional correlates of ASD symptoms in a large sample of people diagnosed with schizophrenia.

The severity of ASD symptoms was measured with the PANSS Autism Severity Scale (PAUSS) in 921 individuals recruited for the Italian Network for Research on Psychoses multicenter study. Based on the PAUSS scores, three groups of subjects were compared on a wide array of cognitive and functional measures.

Subjects with more severe ASD symptoms showed a poorer performance in the processing speed (p = 0.010), attention (p = 0.011), verbal memory (p = 0.035), and social cognition (p = 0.001) domains, and an overall lower global cognitive composite score (p = 0.010). Subjects with more severe ASD symptoms also showed poorer functional capacity (p = 0.004), real-world interpersonal relationships (p < 0.001), and participation in community-living activities (p < 0.001).

These findings strengthen the notion that ASD symptoms may have a relevant impact on different aspects of the disease, crucial to the life of people with schizophrenia. Prominent ASD symptoms may characterize a specific subpopulation of individuals with SSD.

One in six adolescents suffers from mental health problems. Despite the presence of general information on Italian adolescents' mental health, researches conducted with standardized assessment tools are scarce in the literature. We evaluated the prevalence of self-reported behavioral and emotional problems in a group of Italian adolescents and examined their relation to socio-demographical variables.

This population-based sampling survey was conducted on high school students aged 14–18 from urban areas of Rome and Latina. Participants completed Youth Self-Report (YSR) and a socio-demographic schedule to collect information on age, gender, type of school attended, socio-economic status, urbanicity.

Final sample consisted of 1400 adolescents (38.61% male, mean age 16 years, s.d. 1.42). Prevalence of Internalizing Problems, Externalizing Problems and Total Problems was 29.55%, 18.34% and 24.13%. In our multivariable model, Internalizing Symptoms were not explained by sociodemographic variables while Externalizing Symptoms were explained by Male Gender [OR = 1.53 (1.14–2.06)], older age [OR = 2.06 (1.52–2.79)] and attending a Technical and Professional Institute [OR = 2.15 (1.53–3.02)], with an adjusted R2 = 4.32%. Total Problems were explained by School Type [Technical and Professional Institutes and Art and Humanities v. Grammar and Science School; OR respectively 1.93 (1.40–2.67) and 1.64 (1.08–2.47)], adjusted R2 = 1.94.

The study provides, for the first time, evidence of a great prevalence of self-reported behavioral and emotional problems in a large sample of Italian adolescents, highlighting the role of different socio-demographic variables as risk factors for externalizing behaviors. Our results emphasize the urgent need for implementing prevention programs on mental health in adolescence.

Greater levels of insight may be linked with depressive symptoms among patients with schizophrenia, however, it would be useful to characterize this association at symptom-level, in order to inform research on interventions.

Data on depressive symptoms (Calgary Depression Scale for Schizophrenia) and insight (G12 item from the Positive and Negative Syndrome Scale) were obtained from 921 community-dwelling, clinically-stable individuals with a DSM-IV diagnosis of schizophrenia, recruited in a nationwide multicenter study. Network analysis was used to explore the most relevant connections between insight and depressive symptoms, including potential confounders in the model (neurocognitive and social-cognitive functioning, positive, negative and disorganization symptoms, extrapyramidal symptoms, hostility, internalized stigma, and perceived discrimination). Bayesian network analysis was used to estimate a directed acyclic graph (DAG) while investigating the most likely direction of the putative causal association between insight and depression.

After adjusting for confounders, better levels of insight were associated with greater self-depreciation, pathological guilt, morning depression and suicidal ideation. No difference in global network structure was detected for socioeconomic status, service engagement or illness severity. The DAG confirmed the presence of an association between greater insight and self-depreciation, suggesting the more probable causal direction was from insight to depressive symptoms.

In schizophrenia, better levels of insight may cause self-depreciation and, possibly, other depressive symptoms. Person-centered and narrative psychotherapeutic approaches may be particularly fit to improve patient insight without dampening self-esteem.