Deficits in social cognition (SC) are significantly related to community functioning in schizophrenia (SZ). Few studies investigated longitudinal changes in SC and its impact on recovery. In the present study, we aimed: (a) to estimate the magnitude and clinical significance of SC change in outpatients with stable SZ who were assessed at baseline and after 4 years, (b) to identify predictors of reliable and clinically significant change (RCSC), and (c) to determine whether changes in SC over 4 years predicted patient recovery at follow-up.

The reliable change index was used to estimate the proportion of true change in SC, not attributable to measurement error. Stepwise multiple logistic regression models were used to identify the predictors of RCSC in a SC domain (The Awareness of Social Inference Test [TASIT]) and the effect of change in TASIT on recovery at follow-up.

In 548 participants, statistically significant improvements were found for the simple and paradoxical sarcasm of TASIT scale, and for the total score of section 2. The reliable change index was 9.8. A cut-off of 45 identified patients showing clinically significant change. Reliable change was achieved by 12.6% and RCSC by 8% of participants. Lower baseline TASIT sect. 2 score predicted reliable improvement on TASIT sect. 2. Improvement in TASIT sect. 2 scores predicted functional recovery, with a 10-point change predicting 40% increase in the probability of recovery.

The RCSC index provides a conservative way to assess the improvement in the ability to grasp sarcasm in SZ, and is associated with recovery.

Resilience is defined as the ability to modify thoughts to cope with stressful events. Patients with schizophrenia (SCZ) having higher resilience (HR) levels show less severe symptoms and better real-life functioning. However, the clinical factors contributing to determine resilience levels in patients remain unclear. Thus, based on psychological, historical, clinical and environmental variables, we built a supervised machine learning algorithm to classify patients with HR or lower resilience (LR).

SCZ from the Italian Network for Research on Psychoses (N = 598 in the Discovery sample, N = 298 in the Validation sample) underwent historical, clinical, psychological, environmental and resilience assessments. A Support Vector Machine algorithm (based on 85 variables extracted from the above-mentioned assessments) was built in the Discovery sample, and replicated in the Validation sample, to classify between HR and LR patients, within a nested, Leave-Site-Out Cross-Validation framework. We then investigated whether algorithm decision scores were associated with the cognitive and clinical characteristics of patients.

The algorithm classified patients as HR or LR with a Balanced Accuracy of 74.5% (p < 0.0001) in the Discovery sample, and 80.2% in the Validation sample. Higher self-esteem, larger social network and use of adaptive coping strategies were the variables most frequently chosen by the algorithm to generate decisions. Correlations between algorithm decision scores, socio-cognitive abilities, and symptom severity were significant (pFDR < 0.05).

We identified an accurate, meaningful and generalizable clinical-psychological signature associated with resilience in SCZ. This study delivers relevant information regarding psychological and clinical factors that non-pharmacological interventions could target in schizophrenia.

People with severe mental illnesses (SMI) have a mortality rate two times higher compared to the general population, with a decade of years of life lost. In this randomized controlled trial (RCT), we assessed in a sample of people with bipolar disorder, major depressive disorder, and schizophrenia spectrum disorder, the efficacy of an innovative psychosocial group intervention compared to a brief psychoeducational group intervention on patients’ body mass index (BMI), body weight, waist circumference, Framingham and HOMA-IR indexes.

This is a multicentric RCT with blinded outcome assessments carried out in six Italian university centers. After recruitment patients were randomized to receive a 6-month psychosocial intervention to improve patients’ physical health or a brief psychoeducational intervention. All recruited patients were assessed with standardized assessment instruments at baseline and after 6 months. Anthropometric parameters and blood samples have also been collected.

Four-hundred and two patients with a diagnosis of bipolar disorder (43.3%), schizophrenia or other psychotic disorder (29.9%), or major depression (26.9%) were randomly allocated to the experimental (N = 206) or the control group (N = 195). After 6 months, patients from the experimental group reported a significant reduction in BMI (odds ratio [OR]: 1.93, 95% confidence intervals [CI]: 1.31–2.84; p < 0.001), body weight (OR = 4.78, 95% CI: 0.80–28.27, p < 0.05), and waist circumference (OR = 5.43, 95% CI: 1.45–20.30, p < 0.05). Participants with impaired cognitive and psychosocial functioning had a worse response to the intervention.

The experimental group intervention was effective in improving the physical health in SMI patients. Further studies are needed to evaluate the feasibility of this intervention in real-world settings.

Previous researches highlighted among patients with schizophrenia spectrum disorders (SSD) a significant presence of autistic traits, which seem to influence clinical and functional outcomes. The aim of this study was to further deepen the investigation, evaluating how patients with SSD with or without autistic traits may differ with respect to levels of functioning, self-esteem, resilience, and coping profiles.

As part of the add-on autism spectrum study of the Italian Network for Research on Psychoses, 164 outpatients with schizophrenia (SCZ) were recruited at eight Italian University psychiatric clinics. Subjects were grouped depending on the presence of significant autistic traits according to the Adult Autism Subthreshold Spectrum (AdAS Spectrum) instrument (“AT group” vs “No AT group”). Other instruments employed were: Autism Spectrum Quotient (AQ), Specific Levels of Functioning (SLOF), Self-Esteem Rating scale (SERS), Resilience Scale for Adults (RSA), and brief-COPE.

The “AT group” reported significantly higher scores than the “No AT group” on SLOF activities of community living but significantly lower scores on work skills subscale. The same group scored significantly lower also on SERS total score and RSA perception of the self subscale. Higher scores were reported on COPE self-blame, use of emotional support and humor domains in the AT group. Several correlations were found between specific dimensions of the instruments.

Our findings suggest the presence of specific patterns of functioning, resilience, and coping abilities among SSD patients with autistic traits.

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.