Investigating predictive factors of dialectical behavior therapy skills training efficacy for alcohol and concurrent substance use disorders: A machine learning study.

Background: Dialectical Behavior Therapy Skills Training (DBT-ST) as stand-alone treatment has demonstrated promising outcomes for the treatment of alcohol use disorder (AUD) and concurrent substance use disorders (SUDs). However, no studies have so far empirically investigated factors that might predict efficacy of this therapeutic model.

Methods: 275 treatment-seeking individuals with AUD and other SUDs were consecutively admitted to a 3-month DBT-ST program (in- + outpatient; outpatient settings).

Risk Perception and Media in Shaping Protective Behaviors: Insights From the Early Phase of COVID-19 Italian Outbreak.

In the absence of target treatments or vaccination, the SARS-CoV-2 pandemic can be impeded by effectively implementing containment measures and behaviors. This relies on individuals' adoption of protective behaviors, their perceived risk, and the use and trust of information sources. During a health emergency, receiving timely and accurate information enables individuals to take appropriate actions to protect themselves, shaping their risk perception.

A peripheral inflammatory signature discriminates bipolar from unipolar depression: A machine learning approach.

Background: Mood disorders (major depressive disorder, MDD, and bipolar disorder, BD) are considered leading causes of life-long disability worldwide, where high rates of no response to treatment or relapse and delays in receiving a proper diagnosis (~60% of depressed BD patients are initially misdiagnosed as MDD) contribute to a growing personal and socio-economic burden. The immune system may represent a new target to develop novel diagnostic and therapeutic procedures but reliable biomarkers still need to be found.

Methods: In our study we predicted the differential diagnosis of mood disorders by considering the plasma levels of 54 cytokines, chemokines and growth factors of 81 BD and 127 MDD depressed patients.

Neuropsychological deficits correlate with symptoms severity and cortical thickness in Borderline Personality Disorder.

Background: Neuropsychological abnormalities have been proposed to contribute to the development and maintenance of Borderline Personality Disorder (BPD). Previous meta-analyses and reviews confirmed deficits in a broad range of cognitive domains, including attention, cognitive flexibility, memory, executive functions, planning, information processing, and visuospatial abilities, often suggested to underlie brain abnormalities. However, no study directly explored the structural neural correlates of these deficits in BPD, also accounting for the possible confounding effect of pharmacological treatments, often used as adjunctive symptom-targeted therapy in clinical setting.