Background: Alcohol use disorder (AUD) is a major public health concern due to its various physical, psychological, and social consequences. Despite regulatory differences, abstinence remains the primary treatment objective. Addressing the multifaceted nature of alcohol use disorder requires a comprehensive approach.Methods: 150 AUD patients (66%male) with a mean age of 54.10 ± 11.3 years were recruited for the study. Depression, impulsivity, alexithymia, and hopelessness were assessed to determine if there were significant differences in these dimensions between abstinent (N=72) and active drinkers (N=78).Results: The study found significant differences in the psychological dimensions scores, active drinkers exhibited higher levels of depression, impulsivity, alexithymia, and hopelessness compared to abstinent patients.Conclusion: Treatment outcomes for patients with AUD vary between regulatory agencies, but abstinence remains the safest and most preferred objective in managing AUD. Prioritizing abstinence-oriented interventions is crucial for achieving long term recovery and minimizing relapse risk. These results emphasize the intricate relationship between AUD and mental health issues, highlighting the need for comprehensive interventions addressing both alcohol consumption and associated psychological distress. Promoting abstinence (or at least reducing alcohol consumption) not only preserves mental health but also prevents life-threatening consequences such as suicide.

Sensory processing is a fundamental aspect of human experience, and varies significantly between individuals, potentially affecting individual functioning, behaviour, and mental health. This study investigated the associations between sensory processing and psychopathology in a sample of the general population. Participants responded to a general psychiatric screening tool (DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure-Adult) and to the Adolescent/Adult Sensory Profile (AASP) questionnaire. The sample comprised 1108 young adults (77.25% females, mean age 22.6). Data were analysed using item response theory and Bayesian network analyses, revealing specific associations between sensory profiles and psychopathological dimensions. Specifically, we detected associations between the low registration sensory profile and the dimensions of psychosis, substance use, and mania. Sensation seeking was associated with mania. Sensory sensitivity was related to depression and mania, while sensation avoiding was inversely correlated with mania. These findings suggest that reduced external sensory awareness may be linked to a predisposition to psychosis, while a multifaceted sensory processing pattern may indicate vulnerability to mood disorders. Assessing sensory processing could yield crucial insights into individual susceptibilities to mental disorders and help identify targeted preventive and therapeutic strategies

Background: Peripersonal Space (PS) is represented as the immediate area surrounding an individual. The extent of PS changes in relation to several factors, including emotional states, type of relationship or psychopathology. Attachment anxiety has an impact on the social adaptability of peripersonal space and anxiety and fear are associated with an expansion of peripersonal space, possibly serving as a mechanism of self-protection. Peripersonal space appears to be intricately linked to various psychiatric conditions like anxiety disorders and converging evidence suggests that social maladjustment may predict or exacerbate eating disorder symptoms expression.Methods: Fifty-eight healthy adolescents (38F, 20M) performed a comfort distance estimation task to assess peripersonal space. The Adolescent/Adult Sensory Profile (AASP) was used to assess sensory profiles and the SAFA protocol to investigate psychopathological aspects. Data was analysed using Network Analysis, estimating a Gaussian Graphical Models with a Bayesian approach.Results: We found that the task related to comfort estimation distance demonstrated a correlation with the visual scale of the Adolescent/Adult Sensory Profile (AASP). Additionally, a correlation was observed with the Eating Disorder scale of the SAFA protocol. The touch scale also was negatively correlated with Eating disorder symptoms but not with the comfort estimation task.Conclusion: Our results demonstrate a relation between peripersonal space and eating disorder symptoms in healthy adolescents in line with previous findings in adults with eating disorders diagnosis. These findings suggest that socio-emotional difficulties may be possible precursors or reinforce for the development of an eating disorder symptoms.

Purpose: Reinforcement learning with reversal is a paradigm frequently employed in neuropsychology to assess the adaptive capacity and flexibility in individuals in non-stationary environments. Each single behavior, however, depends on the superimposition of multiple factors, which are still not completely understood. Methods: We optimize a neurocomputational model of the Basal Ganglia to simulate the behavior of 18 patients with Parkinson’s disease (both ON and OFF medication) and 14 control subjects during a two-choice probabilistic reversal learning task (with 80–20% reward probabilities). The individual behavior (in terms of the cumulative number of correct responses during a 40-trials direct phase and a 40-trial reversal phase) is reproduced by fitting a few model parameters for each individual, representing the tonic dopamine level, Hebbian learning, and the exploratory attitude (noise level). Results: Results show that very different responses can be explained quite well, ascribing them to the varying combination of the aforementioned individual factors. The tonic dopamine level is significantly different for patients in ON and OFF medication, while the other parameters were not statistically different. A regression analysis reveals that the value of the Hebbian learning rate is correlated with the subject's sensitivity to punishments. In contrast, the noise standard deviation is correlated with exploration, i.e., the tendency to modify the choice even after a reward. Conclusion: The results provide a mechanistic explanation of the various factors that affect adaptation and flexibility in reinforcement learning, representing a first step toward characterizing and understanding the diverse behaviors on an individual basis.