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Empirical literature has yielded a positive association between psychopathy levels and suicide attempts. This association is centred around impulsivity and disinhibitory facets of psychopathy, whereas suicide and emotional poverty remain independent. Evidence about the relation between suicide and psychopathy in mentally disordered offenders is not conclusive. The present work explores the relation between several measures of antisocial personality, suicide attempt and deliberate self mutilation in a sample of inmates from a forensic psychiatric hospital. Results support the association between disinhibitory aspects of personality and suicide in this population.

Background Italy was one of the first European countries to be affected by Covid-19. Due to the severity of the pandemic, the Italian government imposed a nationwide lockdown which had a great impact on the population, especially adolescents. Distance-learning, moving restrictions and pandemic-related concerns, resulted in a particularly stressful situation. Objective This cross-sectional study aims to analyse substance consumption and its associated factors during the Covid-19 lockdown imposed by the Italian government. Methods ESPAD is a questionnaire that is administered yearly in Italian high schools. In 2020, it was administered online during dedicated hours of distance learning, collecting data from 6027 Italian students (52.4% were male) aged 15–19. Data collected from the 2020 questionnaire was matched with that collected in 2019, in order to make them comparable. Results The prevalence of consumption of each substance decreased during the restriction period, and the most used substance during the lockdown period was alcohol (43.1%). There were some changes in factors associated with psychoactive substance use, especially painkillers and non-prescription drugs. For instance, unlike what was observed in the 2019 model, in 2020 spending money without parental control was associated with painkillers and non-prescription drug use while risk perception was not. Conclusions The restrictions and the increased difficulties in obtaining psychoactive substances did not prevent their consumption, and students with particular risk factors continued to use them, possibly changing the substance type of substance. This information is useful in order to better understand adolescents’ substance use during the ongoing pandemic.

Purpose This article reports on an ongoing research project, which is aimed at implementing advanced probabilistic models for real-time identification of hazardous events at construction sites. The model has intelligent capabilities for near real-time automated recognition of hazardous events during the execution phase. To achieve this, features of Bayesian Networks have been exploited. In addition, inputs to the model are assumed to be provided by a pervasive monitoring system deployed on the site. The need for this kind of intelligent tool is determined by the complexity inherent in construction sites, due to a variety of reasons, such as heterogeneity of the actors, the simultaneous nature of operations, harsh contextual conditions, and the only partially efficient current approach based on health and safety plans. Hence, this model is proposed as a support tool for health and safety coordinators for supervision of sites as they cannot guarantee a continuous physical presence. Method Given that there are no long-time series on past occurrences of hazardous events in all the potential contextual combinations presently available, the probabilistic models cannot be learned just through datasets. For that reason, the available data have been integrated with expert opinions. In particular, the conditional probabilities of the Bayesian networks are estimated by an elicitation process of subjective knowledge from the opinions of experts. The complexity of the phenomena under analysis are modelled as a tree structure with several levels (corresponding to the work-breakdown structure hierarchy), which itself is based on the top-down technique; it provides therefore a clear view of the global picture. The built-hierarchical tree allows the expert to weigh more easily causal relationships involved and also to define the qualitative structure of the net. Furthermore, the article describes and tests how conditional probabilities of the variables in the networks can be estimated, through gathering and interviewing groups of stakeholders and experts. Results & Discussion Our research has led to the definition of a probabilistic model using elicitation techniques for subjective knowledge. Furthermore, the development of such a model is part of a wider system relying on the implementation of a real-time monitoring network.