Suicide Risk Analysis and Psycho-Emotional Risk Factors Using an Artificial Neural Network System.

Suicidal behavior among young people has become an increasingly relevant topic after the COVID-19 pandemic and constitutes a public health problem. This study aimed to examine the variables associated with suicide risk and determine their predictive capacity. The specific objectives were: (1) to analyze the relationship between suicide risk and model variables and (2) to design an artificial neural network (ANN) with predictive capacity for suicide risk. The sample comprised 337 youths aged 18-33 years. An ex post facto design was used. The results showed that emotional attention, followed by problem solving and perfectionism, were variables that contributed the most to the ANN's predictive capacity. The ANN achieved a hit rate of 85.7%, which is much higher than chance, and with only 14.3% of incorrect cases. This study extracted relevant information on suicide risk and the related risk and protective factors via artificial intelligence. These data will be useful for diagnosis as well as for psycho-educational guidance and prevention. This study was one of the first to apply this innovative methodology based on an ANN design to study these variables.

Doctors and Nurses: A Systematic Review of the Risk and Protective Factors in Workplace Violence and Burnout.

The present study aims analyze the risk factors that lead to high levels of burnout among nurses and physicians and the protective factors that prevent them. Thus, it is also intended to explore the possible correlation between physical and verbal violence produced at work and the symptoms derived from burnout. Methods: The search was carried out on the Scopus, PubMed and Web of Science databases between 2000 and 2019 (on which date the bibliographic search ends). Descriptive studies estimating the prevalence of workplace violence and risk and protective factors and burnout were included. An adapted version of the Downs and Black quality checklist was used for article selection. 89.6 percent of the studies analysed were in the health sector. There is a significant correlation between burnout symptoms and physical violence at work. On the one hand, the risk factors that moderate this correlation were of structural/organisational type (social support, quality of the working environment, authoritarian leadership, little autonomy or long working days, etc.) and personal type (age, gender, nationality or academic degree, etc.). On the other hand, protective factors were the quality of the working environment, mutual support networks or coping strategies. The results were analysed in-depth and intervention strategies were proposed.