Influence of school-level and family-level variables on Chinese college students’ aggression

Violent Behaviours among Adolescents and Young Adults: Association with Psychoactive Substance Use and Parenting Styles

This study extends existing research on the relationship between psychoactive substance use among young people and violent behaviour, by evaluating the possible effect of the modification of parenting in a nationally representative sample of 14,685 Italian students drawn from the 2019 wave of the ESPAD Italia survey (51% male; mean age about 17 years). Parental dimensions considered in the study were rule-setting, monitoring, and emotional support, as well as the possible absence of a parent. Relative risk ratios and binary logistic regressions were used to estimate the associations separately for adolescents (15–17) and young adults (18–19). Overall, parental rule-setting, perceived parental monitoring, and emotional support were protective factors for substance use, and the strength of this relationship increased with the frequency of use. Among adolescents, the absence of a parent represented a risk factor. In both age groups, the odds of engaging in violent behaviour was increased among those reporting alcohol intoxication and substance use and the greater the frequency of use, the greater the increase in the odds. As parental monitoring and emotional support decreased, the odds of engaging in violent behaviour increased (except in the case of lower parental support among young adults), while the opposite applies to parental rule-setting. The odds of engaging in violent behaviour were increased among those reporting the absence of a parent only in the adolescent age group. Parental rule-setting was found to have an effect only among adolescents, increasing the odds of violent behaviour among frequent drinkers. Our results might be helpful to signal adolescents who would be more prone to adopt violent behaviour in order to target prevention policies.

Psychosocial Factors Predict the Level of Aggression of People with Drug Addiction: A Machine Learning Approach

This study aimed to identify the relevant psychosocial factors that can predict the aggression in people with drug addiction. A total of 896 male participants (Mean_age = 38.30 years) completed the survey. Gradient boosting regression, a machine learning algorithm, was used to find the relevant psychosocial variables, such as psychological security, psychological capital, interpersonal trust and alexithymia, that may be significantly related to aggressive behavior. Results showed that the five most important factors in the prediction of aggression are interpersonal trust, psychological security, psychological capital, parental conflict and alexithymia. A high level of interpersonal trust, psychological security and psychological capital can predict a low level of aggression in people with drug addiction, while a high level of parental conflict and alexithymia can predict a high level of aggression. Overall, the findings highlight the need to focus interventions according to the relation between these psychosocial factors and aggression in order to decrease violence.