ABSTRACT

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.

摘要

本研究旨在确定可以预测吸毒成瘾者攻击性的相关心理社会因素。共有 896 名男性参与者（平均_年龄 = 38.30 年）完成了调查。梯度提升回归是一种机器学习算法，用于寻找可能与攻击行为显着相关的相关心理社会变量，如心理安全、心理资本、人际信任和述情障碍。结果表明，预测攻击性的五个最重要因素是人际信任、心理安全、心理资本、父母冲突和述情障碍。高水平的人际信任、心理安全和心理资本可以预测吸毒者的低攻击性，而高水平的父母冲突和述情障碍可以预测高水平的攻击。总体，