Lu Hong, Xie Chuyin, Lian Peican, Yu Chengfu, Xie Ying
Center for Brain and Cognitive Sciences, School of Education, Guangzhou University, Guangzhou, China.
School of Education, Research Center of Adolescent Psychology and Behavior, Guangzhou University, Guangzhou, China.
Psychol Health Med. 2022 Jun;27(5):1168-1175. doi: 10.1080/13548506.2021.1910321. Epub 2021 Apr 19.
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 ( = 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.
本研究旨在确定能够预测吸毒成瘾者攻击行为的相关心理社会因素。共有896名男性参与者（平均年龄 = 38.30岁）完成了调查。采用梯度提升回归这一机器学习算法来找出可能与攻击行为显著相关的心理社会变量，如心理安全感、心理资本、人际信任和述情障碍。结果表明，预测攻击行为的五个最重要因素是人际信任、心理安全感、心理资本、父母冲突和述情障碍。高水平的人际信任、心理安全感和心理资本可预测吸毒成瘾者的低攻击水平，而高水平的父母冲突和述情障碍则可预测高攻击水平。总体而言，研究结果凸显了根据这些心理社会因素与攻击行为之间的关系来聚焦干预措施以减少暴力行为的必要性。
