%0 Journal Article
%T Psychosocial factors predict the level of aggression of people with drug addiction: a machine learning approach
%J Psychology, health and medicine
%D 2021
%A Lu, Hong
%A Xie, Chuyin
%A Lian, Peican
%A Yu, Chengfu
%A Xie, Ying
%V ePub
%N ePub
%P ePub-ePub
%X 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. <br><br>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.<p /> <p>Language: en</p>
%G en
%I Informa - Taylor and Francis Group
%@ 1354-8506
%U http://dx.doi.org/10.1080/13548506.2021.1910321