@article{ref1,
title="Psychosocial factors predict the level of aggression of people with drug addiction: a machine learning approach",
journal="Psychology, health and medicine",
year="2021",
author="Lu, Hong and Xie, Chuyin and Lian, Peican and Yu, Chengfu and Xie, Ying",
volume="ePub",
number="ePub",
pages="ePub-ePub",
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. <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>",
language="en",
issn="1354-8506",
doi="10.1080/13548506.2021.1910321",
url="http://dx.doi.org/10.1080/13548506.2021.1910321"
}