TY  - JOUR
PY  - 2021//
TI  - Psychosocial factors predict the level of aggression of people with drug addiction: a machine learning approach
JO  - Psychology, health and medicine
A1  - Lu, Hong
A1  - Xie, Chuyin
A1  - Lian, Peican
A1  - Yu, Chengfu
A1  - Xie, Ying
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - 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>
LA  - en
SN  - 1354-8506
UR  - http://dx.doi.org/10.1080/13548506.2021.1910321
ID  - ref1
ER  -