A discriminant analysis model of psychosocial predictors of problematic Internet use and cannabis use disorder in university students

Autor: Mehdi Akbari, Mohammad Hossein Bahadori, Shahram Mohammadkhani, Daniel C. Kolubinski, Ana V. Nikčević, Marcantonio M. Spada
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Addictive Behaviors Reports, Vol 14, Iss , Pp 100354- (2021)
Druh dokumentu: article
ISSN: 2352-8532
DOI: 10.1016/j.abrep.2021.100354
Popis: Researchers have found similarities and differences between behavioral and drug addictions. The present study was designed to explore which of a series of psychosocial predictors of addictive behaviors could differentiate problematic Internet use (PIU) and Cannabis Use Disorder (CUD) in a sample of University students. A total of 144 participants (76 males, mean age = 23.03 years ± 2.83) were separated into three groups: those presenting with PIU (18 females, Mean age = 22.27 years), those presenting with CUD (22 female, Mean age = 22.73 years), and a control group (28 female, Mean age = 24.04 years). Participants completed the Internet Abusive Use Questionnaire (IAUQ), the Severity of Dependence Scale (SDS), the Multidimensional Scale of Perceived Social Support (MSPSS), the Barratt Impulsiveness Scale-11 (BIS-11), the Multidimensional Distress Tolerance Scale (MDTS), the Emotion Regulation Questionnaire (ERQ), the Metacognitions Questionnaire-30 (MCQ-30), and the Repetitive Thinking Questionnaire-10 (RTQ-10). The classification analysis results showed that 68.8% of the control group, 70.8% of the PIU group, and 81.3% of the CUD group were correctly classified in their respective groups. In addition, the results of the discriminant function analysis showed that there was a significant difference between members of the PIU and CUD groups in the degree of family support (0.45), significant other (0.33), tolerance of physical discomfort (0.30), reappraisal (0.42), and cognitive confidence (0.35). The findings provide evidence that specific psychosocial predictors can discriminate PIU from CUD.
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