Cart and Chaid Analyses of Some Variables that Predict Internet Addiction

Gunuc S.

TURK PSIKOLOJI DERGISI, vol.28, no.71, pp.88-104, 2013 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 28 Issue: 71
  • Publication Date: 2013
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.88-104
  • Keywords: Internet addiction, perceived social support, CART, CHAID, decision trees, SOCIAL SUPPORT, ADOLESCENTS, DISORDER, CRITERIA, ONLINE, FAMILY, LIFE
  • Anadolu University Affiliated: Yes


The aims of the current study centered on investigating some of the variables that predicted internet addiction in adolescents with the help of decision tree techniques and comparing and contrasting the differences in internet addiction prediction as a categorical and continuous variable by utilizing CART and CHAID techniques. The sample of the study consisted of 165 adolescents with normal development consulting the children's clinic of a State Hospital in Turkey for five months in 2012 for temporary problems related to the period of adolescence. It was used data collection tools which are Internet Addiction Scale, Multidimensional Scale of Perceived Social Support and personal information form. In the study, predicted or dependent variable was internet addiction whereas predictor or independent variables were 17 variables related to social relationships and internet use In conclusion, the current study found a negative relationship between internet addiction and perceived social support from family and friends. Also, it found a positive relationship between internet addiction and the duration of internet use. The study also identified that using internet for purposes of games, chat or pornography increased the level of addiction. When internet addiction was investigated as a categorical or continuous variable, CART and CHAID analyses findings showed that clearer information and findings were obtained by including internet addiction to the analyses as a continuous variable. In addition, CART and CHAID findings were compared and it was observed that CART analysis predicted the model more correctly compared to CHAID analysis. However, it was observed that the difference was not large between CART and CHAID findings.