A Mixture Modeling of the Predictors of Internet Addiction: Cognition and Dissociation.

Abstract

This study aimed to explore the heterogeneity in the symptoms of pathological Internet use. The predictive role of online cognitions and online dissociative experiences on pathological Internet use were investigated. Three hundred and ninety Turkish undergraduate students (261 females) participated in the study. Latent class analysis (LCA) was performed. Items responses on the 26-item Chen Internet Addiction Scale were subjected to LCA. The LCA identified three latent classes: (1) Normal Internet Users (n = 141, 36.15%), (2) Problematic Internet Users (n = 148, 37.95%), and (3) Pathological Internet Users (n = 101, 25.90%). The multinomial regression analysis showed that online cognitions, anxious arousal, and online dissociation were significantly associated with pathological Internet use. Our findings showed that the online dissociation as measured by the Van Online Dissociative Experiences Schedule and mental dissociation as indexed by the Dissociative Experiences Scale are qualitatively different constructs in relation to addictive behaviors on the net. Online dissociation and online cognitions seem to be crucial vulnerability factors for pathological Internet use.