Predictive power of the DSM-5 criteria for internet use disorder: A CHAID decision-tree analysis

Abstract

IntroductionAlthough the majority of internet users enjoy the internet as a recreational activity, some individuals report problematic internet use behaviors causing negative psychosocial consequences. Therefore, it is important to have precise and valid diagnostic criteria to ensure suitable treatment for those affected and avoid over-pathologization.MethodsThe aim of the present study was to determine which of the nine DSM-5 criteria of internet gaming disorder (IGD) are crucial in distinguish pathological from non-pathological internet use based on the questionnaire-based response behavior of the participants by applying the Chi-squared automatic interaction detection (CHAID) decision tree analysis. Under consideration of the nine DSM-5 criteria for IGD and according to the short-form scale to assess Internet Gaming Disorder (IGDS-SF9) the DSM-5 criteria were formulated as questions and applied to the broader concept of Internet Use Disorder (IUD). The nine questions were answered on a 5-point Likert scale from “never” to “very often.” In accordance with the IGDS-SF9 participants were assigned to IUD-5plus if at least 5 of the 9 criteria were answered with “very often.” The study was conducted in Germany (N = 37,008; mean age: 32 years, SD = 13.18, 73.8% male).ResultsAlthough “loss of control,” “continued overuse” and “mood regulation” were the most endorsed criteria, the analysis indicated that the criterion “jeopardizing” was found as the best predictor for IUD-5plus, followed by “loss of interest” and “continued overuse.” Overall 64.9% of all participants who were in the IUD-5plus, could been identified by the fulfillment of the three criteria mentioned above.DiscussionThe results found support for adjustment of the DSM-5 criteria of IGD in accordance to ICD-11. If the predictive power of the three criteria can be replicated in future representative studies, such a decision tree can be used as guidance for diagnostics to capture the particularly relevant criteria.