Adding Clinical Validity to the Statistical Power of Large-Scale Epidemiological Surveys on Internet Addiction in Adolescence

Article AbstractObjective: Research has indicated that internet addiction is associated with psychosocial maladjustment in adolescence. Many epidemiologic surveys are lacking representativeness, and knowledge on disorder-specific risk factors is scarce. One weakness of epidemiologic studies often regards their lack of generalizability to clinical reality. The aim of this study was to provide a detailed description of internet addiction among adolescents, focusing on its prevalence in a population-based context, psychopathological correlates, and predisposing factors.Methods: The main analyses were based on 2 large representative samples of German adolescents (N = 9,293; 12-19 years) collected in 2012, and the results were validated on a consecutive sample of 237 treatment-seeking adolescents (from 2009-2014). The Scale for the Assessment of Internet and Computer Game Addiction (AICA-S), Strengths and Difficulties Questionnaire (SDQ), Symptom Checklist-90 Revised (SCL-90R), and NEO-Five Factor Inventory (NEO-FFI) were administered.Results: Internet addiction occurred in 2.6% of adolescents, with almost comparable rates in both genders, whereas female patients (1.3%) were underrepresented among the treatment seekers. Internet-addicted adolescents from the clinical and the nonclinical setting displayed higher psychopathology (SDQ: P < .001) and functional impairment (Global Assessment of Functioning: P < .001) than adolescents with nonproblematic internet use. Low conscientiousness (in boys: β = -0.161 to -0.220; in girls: β = -0.103 to -0.240) and high negative affect (in boys: β = 0.141 to -0.193; in girls: β = 0.175 to 0.290) were personality correlates of internet addiction.Conclusions: Internet addiction is a widespread problematic behavior among male and female adolescents, and it is related to psychopathological symptoms. Low conscientiousness and high negative affect were identified as stable correlates for internet addiction independent of age and gender and can therefore be considered as risk factors for internet addiction.