The Effect of Cognitive-Behavioral Therapy on Reducing Symptoms and Negative Consequences of Internet Addiction in Adolescents: A Systematic Review and Meta-Analysis

Background and aims: Internet addiction among adolescents has become an increasingly important public health concern worldwide. This study examined the effectiveness of cognitive-behavioral therapy (CBT) in reducing the symptoms and negative consequences of internet addiction in adolescents. Methods: A systematic search was conducted in English, Persian, and other languages for clinical and experimental studies published between 2000 and 2025 on adolescents aged 13–18 years with internet addiction, focusing on CBT-based interventions. Eligible studies compared CBT with control or non-addicted groups and reported outcomes related to reductions in social media addiction. Two independent reviewers screened studies, extracted data, and assessed methodological quality using the Consolidated Standards of Reporting Trials (CONSORT) checklist. Publication bias was evaluated using the Egger test. Primary outcomes were analyzed using a random-effects model in Stata 17 to account for expected heterogeneity. Results: This meta-analysis of nine studies found that CBT significantly reduces internet addiction in adolescents (SMD=1.05, P=0.003), although results varied widely across studies (I²=94.4%). Individual CBT interventions were consistently effective, while group-based interventions demonstrated greater variability and, in some cases, less significance. Experimental studies yielded more reliable positive effects than clinical trials. Secondary outcomes revealed only modest reductions in overall time spent online following group CBT. Meta-regression analyses did not explain the high heterogeneity, indicating that unmeasured factors may influence outcomes. No significant publication bias was detected, supporting the robustness of the findings. Conclusion: CBT effectively reduces internet addiction among adolescents; however, more standardized, high-quality studies are needed to optimize interventions.