Background Adolescents or young adults’ physical and mental health, along with their academic performance, are negatively impacted by Internet addiction (IA), with such behavior being associated with the onset of cognitive and mental health disorders. Consequently, this issue has emerged as a pressing global social problem that demands urgent resolution. Objective This research employed a meta-analytic approach to systematically assess the efficacy of diverse exercise-based interventions in mitigating IA among university students. The primary objective was to determine optimal therapeutic exercise modalities and formulate evidence-based guidelines for subsequent intervention strategies targeting adolescent internet overuse. Methods A comprehensive systematic literature search was conducted across multiple international and domestic databases, including Web of Science, PubMed, Embase, Cochrane Library, China Knowledge, and Wanfang. Methodological quality was evaluated utilizing the revised Cochrane Risk of Bias tool for randomized trials. Subsequently, both conventional and network meta-analyses were performed employing Review Manager 5.3 and Stata 14.0 statistical software packages. Results Traditional meta-results showed that exercise intervention was better than the control group in improving adolescent IA (SMD= -2.33, 95%CI -3.00, -1.66). Network meta-analysis(NMA) showed that Combined movement (CM) improved adolescent IA better than Control group (CG) (SMD-3.47, 95% -4.85, -2.10), and CM had the highest probability of being the best intervention for IA (SUCRA = 86.7%). Conclusion Exercise-based interventions demonstrate significant therapeutic efficacy in addressing IA, with CM exhibiting superior effectiveness for adolescent populations. Nevertheless, given the methodological limitations imposed by restricted sample sizes and heterogeneous literature quality, future large-scale randomized controlled trials are warranted to validate these preliminary findings. Systematic review registration https://www.crd.york.ac.uk/prospero/ , identifier CRD420251006694.
Li et al. (Wed,) studied this question.