SynthesisPeerJ2025
Effectiveness of exercise as an intervention for internet addiction in adolescents: a meta-analysis.
Synthesis in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Temporal relationship between physical activity, social anxiety, and internet addiction among adolescents: a cross-lagged analysis.Scientific reports · 2026Article
- Multiscale Mechanisms of Exercise-Induced Neuroplasticity: From Molecular Pathways to Network Dynamics and Behavioral Adaptation.Brain sciences · 2026Review
- Effects of a Dance-Based Intervention on Affective States and Self-Esteem in Adolescents Receiving Psychiatric Care: Differences Between Youth with and Without Problematic Internet Use-A Pilot Study.Behavioral sciences (Basel, Switzerland) · 2026Article
- Aerobic running at different intensities produces distinct temporal patterns of improvement in depression, anxiety, and stress among adolescents with problematic internet use.Frontiers in psychology · 2026Article
- Exercise-based interventions for problematic short-video use: a narrative review of current evidence and potential psychological pathways.Frontiers in psychology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Internet addiction, particularly among adolescents, has become a pressing global concern, impacting psychological well-being and daily functioning. This meta-analysis aims to evaluate the effectiveness of exercise interventions in mitigating symptoms of internet addiction among adolescents. Methods: A comprehensive literature search was conducted across PubMed, Web of Science (WoS), Cochrane Library, Embase, Scopus, and China National Knowledge Infrastructure (CNKI) databases up to January 1, 2025. The search yielded 266 records, of which nine studies involving 654 adolescents met the inclusion criteria. The quality of the included studies was assessed using the Cochrane Risk of Bias tool. Meta-analyses, subgroup analyses, and sensitivity analyses were conducted using Review Manager 5.4 and Stata 17.0. Publication bias was evaluated using Egger's tests. This study is registered with PROSPERO (CRD42025632958). Results: The random effects model revealed that exercise interventions significantly reduced internet addiction scores compared to the control group (standardized mean difference (SMD) = -1.11, 95% CI [-1.60 to -0.62], Conclusions: These findings underscore the importance of integrating physical activity into therapeutic strategies for managing internet addiction. The findings of this study will be useful for healthcare workers and adolescents with Internet addiction. However, due to the high heterogeneity of the included literature, these findings should be interpreted with caution.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.