Evidence Hub

Global prevalence of internet addiction among university students: a systematic review and meta-analysis

Xin Liu, Zhen Gui, Zi-Mu Chen, Yuan Feng, Xiao-dan Wu, Zhao-Hui Su, T. Cheung, G. Ungvari et al.

Current Opinion in Psychiatry, 2025

128,020 participants · 42 citations

Abstract

Purpose of review The prevalence of internet addiction among university students has been extensively studied worldwide, however, the findings have been mixed. This meta-analysis aimed to examine the global prevalence of internet addiction in university students and identify its potential moderators. Recent findings A total of 101 eligible studies, comprising 128020 participants across 38 countries and territories, were included. The pooled global prevalence of internet addiction among university students was 41.84% [95% confidence interval (95% CI): 35.89–48.02]. Significant differences in the prevalence were observed across different income levels, regions, periods of COVID-19 pandemic, and cut-off values of the Internet Addiction Test (IAT). Sample size was negatively associated with internet addiction prevalence, while depression prevalence was positively associated with internet addiction prevalence. Male students had a significantly higher risk of internet addiction compared to female students [pooled odd ratio (OR): 1.32, 95% CI: 1.19–1.46]. Summary This meta-analysis found that the prevalence of internet addiction was high among university students, which has increased since the COVID-19 pandemic. Screening and intervention measures to address internet addiction should prioritize students with an increased risk including male students, those from lower-income regions and those with depression.

How strong is the evidence?

Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 128,020 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free