Prevalence of Internet Addiction and Gaming Disorders in Southeast Asia: A Meta-Analysis

Abstract

This meta-analytic review aimed to examine the pooled prevalence rates of Internet addiction and gaming disorders in Southeast Asia. Several databases including PubMed, MEDLINE, PsycINFO, Web of Science, Embase, and Cochrane Central were searched and a total of 24 studies were included in this study. The selection of studies was conducted in accordance to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Two meta-analyses were conducted to examine data on Internet addiction and gaming disorders separately. A random-effects model was employed to derive the pooled prevalence rate. Mixed-effects meta-regression and subgroup analyses were performed to examine the moderators of the between-study heterogeneity. Publication bias was tested using the Egger's regression test and funnel plot. Only seven out of the 11 Southeast Asian countries were represented in the literature. All except for two of the included studies were cross-sectional in nature. The findings revealed a pooled prevalence rate of 20.0% (95% confidence interval: 14.5%-27.0%) and 10.1% (95% confidence interval: 7.3%-13.8%) for Internet addiction and gaming disorders respectively. Mean age and study population were significant moderators of the between-study heterogeneity in the prevalence rates of gaming disorders such that samples involving older participants showed higher prevalence rate than those involving younger individuals. Country of study was found to be significant moderator of the between-heterogeneity for both Internet addiction and gaming disorders, however the findings should be interpreted with caution due to the small and unbalanced sample sizes. There was no significant publication bias. Such epidemiology research should be extended to the Southeast Asian countries that have not been studied or are under-studied. Given that the prevalence rates appear to be higher in Southeast Asia than in other world regions, future research should also explore the factors behind these inter-regional differences. Further longitudinal studies should also be conducted to examine the trajectories of such disorders.

Prevalence And Risk Factors Of Internet Addiction Among Hungarian High School Teachers

“…In a recent meta analysis the rate of internet addiction was 7.2% in the general population, which is far lower than it would be expected by the IA rate of adolescents which can be as high as 20% (13,14). In out study the rate of IA was 5.2%, which is comparable to the above mentioned ndings.…”

Prevalence of Internet Gaming Disorder and Its Association With Personality Traits and Gaming Characteristics Among Chinese Adolescent Gamers

“…It can be speculated that young adults and college students tend to have more autonomy and opportunities to use smart devices than younger students do. Therefore, due to their technological proficiency and lack of external supervision, they may be more prone to suffer from gaming disorders ( 14 ). More research is needed to verify these results.…”

“…Due to the differences in measurement tools and cultural backgrounds, different prevalence rates of IGD were reported among young people. For example, prevalence in Europe was between 1.2 and 1.6% (11,12), while in Asia it ranged from 1.6 to 18.4% (13)(14)(15). Some studies reported that the rates of possible IGD among adolescents in China ranged between 2.0 (15) and 17.0% (16).…”

Prevalence and Risk Factors of Internet Addiction among Hungarian High School Teachers

“…Although this technological revolution has improved many aspects of our lives and it is now an essential part of the everyday routine, including work, private life and social functioning, many studies reported the misuse of internet (problematic internet use, internet addiction; IA) as summarized in a recent meta-analysis including 113 epidemiologic studies covering 693,306 subjects showed that the pooled prevalence of internet addiction was 7.02% (95% CI, 6.09–8.08%) in the population aged 7–60 years [ 1 ]. Age (adolescent samples), lower cut-off scores (and type of questionnaire), sample size (more common is smaller samples), and country of origin (more frequent in Asian studies) were significant predictors of higher prevalence [ 2 , 3 ].…”