Higher levels of internet gaming disorder exist in males & higher levels of social media addiction exist in females; the effect sizes were larger in Europe and the Americas than in Asia

Do men become addicted to internet gaming and women to social media? A meta-analysis examining gender-related differences in specific internet addiction. Wenliang Su et al. Computers in Human Behavior, July 13 2020, 106480. https://doi.org/10.1016/j.chb.2020.106480

Highlights
• Gender differences exist globally in specific internet use behaviors/disorders.
• Higher levels of internet gaming disorder (IGD) exist in males.
• Higher levels of social media addiction (SMA) exist in females.
• The moderating influence of region existed in IGD and SMA.
• Studies of IGD and SMA may unmask features lost in studies of internet addiction.

Abstract: Males have been proposed to be more vulnerable to internet addiction (IA) than females. However, males and females may differ with respect to specific patterns and types of internet usage and related IA. To investigate further, a meta-analysis was conducted to investigate gender-related differences in internet gaming disorder (IGD) and social media addiction (SMA). The current meta-analysis aimed to quantify gender-related effect sizes relating to IGD and SMA, examine potential moderating influences of regions and other possible confounds, and compare the findings with generalized IA at the country level. The meta-analysis comprised 53 effect sizes with 82,440 individuals from 21 countries/regions for IGD, and 41 effect sizes with 58,336 individuals from 22 countries/regions for SMA. A random-effects model confirmed important gender-specific distinctions as men were more likely to exhibit IGD than women (g = 0.479) and less likely to exhibit SMA than women (g = −0.202). Additional moderator analyses revealed that effect sizes of IGD and SMA were larger in Europe and the Americas than in Asia. Further analyses indicated that the effect sizes of gender-related differences in IGD and SMA at the country-level were significantly larger than those in generalized IA, which suggests that gender-related differences in specific IAs may be underestimated in the “umbrella” of generalized IA. Results have implications for explaining why males and females may become addicted to internet use through different pathways.