Correlations between social media addiction and anxiety, depression, FoMO, loneliness and self-esteem among students: A systematic review and meta-analysis

Background and aims With the ubiquity of the internet, social media have become an essential part of daily life. There are various types of social media, such as Facebook, Twitter, TikTok, WeChat and SNS. Social media addiction (SMA) was found to be significantly associated with mental health concerns, self-esteem, fear of missing out (FoMO), and loneliness on the basis of a literature review concerning SMA. To further explore the connections between SMA and anxiety, depression, self-esteem, FoMO and loneliness, we performed a meta-analysis to quantitatively synthesize the previous findings, Methods The PubMed, Embase, Web of Science, Chinese National Knowledge Infrastructure (CNKI), Chinese Biological Medicine (CBM) and Technology Journal Database (VIP) databases were accessed to perform a systematic review and meta-analysis. This search was updated in April. Pooled Pearson’s correlation coefficients between SMA and anxiety, depression, loneliness, FoMO and self-esteem were calculated with STATA software via a random or fixed effects model. Results Thirty-two studies involving a total of 26166 students were identified. The meta-analysis revealed positive correlations between SMA and anxiety, depression, loneliness and FoMO (anxiety: summary r = 0.31, 95% CI = 0.25–0.36, P < 0.001; depression: summary r = 0.31, 95% CI = 0.27–0.34, P < 0.001; loneliness: summary r = 0.21, 95% CI = 0.13–0.29, P < 0.001; FoMO: summary r = 0.41, 95% CI = 0.36–0.45, P < 0.001). A negative correlation was found between self-esteem and SMA (self-esteem: summary r = -0.24, 95% Cl = -0.26– -0.22, P<0.001). Conclusions This meta-analysis revealed that SMA was positively associated with anxiety, depression and loneliness but negatively associated with self-esteem. These findings indicate that students with SMA are more likely to suffer from anxiety, depression and loneliness. Conducting larger prospective studies would be beneficial to verify our findings.