Social Media Use and Mental Health During the COVID-19 Pandemic: A Meta-Analysis of 14 Cross-Sectional Studies

Background: The isolation due to early coronavirus disease 2019 (COVID-19) quarantine had people using social media more than ever. Yet, there had been contradictory claims regarding the effect of social media use on mental health. To have a comprehensive rationale for resolving conflicting claims about mental health, we aimed to summarize the association between the time spent on social media during COVID-19 quarantine and mental health indicators, including anxiety, depression, and psychological distress. Methods: We included 327 studies from the PubMed, Embase, and Cochrane Library databases in our meta-analysis. These studies evaluated the association between social media use and mental health outcomes, including anxiety, depression, and distress ascertained by a screening tool with a validated cut-off value. Based on how the findings were presented in the original studies, we summarized the final 14 studies in terms of the odds ratios (ORs), regression coefficient (beta), and correlation coefficient (Pearson's r). Data analyses included a random-effect model and an assessment of inter-study heterogeneity. Findings: The time spent on social media was significantly associated with clinical anxiety and depression (anxiety: OR = 1·55, 95% CI: 1·31–1·83, I2 = 26·77%; Depression: OR = 1·43, 95% CI 1·14–1·80, I2 = 67·16%). However, no significant association was found in psychological distress (β = 0·09, 95% CI -0·29–0·46, I2 = 80·53%). Interpretation: Our analysis demonstrated that the time spent on social media was associated with a higher likelihood of anxiety and depression, but no significant association was observed with symptoms of psychological distress. Registration Details: This meta-analysis review was registered with PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration No CRD42021260223, 15 June 2021). Funding Information: This study was supported by the National Research Foundation of Korea, funded by the Ministry of Science (2020R1C1C1003502), awarded to Sun Jae Jung. Declaration of Interests: None.