US Soldiers and Leadership Roles: COVID-19, Mental Health and Public Health Guidelines - BMC Public Health

Social media use and mental health during the COVID-19 pandemic in young adults: a meta-analysis of 14 cross-sectional studies – BMC Public Health

Eligibility criteria

Studies were included that met the following criteria: (1) use of the English language; (2) carried out after 11 March 2020 (the date on which the WHO declared a pandemic) and published by 20 December 2020; (3) data collected using a validated mental health symptom tool (e.g., patient health questionnaire: PHQ9, generalized anxiety disorder-7 items: GAD-7); (4) available full texts; (5) measured time spent on a social media platform in continuous or categorical variables; (5) provided their results in OR, β and / or Pearson’s ra (6) studies measured mental health symptoms such as anxiety and depression.

Studies with the following characteristics were excluded: (1) Studies examined traditional social media (eg television and radio); (2) case reports, letters, comments and narrative reviews without quantitative results; and (3) studies using a language other than English.

Studies examining the relationship between time spent on social networks and mental health outcomes (eg anxiety and depression) were summarized in Supplement 1. The magnitude of the overall effect of this meta-analysis was presented mainly in terms of odds (Figure 2).

Study selection

The principles of the search strategy were as follows: (1) “Social media” or individual social media titles in the title, keyword and abstract of the results; (2) Terms referring to mental health with COVID-19 in the title (eg depression, anxiety or blue).

To identify the studies, a systematic literature search was performed in the PubMed, Embase and Cochrane Library databases. The publication date limits are from March 2020 to December 20, 2020. The search terms for systematic search were as follows: (1) (“COVID-19” OR “corona”) A (“mental health” OR depression * OR anxiety) A (” social media “OR” Instagram “OR” Facebook “OR” twitter “) for PubMed, (2) (” coronavirus disease 2019 ‘/ exp / mj) A (“mental health” / exp / mj OR “depression” / exp OR “Anxiety” / exp) A (“social media” / exp./mj OR “Facebook” / exp. OR “twitter” / exp. OR “Instagram” / exp) for Embase; (3) A (“COVID-19” OR “corona”) A (“mental health” OR depression * OR “anxiety”) A (“social media” OR “Instagram” OR “Facebook” OR “twitter”) for the Cochrane Library .

The articles were first screened by title reviews, followed by a full-text review. Each selection phase involved three independent researchers (two physicians [SJJ and YRL] and one graduate student from the Department of Epidemiology [YJJ]). Each article was independently evaluated first by two researchers (YJJ and YRL) and a third researcher (SJJ) mediated the final selection in case of differences of opinion.

Data extraction

Study data were extracted by two independent researchers (YRL and YJJ). The only author first extracted the information and the second author checked the accuracy. The information extracted is as follows: country of study, sample group of participants, age group of the sample, date of data collection, mental health measures, information on the magnitude of the effect, time of social media use and whether an adjustment was made for each analysis (see Supplemental Material 1). The studies were categorized according to a cumulative effect size estimate [OR]beta estimate from multiple linear regression [β]and correlation coefficient [Pearson’s r]).

Exposure variables

The final post-search studies measured the amount of time spent on social media, which were either categorical or continuous variables (see Supplementary Material 1). It was measured by answering a questionnaire: “How often have you been exposed to social networks? [categorical]”And” How long (in hours) have you been exposed to social media? [continuous]The exposure measurement was expressed in different words as follows: “Less” vs. “Often”, “Less” vs. “Often”, “less than 1 hour” vs. “2 hours or more” or “less than 3” hours vs. “3 hours or more.” To calculate the overall effect, these individually measured exposure levels were operationally redefined (eg “Less” and “Few” were considered the same as “less than 2 hours;”, “less than 1 hour”, ” Often “and” Often “.” Were considered “2 hours or more” and “3 hours or more”).

Result variables

The results of the studies included were “anxiety” and “depression”. Anxiety was assessed using GAD-7 (limit: 10+), DASS-21 and PHQ-9, while depression was measured using PHQ-9 (limit: 10+), WHO-5 (limit: 13+) and GHQ-28 (cut-off: 24+). Anxiety and depression measured using screening tools with cut-off values ​​represented outcome ratio results (see Supplementary Material 1).

Statistical analysis

All statistical analyzes and visualizations were performed with the package “meta”, “metaphor” and “dmeter” version R 3.6.3 ( using a random effect model [13,14,15]. The measures of effect were odds ratio, regression coefficient, and Pearson’s r, which calculated the relationship between the increase in social media use and the symptoms of anxiety and depression. In each study, the relationship to mental health levels in the frequent social media use group (compared to the low frequency group) was calculated as a odds ratio and the relationship to the increase in mental health levels per hour was calculated as the regression coefficient (β) and Pearson’s r. used to calculate the pooled effects (eg, odds ratio, regression coefficient, and Pearson’s r) were used as the adjusted value with the covariates from each study, not with the unadjusted gross values.

Combined effects sizes, Cochran’s Q and I2 to assess heterogeneity were calculated. The combined effect sizes, CIs, and prediction intervals were calculated by estimating the combined effect and CIs using the Hartung-Knapp-Sidik-Jonkman method, which is known to be one of the most conservative methods. [16]. The degree of heterogeneity was categorized as low, medium or high with thresholds of 25, 50 and 75%, respectively. [17]. Possible causes of heterogeneity between study results were investigated by statistical methods such as impact analysis, Baujat graph, omission analysis, and graphical representation of heterogeneity analysis. [18]. In addition, publication bias was assessed using funnel graphs, Egger tests, and the trim-and-fill method [19].

Quality assessment

The quality assessment was performed by two independent researchers, a psychiatrist (SHK) and an epidemiologist (YRL), using a non-randomized bias risk assessment tool (RoBANS) who can evaluate cross-sectional studies. [20]. RoBANS has been validated with medium reliability and good validity. RoBANS covers cross-sectional studies and includes six items: participant selection, confusion, exposure measurement, blinding of assessment results, missing results and selective reporting of results. Each item is rated as “high distortion risk”, “low distortion risk” or “uncertain”. For example, based on “participant selection”, each researcher described an article as having a “high risk of bias” if, for example, the definitions of depression in patients were based on data he or she provided. In cross-sectional studies, cases of incorrect classification due to an unreliable separate questionnaire for categorizing patients with depression were rated as “high risk”. For qualitative evaluation, studies with two or more grades of “high risk of bias” were classified as “low quality”. The study was rated as “good” only if the evaluators’ ratings were the same. For the sensitivity analysis, an additional analysis was performed involving only “high quality” studies and this was compared with aggregate estimates of the overall results (see Table 1).

Table 1 Associations between social media use and anxietyAND and depressionb

Ethical approval

The preferred reporting items for the Systematic Review and Meta-Analysis (PRISMA) Guidelines 2020 were followed for this study. No ethical approval and patient consent is required as these study data are based on published literature. This meta-analysis was registered with PROSPERO (, registration number CRD42021260223, 15 June 2021).

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