Prior research has investigated the link between social media use (SMU) and negative well-being. However, the connection with positive well-being has not been extensively studied, leading to a situation where there are inconsistent and inconclusive findings. This study fills this gap by examining the correlation between excessive and problematic SMU and subjective as well as psychological well-being (PWB). We conducted a systematic search across databases such as PubMed, Scopus, and Web of Science, and gray literature sources such as Research Gate and ProQuest, yielding 51 relevant studies for meta-analysis, encompassing a sample size of 680,506 individuals. Employing the Newcastle-Ottawa Scale, we assessed study quality, whereas statistical analysis was executed using R Studio. Excessive SMU showed no significant association with subjective (ES = 0.003, 95% confidence interval [95% CI]: -0.08, 0.09; p = 0.94, I2 = 95.8%, k =16) and PWB (ES = 0.16, 95% CI: -0.15, 0.45; p = 0.26, I2 = 98%, k = 7). Conversely, problematic SMU showed a negative correlation with subjective (ES = -0.14, 95% CI: -0.20, -0.09; p = 0.00, I2 = 93.3%, k = 25) and PWB (ES = -0.19, 95% CI: -0.31, -0.06; p = 0.01, I2 = 95%, k = 5), with two outliers removed. No publication bias was detected. Subgroup analysis highlighted effects of "sampling method" (p < 0.05), "study quality" (p < 0.05), "developmental status" (p < 0.05), "forms of social media" (p < 0.05), and "type of population" (p < 0.01) on the estimated pooled effect sizes. Although univariate meta-regression showed the effects of "% of Internet users" (p < 0.05) and "male%" (p < 0.05), and multivariate meta-regression showed the combined effect of moderators only on the relationship between problematic SMU and subjective well-being.

中文翻译：

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社交媒体使用和福祉：系统评价和荟萃分析。


先前的研究调查了社交媒体使用 （SMU） 与负面幸福感之间的联系。然而，与积极幸福感的联系尚未得到广泛研究，导致出现不一致和不确定的结果。本研究通过检查过度和有问题的 SMU 与主观和心理健康 （PWB） 之间的相关性来填补这一空白。我们在 PubMed、Scopus 和 Web of Science 等数据库以及 Research Gate 和 ProQuest 等灰色文献来源中进行了系统检索，产生了 51 项用于荟萃分析的相关研究，涉及 680,506 人的样本量。我们采用 Newcastle-Ottawa 量表评估研究质量，而使用 R Studio 进行统计分析。过度的 SMU 与主观 （ES = 0.003,95% 置信区间 [95% CI]： -0.08， 0.09;p = 0.94，I2 = 95.8%，k = 16）和 PWB （ES = 0.16,95% CI： -0.15， 0.45;p = 0.26，I2 = 98%，k = 7） 没有显著相关性。相反，有问题的 SMU 与主观 （ES = -0.14， 95% CI： -0.20， -0.09;p = 0.00， I2 = 93.3%， k = 25） 和 PWB （ES = -0.19， 95% CI： -0.31， -0.06;p = 0.01， I2 = 95%，k = 5） 呈负相关，并去除了两个异常值。未检测到发表偏倚。亚组分析强调了“抽样法”（p < 0.05）、“研究质量”（p < 0.05）、“发展状况”（p < 0.05）、“社交媒体形式”（p < 0.05）和“人口类型”（p < 0.01）对估计的合并效应大小的影响。尽管单变量 meta 回归显示“互联网用户百分比”（p < 0.05）和“男性%”（p < 0.05） 和多变量 meta 回归显示调节因子的综合影响仅对有问题的 SMU 与主观幸福感之间的关系。