San Diego State University, United States of America.
New York University-Stern School of Business, United States of America.
Acta Psychol (Amst). 2022 Apr;224:103512. doi: 10.1016/j.actpsy.2022.103512. Epub 2022 Jan 29.
An important 2019 paper applied a novel analytic technique called Specification Curve Analysis (SCA) to data from three large-scale community samples to investigate the association between adolescent technology use and mental health/well-being. The paper concluded that an association exists but is tiny, with median betas between -0.01 and -0.04. This association was reported to be smaller than links between mental health and various innocuous variables in the datasets such as eating potatoes, and therefore to be of no practical significance. The current paper re-ran SCA on the same datasets while applying alternative analytic constraints on the model specification space, including: 1) examining specific digital media activities (e.g., social media) separately rather than lumping all "screen time" including TV together; 2) examining boys and girls separately, rather than examining them together; 3) excluding potential mediators from the list of controls; and 4) treating scales equally (rather than allowing one scale with many subscales to dominate all others). We were able to reproduce the original results with the original configurations. When we used the revised constraints, we found several much larger relationships than previously reported. In particular: among girls, there is a consistent and substantial association between mental health and social media use (median betas from -0.11 to -0.24). These associations were stronger than links between mental health and binge drinking, sexual assault, obesity, and hard drug use, suggesting that these associations may have substantial practical significance as many countries are experiencing rising rates of depression, anxiety, and suicide among teenagers and young adults.
一篇重要的 2019 年论文应用了一种新颖的分析技术,称为规范曲线分析(SCA),对来自三个大型社区样本的数据进行分析,以研究青少年技术使用与心理健康/幸福感之间的关联。该论文得出的结论是存在关联,但关联很小,中位数贝塔值在-0.01 到-0.04 之间。该关联被报道比数据集中心理健康与各种无害变量(如吃土豆)之间的关联小,因此没有实际意义。本文在相同的数据集中重新运行了 SCA,同时对模型规范空间应用了替代的分析约束,包括:1)分别检查特定的数字媒体活动(如社交媒体),而不是将所有“屏幕时间”(包括电视)汇总在一起;2)分别检查男孩和女孩,而不是一起检查;3)从控制变量列表中排除潜在的中介变量;4)平等对待量表(而不是允许一个具有许多子量表的量表主导所有其他量表)。我们能够使用原始配置重现原始结果。当我们使用修订后的约束时,我们发现了几个比以前报告的大得多的关系。特别是:在女孩中,心理健康与社交媒体使用之间存在一致且显著的关联(中位数贝塔值从-0.11 到-0.24)。这些关联比心理健康与狂欢饮酒、性侵犯、肥胖和使用硬毒品之间的关联更强,这表明这些关联可能具有相当大的实际意义,因为许多国家的青少年和年轻人中抑郁、焦虑和自杀的比例正在上升。