Han Xiaoning, Zhou Enze, Liu Dong
School of Journalism and Communication, Renmin University of China, Beijing, China.
J Med Internet Res. 2024 Apr 23;26:e48356. doi: 10.2196/48356.
This paper explores the widely discussed relationship between electronic media use and sleep quality, indicating negative effects due to various factors. However, existing meta-analyses on the topic have some limitations.
The study aims to analyze and compare the impacts of different digital media types, such as smartphones, online games, and social media, on sleep quality.
Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the study performed a systematic meta-analysis of literature across multiple databases, including Web of Science, MEDLINE, PsycINFO, PubMed, Science Direct, Scopus, and Google Scholar, from January 2018 to October 2023. Two trained coders coded the study characteristics independently. The effect sizes were calculated using the correlation coefficient as a standardized measure of the relationship between electronic media use and sleep quality across studies. The Comprehensive Meta-Analysis software (version 3.0) was used to perform the meta-analysis. Statistical methods such as funnel plots were used to assess the presence of asymmetry and a p-curve test to test the p-hacking problem, which can indicate publication bias.
Following a thorough screening process, the study involved 55 papers (56 items) with 41,716 participants from over 20 countries, classifying electronic media use into "general use" and "problematic use." The meta-analysis revealed that electronic media use was significantly linked with decreased sleep quality and increased sleep problems with varying effect sizes across subgroups. A significant cultural difference was also observed in these effects. General use was associated with a significant decrease in sleep quality (P<.001). The pooled effect size was 0.28 (95% CI 0.21-0.35; k=20). Problematic use was associated with a significant increase in sleep problems (P≤.001). The pooled effect size was 0.33 (95% CI 0.28-0.38; k=36). The subgroup analysis indicated that the effect of general smartphone use and sleep problems was r=0.33 (95% CI 0.27-0.40), which was the highest among the general group. The effect of problematic internet use and sleep problems was r=0.51 (95% CI 0.43-0.59), which was the highest among the problematic groups. There were significant differences among these subgroups (general: Q=14.46, P=.001; problematic: Q=27.37, P<.001). The results of the meta-regression analysis using age, gender, and culture as moderators indicated that only cultural difference in the relationship between Eastern and Western culture was significant (Q=6.69; P=.01). All funnel plots and p-curve analyses showed no evidence of publication and selection bias.
Despite some variability, the study overall confirms the correlation between increased electronic media use and poorer sleep outcomes, which is notably more significant in Eastern cultures.
本文探讨了电子媒体使用与睡眠质量之间广泛讨论的关系，指出各种因素会产生负面影响。然而，现有的关于该主题的荟萃分析存在一些局限性。
本研究旨在分析和比较不同类型数字媒体，如智能手机、网络游戏和社交媒体，对睡眠质量的影响。
该研究遵循系统评价与荟萃分析的首选报告项目（PRISMA）指南，对2018年1月至2023年10月期间多个数据库（包括科学网、医学期刊数据库、心理学文摘数据库、医学期刊数据库、科学直连数据库、Scopus数据库和谷歌学术）中的文献进行了系统的荟萃分析。两名经过培训的编码员独立对研究特征进行编码。效应量使用相关系数计算，作为跨研究电子媒体使用与睡眠质量之间关系的标准化度量。使用综合荟萃分析软件（版本3.0）进行荟萃分析。采用漏斗图等统计方法评估不对称性的存在，并使用p曲线检验来检验可能表明发表偏倚的p值操纵问题。
经过全面筛选过程，该研究纳入了55篇论文（56项），涉及来自20多个国家的41,716名参与者，将电子媒体使用分为“一般使用”和“问题使用”。荟萃分析表明，电子媒体使用与睡眠质量下降和睡眠问题增加显著相关，各亚组的效应量各不相同。在这些影响中还观察到了显著的文化差异。一般使用与睡眠质量显著下降相关（P<.001）。合并效应量为0.28（95%置信区间0.21 - 0.35；k = 20）。问题使用与睡眠问题显著增加相关（P≤.001）。合并效应量为0.33（95%置信区间0.28 - 0.38；k = 36）。亚组分析表明，一般智能手机使用与睡眠问题的效应量为r = 0.33（95%置信区间0.27 - 0.40），在一般组中最高。问题性网络使用与睡眠问题的效应量为r = 0.51（95%置信区间0.43 - 0.59），在问题组中最高。这些亚组之间存在显著差异（一般组：Q = 14.46，P =.001；问题组：Q = 27.37，P<.001）。以年龄、性别和文化作为调节变量的荟萃回归分析结果表明，只有东西方文化之间关系的文化差异显著（Q = 6.69；P =.01）。所有漏斗图和p曲线分析均未显示发表和选择偏倚的证据。
尽管存在一些变异性，但该研究总体上证实了电子媒体使用增加与较差睡眠结果之间的相关性，这在东方文化中尤为显著。
