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孟加拉国大学生中社交媒体成瘾、社交媒体疲劳、错失恐惧与睡眠质量之间的关联:一项横断面研究。

Associations between social media addiction, social media fatigue, fear of missing out, and sleep quality among university students in Bangladesh: a cross-sectional study.

作者信息

Rahman Moinur, Rabby Md Fajla, Kabir Md Rayhan, Anjum Rezwana, Saha Onnesha, Bhuiyan Md Abrar Azim, Emon Hasibul Hassain, Hossain Md Moyazzem

机构信息

Department of Statistics and Data Science, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh.

Jahangirnagar University Research Society, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh.

出版信息

J Health Popul Nutr. 2025 May 10;44(1):152. doi: 10.1186/s41043-025-00896-1.

DOI:10.1186/s41043-025-00896-1
PMID:40349076
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12065153/
Abstract

BACKGROUND

The relationship between social media use and sleep quality is complicated and may be impacted by several contextual factors, including age, socioeconomic status, living environment, and other medical issues. It is necessary to explore the relationship between social media usage and poor sleep outcomes among university students. However, little is known about the connection between sleep issues and the detrimental effects of social media use. This study aims to investigate the relationship between social media, social media addiction (SMA), social media fatigue (SMF), fear of missing out (FoMO), and sleep quality (SQ) in Bangladeshi students.

METHODS

Primary data were collected from 611 university students using a stratified random sampling technique. The Pittsburgh Sleep Quality Index and other variables of scales such as SMA, SMF, and FoMO were used in this survey. Descriptive statistics of participants and logistic regression were used to identify significant factors, and ANOVA was used to compare the means of multiple groups to determine.

RESULTS

Findings revealed that 413 (67.57%) respondents have sleep disruption, and most of the participants used social media for 0-2 h daily, however, only a small portion exceeded 8 h. This study also found that SMA, SMF, and FoMO significantly impact the SQ, where students with low SMF scores were 6.85 times more likely to report good sleep quality than those with high SMF scores. Low SMA scores are 2.04 times more likely to have good SQ compared to the high scores of SMA, and for FoMO, the low scores are 2.22 times more likely to have good SQ compared to high scorers of FoMO. Among the participating students, 47% of the students rated their health as "good", 45% as "fair", and 4% as "poor". The study found that sleep SQ has a significant impact on self-reported health status, with good SQ having a 0.598 times lower risk of fair health conditions than those with bad SQ. Moreover, social media use, time spent on social media, and how many hours you usually sleep at night in the past month covariates show a significant impact on student health.

CONCLUSION

University students were more likely to have sleep issues after using social media in ways that caused negative effects like SMF, SMA, and FoMO. Social media overactivity reduces sleep quality and affects on also self-reported health, respectively.

摘要

背景

社交媒体使用与睡眠质量之间的关系较为复杂,可能受到多种背景因素的影响,包括年龄、社会经济地位、生活环境以及其他健康问题。有必要探究大学生群体中社交媒体使用与不良睡眠结果之间的关系。然而,关于睡眠问题与社交媒体使用的有害影响之间的联系,我们所知甚少。本研究旨在调查孟加拉国学生中社交媒体、社交媒体成瘾(SMA)、社交媒体疲劳(SMF)、错失恐惧症(FoMO)与睡眠质量(SQ)之间的关系。

方法

采用分层随机抽样技术,从611名大学生中收集原始数据。本调查使用了匹兹堡睡眠质量指数以及SMA、SMF和FoMO等量表的其他变量。运用参与者的描述性统计和逻辑回归来确定显著因素,并使用方差分析来比较多组均值以进行判定。

结果

研究结果显示,413名(67.57%)受访者存在睡眠障碍,大多数参与者每天使用社交媒体0 - 2小时,然而,只有一小部分人使用时间超过8小时。本研究还发现,SMA、SMF和FoMO对SQ有显著影响,SMF得分低的学生报告良好睡眠质量的可能性比得分高的学生高6.85倍。SMA得分低的学生拥有良好睡眠质量的可能性比得分高的学生高2.04倍,对于FoMO而言,得分低的学生拥有良好睡眠质量的可能性比得分高的学生高2.22倍。在参与调查的学生中,47%的学生将自己的健康状况评为“良好”,45%评为“一般”,4%评为“较差”。研究发现,睡眠质量对自我报告的健康状况有显著影响,睡眠质量良好的学生出现健康状况一般的风险比睡眠质量差的学生低0.598倍。此外,社交媒体使用情况、在社交媒体上花费的时间以及过去一个月中通常每晚的睡眠时间等协变量对学生健康有显著影响。

结论

大学生在以导致SMF、SMA和FoMO等负面影响的方式使用社交媒体后,更有可能出现睡眠问题。社交媒体过度使用分别降低了睡眠质量并影响了自我报告的健康状况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a96/12065153/edc915879157/41043_2025_896_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a96/12065153/fc0c22f9af31/41043_2025_896_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a96/12065153/9cc74ac823ec/41043_2025_896_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a96/12065153/edc915879157/41043_2025_896_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a96/12065153/fc0c22f9af31/41043_2025_896_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a96/12065153/9cc74ac823ec/41043_2025_896_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a96/12065153/edc915879157/41043_2025_896_Fig3_HTML.jpg

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