Evidence map›Paper›PMID 39394184›Full record

ArticleTranslational psychiatry2024

Association between social media use and depressive symptoms in middle-aged and older Chinese adults.

Yanling Qi, Chenghe Zhang, Mei Zhou, Ruiyuan Zhang, Yuxiao Chen, Changwei Li

Abstract read
In one paragraph

Article in Translational psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yanling QiZhou Enlai School of Government, Nankai University, Tianjin, China.
Chenghe ZhangZhou Enlai School of Government, Nankai University, Tianjin, China.
Mei ZhouSchool of Public Administration, Southwestern University of Finance and Economics, Chengdu, Sichuan, China.
Ruiyuan ZhangDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
Yuxiao ChenSchool of Politics and Public Administration, Zhengzhou University, Zhengzhou, Henan, China.
Changwei LiDepartment of Epidemiology, O'Donnell School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA. changwei.li@utsouthwestern.edu.ORCID 0000-0002-9203-304X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The burden of depressive symptoms among middle-aged and older Chinese during the COVID-19 pandemic is unclear, and the contribution of social media use to depressive symptoms in this population has not been studied. To address the gaps, we analyzed data from the China Health and Retirement Longitudinal Study, nationally representative biannual surveys among adults aged ≥45 years. Social media use and depressive symptoms were measured in the 2018 and 2020 surveys. We tested longitudinal associations between baseline (2018) social media activities and risk of depressive symptoms in two years among 9121 participants without depressive symptoms. We also evaluated whether social media activity could reduce depressive symptoms during this period among 5302 individuals with depressive symptoms at baseline. Depressive symptoms affected 36·0% of this population in 2020. Women, individuals living in rural areas, and residents of western China provinces were particularly affected. Among participants without depressive symptoms, engaging in social media activities at baseline was associated with a 24.0% (95% confidence interval [CI]: 10-36%) lower likelihood of developing depressive symptoms over the next two years. Among depressed participants, compared to individuals not using social media, those initiating three or more social media activities during this period had 1.24 (95% CI: 1.05-1.46) times higher chance of becoming non-depressed, and those using social media all the time were 1·36 (95% CI: 1·09-1·72) times more likely to become non-depressed. In conclusion, middle-aged and older Chinese adults have a substantial burden of depressive symptoms, and social media activities may help to prevent and reduce the symptoms.

Indexed as

DepressionSocial MediaAgedChinaCOVID-19East Asian PeopleFemaleHumansLongitudinal StudiesMaleMiddle Aged

Identifiers

PMID39394184
PMCPMC11470045

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.