Evidence map›Paper›PMID 35564330›Full record

Trial reportInternational journal of environmental research and public health2022

Problematic Social Media Use and Depressive Outcomes among College Students in China: Observational and Experimental Findings.

Yonghua Chen, Xi Liu, Dorothy T Chiu, Ying Li, Baibing Mi, Yue Zhang, Lu Ma, Hong Yan

Open access · goldAbstract readObservational StudyRandomized Controlled Trial
In one paragraph

Trial report in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 3 pooled it
13.0field-weighted citation impact, top 1% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

18 citing papers in PubMed, 3 syntheses or guidelines pooled it, 39 citations in OpenAlex.

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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

8 authors at 3 institutions in 2 countries.

Yonghua ChenSchool of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710000, China.
Xi LiuSchool of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710000, China.
Dorothy T ChiuCommunity Health Sciences Division, School of Public Health, University of California, Berkeley, CA 94704, USA.ORCID 0000-0002-4826-6217
Ying LiDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710000, China.
Baibing MiDepartment of Epidemiology and Biostatistic, School of Public Health & Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an 710060, China.
Yue ZhangNursing Department, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710000, China.
Lu MaGlobal Health Institute, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710000, China.
Hong YanSchool of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710000, China.
Xi'an Jiaotong University · CNSecond Affiliated Hospital of Xi'an Jiaotong University · CNBerkeley Public Health Division · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Problematic social media use is increasing in China and could be a risk factor for depression. We investigated cross-sectional associations between problematic social media use and depressive outcomes among Chinese college students with potential mediation by perceived social support, social media violence, and loneliness. Thereafter, we evaluated the effectiveness of a one-month group counseling intervention in reducing depressive symptoms related to social media addiction. Methods: Depressive symptoms, social media addiction, perceived social support, social media violence, and loneliness were self-reported among 21,000 college students in Shaanxi province, China. A randomized controlled trial was designed based on the results of the observational study and Satir Transformational Systemic Therapy (STST) among 60 college students assigned to intervention (N = 30) or control/no treatment (N = 30). Self-administered surveys were completed at baseline (T1), at the end of the 1-month intervention (T2), and at 2-month follow-up post-intervention (T3). Results: After controlling for relevant covariates, more problematic social media use was associated with more depressive symptoms (β = 0.18, p < 0.001) and depression (OR = 1.08, 95% CI: 1.075, 1.092). Multiple mediation analyses found that perceived social support, social media violence, and loneliness significantly mediated associations between problematic social media use and depressive symptoms (model fit: RMSEA = 0.065, GFI = 0.984, CFI = 0.982). Bootstrapping revealed significant indirect effects of problematic social media use on depressive symptoms through the mediators named above (0.143, 95% CI: 0.133, 0.156). The subsequently informed intervention significantly reduced depressive symptoms at T2 (mean difference: −12.70, 95% CI: −16.64, −8.76, p < 0.001) and at T3 (mean difference: −8.70, 95% CI: −12.60, −4.80, p < 0.001), as well as levels of social media addiction, perceived social support, social media violence, and loneliness. Conclusions: Problematic social media use is a risk factor for depressive outcomes among Chinese college students, and perceived social support, social media violence, and loneliness mediate this association. STST-based group counseling may reduce depressive symptoms related to high social media usage in this population.

Indexed as

Social MediaChinaCross-Sectional StudiesDepressionHumansStudentscollege studentsdepressive symptomslonelinessperceived social supportsocial media usesocial media violence

Identifiers

PMID35564330
PMCPMC9099455
OpenAlexW4224219522

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.