Evidence map›Paper›PMID 40811685›Full record

SynthesisJournal of medical Internet research2025

Social-Media-Based Mental Health Interventions: Meta-Analysis of Randomized Controlled Trials.

Qiyang Zhang, Zixuan Huang, Yuan Sui, Fu-Hung Lin, Hongjie Guan, Li Li, Ke Wang, Amanda Neitzel

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
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.

Qiyang Zhang *Yong Loo Lin School of Medicine, National University of Singapore, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore, 65 66012186.ORCID http://orcid.org/0000-0001-7474-2435
Zixuan Huang *School of Education, Johns Hopkins University, Baltimore, MD, United States.ORCID http://orcid.org/0009-0004-5235-1627
Yuan SuiSchool of Education, Johns Hopkins University, Baltimore, MD, United States.ORCID http://orcid.org/0009-0005-0917-1847
Fu-Hung LinSchool of Education, Johns Hopkins University, Baltimore, MD, United States.ORCID http://orcid.org/0009-0005-1766-2873
Hongjie GuanDepartment of Educational Policy Studies, College of Education and Human Development, Georgia State University, Atlanta, GA, United States.ORCID http://orcid.org/0009-0005-4816-958X
Li LiSchool of Education, Johns Hopkins University, Baltimore, MD, United States.ORCID http://orcid.org/0009-0008-0931-7174
Ke WangSchool of Education, Johns Hopkins University, Baltimore, MD, United States.ORCID http://orcid.org/0009-0001-0996-6958
Amanda NeitzelSchool of Education, Johns Hopkins University, Baltimore, MD, United States.ORCID http://orcid.org/0000-0002-4676-9320

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Compared with other forms of online mental health interventions, programs delivered through social media apps may require less training and be more acceptable and accessible to various populations. During and after the pandemic, both the number of social media users and the prevalence of social-media-based mental health interventions increased significantly. However, to the best of the authors' knowledge, no meta-analysis so far has focused on rigorous social-media-based mental health interventions for general populations. Objective: This preregistered meta-analysis synthesized findings from rigorously designed randomized controlled trials (RCTs) (ie, decent sample size, low attrition, and comparable baseline conditions) to understand whether social-media-based mental health RCTs work as expected in reducing mental health issues. Methods: We searched for articles through database queries, hand searching, and forward and backward citation tracking, which yielded 11,658 studies. We only included social-media-based RCTs with a decent sample size (n≥30 for each experimental condition at baseline assessment), low differential attrition between treatments and controls (<15%), equivalent baseline conditions (differences between conditions <0.25 SDs), published after 2005, and delivered by nonresearchers. These RCTs must aim at reducing mental health issues, such as depression, anxiety, and stress. We excluded one-item outcome measures. Results: After double-blinded screening, 17 eligible studies (total sample sizes=5624) were included in this meta-analysis. Meta-regression results showed that, on average, these social-media-based interventions were effective (effect size [ES]=0.32, P<.001, NES=61, 95% CI 0.24-0.45, I²=88.10, τ2=0.13) for the general population (range of mean age: 15.27~59.65). In other words, social-media-based interventions were effective at reducing anxiety (ES=0.33, P=.04, n=27), depression (ES=0.31, P<.001, n=31), and stress (ES=0.69, P=.02, n=12). Moderator analysis showed that social-media-based interventions are more effective when the participants are more than 70% female, when the programs are human-guided, social-oriented, and when control groups are care as usual. Furthermore, we conducted a risk of bias analysis, publication bias analysis, and sensitivity analysis, which show low risks of bias and robust findings. The biggest limitation of this review is the small sample size of 17 included studies, which restricts the power of our models. Conclusions: While technology can be a double-edged sword, this meta-analysis highlighted social media's benefits and future potential in the treatment of mental health symptoms.

Indexed as

Mental DisordersMental HealthRandomized Controlled Trials as TopicSocial MediaHumansanxietydepressionmeta-analysisrandomized controlled trialssocial-media-based interventionssystematic review

Identifiers

PMID40811685
PMCPMC12352706

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.