Evidence map›Paper›PMID 38628982›Full record

ArticlePsychology research and behavior management2024

Understanding Social Media Information Sharing in Individuals with Depression: Insights from the Elaboration Likelihood Model and Schema Activation Theory.

Qiang Liu, FeiFei Su, Aruhan Mu, Xiang Wu

Abstract read
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Article in Psychology research and behavior management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Qiang Liu *School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China.
FeiFei Su *School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China.
Aruhan MuSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China.
Xiang WuSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: How individuals engage with social media can significantly impact their psychological well-being. This study examines the impact of social media interactions on mental health, grounded in the frameworks of the Elaboration Likelihood Model and Schema Activation Theory. It aims to uncover behavioral differences in information sharing between the general population and individuals with depression, while also elucidating the psychological mechanisms underlying these disparities. Methods: A pre-experiment (N=30) and three experiments (Experiment 1a N=200, Experiment 1b N=180, Experiment 2 N=128) were executed online. These experiments investigated the joint effects of information quality, content valence, self-referential processing, and depression level on the intention to share information. The research design incorporated within-subject and between-subject methods, utilizing SPSS and SPSS Process to conduct independent sample t-tests, two-factor ANOVA analyses, mediation analyses, and moderated mediation analyses to test our hypotheses. Results: Information quality and content valence significantly influence sharing intention. In scenarios involving low-quality information, individuals with depression are more inclined to share negative emotional content compared to the general population, and this tendency intensifies with the severity of depression. Moreover, self-referential processing acts as a mediator between emotional content and intention to share, yet this mediation effect weakens as the severity of depression rises. Conclusion: Our study highlights the importance of promoting viewpoint diversity and breaking the echo chamber effect in social media to improve the mental health of individuals with depression. To achieve this goal, tailoring emotional content on social media could be a practical starting point for practice.

Indexed as

cognitive schemacontent valencedepressioninformation qualityinformation-sharing behaviorself-referential processingsocial media

Identifiers

PMID38628982
PMCPMC11020237

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