Evidence map›Paper›PMID 42352767›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

When Social Skills Backfire: Social Media Overuse as a Pathway Linking Social Competence and Health Across Cultures.

Shaoyu Ye, Kevin K W Ho

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Shaoyu YeInstitute of Library, Information and Media Science, University of Tsukuba, Tsukuba 305-8550, Japan.ORCID 0000-0003-4464-9736
Kevin K W HoInstitute of Business Sciences, University of Tsukuba, Tokyo 112-0012, Japan.ORCID 0000-0003-1304-0573

Funding

Japan Society for the Promotion of Science 23K21842 & 21H03770
6 · The paper itself

Abstract

This study investigates how self-presentation and social skills relate to physical health among university students in Japan and Hong Kong, with particular attention to the mediating roles of social media use and social support. We conducted two online surveys; as a result, 452 participants in Japan and 289 participants in Hong Kong were analyzed using multi-group structural equation modeling. Across both samples, social skills were directly associated with increased physical symptoms, and this direct association was substantially stronger than the indirect association through social support, which was linked to fewer physical symptoms. Notable cross-cultural differences also emerged. In Japan, self-presentation was directly associated with increased respiratory-sleep symptoms (R-SSs), and this direct association was stronger than the indirect pathway through posting frequency and time spent on social media. In contrast, in Hong Kong, no direct association between self-presentation and physical symptoms was detected, although an indirect association through social media usage time-leading to increased R-SS-emerged at a marginally significant level. These findings highlight the dual and context-dependent effects of personal attributes in digital environments, demonstrating that characteristics typically associated with positive social functioning may produce unintended health consequences online. By integrating personal factors, social media behaviors, and cultural context, this study advances understanding of digital well-being and physical health in contemporary societies.

Indexed as

gastrointestinal problemsheadacheHong KongJapanrespiratory infectionself-presentationsleeping disturbancesocial media usesocial skills

Identifiers

PMID42352767
PMCPMC13295675

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.