ArticleBMC psychology2024
Would you be healthier if you had more social capital? Focusing on university students' social media use in Japan.
Article in BMC psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Social Media Use and Health: What We Have Known So Far, and What We Need to Investigate in the Future.Healthcare (Basel, Switzerland) · 2026Review
- When Social Skills Backfire: Social Media Overuse as a Pathway Linking Social Competence and Health Across Cultures.Behavioral sciences (Basel, Switzerland) · 2026Article
- Differential pathways linking social interaction and Loneliness among university students in the age of artificial intelligence: the mediating role of Social Capital.Frontiers in psychology · 2026Article
- The impact of social media use on college students' mental health: a narrative review.Frontiers in public health · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study examined how university students' social media use is related to their mental health (subjective well-being [SWB] and loneliness) and perceived physical health. A cognitive bias model and a social network mediation model were used to compare social capital formed via face-to-face and online communication, considering the effects of personality traits (i.e., social skills, generalized trust, and social tolerance).
methodsWe conducted a self-report survey with 409 university students in Japan from August to September 2022. Four patterns of social media use were analyzed: (1) Twitter only, (2) LINE + Twitter, (3) Instagram + Twitter, and (4) Discord + Twitter. Relationships between the variables were investigated with a structural equation modeling analysis using SmartPLS 4.0.
resultsOverall, regardless of social media use patterns, personality traits had positive direct effects on mental health and also had positive effects on social capital via face-to-face (FTF) communication, which had mediating effects on the improvement of mental health. FTF social capital had a positive relationship with online social capital, which did not have relationships with mental or perceived physical health. Additionally, perceived physical health decreased loneliness but was not associated with SWB. Social media use negatively affected perceived physical health but had no effect on SWB or loneliness. Finally, different relationships between personality traits and social media use, FTF social capital and SWB, social media use and perceived physical health were observed among the four patterns of social media use.
conclusionThis study has implications for improving the health of young adults in the "mobile x social era." In particular, we provide suggestions to help young adults improve their mental health.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.