Evidence map›Paper›PMID 42073934›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

Which Ties Matter? Differential Effects of Family, Peer, and Community Support on Short-Video Engagement Among Older Adults.

Ziqing Yang, Xiaoxin Yu, Hao Gao

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Ziqing YangSchool of Modern Circulation, Guangxi International Business Vocational College, Nanning 530007, China.ORCID 0009-0002-1144-3408
Xiaoxin YuSchool of Modern Circulation, Guangxi International Business Vocational College, Nanning 530007, China.
Hao GaoSchool of Journalism and Communication, Nanjing Normal University, Nanjing 210097, China.ORCID 0000-0002-9749-008X

Funding

Guangxi Philosophy and Social Science Research Project 24XWC002
6 · The paper itself

Abstract

Short-form video (SFV) platforms have become a central part of older adults' digital lives, yet their psychological implications remain theoretically contested. Drawing on social empowerment theory, Self-Determination Theory, attachment theory, and the displacement hypothesis, this study examined whether different sources of social support-family, peer, and community-exert differential effects on life satisfaction through SFV engagement and social connectedness. Survey data were collected from 385 community-dwelling Chinese older adults (mean age = 70.6 years) and analyzed using bootstrapped serial mediation models with 5000 resamples. The results revealed clear source differentiation, as family support most strongly predicted SFV engagement and showed the largest total association with life satisfaction, consistent with a social empowerment mechanism. Community participation showed a weaker but still positive association with engagement, whereas peer support was unrelated to engagement. Across pathways, higher SFV engagement was associated with lower social connectedness, while greater social connectedness was associated with higher life satisfaction. However, none of the chained indirect effects reached significance, suggesting that social support influenced life satisfaction primarily through direct rather than serially mediated pathways. These findings demonstrate the importance of disaggregating social support by source and contribute to a more precise framework for understanding older adults' digital well-being.

Indexed as

agingchained mediationChinalife satisfactionolder adultsshort-form videosocial empowermentsocial support

Identifiers

PMID42073934
PMCPMC13113649

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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.