Evidence mapPaperPMID 41214216Full record

ArticleScientific reports2025

The Interaction Mechanism of Short Video Platform Usage Experience on the Subjective Well-Being of China's Rural Elderly.

Xinlian Li, Junping Xu, Ning Tang, Hongfeng Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Xinlian LiCollege of Media and International Culture, Zhejiang University, Hangzhou, 310058, China.
Junping XuCollege of Media and International Culture, Zhejiang University, Hangzhou, 310058, China. xjp1110@zju.edu.cn.
Ning TangFaculty of Humanities and Social Sciences, Macao Polytechnic University, Macao, 999078, China.
Hongfeng ZhangFaculty of Humanities and Social Sciences, Macao Polytechnic University, Macao, 999078, China.

Funding

Macao Polytechnic University RP/FCHS - 01/2023
6 · The paper itself

Abstract

Against the backdrop of deepening population aging in China, the phenomenon of empty-nest elderly in rural areas has become increasingly prominent. This study explores the impact of Douyin usage on the subjective well-being (WB) of rural empty-nest elderly, constructing a research model based on the stimulus-organism-response (SOR) framework. The model integrates seven constructs: interactivity, entertainment, relative advantage, compatibility, habit, flow experience, and WB. Data were collected through questionnaires from 407 elderly respondents in rural Sichuan Province, analyzed using a hybrid approach combining partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN). PLS-SEM results show that interactivity and entertainment value significantly enhance WB through direct and indirect effects mediated by usage habit and flow experience. Entertainment value exerts a stronger influence on flow experience, while interactivity plays a more pivotal role in cultivating usage habits. The ANN analysis validates the model's robustness, reveals nonlinear interactions among constructs, and ranks the relative importance of predictors, aligns broadly with the findings of PLS-SEM. The findings not only expand the theoretical understanding of digital technology use and elderly well-being but also offer empirical support for digital solutions to rural aging governance.

Indexed as

Rural PopulationAgedAged, 80 and overChinaFemaleHumansMaleMiddle AgedNeural Networks, ComputerSurveys and QuestionnairesANNEmpty-nest elderlyPLS-SEMShort-form videoS-O-R modelTikTok

Identifiers

PMID41214216
PMCPMC12603165

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.