Impact of YouTube User‐Generated Content on News Dissemination and Youth Information Reception.
Background: User‐generated content (UGC) on YouTube has reshaped news dissemination, fostered engagement, raised concerns about credibility, algorithmic influence and the spread of misinformation. This study addresses the gap in understanding how UGC engagement, trust and algorithmic awareness influ...
| Publicado en: | Health Expectations Vol. 28; no. 5; pp. 1 - 14 |
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| Autores principales: | , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Oct2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188926540&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188926540 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13696513 EVY jtl: Health Expectations issn: 13696513 maglogo: Y pubinfo: dt: Oct2025 vid: 28 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 188926540 188926540 188926540 10.1111/hex.70408 188926540 ppf: 1 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Impact of YouTube User‐Generated Content on News Dissemination and Youth Information Reception. aug: au: Chunqiong, Wu Shan, Jiang Jianhong, Sun Yingqi, Liu affil: School of Economics and Management, Yango University, Fuzhou Fujian Province,, China sug: subj: Diffusion of Innovation Mobile Applications Trust Social Media Algorithms News Digital Media In Adolescence Information Literacy Human Male Female Adolescence Adult Qualitative Studies Multimethod Studies Interviews Content Analysis Multivariate Analysis Structural Equation Modeling Thematic Analysis Misinformation United States Brazil China Japan India Random Assignment Purposive Sample Analysis of Variance Descriptive Statistics Inferential Statistics Exploratory Research Factor Analysis Data Analysis Software kappa Statistic Funding Source Consumer Attitudes Adolescent: 13-18 years Adult: 19-44 years Male Female ab: Background: User‐generated content (UGC) on YouTube has reshaped news dissemination, fostered engagement, raised concerns about credibility, algorithmic influence and the spread of misinformation. This study addresses the gap in understanding how UGC engagement, trust and algorithmic awareness influence digital news consumption. Methods: A convergent parallel mixed‐methods design was employed, integrating survey data (n = 100), qualitative interviews and content analysis of 200 YouTube news videos. Data were collected over 6 weeks. Quantitative analyses included ANOVA, multivariate regression and structural equation modelling (SEM), while qualitative data were thematically analysed to contextualise statistical findings. Results: UGC news consumption (M = 3.21, SD = 1.14) exceeded traditional news (M = 2.95, SD = 1.20), with trust in UGC (M = 3.48, SD = 1.05) surpassing traditional sources (M = 3.12, SD = 1.17). SEM analysis confirmed that UGC engagement significantly increased trust (β = 0.42, p < 0.001), while algorithmic influence negatively affected trust (β = −0.33, p = 0.015). Sensationalist content attracted higher engagement (30.0%) but had lower credibility, with misinformation prevalent in 38.0% of analysed videos. Conclusion: Findings highlight the need for platform transparency, stronger content verification and policy interventions to balance engagement‐driven algorithms and news credibility. Media literacy initiatives are crucial for equipping users with the critical evaluation skills they need. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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