AUTHOR=Guo Yi , Gong Zhuliu , Zhang Ziyi , Ma Baotong , Xia Ruitong , Lu Yuanwei , Liu Jingwen , Xin Hanjia , Cao Yumeng , Yang Saier , Li Runqing , Liu Yi , Fan Siyuan 

TITLE=Exploring the relation between media usage frequency and anxiety among Chinese residents: a latent profile analysis

JOURNAL=Frontiers in Psychiatry

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2025.1475626

DOI=10.3389/fpsyt.2025.1475626

ISSN=1664-0640

ABSTRACT=ObjectiveThis study investigates the relationship between media usage patterns and anxiety levels, specifically examining how different media usage profiles influence anxiety across various demographic groups.MethodologyA total of 11,031 respondents from 120 cities across China were classified into three media usage profiles—Traditional Media-Dominant Users, New Media-Dominant Users, and Omni-Media Users—using Latent Profile Analysis (LPA) based on their media usage frequency. Demographic covariates were excluded during the initial profiling to ensure the analysis focused solely on media usage patterns. Multiple linear regression analyses were then conducted to examine the relationship between media usage types and anxiety levels. Finally, factors influencing anxiety across the different media usage profiles were explored separately.ResultsThe analysis revealed that both Traditional Media-Dominant and Omni-Media Users exhibited significantly higher levels of anxiety compared to New Media-Dominant Users. Factors such as geographic region, health literacy, income, debt, employment stability, and property ownership showed varying effects on anxiety across the profiles. Additionally, perceived stress and depression were identified as consistent, positive predictors of anxiety in all media usage groups.ConclusionsCompared to New Media-Dominant Users, both Traditional Media-Dominant and Omni-Media Users exhibited stronger associations with anxiety. These findings suggest that anxiety is influenced by multiple intersecting factors across media usage profiles, highlighting the need for tailored interventions that consider individuals’ specific media engagement patterns.