From active users to passive watchers: Profiles of TikTok engagement and mental health predictors

Prior studies suggest that TikTok users vary in their engagement behaviors, including passive viewing, participatory interaction, and content creation, and exhibit varying levels of problematic-use risk. Yet it remains unclear which combinations of these engagement behaviors correspond to higher versus lower risk, and which psychological vulnerabilities contribute to high-risk patterns. In a two-wave study of 715 Chinese young adults, we applied latent profile analysis (LPA) to problematic TikTok use and the frequency of passive viewing, participatory, and contributory behaviors at Time 2. We then used multinomial logistic regression with the three-step method to prospectively examine how Time 1 measures of psychopathology and related affective/cognitive vulnerabilities, including depression, social anxiety, life satisfaction, emotion dysregulation, and boredom proneness, predicted TikTok profile membership. Four profiles emerged: Minimal Users (6.7%), Passive Watchers with High Problematic Use Tendencies (38.0%), Moderate Users with Mild Problematic Use Tendencies (42.4%), and Active Users with Low Problematic Use Tendencies (12.9%). Greater life satisfaction, lower social anxiety, and lower boredom proneness at baseline predicted membership in the Active rather than Passive, Moderate, or Minimal profiles. Greater emotion dysregulation predicted membership in the Passive rather than Moderate profile. These findings highlight substantial heterogeneity in TikTok use and suggest that higher baseline psychological wellbeing may increase the likelihood of more active and less problematic patterns of engagement. The current study extends prior LPA research by specifying how risk manifests in everyday use, identifying contributors to high-risk profiles, and extending empirical support for the I-PACE theoretical framework of Internet use disorders.

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Publication Details

Journal
Addictive Behaviors
Published
2025-11-09
DOI
https://doi.org/10.1016/j.addbeh.2025.108552
Primary Topic
Impact of Technology on Adolescents
Type
article
Field-Weighted Citation Impact
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article

From active users to passive watchers: Profiles of TikTok engagement and mental health predictors

Jon D. Elhai, Nisha Yao, Jing Chen
Addictive Behaviors
Impact of Technology on Adolescents
article

From active users to passive watchers: Profiles of TikTok engagement and mental health predictors

Jon D. Elhai, Nisha Yao, Jing Chen
article en

Abstract

Prior studies suggest that TikTok users vary in their engagement behaviors, including passive viewing, participatory interaction, and content creation, and exhibit varying levels of problematic-use risk. Yet it remains unclear which combinations of these engagement behaviors correspond to higher versus lower risk, and which psychological vulnerabilities contribute to high-risk patterns. In a two-wave study of 715 Chinese young adults, we applied latent profile analysis (LPA) to problematic TikTok use and the frequency of passive viewing, participatory, and contributory behaviors at Time 2. We then used multinomial logistic regression with the three-step method to prospectively examine how Time 1 measures of psychopathology and related affective/cognitive vulnerabilities, including depression, social anxiety, life satisfaction, emotion dysregulation, and boredom proneness, predicted TikTok profile membership. Four profiles emerged: Minimal Users (6.7%), Passive Watchers with High Problematic Use Tendencies (38.0%), Moderate Users with Mild Problematic Use Tendencies (42.4%), and Active Users with Low Problematic Use Tendencies (12.9%). Greater life satisfaction, lower social anxiety, and lower boredom proneness at baseline predicted membership in the Active rather than Passive, Moderate, or Minimal profiles. Greater emotion dysregulation predicted membership in the Passive rather than Moderate profile. These findings highlight substantial heterogeneity in TikTok use and suggest that higher baseline psychological wellbeing may increase the likelihood of more active and less problematic patterns of engagement. The current study extends prior LPA research by specifying how risk manifests in everyday use, identifying contributors to high-risk profiles, and extending empirical support for the I-PACE theoretical framework of Internet use disorders.

Addictive BehaviorsVol. 173
Shanghai University of Sport (CN), Capital University of Physical Education and Sports (CN), University of Toledo (US)
Openalex Percentile: Top 56%
Impact of Technology on Adolescents
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