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ORIGINAL RESEARCH article

Front. Psychol.

Sec. Sport Psychology

Enhancing adolescents' exercise motivation with generative AI anthropomorphism: a chain-mediated model of technology acceptance and self-efficacy

Provisionally accepted
Kaiyuan  WangKaiyuan Wang1Hongxin  LiHongxin Li1Guo  YuGuo Yu2Gang  LiGang Li3Yu  SongYu Song1*
  • 1Shanghai University of Sport, Shanghai, China
  • 2Loughborough University School of Sport Exercise and Health Sciences, Loughborough, United Kingdom
  • 3Shandong University of Finance and Economics, Jinan, China

The final, formatted version of the article will be published soon.

Abstract Introduction: In the era of human-machine integration, digital technology highlights its important enabling role in the development of youth sports. The objective of this study is to examine the mechanism through which AI Anthropomorphism is associated with exercise motivation among adolescents. Methods: The data were derived from a sample of 1,018 adolescents aged 6 to 18 across the country. The AI anthropomorphism scale, the Generative artificial intelligence acceptance (GAIA), the General Self-Efficacy Scale (GSES), and the Physical Activity Motivation Scale (MPAM-R) were used to assess AI anthropomorphism, technology acceptance, self-efficacy and exercise motivation. Results: This study found that AI anthropomorphism is significantly associated with adolescents' motivation for physical activity. Further analysis reveals that technology acceptance and self-efficacy independently serve as mediators and chain mediators, respectively, in this relationship, clarifying the underlying psychological mechanisms. Conclusion: This study elucidates the mechanism by which AI anthropomorphism is associated with adolescents' motivation for exercise motivation, offering theoretical support for understanding such behavior and practical guidance for implementation.

Keywords: AI Anthropomorphism1, Technology acceptance2, self-efficacy3, exercise motivation4, adolescents5, multi-group SEM6

Received: 09 Jul 2025; Accepted: 23 Oct 2025.

Copyright: © 2025 Wang, Li, Yu, Li and Song. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Yu Song, 17862919952@163.com

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