Evidence map›Paper›PMID 41346507›Full record

ArticleFrontiers in psychology2025

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

Kaiyuan Wang, Hongxin Li, Guo Yu, Gang Li, Yu Song

Abstract read
In one paragraph

Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Kaiyuan WangSchool of Economics and Management, Shanghai University of Sport, Shanghai, China.
Hongxin LiSchool of Economics and Management, Shanghai University of Sport, Shanghai, China.
Guo YuSchool of Sport Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom.
Gang LiPhysical Education College, Shandong University of Finance and Economics, Jinan, China.
Yu SongSchool of Economics and Management, Shanghai University of Sport, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 6-18 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.

Indexed as

adolescentsAI anthropomorphismexercise motivationmulti-group SEMself-efficacytechnology acceptance

Identifiers

PMID41346507
PMCPMC12672428

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.