Perceived support from AI health tools and exercise adherence among university students: a three-wave study of exercise self-efficacy and autonomous motivation
4 affiliations
- 1The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
- 2Hunan First Normal University, Changsha, China
- 3Department of Educational Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
- 4Guangdong Pharmaceutical University, Guangzhou, China
Abstract
Maintaining regular exercise is challenging for many university students, and AI-enabled health tools are increasingly used to provide individualized exercise guidance and support. This study examined whether perceived exercise support from AI health tools was prospectively associated with later exercise adherence and whether exercise self-efficacy and autonomous motivation were involved in this association. A three-wave survey was conducted among 438 university students in China who were existing users of AI health tools with exercise-support functions. Perceived AI exercise support and baseline exercise adherence were assessed at T1, exercise self-efficacy at T2, and autonomous motivation and exercise adherence at T3. Structural equation modeling with bias-corrected bootstrap procedures was used, with baseline exercise adherence and relevant covariates controlled. Perceived AI exercise support at T1 was positively associated with exercise self-efficacy at T2 (β =0.36, p <0.001), which was positively associated with autonomous motivation at T3 (β =0.41, p <0.001). Autonomous motivation at T3 was concurrently associated with exercise adherence at T3 (β =0.29, p <0.001). The serial indirect association was significant (β = 0.04, 95% CI [0.02, 0.06]), and the direct association between perceived AI exercise support and T3 exercise adherence remained significant (β =0.11, p = 0.028). These findings are consistent with a psychological sequence in which perceived AI exercise support is associated with greater exercise self-efficacy and more autonomous motivation, which in turn is associated with exercise adherence. Because autonomous motivation and adherence were measured concurrently at T3, the final link should be interpreted as a within-wave association rather than as evidence of a fully longitudinal causal mediation process.
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BibTeX
@article{lu2026perceived,
title = {{Perceived support from AI health tools and exercise adherence among university students: a three-wave study of exercise self-efficacy and autonomous motivation}},
author = {Yuchao Lu and Ruihong Tang and Baijie Zeng and Jiazeng Sun and Shaoheng Liang and Degui Fu},
journal = {Frontiers in Psychology},
year = {2026},
month = oct,
doi = {10.3389/fpsyg.2026.1872095},
url = {https://doi.org/10.3389/fpsyg.2026.1872095},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Perceived support from AI health tools and exercise adherence among university students: a three-wave study of exercise self-efficacy and autonomous motivation
AU - Yuchao Lu
AU - Ruihong Tang
AU - Baijie Zeng
AU - Jiazeng Sun
AU - Shaoheng Liang
AU - Degui Fu
PY - 2026
DA - 2026/10/12
JO - Frontiers in Psychology
DO - 10.3389/fpsyg.2026.1872095
UR - https://doi.org/10.3389/fpsyg.2026.1872095
AB - Maintaining regular exercise is challenging for many university students, and AI-enabled health tools are increasingly used to provide individualized exercise guidance and support. This study examined whether perceived exercise support from AI health tools was prospectively associated with later exercise adherence and whether exercise self-efficacy and autonomous motivation were involved in this association. A three-wave survey was conducted among 438 university students in China who were existing users of AI health tools with exercise-support functions. Perceived AI exercise support and baseline exercise adherence were assessed at T1, exercise self-efficacy at T2, and autonomous motivation and exercise adherence at T3. Structural equation modeling with bias-corrected bootstrap procedures was used, with baseline exercise adherence and relevant covariates controlled. Perceived AI exercise support at T1 was positively associated with exercise self-efficacy at T2 (β =0.36, p <0.001), which was positively associated with autonomous motivation at T3 (β =0.41, p <0.001). Autonomous motivation at T3 was concurrently associated with exercise adherence at T3 (β =0.29, p <0.001). The serial indirect association was significant (β = 0.04, 95% CI [0.02, 0.06]), and the direct association between perceived AI exercise support and T3 exercise adherence remained significant (β =0.11, p = 0.028). These findings are consistent with a psychological sequence in which perceived AI exercise support is associated with greater exercise self-efficacy and more autonomous motivation, which in turn is associated with exercise adherence. Because autonomous motivation and adherence were measured concurrently at T3, the final link should be interpreted as a within-wave association rather than as evidence of a fully longitudinal causal mediation process.
SN - 1664-1078
ER -