From Digital Engagement to Physical Activity: A Four-Wave Test of Behavioral Spillover in Online Fitness Communities

Continued use of fitness technology is often treated as a prerequisite for health behavior change, yet platform engagement and behavioral regulation may operate through different mechanisms. This four-wave panel study tested whether an engagement pathway in online fitness communities extends across the digital–physical boundary. After a priori quality screening, 506 Chinese adults who had used the community functions of a smart fitness platform, application, or wearable device within the previous three months and had access to a community activity venue were retained at T1, with 417 at T2, 377 at T3, and 394 at the outcome-only T4 wave. A unified full-information maximum-likelihood path system adjusted for prior outcomes and demographics and used 2000 participant-level bootstrap resamples. Perceived interaction at T1 predicted social presence (β = 0.297), flow (β = 0.355), and belonging (β = 0.245) at T2, and all three independently predicted continuance intention at T3 (βs = 0.203–0.302). Continuance intention is the intention to keep using the community, not observed use. It showed no detectable association with physical activity at T4 once prior activity was controlled (β = 0.016, 95% CI [−0.061, 0.082]), and the serial indirect effects were likewise undetectable. This did not follow from conditioning on the strong autoregressive path: the zero-order correlation between continuance intention and later activity was 0.068, while associations along the hypothesized within-platform chain ranged from 0.218 to 0.563. Missing-data, complete-case, log-transformed, and inverse-probability-weighted specifications converged. Exploratory equivalence testing rendered standardized effects of ±0.10 or larger implausible (p = 0.012) but not ±0.05, and a BIC approximation favored the model without the path (BF01 = 17.81). Experiences that sustain digital continuity should not be assumed to produce physical activity spillover.

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Publication Details

Journal
Behavioral Sciences
Published
2026-09-14
DOI
https://doi.org/10.3390/bs16091645
Primary Topic
Behavioral Health and Interventions
Type
article
Field-Weighted Citation Impact
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article

From Digital Engagement to Physical Activity: A Four-Wave Test of Behavioral Spillover in Online Fitness Communities

Pengcheng Chang, Qiuhan Zhu, Xiangnan Li, Youzenan Tu
Behavioral Sciences
Behavioral Health and Interventions
article

From Digital Engagement to Physical Activity: A Four-Wave Test of Behavioral Spillover in Online Fitness Communities

Pengcheng Chang, Qiuhan Zhu, Xiangnan Li, Youzenan Tu
article en

Abstract

Continued use of fitness technology is often treated as a prerequisite for health behavior change, yet platform engagement and behavioral regulation may operate through different mechanisms. This four-wave panel study tested whether an engagement pathway in online fitness communities extends across the digital–physical boundary. After a priori quality screening, 506 Chinese adults who had used the community functions of a smart fitness platform, application, or wearable device within the previous three months and had access to a community activity venue were retained at T1, with 417 at T2, 377 at T3, and 394 at the outcome-only T4 wave. A unified full-information maximum-likelihood path system adjusted for prior outcomes and demographics and used 2000 participant-level bootstrap resamples. Perceived interaction at T1 predicted social presence (β = 0.297), flow (β = 0.355), and belonging (β = 0.245) at T2, and all three independently predicted continuance intention at T3 (βs = 0.203–0.302). Continuance intention is the intention to keep using the community, not observed use. It showed no detectable association with physical activity at T4 once prior activity was controlled (β = 0.016, 95% CI [−0.061, 0.082]), and the serial indirect effects were likewise undetectable. This did not follow from conditioning on the strong autoregressive path: the zero-order correlation between continuance intention and later activity was 0.068, while associations along the hypothesized within-platform chain ranged from 0.218 to 0.563. Missing-data, complete-case, log-transformed, and inverse-probability-weighted specifications converged. Exploratory equivalence testing rendered standardized effects of ±0.10 or larger implausible (p = 0.012) but not ±0.05, and a BIC approximation favored the model without the path (BF01 = 17.81). Experiences that sustain digital continuity should not be assumed to produce physical activity spillover.

Behavioral SciencesVol. 16(9)
Zhengzhou University (CN)
Openalex Percentile: Top 9%
Behavioral Health and Interventions
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