Perceived AI acceptance and occupational well-being among university physical education teachers: a cross-sectional serial mediation model of digital well-being and innovative work behavior

Objective This study aimed to test a serial mediation model examining whether perceived AI acceptance is indirectly associated with university physical education (PE) teachers’ occupational well-being through digital well-being and innovative work behavior, as proposed on the basis of Conservation of Resources theory. Methods A cross-sectional design was adopted, and 807 university PE teachers were recruited from multiple universities in six provinces and municipalities of China through online convenience and snowball sampling. Self-report scales were employed to measure perceived AI acceptance (adapted from the Technology Acceptance Model), digital well-being (a researcher-developed instrument based on a published theoretical framework), innovative work behavior (general innovative behavior in one’s work role), and occupational well-being (the Job-related Affective Well-being Scale). The measurement structure was examined by confirmatory factor analysis, and indirect associations were estimated by bootstrapping (PROCESS Model 6, 5,000 resamples) using observed composite scores. Results Perceived AI acceptance was significantly and positively associated with occupational well-being (total effect B = 0.181, 95% CI [0.143, 0.220]). Three indirect associations were observed: via digital well-being ( B = 0.042, 95% CI [0.027, 0.059]), via innovative work behavior ( B = 0.040, 95% CI [0.026, 0.056]), and via digital well-being and innovative work behavior in sequence ( B = 0.021, 95% CI [0.015, 0.030]). The total indirect effect was 0.103, accounting for 56.91% of the total effect, while the direct effect accounted for 43.09%. Bootstrap confidence intervals for all indirect effects excluded zero. Conclusion Because the data are cross-sectional and self-reported, the results indicate statistical indirect associations and not temporal or causal mediation. The observed pattern is consistent with a Conservation of Resources-based sequence from perceived AI acceptance to digital well-being, innovative work behavior, and occupational well-being, which is theoretically proposed and not empirically established. The findings suggest that digital well-being and supportive conditions for innovative work behavior may merit attention in efforts to support PE teachers’ occupational well-being during AI integration; longitudinal research is needed to test these possibilities.

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Publication Details

Journal
Frontiers in Psychology
Published
2026-10-26
DOI
https://doi.org/10.3389/fpsyg.2026.1999813
Primary Topic
Technostress in Professional Settings
Type
article
Field-Weighted Citation Impact
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article

Perceived AI acceptance and occupational well-being among university physical education teachers: a cross-sectional serial mediation model of digital well-being and innovative work behavior

Jun Miao
1 links
Frontiers in Psychology
Technostress in Professional Settings
article

Perceived AI acceptance and occupational well-being among university physical education teachers: a cross-sectional serial mediation model of digital well-being and innovative work behavior

Jun Miao
article en

Abstract

Objective This study aimed to test a serial mediation model examining whether perceived AI acceptance is indirectly associated with university physical education (PE) teachers’ occupational well-being through digital well-being and innovative work behavior, as proposed on the basis of Conservation of Resources theory. Methods A cross-sectional design was adopted, and 807 university PE teachers were recruited from multiple universities in six provinces and municipalities of China through online convenience and snowball sampling. Self-report scales were employed to measure perceived AI acceptance (adapted from the Technology Acceptance Model), digital well-being (a researcher-developed instrument based on a published theoretical framework), innovative work behavior (general innovative behavior in one’s work role), and occupational well-being (the Job-related Affective Well-being Scale). The measurement structure was examined by confirmatory factor analysis, and indirect associations were estimated by bootstrapping (PROCESS Model 6, 5,000 resamples) using observed composite scores. Results Perceived AI acceptance was significantly and positively associated with occupational well-being (total effect B = 0.181, 95% CI [0.143, 0.220]). Three indirect associations were observed: via digital well-being ( B = 0.042, 95% CI [0.027, 0.059]), via innovative work behavior ( B = 0.040, 95% CI [0.026, 0.056]), and via digital well-being and innovative work behavior in sequence ( B = 0.021, 95% CI [0.015, 0.030]). The total indirect effect was 0.103, accounting for 56.91% of the total effect, while the direct effect accounted for 43.09%. Bootstrap confidence intervals for all indirect effects excluded zero. Conclusion Because the data are cross-sectional and self-reported, the results indicate statistical indirect associations and not temporal or causal mediation. The observed pattern is consistent with a Conservation of Resources-based sequence from perceived AI acceptance to digital well-being, innovative work behavior, and occupational well-being, which is theoretically proposed and not empirically established. The findings suggest that digital well-being and supportive conditions for innovative work behavior may merit attention in efforts to support PE teachers’ occupational well-being during AI integration; longitudinal research is needed to test these possibilities.

Frontiers in PsychologyVol. 17
Sichuan Film and Television University (CN)
Openalex Percentile: Top 8%
Technostress in Professional Settings
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