Physical activity and academic performance in adolescents: chain mediation through self-regulation and self-efficacy with gender and urban–rural differences

Background: Empirical evidence increasingly supports a positive association between physical activity and adolescent academic performance, yet most studies rely on single-mediator models and rarely examine serial mediation or demographic heterogeneity.

Methods: Using nationally representative data from the China Education Panel Survey (CEPS, 2014–2015), this investigation analyzed 8,037 secondary school students. Nested regression models were first estimated to assess the direct association between physical activity and academic performance. Structural equation modeling with bootstrap resampling was then applied to examine mediation pathways through self-regulation and self-efficacy, followed by multi-group analyses across gender and urban–rural subgroups.

Results: Physical activity was positively associated with academic performance. Mediation analysis indicated that this association operated through self-regulation and self-efficacy, including a serial pathway of “physical activity → self-regulation → self-efficacy → academic performance.” Heterogeneity analysis further showed that this serial mediation was stronger for males than females and for rural students than urban students, with males and rural students relying more on self-regulation, whereas females and urban students showed a relatively greater contribution of self-efficacy.

Conclusion: Physical activity enhances adolescents’ academic performance through psychological mechanisms such as self-regulation and self-efficacy, including a mediated pathway from self-regulation to self-efficacy. The strength and relative importance of these pathways vary by gender and urban/rural location: boys and rural students benefit more from self-regulation, while girls and urban students rely more on self-efficacy. Therefore, physical activities conducted in schools and homes should explicitly integrate training in self-regulation and self-efficacy into physical education classes and after-school activities, and be adjusted according to gender and environmental differences.

1 Introduction

Regular physical activity confers multifaceted benefits for children and adolescents, including improved physical fitness, cardiometabolic health, skeletal development, cognitive functioning, and psychological well-being (Pinho et al., 2024; Migueles et al., 2023; Proia et al., 2021; Liu et al., 2025; Liu et al., 2024). The World Health Organization recommends that children and adolescents aged 5–17 years accumulate at least 60 min of moderate-to-vigorous physical activity daily (World Health Organization, 2022). However, a pooled analysis of 298 school-based surveys from 146 countries revealed that around 81% of adolescents aged 11–17 years do not meet this guideline (Guthold et al., 2020), and national reports indicate that only about one quarter of Chinese students achieve established health-related fitness standards (Xinhua News, 2021).

In China’s current educational environment—characterized by exam-oriented schooling and widespread parental academic anxiety—physical activity is often viewed as a distraction that “takes up study time” and “distracts attention.” As a result, extracurricular time is frequently devoted to additional academic tutoring, while opportunities for movement are reduced (Hao W. et al., 2022). However, evidence from other countries challenges this view. Álvarez-Bueno et al. (2017) conducted a meta-analysis of school-based physical activity interventions for children aged 4–13 years from 11 countries (the United States, Australia, the Netherlands, Sweden, Canada, Denmark, Germany, India, Norway, South Africa, and Spain) and found that physical education lessons and other structured school programmes improved classroom behavior and enhanced multiple aspects of academic achievement, particularly in mathematics, reading, and overall performance. Similarly, Sember et al. (2020) synthesised 44 intervention studies from multiple countries involving school-aged children aged 5–16 years and reported small but positive effects of school-based physical activity on academic performance, with stronger benefits when interventions were delivered by highly qualified personnel such as physical education teachers. Loturco et al. (2022) reviewed physical activity programmes implemented from kindergarten through high school in 12 countries (Australia, Brazil, Canada, Chile, Croatia, Denmark, Israel, Malaysia, the Netherlands, Norway, Spain, and the United States) and showed that gains in mathematics tended to be larger than those in language and reading. This shows that in various international educational environments, sports activities do not harm academic performance; on the contrary, they may slightly improve academic performance, especially in mathematics.

Bandura’s Social Cognitive Theory (SCT) provides the overarching framework for this study (Bandura, 1986, 1997). SCT posits that human functioning arises from triadic reciprocal determinism, whereby personal factors, behavior, and the social environment continuously interact to shape one another. Within this framework, individuals are conceptualised as proactive agents who exercise personal agency through processes such as observational learning, forethought, self-regulation, and self-reflection (Bandura, 2001). Two constructs are central to the present investigation. Self-efficacy refers to individuals’ beliefs in their capabilities to organise and execute the actions required to attain desired outcomes and thereby influences task choice, effort, and persistence in the face of obstacles (Bandura, 1997). Self-regulation refers to the capacity to set goals, mobilise strategies, monitor progress, and adjust thoughts, emotions, and behaviors in line with internal standards (Chen et al., 2024). In the context of learning, academic self-efficacy and self-regulatory skills have repeatedly been identified as key psychosocial predictors of engagement, persistence, and performance (Zimmerman, 2000; Artino, 2012; Schunk and DiBenedetto, 2020). Recent research emphasizes that academic self-efficacy and self-regulation are key predictors of student academic achievement. Regarding self-efficacy, a 2024 meta-analysis found a moderate correlation between it and academic performance in online learning environments (Da, 2024). A literature review covering 2018–2023 also confirmed this finding, identifying a sustained positive correlation in blended learning environments (Yokoyama, 2024). Meanwhile, other studies have highlighted the crucial role of self-regulation. Theobald (2021) found that self-regulation training in higher education significantly improved students’ academic performance and resource management strategies. Similarly, research in K-12 and higher education has confirmed the positive impact of self-regulation interventions on learning outcomes (Xu et al., 2023; Guntur and Purnomo, 2024), while research in continuing education shows that regular self-regulation practice leads to better learning outcomes (Hemmler and Ifenthaler, 2024). In summary, these findings suggest that enhancing self-efficacy and self-regulation is an effective pathway to academic success.

Physical activity is an important context for enhancing both self-regulation and self-efficacy. A systematic review of 46 studies on young children showed that higher levels of physical activity are generally associated with better self-regulation, whereas children with low physical activity and poor self-regulation tend to display less favourable behavioral and developmental profiles (D’Cruz et al., 2024). Among adolescents, emotional self-regulation has been found to partially mediate the relationship between physical activity habits and subjective well-being, suggesting that regular activity helps adolescents cope more adaptively with their emotions (Fuentealba-Urra et al., 2023). Systematic reviews and meta-analyses of cognitively engaging physical activity interventions have further reported small but significant improvements in executive functions—particularly inhibitory control—among children and adolescents, with longer, more frequent programmes and game-like tasks yielding stronger effects (Mao et al., 2024). Consistent with this, a large cross-sectional study of primary school students showed that daily physical activity and participation in organised sports were positively associated with executive function, especially in sports that place higher tactical and cognitive demands on participants (Yang et al., 2024). Physical activity is also positively related to adolescents’ self-efficacy. A meta-analysis of correlates of youth physical activity demonstrated that self-efficacy plays a substantial role in the pathway from social support to adolescents’ physical activity, highlighting its central function in activity-related behavior change (Lin et al., 2024). Recent large-scale adolescent surveys have further emphasised self-efficacy as a key mechanism. In a sample of Chinese middle school students, physical activity was positively associated with self-efficacy and stress self-management, and these variables jointly contributed to the association between physical activity and mental health (Zhang et al., 2024). In a population-based study of Norwegian adolescents, those who met physical activity recommendations reported higher self-efficacy and better mental health profiles than peers who were insufficiently active (Grasaas et al., 2024). Overall, regular physical activity provides opportunities for successful self-regulation, strengthen general and thereby indirectly promote adolescents’ academic performance.

Based on the theoretical framework and empirical evidence, this study proposes the following hypotheses:

H1: Physical activity positively predicts academic performance among adolescents.

H2: Self-regulation mediates the relationship between physical activity and academic performance.

H3: Self-efficacy mediates the relationship between physical activity and academic performance.

H4: Self-regulation and self-efficacy play a serial mediating role in the relationship between physical activity and academic performance (Physical Activity → Self-Regulation → Self-Efficacy → Academic Performance).

H5: These mediation pathways exhibit significant heterogeneity across gender and urban-rural groups.

2 Research design

2.1 Analytical framework

All analyses were conducted in Stata 17.0. First, descriptive statistics and Pearson correlations were calculated to characterise the study variables and examine their bivariate associations. Second, nested linear regression models were estimated to assess the association between physical activity and academic performance while sequentially adjusting for covariates (Aiken et al., 1991). Third, structural equation modelling (SEM) was used to test the hypothesised mediation and serial mediation pathways via self-regulation and self-efficacy (Kline, 2023). Model fit was assessed using standard SEM fit indices (CFI, TLI, RMSEA, SRMR; Lomax, 2004). Indirect effects were estimated with bias-corrected bootstrap confidence intervals based on 5,000 resamples (Preacher and Hayes, 2008). Finally, multi-group SEM was used to estimate the model separately for gender and residential, and to examine whether structural paths differed across groups based on comparisons of model fit indices and key path coefficients (Byrne, 2013).

2.2 Data source and variable selection

2.2.1 Data source

This investigation utilizes data from the China Education Panel Survey (CEPS), a nationally representative longitudinal study employing multi-stage probability proportional to size (PPS) sampling methodology. CEPS encompasses over 20,000 students from 112 schools across diverse geographic regions, providing comprehensive individual, familial, institutional, and community-level information. The survey protocol includes baseline data collection (2013–2014) and subsequent 7th-grade follow-up assessments (2014–2015). Our analysis leverages the most recent wave (2014–2015), yielding a final analytical sample of 8,037 secondary school students after listwise deletion of cases with missing values on study variables.

2.2.2 Variable operationalization

Detailed variable specifications are presented in Table 1, encompassing outcome measures, primary predictors, mediating variables, and comprehensive control covariates across individual, familial, and institutional domains. The reliability of the two-item scales used as mediating variables (self-regulation and self-efficacy) was assessed. The scale for self-regulation yielded a Cronbach’s alpha of 0.807, and the scale for self-efficacy yielded a Cronbach’s alpha of 0.713. These reliability coefficients meet and exceed the generally accepted threshold for social science research (α ≥ 0.70), thereby validating the constructs for subsequent analysis.

Table 1

Table 1. Variable descriptions and measurement specifications.

2.3 Model specification

The baseline association between physical activity and academic performance was specified using a linear regression model of the form shown in Equation 1:

$\begin{array}{ll}A{P}_i={\alpha }_0+{\alpha }_{1}P{A}_i+{\alpha }_2{X}_i+{\in }_i& (1)\end{array}$

Where $A{P}_i$ represents academic performance for student $i$ , $\mathit{PA}$ denotes physical activity, $X_i$encompasses comprehensive control covariates including individual characteristics (gender, household registration, extracurricular tutoring, boarding status), family characteristics (parental education, economic status), and school characteristics (institutional ranking, governance type), and ${\in }_i$ is the error term. This specification follows standard practice in educational and epidemiological research (Wooldridge, 2016).

The mediation and serial mediation hypotheses were specified within a structural equation modelling framework. The structural part of the model can be written as:

$\begin{array}{ll}{\mathrm{M}}_{1i}={\beta }_{10}+{\beta }_{11}P{A}_i+{\beta }_{12}{X}_i+{\in }_{1i}& (2)\end{array}$

$\begin{array}{ll}{\mathrm{M}}_{2i}={\beta }_{20}+{\beta }_{21}P{A}_i+{\beta }_{22}{X}_i+{\in }_{2i}& (3)\end{array}$

$\begin{array}{ll}A{P}_i={\gamma }_0+{\gamma }_{1}P{A}_i+{\gamma }_2{\mathrm{M}}_{1i}+{\gamma }_3{\mathrm{M}}_{2i}+{\gamma }_4{X}_i+{\in }_i& (4)\end{array}$

Where ${\mathrm{M}}_{1i}$ and ${\mathrm{M}}_{2i}$ represent self-regulation and self-efficacy, respectively. Indirect and serial indirect effects were quantified using the product-of-coefficients approach (MacKinnon, 2012). Their statistical significance was assessed with bias-corrected 95% bootstrap confidence intervals based on 5,000 resamples, as recommended for mediation and serial mediation models (Hayes, 2017).

To examine demographic heterogeneity in the mediation mechanisms, multi-group SEM was conducted by gender and residential location. For each subgroup, the same structural model specified in Equations 2–4 was estimated, and differences in structural paths and indirect effects were examined by comparing model fit indices and key path coefficients across groups (Cheung and Rensvold, 2002).

3 Results

3.1 Group comparisons of physical activity and academic-related variables

Chi-square tests and Mann–Whitney U tests were used to examine sociodemographic differences between physically active and inactive groups. As shown in Table 2, males had higher rates of physical inactivity than females (p < 0.001), and rural students had higher rates than urban students (p < 0.01). Students with lower parental educational attainment showed lower physical inactivity rates than those with highly educated parents (p < 0.01). Students attending average or below-average schools had higher physical inactivity rates than those in high-ranking schools (p < 0.01). The physically active group reported higher self-regulation and self-efficacy scores than the inactive group (p < 0.001).

Table 2

Table 2. Sociodemographic characteristics by physical activity status [n (%)].

As illustrated in Figure 1, physical activity was positively correlated with academic performance (r = 0.240, p < 0.001), self-efficacy (r = 0.183, p < 0.001), and self-regulation (r = 0.240, p < 0.001). Self-efficacy and self-regulation were also positively correlated (r = 0.246, p < 0.001).

Figure 1

Figure 1. Correlation heatmap of study variables.

3.2 Association between physical activity and adolescent academic performance

To examine the association between physical activity and adolescent academic performance, five nested regression models were estimated, progressively adding individual, family, school, and psychological variables. The results are presented in Table 3. In Model (1), which included only physical activity as the explanatory variable, physical activity was positively associated with academic performance (β = 7.848, p < 0.001). In Model (2), after additionally controlling for gender, household registration type, extracurricular tutoring, and boarding status, the coefficient for physical activity decreased to 5.521 (p < 0.001) but remained statistically significant. Across Models (2) to (5), female students showed higher academic performance than males, with regression coefficients ranging from 7.30 to 8.19 (p < 0.001). Students with rural household registration had lower academic performance than urban students, with coefficients increasing from −5.353 in Model (2) to −1.372 in Model (5) (p < 0.001). Model (3), which added family background variables, showed that higher parental educational attainment and better family economic status were associated with higher academic performance. Students whose parents had tertiary or postgraduate education scored higher than those in the reference group (β = 15.520 and β = 13.880; p < 0.001). Model (4), including school-level variables, indicated that students from high-ranking schools had higher scores than those from average or below-average schools (β = 9.195, p < 0.001), whereas students in private schools scored lower than those in public schools (β = −4.066, p < 0.001). In Model (5), after adding self-regulation and self-efficacy, the coefficient for physical activity further decreased to 2.804 (p < 0.05). Self-regulation and self-efficacy were both positively associated with academic performance (β = 1.444 and β = 1.287; p < 0.001). The model R² increased from 0.005 in Model (1) to 0.193 in Model (5). AIC and BIC values decreased across successive models (Table 3).

Table 3

Table 3. Regression results of physical activity impact on adolescent academic performance.

3.3 Mediation mechanisms and group heterogeneity

Structural equation modelling with bootstrap resampling (5,000 iterations) was used to examine the mediating roles of self-regulation and self-efficacy in the association between physical activity and academic performance. The results are presented in Table 4. The total effect of physical activity on academic performance was 4.953, of which the direct effect was 2.347, accounting for 47.39% of the total effect. The total indirect effect through self-regulation and self-efficacy was 2.706, representing 52.61% of the total effect. As shown in Figure 2, three indirect pathways were identified: a single mediation pathway through self-regulation, a single mediation pathway through self-efficacy, and a serial mediation pathway involving both mediators. The indirect effect through self-regulation was 1.418 (95% CI [0.954, 1.882]), and the indirect effect through self-efficacy was 1.099 (95%CI[0.769, 1.428]). The serial mediation pathway “physical activity → self-regulation → self-efficacy → academic performance” yielded an indirect effect of 0.190 (95% CI [0.118, 0.262]).

Table 4

Table 4. Mediation analysis results for total sample (bootstrap).

Figure 2

Figure 2. Mediation pathways from physical activity to academic performance: (a) simple mediation via self-regulation; (b) simple mediation via self-efficacy; (c) serial mediation via self-regulation and self-efficacy.

Gender-stratified mediation results are shown in Table 5. Among males, the total indirect effect of physical activity on academic performance was 3.146, accounting for 63.5% of the total effect. Among females, the corresponding total indirect effect was 1.848, accounting for 51.1% of the total effect. For males, the mediation pathway via self-regulation contributed 38.0% of the total effect, the mediation pathway via self-efficacy contributed 21.5%, and the serial mediation pathway contributed 4.0%. For females, the mediation pathway via self-efficacy contributed 26.7% of the total effect, the mediation pathway via self-regulation contributed 21.0%, and the serial mediation pathway contributed 3.7%.

Table 5

Table 5. Mediation analysis results by gender (bootstrap).

Urban–rural stratified results are presented in Table 6. The total indirect effect was 2.828 (51.10%) among rural students and 1.849 (48.50%) among urban students. For rural students, the mediation pathway via self-regulation accounted for 33.80% of the total effect, the mediation pathway via self-efficacy accounted for 15.40%, and the serial mediation pathway accounted for 2.80%. For urban students, the corresponding proportions were 39.90% for the mediation pathway via self-regulation, 22.40% for the mediation pathway via self-efficacy, and 4.40% for the serial mediation pathway.

Table 6

Table 6. Mediation effect test results by household registration (bootstrap).

4 Discussion

This study examined whether physical activity is associated with adolescents’ academic performance and whether this association is explained by self-regulation and self-efficacy, including a serial mediation pathway, as well as whether these mechanisms differ by gender and urban–rural residence. Using nationally representative data, the analyses showed that physical activity was positively related to academic performance; that self-regulation and self-efficacy each partially mediated this association, alongside a statistically significant serial mediation pathway from physical activity to self-regulation to self-efficacy to academic performance; furthermore, the strength and relative contribution of these mediating pathways differed by gender and urban/rural residence.

The positive correlation between physical activity and academic performance is consistent with recent findings, indicating that physical activity has a moderate benefit to academic performance, particularly in mathematics and overall academic performance (Álvarez-Bueno et al., 2017; Sember et al., 2020; Loturco et al., 2022; Singh et al., 2022). In addition to this association, recent research further confirms that academic self-efficacy and self-regulation are among the most reliable psychosocial predictors of academic performance. Meta-analyses and review reports show that there is a moderate positive correlation between academic self-efficacy and academic achievement across various learning contexts (Da, 2024; Yokoyama, 2024), and self-regulated learning interventions have been shown to produce small to moderate improvements in student grades and learning outcomes (Theobald, 2021; Xu et al., 2023; Guntur and Purnomo, 2024; Hemmler and Ifenthaler, 2024). In the area of physical activity, empirical research indicates that participation in sports is associated with higher self-efficacy and better academic performance; among Chinese university students, participation in sports has been found to partially improve academic performance by enhancing general self-efficacy (Li et al., 2022), and self-efficacy has been identified by systematic reviews and meta-analyses as a key mediator between social support and adolescent physical activity (Lin et al., 2024; Liu et al., 2024). Cross-sectional and longitudinal studies of Chinese and Norwegian adolescents further demonstrate that achieving recommended levels of physical activity is associated with higher self-efficacy and better mental health (Zhang et al., 2024; Grasaas and Sandbakk, 2024). Supplementary evidence from younger children suggests that self-regulation partially mediates the relationship between physical activity and academic achievement (Vasilopoulos et al., 2023), and that physical activity is positively correlated with self-regulation (D’Cruz et al., 2024; Fuentealba-Urra et al., 2023). Combined with the findings of this study, this model supports a dual psychological pathway: physical activity promotes academic achievement by enhancing self-regulation and self-efficacy.

Stratified analysis by gender showed that the overall mediating effect was greater for males than for females, with significant differences in the primary mediating pathways. For boys, the indirect effects generated through self-regulation were more significant; while for girls, the pathway generated through self-efficacy accounted for a larger proportion of the overall effect. This pattern is consistent with previous research findings that have shown male adolescents exhibit stronger behavioral regulation and performance-oriented motivation in physical activities, while women tend to focus more on internalized or self-referential motivation (Biddle and Batterham, 2015; Opdenakker, 2022). From the perspective of social cognitive theory, female students typically place greater emphasis on perceived competence, self-evaluation, and intrinsic motivation in both physical and academic fields (Crocker et al., 2004; Schunk and DiBenedetto, 2020). In contrast, the stronger benefits gained by boys through self-regulation may reflect a socialization process that emphasizes goal-oriented behavior and extrinsic success (Morosanova et al., 2023). Neuroimaging studies have reinforced this view, finding that boys show higher activation in the prefrontal cortex regions associated with behavioral control during movement, while girls show greater activation in the medial prefrontal cortex regions associated with self-reference processing (Davis et al., 2011).

Stratified analysis by urban–rural status reveals that rural students exhibit a stronger overall mediating effect, with self-regulation playing a predominant role. This aligns with findings that functional physical activity among rural adolescents is closely linked to the development of self-regulation abilities (Zhang et al., 2023). Furthermore, resource constraints in rural areas may foster a “necessity-driven” developmental model, compelling adolescents to adopt effective behavioral regulation strategies (Li and Wang, 2024). Conversely, urban students demonstrate a more balanced profile, where self-regulation, self-efficacy, and serial mediation pathways jointly contribute to the association. While access to diverse and structured sports programs affords urban youth multiple opportunities to cultivate positive self-beliefs (Chen et al., 2023), the complexity of urban environments often necessitates role-balancing. This complexity potentially disperses developmental benefits across various psychological domains rather than concentrating them within a single mechanism (Martinez and Rodriguez, 2024; Mishra et al., 2023).

5 Conclusion

This study found a positive correlation between physical activity and adolescents’ academic performance. This association is partially explained by self-regulation and self-efficacy, highlighting a serial mediation pathway from physical activity to self-regulation, subsequently to self-efficacy, and ultimately to academic performance. Notably, this mediation effect was more pronounced in boys and rural students, who relied primarily on the self-regulation pathway, whereas girls and urban students demonstrated a relatively stronger reliance on self-efficacy. Therefore, schools and families should not only increase physical activity time but also explicitly integrate self-regulation and self-efficacy training into physical education. In-school PE classes and after-school programs can foster these psychological attributes through goal setting, task planning, and the design of challenging yet achievable activities. Specifically, interventions for boys and rural students might prioritize behavioral regulation, while those for girls and urban students could focus on enhancing academic and physical self-efficacy through supportive feedback and autonomy-supportive instruction.

5.1 Research limitations

This study has several limitations. First, key variables such as physical activity, self-regulation, and self-efficacy are based on self-reports, which may introduce recall bias or social desirability effects. However, academic performance was derived from objective examination records, which helps to mitigate the concern of common method bias associated with relying solely on self-reported data. Second, the cross-sectional study design cannot establish causal relationships between physical activity, psychological mechanisms, and academic outcomes. Third, the model focuses only on self-regulation and self-efficacy, without incorporating other potential mechanisms. Finally, the data comes from Chinese adolescents, so whether the results can be generalized to other cultural and educational backgrounds remains to be tested.

5.2 Future research

Future research will focus on explicitly integrating self-regulation and self-efficacy training into physical activity interventions to assess their causal impact on academic performance. Furthermore, research should explore how the type, intensity, and context of physical activity, as well as environmental factors such as classroom atmosphere and teacher support, moderate these effects. In addition, longitudinal and multi-level research designs spanning different educational stages and regions are crucial for mapping the developmental trajectories of these mediating pathways and will contribute to the development of precise physical education policies.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

LC: Conceptualization, Data curation, Methodology, Writing – original draft. DL: Software, Validation, Visualization, Writing – review & editing. CT: Formal analysis, Investigation, Project administration, Supervision, Visualization, Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

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Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2025.1686270/full#supplementary-material

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