The Influence of University Physical Education Environments on College Students' Sports Participation Behavior: The Chain Intermediation Effect of Developing Self-Efficacy and Exercise Motivation

The Influence of University Physical Education Environments on College Students' Sports Participation Behavior: The Chain Intermediation Effect of Developing Self-Efficacy and Exercise Motivation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Influence of University Physical Education Environments on College Students' Sports Participation Behavior: The Chain Intermediation Effect of Developing Self-Efficacy and Exercise Motivation Yong Jiang, Wenhe Zhu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9082915/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract To explore the influence mechanism of University Physical Education Environment on college students' Sports Participation Behavior and to examine the mediating roles of Developing Self-Efficacy and Exercise Motivation, this study constructs a chained mediation model based on social cognitive theory. A combination of stratified cluster sampling and convenience sampling was employed to conduct a questionnaire survey among 700 college students from multiple universities in eastern China. Measurements were conducted using the University Physical Education Environment Scale, Developing self-efficacy Scale, Exercise Motivation Scale, and Sports Participation Behavior Scale. SPSS and the PROCESS macro (Model 6) were utilized for correlation analysis, regression analysis, and Bootstrap mediation effect testing. Results indicate that the University Physical Education Environment significantly and positively correlates with Developing Self-Efficacy, Exercise Motivation, and Sports Participation Behavior. It significantly and positively predicts students' Sports Participation Behavior. Developing Self-Efficacy and Exercise Motivation both significantly mediate the relationship between the University Physical Education Environment and Sports Participation Behavior. Furthermore, the University Physical Education Environment indirectly influences Sports Participation Behavior through the chained pathway “Exercise Motivation → Developing Self-Efficacy,” with the chain intermediation effect being significant. The study demonstrates that the University Physical Education Environment not only directly promotes students' Sports Participation Behavior but also exerts indirect effects by enhancing individual Developing Self-Efficacy and stimulating Exercise Motivation. These findings deepen the psychological mechanism explanation of how the University Physical Education Environment influences students' Sports Participation Behavior, providing theoretical foundations and practical insights for optimizing Physical Education Environment provision and enhancing students' Sports Participation levels in higher education institutions. University Physical Education Environment Sports Participation Behavior Developing self-efficacy Exercise Motivation Figures Figure 1 Figure 2 Introduction The Healthy China 2030 Plan places universities in a key strategic position for enhancing physical activity levels among youth, emphasizing the cultivation of stable healthy behaviors through institutional provision and environmental optimization [ 1 ]. However, insufficient physical activity among college students has become a prominent public health issue. Relevant surveys indicate that Chinese university students generally fail to meet recommended standards for weekly moderate-intensity physical activity. Persistently low activity levels not only increase risks of obesity and cardiovascular disease but also show significant correlations with psychological issues such as anxiety and depression. Despite universities possessing relatively well-developed resource foundations in terms of facilities and curriculum systems, actual utilization rates and exercise persistence remain low, with environmental advantages failing to effectively translate into stable Sports Participation Behavior [ 2 ]. Therefore, revealing the underlying mechanisms through which environmental support converts into sustained behavior holds significant practical and theoretical value. Existing research consistently indicates that supportive University Physical Education environments significantly enhance exercise frequency and duration. However, most studies remain focused on the direct relationship between environment and behavior, with relatively insufficient systematic integration of psychological mediating mechanisms. At the cognitive level, Developing self-efficacy is regarded as a key hub [ 3 ]. According to Social Cognitive Theory, the environment influences individuals' evaluations of their own capabilities through mastery experiences and social support, thereby providing a cognitive foundation for initiating and sustaining behavior. At the motivational level, the sustained implementation of behavior also depends on the quality of motivation. Based on Self-Determination Theory, when the environment satisfies individuals' needs for autonomy, competence, and relatedness, external demands are more likely to be internalized as self-determined motivation, promoting the sustained maintenance of exercise behavior. From an integrated theoretical perspective, the University Physical Education Environment, self-efficacy, and Exercise Motivation may form a sequential pathway of “context-cognition-motivation-behavior”: the environment first strengthens efficacy beliefs, enhanced efficacy further promotes motivation activation, and motivation directly drives sustained behavior. Compared to single or parallel mediation models, this chained structure more systematically reveals the underlying mechanisms through which environments influence Sports Participation Behavior [ 4 ]. Based on this, this study constructs a chained mediation model where the University Physical Education Environment influences college students' Sports Participation Behavior through Developing self-efficacy and Exercise Motivation. This aims to deepen theoretical explanations of the mechanisms and provide evidence for optimizing the University Physical Education Environment and implementing targeted interventions. 1 Theoretical Foundations and Assumptions 1.1 The Impact of University Physical Education Environments on College Students' Sports Participation Behavior The University Physical Education Environment refers to a comprehensive system formed by institutional, spatial, and social support elements surrounding student physical activities within the context of higher education, exhibiting a multi-layered nested structure [ 5 ]. From a structural perspective, it primarily encompasses three dimensions: the institutional environment, the physical environment, and the social support environment [ 6 ]. The institutional environment manifests through institutional arrangements such as curriculum design, evaluation mechanisms, and sports promotion policies, defining behavioral boundaries for student participation in physical activities through rule provision and opportunity structures; The physical environment primarily refers to the accessibility and openness of sports facilities, providing fundamental conditions for student physical activities. The social support environment manifests as the campus sports culture atmosphere and support resources from families and communities, continuously influencing individual behavioral choices through group norms, value orientations, and interactive networks. These multi-layered environmental elements are not isolated but collectively shape the real-world context of college students' Sports Participation Behavior through structural coupling and functional synergy. From a mechanism perspective, the influence of the University Physical Education Environment on Sports Participation Behavior follows the pathway of “environmental perception—cognitive evaluation—behavioral disposition—behavioral manifestation” [ 7 ]. Individuals first form subjective perceptions of environmental resources and support levels, then cognitively evaluate the feasibility and value of exercise based on these perceptions, ultimately developing behavioral dispositions. When campus environments provide ample resources and foster a positive atmosphere, individuals' willingness to participate and readiness to act are strengthened, ultimately translating into actual Sports Participation Behavior. Existing research also indicates that campus environments characterized by robust institutional support, high facility accessibility, and a positive sports culture significantly enhance college students' physical activity participation levels [ 8 ]. Based on this, the following hypothesis is proposed: H1: The University Physical Education Environment significantly and positively predicts college students' Sports Participation Behavior. 1.2 The Mediating Role of Developing Self-Efficacy Developing self-efficacy refers to an individual's subjective assessment of their ability to organize and execute specific behaviors. Developing self-efficacy manifests specifically as college students' belief in their capacity to consistently complete physical exercise tasks, encompassing aspects such as regulating exercise intensity, scheduling time, and coping with difficulties [ 9 ]. Within the interactive structure of “environment-individual-behavior,” self-efficacy occupies a pivotal cognitive position, serving to integrate situational information and regulate behavior [ 10 ]. The University Physical Education Environment influences self-efficacy formation through multiple social-cognitive sources: institutional provision and curriculum systems offer students stable mastery experiences, reinforcing perceived competence; peer participation and role modeling provide vicarious experiences, promoting cognitive internalization of ability judgments; instructor feedback and organizational support constitute verbal persuasion pathways, strengthening beliefs in action feasibility; while safety facilities and positive exercise experiences optimize emotional and physiological states, reducing failure expectations. These pathways collectively facilitate the cognitive transformation of environmental resources into stable efficacy beliefs [ 11 ]. In the process of behavioral regulation, developing self-efficacy plays a crucial role. On one hand, a high level of self-efficacy enhances the perception of action controllability and reduces behavioral initiation resistance. On the other hand, self-efficacy also strengthens goal persistence and effort commitment, maintaining behavioral continuity when facing situational pressures such as fatigue or time conflicts [ 12 ]. Therefore, developing self-efficacy holds significant predictive value for the intensity, frequency, and persistence of Sports Participation Behavior, serving as a crucial cognitive mediator linking environmental factors to behavioral outcomes. Based on this, the following hypothesis is proposed: H2: The University Physical Education Environment significantly influences college students' Sports Participation Behavior through the mediating effect of developing self-efficacy for exercise. 1.3 The Mediating Role of Exercise Motivation Exercise Motivation refers to the behavioral drive formed by individuals based on outcome expectations and self-evaluation, essentially manifesting as action tendencies stimulated by cognitive judgments regarding the value of behavior and the attainability of outcomes [ 13 ]. The University Physical Education Environment embeds itself in the formation process of individual outcome expectations through the synergistic effects of institutional provision, facility conditions, and sports culture. Institutional provision offers stable systemic support for sports participation behavior, enhancing perceptions of behavioral outcome feasibility. Well-equipped facilities increase accessibility to exercise opportunities, making behavioral benefits more tangible. A positive campus sports culture, through reinforcement of social values and construction of group norms, elevates the perceived meaning and appeal of sports engagement [ 14 ]. In this process, individuals integrate and evaluate contextual information through environmental perception, developing stable Exercise Motivation when outcome expectations are imbued with positive value. At the behavioral execution level, Exercise Motivation plays a crucial role in regulating behavior. First, Motivation influences behavioral direction, determining whether individuals engage in physical exercise and their goal priorities. Second, Motivation modulates behavioral commitment, affecting effort levels, time allocation, and participation frequency. Third, Motivation reinforces behavioral repetition through positive feedback, promoting the persistence and habitualization of Sports Participation Behavior [ 15 ]. Thus, Exercise Motivation serves not only as a vital source of energy for initiating physical activity but also as a crucial mechanism for sustaining it. Consequently, the University Physical Education Environment influences college students' Sports Participation Behavior by shaping individual outcome expectations and activating Exercise Motivation. Based on this, the following hypothesis is proposed: H3: The University Physical Education Environment significantly influences college students' Sports Participation Behavior through the mediating effect of Exercise Motivation. 1.4 The Chain Mediating Effect of Developing Self-Efficacy and Exercise Motivation Behavioral regulation is an integrated process where cognitive evaluation mechanisms and motivational generation mechanisms are mutually embedded. Developing self-efficacy reflects an individual's assessment of their ability to complete exercise tasks, belonging to the cognitive evaluation system of behavioral feasibility. Exercise Motivation, meanwhile, reflects the driving force for action formed by individuals based on outcome expectations and value judgments, residing within the behavioral energy regulation system. Within the behavioral regulation framework, these two elements form a continuous, interconnected relationship: self-efficacy provides the cognitive foundation for behavioral feasibility, while motivation activates and channels behavioral energy after value attribution, thereby constituting a chain-like “cognition-motivation” mechanism [ 16 ]. When individuals possess high Developing self-efficacy, they are more likely to develop positive outcome expectations and judgments of success probability. Consequently, the perceived value of behavioral outcomes increases, thereby promoting the generation and reinforcement of Exercise Motivation. This facilitates a continuous transition from cognitive evaluation to motivational activation [ 17 ]. In the context of University Physical Education, the University Physical Education Environment first influences individuals' cognitive systems through institutional provision, resource accessibility, and cultural atmosphere, thereby helping to develop self-efficacy. Subsequently, self-efficacy promotes motivation generation by optimizing outcome expectation structures, and further drives the formation and maintenance of Sports Participation Behavior through motivational regulation mechanisms [ 18 ]. Thus, the University Physical Education Environment does not directly influence behavioral outcomes but instead forms a chain mechanism—“environment-cognition-motivation-behavior”—through continuous transmission between the cognitive and motivational systems. Compared to single mediation pathways, this structure more systematically reveals the internal processes by which the environment influences Sports Participation Behavior [ 19 ]. Based on this, the following hypotheses are proposed: H4: The University Physical Education Environment significantly influences college students' Sports Participation Behavior through the Chain Intermediation Effect of Developing Self-Efficacy and Exercise Motivation.Consequently, the research hypothesis model is constructed as shown in Fig. 1 . 2 Research Subjects and Tools 2.1 Research Subjects and Sampling This study employed a combination of stratified cluster sampling and convenience sampling to conduct a questionnaire survey across multiple comprehensive universities in eastern China. Stratification was first based on university type and grade structure. Within each stratum, samples were drawn using class-based cluster sampling to ensure representativeness across different grades and academic backgrounds [ 20 ]. Inclusion criteria were: full-time undergraduate students enrolled at the institution; ability to independently comprehend the questionnaire content and complete it; voluntary participation in the study. Exclusion criteria included: individuals with severe physical illnesses or contraindications to exercise; respondents exhibiting abnormal completion times or discernible patterns in their responses; and questionnaires with missing values exceeding 5.7% of total items. A total of 743 questionnaires were distributed. After screening for logical consistency and completeness, 700 valid samples were obtained, yielding an effective response rate within the acceptable range for empirical social science research. The sample exhibited relatively balanced distribution across gender and grade levels, spanning freshmen through seniors, thereby adequately reflecting the overall characteristics of the university student population. The overall sample structure showed no significant skewness or clustering of a single group, providing a sound statistical foundation for structural model testing. 2.2 Research Tools This study measured four core variables: University Physical Education Environment, Developing self-efficacy, Exercise Motivation, and Sports Participation Behavior. All scales employed a 1–5 Likert-type scoring method, with higher scores indicating greater levels of the respective variable. 2.2.1 University Physical Education Environment Scale This study employs the University Physical Education Environment Scale developed by Li Junqing et al. (2007). This scale was localized and revised based on existing physical education environment assessment tools, featuring a relatively mature structural framework and practical applicability [ 21 ]. The scale comprises 30 items, comprehensively evaluating the University Physical Education environment across three dimensions: adequacy of facilities, environmental accessibility, and institutional support and sports atmosphere [ 22 ]. The scale employs a five-point Likert scale, where higher scores indicate greater individual endorsement of the University Physical Education Environment. As a structured environmental assessment tool, it features comprehensive item coverage, clear dimensional delineation, and straightforward administration. Demonstrating strong content validity and test-retest reliability, it is widely applied in university physical activity management and related empirical research. In the present study sample, the Cronbach's α for this scale was 0.956, significantly exceeding the commonly accepted standard of 0.70. This indicates extremely high internal consistency, providing a reliable measurement foundation for subsequent model analyses. 2.2.2 Developing self-efficacy scale This study employed the Developing Self-Efficacy Scale developed by Bandura (2006), comprising 18 items, to assess individuals' confidence in maintaining exercise routines across different contexts and potential obstacles [ 23 ]. Originally designed as a unidimensional construct, subsequent validation studies subdivided the scale into two dimensions based on situational characteristics: internal feelings and physiological states (e.g., fatigue, low mood, or physical discomfort); and external situational factors (e.g., unfavorable weather, time constraints, or lack of social support). The scale employs a five-point Likert scale, with higher scores indicating greater Developing self-efficacy [ 24 ]. This self-report instrument, grounded in social cognitive theory, emphasizes systematic assessment of behavioral beliefs across diverse impediments. It demonstrates strong predictive validity and cross-cultural applicability. In the present study sample, Cronbach’s α reached 0.920, indicating excellent reliability and strong internal consistency among items. This confirms the scale’s ability to reliably measure college students’ ability to develop self-efficacy for exercise. 2.2.3 Exercise Motivation Scale This study employed the Exercise Motivations Inventory-2 (EMI-2) scale developed by Markland and Hardy (1993) and revised by Markland and Ingledew (1997) [ 25 ]. This multidimensional Exercise Motivation assessment tool comprises 36 items in its standard version (some studies employ an extended item version), covering 14 motivational dimensions: stress management, revitalization, enjoyment, challenge, social recognition, belongingness, competition, health pressure, disease prevention, active health, weight management, appearance, strength/endurance, and agility [ 26 ]. The scale employs a five-point Likert scale, with higher scores indicating stronger motivation for physical activity participation. Grounded in self-determination theory, this tool systematically integrates intrinsic and extrinsic motivational factors to comprehensively assess multiple drivers of exercise initiation and persistence, demonstrating strong construct validity and cross-cultural applicability. In the present study sample, the scale demonstrated a Cronbach's α of 0.96, indicating exceptional internal consistency that meets measurement requirements for structural model analysis. 2.2.4 Sports Participation Behavior Scale This study employed the Physical Activity Grading Scale developed by Liang Deqing (1994) to measure individual levels of sports participation [ 27 ]. The scale assesses three dimensions: exercise intensity, duration, and frequency. Intensity ranges from 1 (light) to 5 (heavy), duration from 1 (less than 15 minutes) to 5 (over 1 hour), and frequency from 1 (less than once per month) to 5 (daily). The total score is calculated using the formula “intensity × duration × frequency,” with higher scores indicating greater physical activity participation levels [ 28 ]. As a self-report behavioral measurement tool, this scale focuses on quantifying individual physical activity levels. It features a concise structure, intuitive calculation, and user-friendly operation, making it suitable for both adolescent and adult populations. Widely applied in sports psychology and health behavior research, it has demonstrated sound reliability and validity foundations. In the present study sample, the Cronbach's α for this scale was 0.824, exceeding the 0.80 standard. This indicates good internal consistency, demonstrating its ability to reliably reflect college students' Sports Participation Behavior levels. 2.3 Data Collection Procedures This study employed an online questionnaire for data collection, with the survey completed over several weeks. Prior to questionnaire distribution, participants received a standardized explanation outlining the research objectives and completion requirements. The questionnaire's opening page explicitly stated adherence to principles of anonymity and voluntary participation [ 29 ]. Participants could only access the formal questionnaire page after reading and confirming their agreement to the informed consent statement, ensuring the survey process complied with fundamental research ethics standards. To mitigate potential homogeneity bias effects on the findings, multiple control measures were implemented at the program design level: First, the instructions emphasized that there were no right or wrong answers, encouraging respondents to answer based on their genuine feelings to reduce social desirability bias; Second, the order of certain items was randomized to prevent systematic response tendencies. Third, appropriate reverse-scored items were included in the scales to identify and control for mechanical or consistent responses. Furthermore, the research protocol received ethical review approval from the institution prior to implementation. Data collection strictly adhered to ethical principles and academic standards for social science research, ensuring the authenticity and reliability of research data at the procedural level [ 30 ]. 2.4 Data Analysis Methods This study employed SPSS software and the PROCESS macro (Version 4.1) for statistical analysis. First, reliability tests were conducted on each scale, assessing internal consistency through calculation of Cronbach’s α coefficients. Subsequently, descriptive statistical analysis was performed, calculating the mean, standard deviation, skewness, and kurtosis of each variable to examine data distribution characteristics [ 31 ]. Building on this foundation, independent samples t-tests or one-way analysis of variance (ANOVA) were employed to compare differences in key variables across groups with distinct demographic characteristics. Effect size indices were reported to assess the practical significance of these differences [ 32 ]. Subsequently, Pearson correlation analysis was employed to examine linear relationships between variables. Multivariate regression analysis was then used to sequentially test direct effects and potential mediating pathways. To assess chained mediation effects, Model 6 of the PROCESS macro was applied, utilizing 5,000 bootstrap resamples to construct 95% confidence intervals. Mediating effects were deemed significant when confidence intervals excluded zero. The statistical significance level was set at α = 0.05. Standardized regression coefficients and effect size indicators (f²) were reported to assess the model's practical explanatory power. 3 Research Findings 3.1 Common Method Bias Test To guard against potential common method bias in self-reported questionnaire data, this study employed exploratory factor analysis using principal component analysis combined with Promax oblique rotation. This approach examined the potential impact of common method variance on measurement validity and provided diagnostic evidence for subsequent model construction. Data suitability tests revealed a Kaiser-Meyer-Olkin measure of 0.985, significantly exceeding the 0.70 threshold. This indicates extremely strong inter-variable correlations, rendering the data highly suitable for factor analysis [ 33 ]. The Bartlett sphericity test yielded an approximate chi-square value of 35,593.878 (df = 4005, p < 0.001), strongly rejecting the null hypothesis of variable independence and further confirming data suitability for factor extraction. Additionally, diagonal elements in the inverse correlation matrix exceeded 0.40, indicating no severe multicollinearity among observed variables, allowing all to be included in subsequent analysis. The presence of CMB was assessed using Harman's single-factor test. All items were forced onto a single, unrotated common factor, revealing that the first common factor explained 41.861% of the total variance. This value falls within the 40%–50% cautionary range, indicating a certain degree of method covariation in the data, though not yet reaching the severe bias level exceeding 50%. Further analysis revealed nine components with eigenvalues exceeding 1.0, collectively explaining 52.057% of total variance. This indicates variation stems not from a single methodological factor but is distributed across multiple substantive dimensions. Item-factor commonality tests revealed that all selected items exceeded the recommended threshold of 0.50, indicating these items effectively capture variance in their latent variables with high extraction efficiency. However, cross-loadings were observed in the unrotated factor matrix. Therefore, Promax oblique rotation was applied to achieve a more parsimonious factor structure, allowing natural correlations between factors—a particularly suitable approach for multidimensional psychological and behavioral constructs in sports science [ 34 ]. Overall, while moderate common method variance was detected, the first factor explained a reasonable proportion of variance, and the cumulative explanatory power of multiple factors exceeded 50%. This supports the basic construct validity of the measurement tool. 3.2 Demographic Descriptive Statistics Prior to conducting primary hypothesis tests, this study systematically evaluated the reliability of measurement instruments, the distributional characteristics of sample data, and demographic composition to ensure the robustness, validity, and ecological validity of subsequent parametric statistical analyses. Reliability analysis employed Cronbach's α coefficient to assess internal consistency reliability across scales. Results indicate all core scales demonstrated exceptionally high internal consistency: School Physical Environment Scale (30 items) α = 0.956; Developing self-efficacy Scale (18 items) α = 0.920; Exercise Motivation Scale (36 items) α = 0.966; Sports Participation Behavior Scale (6 items) α = 0.824. These coefficients significantly exceeded the stringent threshold of 0.80, with the School Physical Environment and Exercise Motivation scales approaching or surpassing the excellent level of 0.95. This performance substantially exceeded the standard recommended by Nunnally (1978) for basic research and the higher expectations set by Lance et al. (2006) for mature scales in applied research [ 35 ]. Detailed reliability results are presented in Table 1 . Table 1 Internal Consistency Reliability of Core Scales (N = 700) Variable Number of items Cronbach’s α Note School Sports Environment 30 0.956 Extremely high reliability Sports Participation Behavior 18 0.920 High reliability Developing self-efficacy 36 0.966 Extremely high reliability Exercise Motivation 6 0.824 Good reliability Descriptive statistics further reveal the central tendency and dispersion of the sample across core variables (Table 2 ). The means of all variables fell within the upper-middle range of the 5-point Likert scale, indicating that the sample's overall perceptions of the school sports environment, self-efficacy, motivation, and actual Sports Participation Behavior were moderately positive. Standard deviations ranged from 0.765 to 0.863, reflecting moderate individual variation consistent with the expected heterogeneity in sports-related psychological and behavioral variables among college students. The absolute values of skewness and kurtosis were both below 0.80 and 1.00, respectively, far below the lenient thresholds of |2| and |7|. The overall distribution approximated normality, supporting the parametric assumptions for Pearson correlation and multiple linear regression Bootstrap mediation analysis [ 36 ]. The demographic characteristics of the sample further enhance the representativeness and external validity of the study. This study obtained 700 valid questionnaires (N = 700, no missing data), which underwent descriptive statistical analysis using SPSS. Gender distribution was nearly balanced: males accounted for 50.6% (n = 354) and females for 49.4% (n = 346), effectively controlling for potential confounding effects of gender on mediating pathways. Grade distribution was relatively uniform: Freshmen 28.1% (n = 197), Sophomores 23.1% (n = 162), Juniors 25.4% (n = 178), Seniors 23.3% (n = 163). This broadly covered different learning pressures and developmental needs across all undergraduate education stages, enhancing the generalizability of conclusions. Significant heterogeneity in academic backgrounds: 53.4% (n = 374) were physical education majors, while 46.6% (n = 326) were non-physical education majors, with both groups possessing sufficient sample sizes. This disciplinary composition not only reflects natural variation in students' sports-related experiences and cognition but also provides a necessary foundation for subsequent analyses examining the potential moderating or differential effects of disciplinary attributes on perceived sensitivity to the sports environment, Exercise Motivation, and self-efficacy. The distribution of monthly per capita household income exhibits a certain socioeconomic gradient: low-income groups (< 3000 yuan and 3000–6000 yuan) collectively accounted for 70.7%, while the proportion of middle-to-high-income groups was relatively low. Table 2 Demographic Characteristics of the Sample Population attribute Category Quantity Percentage % Gender Male Female 354 346 50.6 49.4 Grade Freshman year Sophomore year Junior year Senior year 197 162 178 163 28.1 23.1 25.4 23.3 Professional Sports Non-Sports 374 326 53.4 46.6 Monthly household income 10000元 224 271 128 77 32.0 38.7 18.3 11.0 To further mitigate multicollinearity risks and facilitate interpretation of path coefficients in conditional process models, this study centered the means of continuous independent variables and mediating variables (Table 3 ). Following centering, the means of all variables approached zero while standard deviations remained unchanged. The absolute values of skewness and kurtosis further decreased, resulting in more stable distribution characteristics [ 37 ]. Table 3 Descriptive Statistics of Core Variables After Decentralization (N = 700) Variable minimum value maximum value mean Standard deviation 偏度 峰度 University Physical Education Environment (Decentralized) -1.76 1.04 0.0015 0.821 -0.744 -0.976 Developing self-efficacy (Decentralization) -1.71 1.01 0.0016 0.765 -0.777 -0.845 Exercise Motivation (Decentralized) -1.66 1.01 -0.0017 0.805 -0.783 -0.971 Note: Decentralization is achieved by subtracting the sample mean; skewness and kurtosis values indicate a distribution close to normal, supporting the parametric statistical hypothesis. Through systematic verification of reliability, distribution characteristics, demographic composition, and data preprocessing, this study demonstrates high data quality and strong sample representativeness. This establishes a reliable statistical foundation for subsequent correlation analysis, regression modeling, and chained mediation effect testing. 3.3 Independent Samples t-Test To systematically examine potential group differences in core constructs based on dichotomous demographic variables, this study employed independent samples t-tests. Levene's test for variance homogeneity was conducted to assess the validity of the hypothesis, and Cohen's d was calculated as an effect size indicator [ 38 ]. This analysis aimed to identify potential influencing factors and provide empirical support for covariate selection in subsequent regression models. All tests employed a two-tailed p < 0.05 significance threshold, with calculations based on decentered variables to ensure coefficient stability [ 39 ]. Levene's test results indicated that the assumption of homogeneity of variances held for all variables (p > 0.05), supporting the applicability of the standard t-test. 3.3.1 Gender Differences Independent samples t-test results indicate no significant between-group differences in school physical education environment, Developing self-efficacy, Exercise Motivation, or Sports Participation Behavior based on gender (Table 4 ). Specifically: The t-value for Developing Self-Efficacy was − 1.079 (df = 698, p = 0.281, Cohen’s d=-0.082); The t-value for Exercise Motivation was − 0.180 (df = 698, p = 0.857, Cohen’s d=-0.014); The t-value for Sports Participation Behavior was − 0.093 (df = 698, p = 0.926, Cohen’s d=-0.007). All absolute effect sizes were less than 0.10, indicating that gender contributed minimally to the systematic variation in these variables. This provides preliminary evidence supporting the gender-neutral hypothesis in contemporary sports behavior research [ 40 ]. Table 4 Comparison of Differences in Various Variables Among Students of Different Genders Gender N M ± SD t p University Physical Education Environment Male 354 3.39 ± 0.83 -0.105 0.916 female 346 3.39 ± 0.79 Sports Participation Behavior Male 354 3.35 ± 0.76 -1.079 0.281 female 346 3.41 ± 0.77 Developing self-efficacy Male 354 3.38 ± 0.83 -0.180 0.857 female 346 3.39 ± 0.81 Exercise Motivation Male 354 3.37 ± 0.88 -0.093 0.926 female 346 3.39 ± 0.85 3.3.2 Differences Between Groups of Only Children The results of the independent samples t-test indicate that whether an individual is an only child does not yield significant overall between-group differences for core variables, but it exhibits a marginal effect on Sports Participation Behavior (Table 5 ). Specifically: t-value for University Physical Education Environment = 0.887 (df = 698, p = 0.375, Cohen’s d = 0.068); t-value for Developing self-efficacy = 0.752 (df = 698, p = 0.453, Cohen’s d = 0.057); the t-value for Sports Participation Behavior was 0.914 (df = 698, p = 0.361, Cohen’s d = 0.070); and the t-value for PA was 0.914 (df = 698, p = 0.361, Cohen’s d = 0.070). All effect sizes were small (d < 0.10), indicating limited explanatory power for this factor in variable variation. However, the marginal p-value for sports participation suggests a potential subtle family structure influence in larger samples (Li et al., 2010). To control for potential family dynamic heterogeneity, this variable was incorporated into the model as a covariate. Table 5 Comparison of Differences in Student Variables Based on Only-Child Status Category N M ± SD t p University Physical Education Environment Yes 374 3.41 ± 0.78 0.887 0.375 No 326 3.36 ± 0.84 Sports Participation Behavior Yes 374 3.40 ± 0.74 0.752 0.453 No 326 3.36 ± 0.79 Developing self-efficacy Yes 374 3.41 ± 0.80 0.914 0.361 No 326 3.35 ± 0.84 Exercise Motivation Yes 374 3.37 ± 0.85 -0.130 0.897 No 326 3.38 ± 0.89 3.4 ANOVA Single-Factor Analysis One-way analysis of variance (ANOVA) was employed to examine the between-group effects of multi-categorical demographic variables on core constructs, supplemented by partial η² as an effect size indicator. LSD and Tamhane post-hoc multiple comparisons were conducted to identify specific sources of differences. Levene's test confirmed homogeneity of variance across all variables (p > 0.05). All analyses were based on centered variables to minimize multicollinearity effects. The significance threshold was set at p < 0.05, with marginal significance defined as p < 0.10 to capture potential threshold effects [ 41 ]. 3.4.1 Differences Between Grade Levels ANOVA results indicate (Table 6 ) that grade level showed marginally significant between-group differences for Exercise Motivation and Sports Participation Behavior: Exercise Motivation (F = 2.131, df = 3/696, p = 0.095, partial η² = 0.009); Sports Participation Behavior (F = 1.769, df = 3/696, p = 0.152, partial η² = 0.008). Post-hoc multiple comparisons (LSD and Tamhane) revealed significant differences between sophomores and seniors in Exercise Motivation and Sports Participation Behavior (p < 0.05), while no significant variation was found between freshmen and juniors. School physical environment (F = 1.147, p = 0.329, partial η² = 0.005) and Developing self-efficacy (F = 1.115, p = 0.342, partial η² = 0.005) showed no significant effects. Overall effect sizes were small (η² < 0.01), indicating that grade level contributed minimally to variance in the variables. However, its marginal effect supports including it as a covariate in the model to control for the influence of learning stage heterogeneity on psychological mechanisms. Table 6 Results of One-Way ANOVA for Core Variables in Grade 6 (N = 700) Related variables Grade M ± SD F p University Physical Education Environment Freshman year 3.38 ± 0.81 1.147 0.329 Sophomore year 3.30 ± 0.81 Junior year 3.43 ± 0.82 Senior year 3.45 ± 0.78 Sports Participation Behavior Freshman year 3.36 ± 0.77 1.115 0.342 Sophomore year 3.31 ± 0.81 Junior year 3.41 ± 0.75 Senior year 3.45 ± 0.74 Developing self-efficacy Freshman year 3.39 ± 0.86 2.131 0.095 Sophomore year 3.25 ± 0.83 Junior year 3.42 ± 0.83 Senior year 3.46 ± 0.77 Exercise Motivation Freshman year 3.36 ± 0.88 1.769 0.152 Sophomore year 3.26 ± 0.90 Junior year 3.40 ± 0.86 Senior year 3.48 ± 0.81 3.4.2 Differences in Monthly Household Income Levels Across Groups ANOVA results indicate (Table 7 ) that monthly household income per capita exhibited a marginally significant effect on Developing self-efficacy (F = 1.307, df = 3/696, p = 0.271, partial η² = 0.006), while showing no significant effects on school physical education environment (F = 1.140, p = 0.332, partial η² = 0.005), Exercise Motivation (F = 1.835, p = 0.139, partial η² = 0.008), and Sports Participation Behavior (F = 1.202, p = 0.308, partial η² = 0.005). Post-hoc multiple comparisons (LSD and Tamhane) revealed a marginal difference in ESE between the low-income group (¥10,000) (p ≈ 0.10), but no significant variation within the middle-income group. Overall effect sizes were small (η² < 0.01), indicating a limited gradient effect of socioeconomic status on psychological constructs. Nevertheless, these marginal effects support including socioeconomic status as a covariate in the model to control for potential moderation of the mediating pathway by economic resource constraints. Table 7 Comparison of Differences in Various Variables of Monthly Household Income Among Students (Single-Factor ANOVA Analysis) Related variables Monthly household income of students M ± SD F p University Physical Education Environment 10000元 3.43 ± 0.78 Sports Participation Behavior 10000元 3.45 ± 0.74 Developing self-efficacy 10000元 3.47 ± 0.77 Exercise Motivation 10000元 3.54 ± 0.81 3.5 Pearson Correlation Analysis Pearson correlation analysis results indicate (Table 8 ) that a significant positive relationship exists between the school physical environment and exercise behavior (r = 0.847, p < 0.001). Exercise Motivation also shows a significant positive correlation with exercise behavior and Sports Participation Behavior (r = 0.856, p < 0.001). Developing self-efficacy also showed a significant positive correlation with Sports Participation Behavior (r = 0.832, p < 0.001). Furthermore, school physical environment showed highly significant positive correlations with Exercise Motivation (r = 0.922, p < 0.001), Developing self-efficacy (r = 0.900, p < 0.001), and Exercise Motivation with Developing self-efficacy (r = 0.904, p < 0.001) [ 42 ]. These correlation results indicate stable positive linear associations among core variables, providing preliminary empirical support for the chained mediation effect hypothesized in this study. They also establish a reliable statistical foundation for subsequent multiple linear regression and Bootstrap mediation effect testing (Table 3 for details). All correlation coefficients reached moderate to strong levels, with absolute values below 0.95, indicating no signs of extreme multicollinearity. This ensures the stability and interpretability of subsequent model estimations.The chained intermediary model is illustrated in Fig. 2 . All four hypotheses (H1–H4) proposed in this study received empirical support. Table 8 Correlation Analysis of Key Variables University Physical Education Environment University Physical Education Environment University Physical Education Environment University Physical Education Environment University Physical Education Environment 1 Sports Participation Behavior .900*** 1 Developing self-efficacy .922*** .904*** 1 Exercise Motivation .847*** .832*** .85*** 1 3.6 Multiple Linear Regression Analysis To examine the direct predictive effect of the University Physical Education Environment on college students' Sports Participation Behavior and to investigate the independent contributions of Developing self-efficacy and Exercise Motivation, this study employed stratified multiple linear regression analysis (Table 9 ). First, demographic covariates (gender, grade level, only child status, per capita monthly household income) were included. Subsequently, the decentralized University Physical Education Environment, Developing Self-Efficacy, and Exercise Motivation were sequentially introduced as predictor variables to control for potential confounders and assess incremental explanatory power [ 43 ]. The final full model demonstrated excellent fit: R = 0.874, R² = 0.765, adjusted R² = 0.762, F(7, 692) = 321.12, p < 0.001. This model explained 76.5% of the total variance in Sports Participation Behavior, indicating strong predictive efficacy of the included variables. After controlling for demographic covariates, standardized regression coefficients for decentralized variables indicated: Developing self-efficacy also significantly and positively predicted exercise behavior (β = 0.215, t = 4.538, p < 0.001); Exercise Motivation exhibited the strongest predictive effect (β = 0.395, t = 7.429, p < 0.001). Even when Developing self-efficacy and Exercise Motivation were included simultaneously, the University Physical Education Environment maintained a significant direct effect, supporting Hypothesis H1. Among demographic covariates, monthly household income per capita showed an independent positive prediction for exercise behavior (β = 0.038, p = 0.042). Being an only child exhibited marginal significance (β = 0.034, p = 0.071), while gender and grade level were not significant (p > 0.05). The overall contribution of covariates was minimal (ΔR² ≈ 0.003), with no change in the direction or significance of the core predictor variables. Table 9 Results of Stratified Multicollinearity Regression (Predicting College Students' Sports Participation Behavior) Predictor variable Model 1 β (SE) Model 2 β (SE) Model 3 β (SE) Model 4 β (SE) VIF Gender -0.001(0.035) -0.001(0.035) -0.001(0.032) -0.001(0.032) 1.008 Grade 0.020(0.015) 0.020(0.015) 0.014(0.014) 0.014(0.014) 1.000 Whether you are an only child 0.032(0.035) 0.032(0.035) 0.034(0.032) 0.034(0.032) 1.000 Monthly household income 0.041(0.018)* 0.041(0.018)* 0.038(0.017)* 0.038(0.017)* 1.000 University Physical Education Environment (Decentralized) 0.848(0.022)*** 0.440(0.036)*** 0.290(0.056)*** 7.954 Developing self-efficacy (Decentralization) 0.215(0.053)*** 0.215(0.053)*** 6.587 Exercise Motivation (Decentralized) 0.395(0.056)*** 8.314 R² 0.003 0.720 0.848 0.765 ΔR² 0.717*** 0.128*** 0.016*** F (df) 0.52(4695) 356.70(5694)*** 645.65(6693)*** 321.12(7692)*** Note: *p < 0.05, **p < 0.01, ***p < 0.001. Coefficients represent standardized β values, with standard errors in parentheses. VIF values are based on the full model (Model 4). To mitigate potential multicollinearity, mean-centering was applied to the University Physical Education Environment, Developing self-efficacy, and Exercise Motivation (Table 10 ). Overall model fit indices remained consistent before and after centering, with no changes in the magnitude, direction, or significance of regression coefficients. Multicollinearity diagnostics revealed variance inflation factors (VIF) for predictor variables ranging from 1.000 to 8.314, with a maximum conditional index of 7.441. This indicates moderate multicollinearity that did not reach critical thresholds. The maximum conditional index before centering reached 30.557, decreasing to 6.024 after centering, significantly improving numerical stability. Although moderate multicollinearity existed among variables (primarily stemming from the theoretical correlation between Developing self-efficacy and Exercise Motivation), VIF values remained below 10, limiting their impact on parameter estimation and Bootstrap indirect effect tests. Table 10 Multicollinearity Diagnosis Results (Complete Model, Comparison Before and After Centering) University Physical Education Environment Pre-centering VIF Centralization Threshold Index VIF after centering Centralization Threshold Index 7.940 30.557 7.954 7.441 Sports Participation Behavior 6.533 6.587 Developing self-efficacy 8.304 8.314 Exercise Motivation 1.000 Note: The condition index is based on eigenvalue decomposition. Centralization significantly improves numerical stability. Residual diagnostics revealed (Table 11 ) that the standardized residuals had a mean of approximately 0, a standard deviation of approximately 1, a skewness of -0.443 (slight left skew), and a kurtosis of 2.316 (slight heavy-tailed distribution). The Durbin-Watson statistic was 1.95, supporting residual independence. The Kolmogorov-Smirnov test (D = 0.065, p < 0.001) and Shapiro-Wilk test (W = 0.968, p < 0.001) rejected the assumption of strict normality. However, these tests are highly sensitive to minor deviations in large samples (N = 700). The residual distribution approximates normality with only slight heavy tails and skewness, showing no severe heteroscedasticity or nonlinear patterns. Given the large sample size and subsequent use of Bootstrap methods, this minor non-normality has limited impact on parameter estimates and the significance of mediating effects. Table 11 Residual Diagnostic Statistics (Full Model) Indicator Value/Statistic Criteria for Judgment Conclusion mean 0.000 Expected ≈ 0 Satisfy Standard deviation 0.998 Expected ≈ 1 Satisfy Skewness -0.443 [-1, 1] For minor Slightly left-leaning Peak Degree 2.316 3 为正态, >3Heavy Tail Slightly heavy-tailed Durbin-Watson 1.95 [1.5, 2.5] non-autocorrelated Independence Satisfaction Kolmogorov-Smirnov D = 0.065, p 0.05 Normal Refusal (Highly Sensitive) Shapiro-Wilk W = 0.968, p 0.05 Normal Refusal (Highly Sensitive) The results indicate that, after controlling for demographic covariates and potential collinearity, the University Physical Education Environment exerts a significant direct predictive effect on college students' physical exercise behavior. Furthermore, both Developing Self-Efficacy and Exercise Motivation were validated as independent contributors, establishing a robust foundation for subsequent chain mediation analysis. 3.7 Testing for Mediating Effects To examine the chain intermediation effect of Exercise Motivation and Developing Self-Efficacy in the relationship between University Physical Education Environments and College Students' Sports Participation Behavior, this study employed Hayes (2022) PROCESS macro Model 6 for serial mediation analysis. The model simultaneously controlled for demographic covariates (gender, grade level, only child status, per capita monthly household income) and employed decentralized variable calculations. A 95% confidence interval (CI) was generated through 5,000 bias-corrected bootstrap resampling to obtain robust nonparametric indirect effect estimates [ 44 ]. 3.7.1 Analysis of Regression Relationships Among Variables The PROCESS macro output displayed three sequential regression equations in the chained mediation model (Table 12 ), with the following results: First, the University Physical Education Environment significantly and positively predicted Exercise Motivation (a₁ = 0.9402, SE = 0.0150, t = 62.647, p < 0.001, 95% CI [0.911, 0.970], standardized coefficient = 0.922), explaining 85.0% of the variance in motivation (R² = 0.850). Second, University Physical Education Environment and Exercise Motivation jointly significantly predicted Developing self-efficacy: University Physical Education Environment → Developing self-efficacy (a₂ = 0.4181, SE = 0.0363, t = 11.508, p < 0.001, standardized coefficient = 0.440); Exercise Motivation → Developing self-efficacy (d₂₁ = 0.4637, SE = 0.0356, t = 13.017, p < 0.001, standardized coefficient = 0.498), with the equation explaining 84.8% of the variance in efficacy (R² = 0.848). Finally, after controlling for mediating variables and covariates, University Physical Education Environment, Developing Self-Efficacy, and Exercise Motivation all significantly and positively predicted Sports Participation Behavior: University Physical Education Environment → Sports Participation Behavior (c' = 0.3112, SE = 0.0558, t = 5.581, p < 0.001, standardized coefficient = 0.290); Exercise Motivation → Sports Participation Behavior (b₁ = 0.4151, SE = 0.0559, t = 7.429, p < 0.001, standardized coefficient = 0.395); Developing self-efficacy → Sports Participation Behavior (b₂ = 0.2424, SE = 0.0534, t = 4.538, p < 0.001, standardized coefficient = 0.215). The full model R² = 0.765 indicates robust relationships among variables [ 45 ]. All regression paths were significant, supporting the structural validity of the chained mediation model. Among demographic covariates, only monthly household income per capita demonstrated an independent positive predictive effect (β = 0.038, p = 0.042), while other variables were insignificant. Overall, this did not alter the significance or direction of the core pathways. Table 12 Regression Relationships Among Variables in the Chain Mediation Model (N = 700, controlling for covariates) Dependent variable Predictor variable b SE β t Value p Value 95%CI lower limit 95%CI upper limit R² Exercise Motivation University Physical Education Environment (Centralization) 0.940 0.015 0.922 62.647 < 0.001 0.911 0.970 0.850 Developing self-efficacy University Physical Education Environment (Centralization) 0.418 0.036 0.440 11.508 < 0.001 0.347 0.489 0.848 Exercise Motivation (Centralized) 0.464 0.036 0.498 13.017 < 0.001 0.394 0.534 Sports Participation Behavior University Physical Education Environment (Centralization) 0.311 0.056 0.290 5.581 < 0.001 0.202 0.421 0.765 Exercise Motivation (Centralized) 0.415 0.056 0.395 7.429 < 0.001 0.305 0.525 Developing self-efficacy (Centralization) 0.242 0.053 0.215 5.538 < 0.001 0.138 0.347 Note: All paths control for gender, grade level, only-child status, and monthly household income per capita. Coefficients represent unstandardized b values (b) and standardized β values. All paths have p < 0.001. 3.7.2 Results of the Chain Mediated Effect Analysis Results of the chained mediational effect analysis (Table 13 ): The total effect was significant (c = 0.9085, SE = 0.0216, t = 42.114, p < 0.001, 95% CI [0.866, 0.951], standardized coefficient = 0.848), indicating that the University Physical Education Environment exerts a significant positive total influence on Sports Participation Behavior [ 46 ]. The direct effect remained significant though weakened after controlling for the mediating variable (c' = 0.3112, SE = 0.0558, t = 5.581, p < 0.001, 95% CI [0.202, 0.421], standardized coefficient = 0.290), supporting the existence of a direct path. The total indirect effect was 0.5973 (Boot SE = 0.0635, 95% Boot CI [0.471, 0.723]), accounting for 65.7% of the total effect, indicating that the mediating path represents the primary mechanism of action. All three specific indirect paths were significant: University Physical Education Environment → Exercise Motivation → Sports Participation Behavior (Ind1 = 0.3903, Boot 95% CI [0.254, 0.528]); University Physical Education Environment → Developing self-efficacy → Sports Participation Behavior (Ind2 = 0.1014, Boot 95% CI [0.052, 0.162]); University Physical Education Environment → Exercise Motivation → Developing self-efficacy → Sports Participation Behavior (chain path, Ind3 = 0.1057, Boot 95% CI [0.055, 0.163]). Path comparison revealed: Path 1 was significantly greater than Path 2 (C1 = 0.2889, Boot 95% CI [0.114, 0.458]) and Path 3 (C2 = 0.2846, Boot 95% CI [0.119, 0.447]), indicating Exercise Motivation as the strongest single mediator; Path 2 showed no significant difference from Path 3 (C3 = -0.0043, Boot 95% CI [-0.049, 0.040]). Table 13 Bootstrap Test Results for Chain Mediation Effects Effect Type Path effect value(b) Boot SE Boot 95% CI lower limit Boot 95% CI upper limit Proportion of the total effect Standardized indirect effect Overall effect 0.909 0.022 0.866 0.951 100% 0.848 Direct effect Direct Path 0.311 0.056 0.202 0.421 34.3% 0.290 Total indirect effect 0.597 0.064 0.471 0.723 65.7% 0.558 Indirect effects Path1 0.390 0.254 0.528 43.0% 0.364 Path2 0.101 0.052 0.162 11.2% 0.095 Path3 0.106 0.055 0.163 11.6% 0.099 Path Comparison C1: Path1-Pat2 0.289 0.114 0.458 C1: Path1-Pat3 0.285 0.119 0.447 C1: Path2-Pat3 -0.004 -0.049 0.040 Note: All 95% bootstrap confidence intervals for indirect effects and comparative pathways exclude zero, indicating statistical significance. Standardized indirect effects are used to compare relative contributions. In summary, The results of the chained mediation analysis support hypotheses H1–H4: The University Physical Education Environment positively influences college students' Sports Participation Behavior through both single and chained mediation pathways via Exercise Motivation and Developing Self-Efficacy. Among these, Exercise Motivation as the primary mediator makes the most significant contribution, while the chained pathway further strengthens the sequential mechanism of motivation-self-efficacy. These findings remain robust after controlling for demographic covariates, providing a solid empirical foundation for subsequent discussions. 4 Discussion 4.1 The Impact of University Physical Education Environments on College Students' Sports Participation Behavior The findings of this study indicate that the University Physical Education Environment significantly and positively predicts college students' Sports Participation Behavior (β = 0.290, p < 0.001). This discovery suggests that the University Physical Education Environment, as a crucial contextual condition in students' daily lives, exerts a stable and promoting effect on the formation of Sports Participation Behavior. From the perspective of behavioral formation mechanisms, the University Physical Education Environment provides students with sustained situational support for physical activities [ 47 ]. The accessibility of sports facilities, the institutionalized arrangement of course systems, and the campus sports culture collectively form the contextual foundation for university students' participation in physical activities. When sports resources are well-allocated, students perceive lower time costs and behavioral barriers when engaging in physical activities, making it easier to integrate such activities into their daily routines. The accessibility of environmental resources lowers the threshold for initiating behavior to some extent, enabling physical activities to become sustainable daily choices. In the university setting, the University Physical Education Environment simultaneously reinforces Sports Participation Behavior through social interaction processes. Physical education courses, campus competitions, and sports club activities provide students with diverse platforms for athletic experiences. Sustained interactive experiences enhance the social attributes of physical activities within campus life, gradually transforming sports participation into a behavior pattern imbued with group identity significance. When physical activities maintain high visibility within campus culture, students are more likely to develop stable participation behaviors within collective contexts. Research findings further indicate that the University Physical Education Environment constitutes a crucial contextual foundation for college students' physical activity behaviors [ 48 ]. A favorable University Physical Education Environment continuously provides behavioral opportunities in daily life, thereby increasing the likelihood of student participation in physical activities. This discovery empirically reveals the significant role of campus contextual factors in shaping college students' physical activity behaviors. 4.2 The Mediating Role of Developing Self-Efficacy Research findings indicate that Developing self-efficacy plays a significant mediating role between the University Physical Education Environment and college students' Sports Participation Behavior. Analysis reveals that the University Physical Education Environment significantly and positively predicts Developing self-efficacy (β = 0.440, p < 0.001), while Developing self-efficacy further significantly predicts Sports Participation Behavior (β = 0.215, p < 0.001). This structural relationship indicates that the University Physical Education Environment indirectly promotes the formation of Sports Participation Behavior by influencing individuals' cognitive evaluations of their capabilities. When confronting behavioral tasks, individuals assess the relationship between their own abilities and the task requirements. When individuals perceive themselves as capable of completing a task, the probability of initiating the behavior and its persistence significantly increase [ 49 ]. The University Physical Education Environment provides students with stable conditions for exercise practice, enabling them to gradually accumulate successful experiences through sustained physical activity. Frequent exercise practice reinforces students' positive evaluations of their athletic abilities, thereby enhancing their ability to develop self-efficacy. As self-efficacy levels increase, students are more likely to maintain exercise behaviors when facing academic pressures, time constraints, or physical fatigue [ 50 ]. Concurrently, peer interactions and modeling behaviors within campus sports settings also strengthen individuals' efficacy perceptions. Through observational learning during sports participation, students acquire behavioral information that fosters positive judgments about their athletic capabilities. As these ability beliefs stabilize, physical activity gains greater prominence in individuals' daily lives. Research findings indicate that the University Physical Education Environment establishes a crucial cognitive pathway—transforming environmental factors into behavioral outcomes—by reinforcing individuals' perceptions of their capabilities. 4.3 The Mediating Role of Exercise Motivation Research findings indicate that Exercise Motivation plays a significant mediating role between the University Physical Education Environment and Sports Participation Behavior. Specifically, the University Physical Education Environment exerts a significant positive influence on Exercise Motivation (β = 0.922, p < 0.001), and Exercise Motivation further significantly predicts Sports Participation Behavior (β = 0.395, p < 0.001). This finding indicates that the University Physical Education Environment promotes the formation of Sports Participation Behavior by stimulating individuals' behavioral motivation systems. Behavioral motivation serves as a crucial psychological link connecting cognitive judgments with behavioral execution [ 51 ]. When individuals develop positive expectations toward a behavior, their behavioral engagement significantly increases. By providing diverse athletic resources and varied physical activity formats, the University Physical Education Environment enables students to gradually develop stable behavioral interest during participation. Both campus physical education courses and extracurricular sports activities play vital roles in this process. Diverse athletic experiences reinforce students' recognition of the value of physical activity, gradually positioning exercise as a meaningful lifestyle choice [ 52 ]. When sports become a stable presence in campus life, students are more likely to reserve space for physical activity within their daily schedules. Enhanced Exercise Motivation also influences behavioral maintenance. Individuals with higher motivation levels typically demonstrate greater engagement in physical activities, including more consistent participation frequency and longer duration. Sustained exercise experiences generate positive feedback loops, further reinforcing Sports Participation Behavior. Research findings indicate that the University Physical Education Environment establishes a crucial motivational mechanism—transforming environmental support into behavioral outcomes—by strengthening students' exercise motivation. 4.4 The Chain Intermediation Effect of Developing Self-Efficacy and Exercise Motivation In further mechanism testing, this study found that Developing self-efficacy and Exercise Motivation constitute a significant chained mediating pathway between the University Physical Education Environment and Sports Participation Behavior. Bootstrap analysis results indicate that this chained mediating effect is significant (indirect effect = 0.1057, 95% CI [0.055, 0.163]). This finding reveals a sequential mechanism through which environmental factors gradually translate into individual psychological systems during the formation of college students' physical activity behaviors [ 53 ]. In terms of the structural relationships among variables, the University Physical Education Environment first enhances students' belief in their own athletic capabilities through resource support and exercise scenario reinforcement, thereby fostering a higher level of Developing self-efficacy. When individuals form positive judgments about their own abilities, their expectations of success in physical activities also increase. This cognitive process further promotes the formation of Exercise Motivation. During behavior formation, self-efficacy provides the cognitive foundation for behavioral motivation. Individuals who confirm their capacity to accomplish exercise tasks are more likely to develop stable participation intentions. As behavioral motivation gradually intensifies, physical activities gain higher priority in individuals' lives, thereby driving sustained engagement in Sports Participation Behavior. This chain of relationships reveals the psychological transmission pathway for the formation of college students' physical activity behaviors [ 54 ]. The University Physical Education Environment, by reinforcing capability cognition, further stimulates behavioral motivation, ultimately influencing Sports Participation Behavior. Environmental factors, cognitive evaluation, and behavioral drive form a continuous structure in the behavioral formation process. Research findings indicate that college students' Sports Participation Behavior is not the result of a single factor but rather a behavioral pattern gradually shaped by the combined effects of environmental support and psychological mechanisms. 4.5 Practical Significance This study provides significant insights for university physical education promotion practices by examining the structural relationships among University Physical Education Environments, Developing Self-Efficacy, Exercise Motivation, and Sports Participation Behavior [ 55 ]. Findings indicate that the University Physical Education Environment exerts a significant positive influence on Sports Participation Behavior (β = 0.290, p < 0.001). Optimizing the physical environment remains a crucial foundation for promoting physical activity among college students. Universities should continuously improve sports facility construction, enhance accessibility to exercise spaces, and optimize equipment allocation in their physical education development plans. A stable supply of sports resources provides students with ongoing opportunities for physical activity, making it easier to integrate exercise into daily campus life. The findings also indicate that the University Physical Education Environment significantly enhances developing self-efficacy (β = 0.440, p < 0.001). Physical education practices should prioritize students' experiential development of athletic competence. Through tiered instruction, skill-based guidance, and progressive training methods, students can achieve success in physical activities. Sustained positive experiences reinforce competence beliefs, thereby increasing willingness to participate in physical activities. Furthermore, Exercise Motivation plays a crucial role in shaping Sports Participation Behavior (β = 0.395, p < 0.001). Universities can increase the visibility and engagement of physical activities in campus life by diversifying sports programs, expanding sports clubs, and organizing varied athletic events. Sustained participation becomes more likely when students develop stable interests in physical activity. The chained mediating pathways revealed by this study indicate that university physical activity promotion strategies should foster synergistic relationships between environmental development and psychological mechanism cultivation. By optimizing the University Physical Education Environment, strengthening perceived competence, and stimulating exercise motivation, stable behavioral promotion mechanisms can be established at the cognitive and motivational levels, thereby enhancing college students' participation in physical activities. 4.6 Research Limitations and Future Prospects This study has made some progress in revealing the psychological mechanisms through which the University Physical Education Environment influences college students' Sports Participation Behavior, while further research opportunities remain. Employing a cross-sectional survey design, this study primarily inferred relationships between variables through statistical path analysis. This methodology effectively reveals structural connections among variables, providing empirical support for understanding the formation mechanisms of college students' physical activity behaviors. The development of physical activity behaviors exhibits distinct temporal dynamics. Future research could utilize longitudinal tracking designs or experimental methodologies to further examine the causal mechanisms through which the University Physical Education Environment influences Sports Participation Behavior, thereby yielding more robust research conclusions. Research data primarily stemmed from individual self-report questionnaires. This method effectively captures students' subjective perceptions of physical activity environments and behavioral experiences. However, self-report data may be subject to individual cognitive biases. Future studies could integrate objective physical activity measurement methods, such as wearable device recordings or campus sports facility usage data, to enhance the objectivity of research findings. This study primarily focused on two psychological variables: Developing self-efficacy and Exercise Motivation. College students' Sports Participation Behavior is influenced by multiple psychological and social factors. Future research could incorporate additional psychological variables—such as peer interactions, sports identity, or emotional experiences—into existing models to construct more systematic behavioral explanatory frameworks. The study sample primarily originates from universities in a specific region. Differences exist in physical resource allocation and campus culture across regional institutions. Future research could further test the stability of the research model through cross-regional sample comparisons, thereby enhancing the generalizability of findings. Declarations Competing interests The authors declare no competing interests. Ethical approval The design of this study followed the guidelines and regulations of the Declaration of Helsinki and approved by Ethics Committee of Liaoning Normal University (LL20254), and all participants signed an informed consent form and were paid for their participation. Funding Liaoning Provincial Social Science Planning Fund General Project Research on High-Quality Construction of Public Fitness Service System Empowered by Digital Intelligence (L25BTY004). Author Contribution Wenhe Zhu was responsible for the data analysis and writing of the original draft preparation. Yong Jiang was responsible for data analysis and methodology. Wenhe Zhu was responsible for the conceptualization, writing, reviewing and editing the draft. Yong Jiang was responsible for the conceptualization, writing, reviewing and editing the draft, and funding acquisition. All authors have read and approved the final manuscript. 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The effects of perceived sport environment on sport gains of Chinese university students: chain mediation between physical activity behavior and sport learning self-efficacy[J]. Front Psychol, 2024, 15: 1466457. Sheng J, Ariffin I A B, Tham J. The influence of exercise self-efficacy and gender on the relationship between exercise motivation and physical activity in college students[J]. Sci Rep, 2025, 15: 11888. Bao H. Association between peer relationships and exercise self-efficacy among college students: the mediating role of physical activity commitment[J]. Front Psychol, 2025, 16: 1533097. Han S, Li B, Wang G, et al. Physical Fitness, Exercise Behaviors, and Sense of Self-Efficacy Among College Students: A Descriptive Correlational Study[J]. Front Psychol, 2022, 13: 932014. Zhao Y S, Ma Q S, Li X Y, et al. The relationship between exercise motivation and exercise behavior in college students: The chain-mediated role of exercise climate and exercise self-efficacy[J]. Front Psychol, 2023, 14: 1130654. Gao X, Li Z, Song Y, et al. Potential categories and influences on college students’ exercise motivation: a latent profile-based analysis[J]. Sci Rep, 2025, 15: 44184. Zhou Lei, Wang Xianliang. An Analysis of the Relationship Among Campus Sports Culture, Student Sense of Belonging, and Participation in Physical Exercise at Jinan University [J]. Journal of Jianghan University (Natural Science Edition), 2020, 48(03): 91–96. Huang Meirong, Zhang Yanping, SUN, et al. Research on the Mechanism for Promoting Sports Integration into Daily Life Among Chinese College Students Based on the Social Ecological Model [J]. Journal of Tianjin University of Sport, 2019, 34(01): 14–22. Ji S, Chen S, Yang X, et al. The effect of sports participation on the social identity of Chinese university students[J]. Front Psychol, 2024, 15: 1511807. Z V Z, K G A, K T K. Psychological adaptation of foreign students to university environment based on academic physical education and sports activities[J]. Teoriya i Praktika Fizicheskoy Kultury, 2021(2):13–15. Dong Y, Weng S, Wang Y. The influence of public welfare sports on college students' sports interest and sports behavior: a longitudinal study[J]. BMC Psychol, 2025, 13(1):1282. Shu Yue, Sun Meirong. The Influence of College Students' Physical Exercise Behavior on Academic Stress: Mediating Role of Self-Efficacy and Moderating Role of Peer Support [C]//Chinese Psychological Society. Abstracts of the 26th National Psychology Conference (Volume 8). Beijing: School of Psychology, Beijing Sport University; Key Laboratory of Sports and Physical Fitness, Ministry of Education, Beijing Sport University; Key Laboratory of Sports Stress Adaptation, General Administration of Sport of China, 2025:101–102. Zhang Si, Liu Xiaoli. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9082915","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619934005,"identity":"093f27c4-179b-41cc-bab7-b37ba453059f","order_by":0,"name":"Yong Jiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYBACxmY4M7nxAYMBaVoSmw2I0oIEEtskiFLH3M787OHXNps8effEtsofBXfkGdgPH92A32Fs5saybWnFhmcett3mMXhm2MCTlnYDvxYGM2nJtsOJG2cktt1mMDjM2CDBY0ZAC/s3uJbCHwaH7YnQwmMm+RGoZb5EYhsDj8HhRGK0lEkznEtL3MDzsFkaqCW5jZBfDPuPb5P8UWaTOL89+eDHH38O2/azHz6GX0sDMKB52RgYDA5ARdjwKQcBeZDjfvwBMhoIKR0Fo2AUjIIRCwDAfU4iacahKQAAAABJRU5ErkJggg==","orcid":"","institution":"Liaoning Normal University","correspondingAuthor":true,"prefix":"","firstName":"Yong","middleName":"","lastName":"Jiang","suffix":""},{"id":619934006,"identity":"1fdc4e6f-dab3-40c6-abc9-d26d7113388d","order_by":1,"name":"Wenhe Zhu","email":"","orcid":"","institution":"Liaoning Normal University","correspondingAuthor":false,"prefix":"","firstName":"Wenhe","middleName":"","lastName":"Zhu","suffix":""}],"badges":[],"createdAt":"2026-03-10 11:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9082915/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9082915/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106639972,"identity":"1f182fd2-4b73-4d8d-a9c6-a51788dde22b","added_by":"auto","created_at":"2026-04-10 17:46:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9748,"visible":true,"origin":"","legend":"\u003cp\u003eIntermediary Model Diagram\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9082915/v1/59b2a9b28cc0620fdbb09726.png"},{"id":106639971,"identity":"f87d6a78-752f-42d5-92fe-04c1744604b2","added_by":"auto","created_at":"2026-04-10 17:46:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":11680,"visible":true,"origin":"","legend":"\u003cp\u003ePathways of the Impact of University Physical Education Environments on College Students' Sports Participation Behavior Outcomes\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9082915/v1/7947d22c3e1d12c3360e6c99.png"},{"id":106726816,"identity":"ac677c83-9a21-4b13-adbe-8796445d6f9c","added_by":"auto","created_at":"2026-04-12 18:37:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1923907,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9082915/v1/be9950fe-5250-41af-a9d9-cbbdf40e7d2c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Influence of University Physical Education Environments on College Students' Sports Participation Behavior: The Chain Intermediation Effect of Developing Self-Efficacy and Exercise Motivation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Healthy China 2030 Plan places universities in a key strategic position for enhancing physical activity levels among youth, emphasizing the cultivation of stable healthy behaviors through institutional provision and environmental optimization [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, insufficient physical activity among college students has become a prominent public health issue. Relevant surveys indicate that Chinese university students generally fail to meet recommended standards for weekly moderate-intensity physical activity. Persistently low activity levels not only increase risks of obesity and cardiovascular disease but also show significant correlations with psychological issues such as anxiety and depression. Despite universities possessing relatively well-developed resource foundations in terms of facilities and curriculum systems, actual utilization rates and exercise persistence remain low, with environmental advantages failing to effectively translate into stable Sports Participation Behavior [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Therefore, revealing the underlying mechanisms through which environmental support converts into sustained behavior holds significant practical and theoretical value.\u003c/p\u003e \u003cp\u003eExisting research consistently indicates that supportive University Physical Education environments significantly enhance exercise frequency and duration. However, most studies remain focused on the direct relationship between environment and behavior, with relatively insufficient systematic integration of psychological mediating mechanisms. At the cognitive level, Developing self-efficacy is regarded as a key hub [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. According to Social Cognitive Theory, the environment influences individuals' evaluations of their own capabilities through mastery experiences and social support, thereby providing a cognitive foundation for initiating and sustaining behavior. At the motivational level, the sustained implementation of behavior also depends on the quality of motivation. Based on Self-Determination Theory, when the environment satisfies individuals' needs for autonomy, competence, and relatedness, external demands are more likely to be internalized as self-determined motivation, promoting the sustained maintenance of exercise behavior.\u003c/p\u003e \u003cp\u003eFrom an integrated theoretical perspective, the University Physical Education Environment, self-efficacy, and Exercise Motivation may form a sequential pathway of \u0026ldquo;context-cognition-motivation-behavior\u0026rdquo;: the environment first strengthens efficacy beliefs, enhanced efficacy further promotes motivation activation, and motivation directly drives sustained behavior. Compared to single or parallel mediation models, this chained structure more systematically reveals the underlying mechanisms through which environments influence Sports Participation Behavior [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Based on this, this study constructs a chained mediation model where the University Physical Education Environment influences college students' Sports Participation Behavior through Developing self-efficacy and Exercise Motivation. This aims to deepen theoretical explanations of the mechanisms and provide evidence for optimizing the University Physical Education Environment and implementing targeted interventions.\u003c/p\u003e"},{"header":"1 Theoretical Foundations and Assumptions","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.1 The Impact of University Physical Education Environments on College Students' Sports Participation Behavior\u003c/h2\u003e \u003cp\u003eThe University Physical Education Environment refers to a comprehensive system formed by institutional, spatial, and social support elements surrounding student physical activities within the context of higher education, exhibiting a multi-layered nested structure [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. From a structural perspective, it primarily encompasses three dimensions: the institutional environment, the physical environment, and the social support environment [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The institutional environment manifests through institutional arrangements such as curriculum design, evaluation mechanisms, and sports promotion policies, defining behavioral boundaries for student participation in physical activities through rule provision and opportunity structures; The physical environment primarily refers to the accessibility and openness of sports facilities, providing fundamental conditions for student physical activities. The social support environment manifests as the campus sports culture atmosphere and support resources from families and communities, continuously influencing individual behavioral choices through group norms, value orientations, and interactive networks. These multi-layered environmental elements are not isolated but collectively shape the real-world context of college students' Sports Participation Behavior through structural coupling and functional synergy.\u003c/p\u003e \u003cp\u003eFrom a mechanism perspective, the influence of the University Physical Education Environment on Sports Participation Behavior follows the pathway of \u0026ldquo;environmental perception\u0026mdash;cognitive evaluation\u0026mdash;behavioral disposition\u0026mdash;behavioral manifestation\u0026rdquo; [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Individuals first form subjective perceptions of environmental resources and support levels, then cognitively evaluate the feasibility and value of exercise based on these perceptions, ultimately developing behavioral dispositions. When campus environments provide ample resources and foster a positive atmosphere, individuals' willingness to participate and readiness to act are strengthened, ultimately translating into actual Sports Participation Behavior. Existing research also indicates that campus environments characterized by robust institutional support, high facility accessibility, and a positive sports culture significantly enhance college students' physical activity participation levels [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Based on this, the following hypothesis is proposed:\u003c/p\u003e \u003cp\u003eH1: The University Physical Education Environment significantly and positively predicts college students' Sports Participation Behavior.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.2 The Mediating Role of Developing Self-Efficacy\u003c/h2\u003e \u003cp\u003eDeveloping self-efficacy refers to an individual's subjective assessment of their ability to organize and execute specific behaviors. Developing self-efficacy manifests specifically as college students' belief in their capacity to consistently complete physical exercise tasks, encompassing aspects such as regulating exercise intensity, scheduling time, and coping with difficulties [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Within the interactive structure of \u0026ldquo;environment-individual-behavior,\u0026rdquo; self-efficacy occupies a pivotal cognitive position, serving to integrate situational information and regulate behavior [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The University Physical Education Environment influences self-efficacy formation through multiple social-cognitive sources: institutional provision and curriculum systems offer students stable mastery experiences, reinforcing perceived competence; peer participation and role modeling provide vicarious experiences, promoting cognitive internalization of ability judgments; instructor feedback and organizational support constitute verbal persuasion pathways, strengthening beliefs in action feasibility; while safety facilities and positive exercise experiences optimize emotional and physiological states, reducing failure expectations. These pathways collectively facilitate the cognitive transformation of environmental resources into stable efficacy beliefs [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the process of behavioral regulation, developing self-efficacy plays a crucial role. On one hand, a high level of self-efficacy enhances the perception of action controllability and reduces behavioral initiation resistance. On the other hand, self-efficacy also strengthens goal persistence and effort commitment, maintaining behavioral continuity when facing situational pressures such as fatigue or time conflicts [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Therefore, developing self-efficacy holds significant predictive value for the intensity, frequency, and persistence of Sports Participation Behavior, serving as a crucial cognitive mediator linking environmental factors to behavioral outcomes. Based on this, the following hypothesis is proposed:\u003c/p\u003e \u003cp\u003eH2: The University Physical Education Environment significantly influences college students' Sports Participation Behavior through the mediating effect of developing self-efficacy for exercise.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.3 The Mediating Role of Exercise Motivation\u003c/h2\u003e \u003cp\u003eExercise Motivation refers to the behavioral drive formed by individuals based on outcome expectations and self-evaluation, essentially manifesting as action tendencies stimulated by cognitive judgments regarding the value of behavior and the attainability of outcomes [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The University Physical Education Environment embeds itself in the formation process of individual outcome expectations through the synergistic effects of institutional provision, facility conditions, and sports culture. Institutional provision offers stable systemic support for sports participation behavior, enhancing perceptions of behavioral outcome feasibility. Well-equipped facilities increase accessibility to exercise opportunities, making behavioral benefits more tangible. A positive campus sports culture, through reinforcement of social values and construction of group norms, elevates the perceived meaning and appeal of sports engagement [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In this process, individuals integrate and evaluate contextual information through environmental perception, developing stable Exercise Motivation when outcome expectations are imbued with positive value.\u003c/p\u003e \u003cp\u003eAt the behavioral execution level, Exercise Motivation plays a crucial role in regulating behavior. First, Motivation influences behavioral direction, determining whether individuals engage in physical exercise and their goal priorities. Second, Motivation modulates behavioral commitment, affecting effort levels, time allocation, and participation frequency. Third, Motivation reinforces behavioral repetition through positive feedback, promoting the persistence and habitualization of Sports Participation Behavior [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Thus, Exercise Motivation serves not only as a vital source of energy for initiating physical activity but also as a crucial mechanism for sustaining it. Consequently, the University Physical Education Environment influences college students' Sports Participation Behavior by shaping individual outcome expectations and activating Exercise Motivation. Based on this, the following hypothesis is proposed:\u003c/p\u003e \u003cp\u003eH3: The University Physical Education Environment significantly influences college students' Sports Participation Behavior through the mediating effect of Exercise Motivation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e1.4 The Chain Mediating Effect of Developing Self-Efficacy and Exercise Motivation\u003c/h2\u003e \u003cp\u003eBehavioral regulation is an integrated process where cognitive evaluation mechanisms and motivational generation mechanisms are mutually embedded. Developing self-efficacy reflects an individual's assessment of their ability to complete exercise tasks, belonging to the cognitive evaluation system of behavioral feasibility. Exercise Motivation, meanwhile, reflects the driving force for action formed by individuals based on outcome expectations and value judgments, residing within the behavioral energy regulation system. Within the behavioral regulation framework, these two elements form a continuous, interconnected relationship: self-efficacy provides the cognitive foundation for behavioral feasibility, while motivation activates and channels behavioral energy after value attribution, thereby constituting a chain-like \u0026ldquo;cognition-motivation\u0026rdquo; mechanism [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. When individuals possess high Developing self-efficacy, they are more likely to develop positive outcome expectations and judgments of success probability. Consequently, the perceived value of behavioral outcomes increases, thereby promoting the generation and reinforcement of Exercise Motivation. This facilitates a continuous transition from cognitive evaluation to motivational activation [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the context of University Physical Education, the University Physical Education Environment first influences individuals' cognitive systems through institutional provision, resource accessibility, and cultural atmosphere, thereby helping to develop self-efficacy. Subsequently, self-efficacy promotes motivation generation by optimizing outcome expectation structures, and further drives the formation and maintenance of Sports Participation Behavior through motivational regulation mechanisms [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Thus, the University Physical Education Environment does not directly influence behavioral outcomes but instead forms a chain mechanism\u0026mdash;\u0026ldquo;environment-cognition-motivation-behavior\u0026rdquo;\u0026mdash;through continuous transmission between the cognitive and motivational systems. Compared to single mediation pathways, this structure more systematically reveals the internal processes by which the environment influences Sports Participation Behavior [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Based on this, the following hypotheses are proposed:\u003c/p\u003e \u003cp\u003eH4: The University Physical Education Environment significantly influences college students' Sports Participation Behavior through the Chain Intermediation Effect of Developing Self-Efficacy and Exercise Motivation.Consequently, the research hypothesis model is constructed as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"2 Research Subjects and Tools","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Research Subjects and Sampling\u003c/h2\u003e \u003cp\u003eThis study employed a combination of stratified cluster sampling and convenience sampling to conduct a questionnaire survey across multiple comprehensive universities in eastern China. Stratification was first based on university type and grade structure. Within each stratum, samples were drawn using class-based cluster sampling to ensure representativeness across different grades and academic backgrounds [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Inclusion criteria were: full-time undergraduate students enrolled at the institution; ability to independently comprehend the questionnaire content and complete it; voluntary participation in the study. Exclusion criteria included: individuals with severe physical illnesses or contraindications to exercise; respondents exhibiting abnormal completion times or discernible patterns in their responses; and questionnaires with missing values exceeding 5.7% of total items. A total of 743 questionnaires were distributed. After screening for logical consistency and completeness, 700 valid samples were obtained, yielding an effective response rate within the acceptable range for empirical social science research. The sample exhibited relatively balanced distribution across gender and grade levels, spanning freshmen through seniors, thereby adequately reflecting the overall characteristics of the university student population. The overall sample structure showed no significant skewness or clustering of a single group, providing a sound statistical foundation for structural model testing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Research Tools\u003c/h2\u003e \u003cp\u003eThis study measured four core variables: University Physical Education Environment, Developing self-efficacy, Exercise Motivation, and Sports Participation Behavior. All scales employed a 1\u0026ndash;5 Likert-type scoring method, with higher scores indicating greater levels of the respective variable.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 University Physical Education Environment Scale\u003c/h2\u003e \u003cp\u003eThis study employs the University Physical Education Environment Scale developed by Li Junqing et al. (2007). This scale was localized and revised based on existing physical education environment assessment tools, featuring a relatively mature structural framework and practical applicability [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The scale comprises 30 items, comprehensively evaluating the University Physical Education environment across three dimensions: adequacy of facilities, environmental accessibility, and institutional support and sports atmosphere [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The scale employs a five-point Likert scale, where higher scores indicate greater individual endorsement of the University Physical Education Environment. As a structured environmental assessment tool, it features comprehensive item coverage, clear dimensional delineation, and straightforward administration. Demonstrating strong content validity and test-retest reliability, it is widely applied in university physical activity management and related empirical research. In the present study sample, the Cronbach's α for this scale was 0.956, significantly exceeding the commonly accepted standard of 0.70. This indicates extremely high internal consistency, providing a reliable measurement foundation for subsequent model analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Developing self-efficacy scale\u003c/h2\u003e \u003cp\u003eThis study employed the Developing Self-Efficacy Scale developed by Bandura (2006), comprising 18 items, to assess individuals' confidence in maintaining exercise routines across different contexts and potential obstacles [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Originally designed as a unidimensional construct, subsequent validation studies subdivided the scale into two dimensions based on situational characteristics: internal feelings and physiological states (e.g., fatigue, low mood, or physical discomfort); and external situational factors (e.g., unfavorable weather, time constraints, or lack of social support). The scale employs a five-point Likert scale, with higher scores indicating greater Developing self-efficacy [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This self-report instrument, grounded in social cognitive theory, emphasizes systematic assessment of behavioral beliefs across diverse impediments. It demonstrates strong predictive validity and cross-cultural applicability. In the present study sample, Cronbach\u0026rsquo;s α reached 0.920, indicating excellent reliability and strong internal consistency among items. This confirms the scale\u0026rsquo;s ability to reliably measure college students\u0026rsquo; ability to develop self-efficacy for exercise.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Exercise Motivation Scale\u003c/h2\u003e \u003cp\u003eThis study employed the Exercise Motivations Inventory-2 (EMI-2) scale developed by Markland and Hardy (1993) and revised by Markland and Ingledew (1997) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This multidimensional Exercise Motivation assessment tool comprises 36 items in its standard version (some studies employ an extended item version), covering 14 motivational dimensions: stress management, revitalization, enjoyment, challenge, social recognition, belongingness, competition, health pressure, disease prevention, active health, weight management, appearance, strength/endurance, and agility [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The scale employs a five-point Likert scale, with higher scores indicating stronger motivation for physical activity participation. Grounded in self-determination theory, this tool systematically integrates intrinsic and extrinsic motivational factors to comprehensively assess multiple drivers of exercise initiation and persistence, demonstrating strong construct validity and cross-cultural applicability. In the present study sample, the scale demonstrated a Cronbach's α of 0.96, indicating exceptional internal consistency that meets measurement requirements for structural model analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4 Sports Participation Behavior Scale\u003c/h2\u003e \u003cp\u003eThis study employed the Physical Activity Grading Scale developed by Liang Deqing (1994) to measure individual levels of sports participation [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The scale assesses three dimensions: exercise intensity, duration, and frequency. Intensity ranges from 1 (light) to 5 (heavy), duration from 1 (less than 15 minutes) to 5 (over 1 hour), and frequency from 1 (less than once per month) to 5 (daily). The total score is calculated using the formula \u0026ldquo;intensity \u0026times; duration \u0026times; frequency,\u0026rdquo; with higher scores indicating greater physical activity participation levels [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. As a self-report behavioral measurement tool, this scale focuses on quantifying individual physical activity levels. It features a concise structure, intuitive calculation, and user-friendly operation, making it suitable for both adolescent and adult populations. Widely applied in sports psychology and health behavior research, it has demonstrated sound reliability and validity foundations. In the present study sample, the Cronbach's α for this scale was 0.824, exceeding the 0.80 standard. This indicates good internal consistency, demonstrating its ability to reliably reflect college students' Sports Participation Behavior levels.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data Collection Procedures\u003c/h2\u003e \u003cp\u003eThis study employed an online questionnaire for data collection, with the survey completed over several weeks. Prior to questionnaire distribution, participants received a standardized explanation outlining the research objectives and completion requirements. The questionnaire's opening page explicitly stated adherence to principles of anonymity and voluntary participation [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Participants could only access the formal questionnaire page after reading and confirming their agreement to the informed consent statement, ensuring the survey process complied with fundamental research ethics standards. To mitigate potential homogeneity bias effects on the findings, multiple control measures were implemented at the program design level: First, the instructions emphasized that there were no right or wrong answers, encouraging respondents to answer based on their genuine feelings to reduce social desirability bias; Second, the order of certain items was randomized to prevent systematic response tendencies. Third, appropriate reverse-scored items were included in the scales to identify and control for mechanical or consistent responses. Furthermore, the research protocol received ethical review approval from the institution prior to implementation. Data collection strictly adhered to ethical principles and academic standards for social science research, ensuring the authenticity and reliability of research data at the procedural level [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data Analysis Methods\u003c/h2\u003e \u003cp\u003eThis study employed SPSS software and the PROCESS macro (Version 4.1) for statistical analysis. First, reliability tests were conducted on each scale, assessing internal consistency through calculation of Cronbach\u0026rsquo;s α coefficients. Subsequently, descriptive statistical analysis was performed, calculating the mean, standard deviation, skewness, and kurtosis of each variable to examine data distribution characteristics [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Building on this foundation, independent samples t-tests or one-way analysis of variance (ANOVA) were employed to compare differences in key variables across groups with distinct demographic characteristics. Effect size indices were reported to assess the practical significance of these differences [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Subsequently, Pearson correlation analysis was employed to examine linear relationships between variables. Multivariate regression analysis was then used to sequentially test direct effects and potential mediating pathways. To assess chained mediation effects, Model 6 of the PROCESS macro was applied, utilizing 5,000 bootstrap resamples to construct 95% confidence intervals. Mediating effects were deemed significant when confidence intervals excluded zero. The statistical significance level was set at α\u0026thinsp;=\u0026thinsp;0.05. Standardized regression coefficients and effect size indicators (f\u0026sup2;) were reported to assess the model's practical explanatory power.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Research Findings","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Common Method Bias Test\u003c/h2\u003e \u003cp\u003eTo guard against potential common method bias in self-reported questionnaire data, this study employed exploratory factor analysis using principal component analysis combined with Promax oblique rotation. This approach examined the potential impact of common method variance on measurement validity and provided diagnostic evidence for subsequent model construction. Data suitability tests revealed a Kaiser-Meyer-Olkin measure of 0.985, significantly exceeding the 0.70 threshold. This indicates extremely strong inter-variable correlations, rendering the data highly suitable for factor analysis [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The Bartlett sphericity test yielded an approximate chi-square value of 35,593.878 (df\u0026thinsp;=\u0026thinsp;4005, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), strongly rejecting the null hypothesis of variable independence and further confirming data suitability for factor extraction. Additionally, diagonal elements in the inverse correlation matrix exceeded 0.40, indicating no severe multicollinearity among observed variables, allowing all to be included in subsequent analysis. The presence of CMB was assessed using Harman's single-factor test. All items were forced onto a single, unrotated common factor, revealing that the first common factor explained 41.861% of the total variance. This value falls within the 40%\u0026ndash;50% cautionary range, indicating a certain degree of method covariation in the data, though not yet reaching the severe bias level exceeding 50%. Further analysis revealed nine components with eigenvalues exceeding 1.0, collectively explaining 52.057% of total variance. This indicates variation stems not from a single methodological factor but is distributed across multiple substantive dimensions. Item-factor commonality tests revealed that all selected items exceeded the recommended threshold of 0.50, indicating these items effectively capture variance in their latent variables with high extraction efficiency. However, cross-loadings were observed in the unrotated factor matrix. Therefore, Promax oblique rotation was applied to achieve a more parsimonious factor structure, allowing natural correlations between factors\u0026mdash;a particularly suitable approach for multidimensional psychological and behavioral constructs in sports science [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Overall, while moderate common method variance was detected, the first factor explained a reasonable proportion of variance, and the cumulative explanatory power of multiple factors exceeded 50%. This supports the basic construct validity of the measurement tool.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Demographic Descriptive Statistics\u003c/h2\u003e \u003cp\u003ePrior to conducting primary hypothesis tests, this study systematically evaluated the reliability of measurement instruments, the distributional characteristics of sample data, and demographic composition to ensure the robustness, validity, and ecological validity of subsequent parametric statistical analyses. Reliability analysis employed Cronbach's α coefficient to assess internal consistency reliability across scales. Results indicate all core scales demonstrated exceptionally high internal consistency: School Physical Environment Scale (30 items) α\u0026thinsp;=\u0026thinsp;0.956; Developing self-efficacy Scale (18 items) α\u0026thinsp;=\u0026thinsp;0.920; Exercise Motivation Scale (36 items) α\u0026thinsp;=\u0026thinsp;0.966; Sports Participation Behavior Scale (6 items) α\u0026thinsp;=\u0026thinsp;0.824. These coefficients significantly exceeded the stringent threshold of 0.80, with the School Physical Environment and Exercise Motivation scales approaching or surpassing the excellent level of 0.95. This performance substantially exceeded the standard recommended by Nunnally (1978) for basic research and the higher expectations set by Lance et al. (2006) for mature scales in applied research [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Detailed reliability results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInternal Consistency Reliability of Core Scales (N\u0026thinsp;=\u0026thinsp;700)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCronbach\u0026rsquo;s α\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNote\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSchool Sports Environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExtremely high reliability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSports Participation Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh reliability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeveloping self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExtremely high reliability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise Motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGood reliability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDescriptive statistics further reveal the central tendency and dispersion of the sample across core variables (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The means of all variables fell within the upper-middle range of the 5-point Likert scale, indicating that the sample's overall perceptions of the school sports environment, self-efficacy, motivation, and actual Sports Participation Behavior were moderately positive. Standard deviations ranged from 0.765 to 0.863, reflecting moderate individual variation consistent with the expected heterogeneity in sports-related psychological and behavioral variables among college students. The absolute values of skewness and kurtosis were both below 0.80 and 1.00, respectively, far below the lenient thresholds of |2| and |7|. The overall distribution approximated normality, supporting the parametric assumptions for Pearson correlation and multiple linear regression Bootstrap mediation analysis [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe demographic characteristics of the sample further enhance the representativeness and external validity of the study. This study obtained 700 valid questionnaires (N\u0026thinsp;=\u0026thinsp;700, no missing data), which underwent descriptive statistical analysis using SPSS. Gender distribution was nearly balanced: males accounted for 50.6% (n\u0026thinsp;=\u0026thinsp;354) and females for 49.4% (n\u0026thinsp;=\u0026thinsp;346), effectively controlling for potential confounding effects of gender on mediating pathways. Grade distribution was relatively uniform: Freshmen 28.1% (n\u0026thinsp;=\u0026thinsp;197), Sophomores 23.1% (n\u0026thinsp;=\u0026thinsp;162), Juniors 25.4% (n\u0026thinsp;=\u0026thinsp;178), Seniors 23.3% (n\u0026thinsp;=\u0026thinsp;163). This broadly covered different learning pressures and developmental needs across all undergraduate education stages, enhancing the generalizability of conclusions. Significant heterogeneity in academic backgrounds: 53.4% (n\u0026thinsp;=\u0026thinsp;374) were physical education majors, while 46.6% (n\u0026thinsp;=\u0026thinsp;326) were non-physical education majors, with both groups possessing sufficient sample sizes. This disciplinary composition not only reflects natural variation in students' sports-related experiences and cognition but also provides a necessary foundation for subsequent analyses examining the potential moderating or differential effects of disciplinary attributes on perceived sensitivity to the sports environment, Exercise Motivation, and self-efficacy. The distribution of monthly per capita household income exhibits a certain socioeconomic gradient: low-income groups (\u0026lt;\u0026thinsp;3000 yuan and 3000\u0026ndash;6000 yuan) collectively accounted for 70.7%, while the proportion of middle-to-high-income groups was relatively low.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of the Sample Population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eattribute\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuantity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e354\u003c/p\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.6\u003c/p\u003e \u003cp\u003e49.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreshman year\u003c/p\u003e \u003cp\u003eSophomore year\u003c/p\u003e \u003cp\u003eJunior year\u003c/p\u003e \u003cp\u003eSenior year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e197\u003c/p\u003e \u003cp\u003e162\u003c/p\u003e \u003cp\u003e178\u003c/p\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003cp\u003e23.1\u003c/p\u003e \u003cp\u003e25.4\u003c/p\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfessional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSports\u003c/p\u003e \u003cp\u003eNon-Sports\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e374\u003c/p\u003e \u003cp\u003e326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.4\u003c/p\u003e \u003cp\u003e46.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly household income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3000元\u003c/p\u003e \u003cp\u003e3000\u0026ndash;6000元\u003c/p\u003e \u003cp\u003e6000\u0026ndash;10000元\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e224\u003c/p\u003e \u003cp\u003e271\u003c/p\u003e \u003cp\u003e128\u003c/p\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003cp\u003e38.7\u003c/p\u003e \u003cp\u003e18.3\u003c/p\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo further mitigate multicollinearity risks and facilitate interpretation of path coefficients in conditional process models, this study centered the means of continuous independent variables and mediating variables (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Following centering, the means of all variables approached zero while standard deviations remained unchanged. The absolute values of skewness and kurtosis further decreased, resulting in more stable distribution characteristics [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics of Core Variables After Decentralization (N\u0026thinsp;=\u0026thinsp;700)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eminimum value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003emaximum value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003emean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e偏度\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e峰度\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity Physical Education Environment (Decentralized)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.976\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeveloping self-efficacy (Decentralization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.845\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise Motivation (Decentralized)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.0017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.971\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: Decentralization is achieved by subtracting the sample mean; skewness and kurtosis values indicate a distribution close to normal, supporting the parametric statistical hypothesis.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThrough systematic verification of reliability, distribution characteristics, demographic composition, and data preprocessing, this study demonstrates high data quality and strong sample representativeness. This establishes a reliable statistical foundation for subsequent correlation analysis, regression modeling, and chained mediation effect testing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Independent Samples t-Test\u003c/h2\u003e \u003cp\u003eTo systematically examine potential group differences in core constructs based on dichotomous demographic variables, this study employed independent samples t-tests. Levene's test for variance homogeneity was conducted to assess the validity of the hypothesis, and Cohen's d was calculated as an effect size indicator [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This analysis aimed to identify potential influencing factors and provide empirical support for covariate selection in subsequent regression models. All tests employed a two-tailed p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 significance threshold, with calculations based on decentered variables to ensure coefficient stability [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Levene's test results indicated that the assumption of homogeneity of variances held for all variables (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), supporting the applicability of the standard t-test.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Gender Differences\u003c/h2\u003e \u003cp\u003eIndependent samples t-test results indicate no significant between-group differences in school physical education environment, Developing self-efficacy, Exercise Motivation, or Sports Participation Behavior based on gender (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Specifically: The t-value for Developing Self-Efficacy was \u0026minus;\u0026thinsp;1.079 (df\u0026thinsp;=\u0026thinsp;698, p\u0026thinsp;=\u0026thinsp;0.281, Cohen\u0026rsquo;s d=-0.082); The t-value for Exercise Motivation was \u0026minus;\u0026thinsp;0.180 (df\u0026thinsp;=\u0026thinsp;698, p\u0026thinsp;=\u0026thinsp;0.857, Cohen\u0026rsquo;s d=-0.014); The t-value for Sports Participation Behavior was \u0026minus;\u0026thinsp;0.093 (df\u0026thinsp;=\u0026thinsp;698, p\u0026thinsp;=\u0026thinsp;0.926, Cohen\u0026rsquo;s d=-0.007). All absolute effect sizes were less than 0.10, indicating that gender contributed minimally to the systematic variation in these variables. This provides preliminary evidence supporting the gender-neutral hypothesis in contemporary sports behavior research [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Differences in Various Variables Among Students of Different Genders\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSports Participation Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDeveloping self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExercise Motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.926\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Differences Between Groups of Only Children\u003c/h2\u003e \u003cp\u003eThe results of the independent samples t-test indicate that whether an individual is an only child does not yield significant overall between-group differences for core variables, but it exhibits a marginal effect on Sports Participation Behavior (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Specifically: t-value for University Physical Education Environment\u0026thinsp;=\u0026thinsp;0.887 (df\u0026thinsp;=\u0026thinsp;698, p\u0026thinsp;=\u0026thinsp;0.375, Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.068); t-value for Developing self-efficacy\u0026thinsp;=\u0026thinsp;0.752 (df\u0026thinsp;=\u0026thinsp;698, p\u0026thinsp;=\u0026thinsp;0.453, Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.057); the t-value for Sports Participation Behavior was 0.914 (df\u0026thinsp;=\u0026thinsp;698, p\u0026thinsp;=\u0026thinsp;0.361, Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.070); and the t-value for PA was 0.914 (df\u0026thinsp;=\u0026thinsp;698, p\u0026thinsp;=\u0026thinsp;0.361, Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.070). All effect sizes were small (d\u0026thinsp;\u0026lt;\u0026thinsp;0.10), indicating limited explanatory power for this factor in variable variation. However, the marginal p-value for sports participation suggests a potential subtle family structure influence in larger samples (Li et al., 2010). To control for potential family dynamic heterogeneity, this variable was incorporated into the model as a covariate.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Differences in Student Variables Based on Only-Child Status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSports Participation Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDeveloping self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExercise Motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.4 ANOVA Single-Factor Analysis\u003c/h2\u003e \u003cp\u003eOne-way analysis of variance (ANOVA) was employed to examine the between-group effects of multi-categorical demographic variables on core constructs, supplemented by partial η\u0026sup2; as an effect size indicator. LSD and Tamhane post-hoc multiple comparisons were conducted to identify specific sources of differences. Levene's test confirmed homogeneity of variance across all variables (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). All analyses were based on centered variables to minimize multicollinearity effects. The significance threshold was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, with marginal significance defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.10 to capture potential threshold effects [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1 Differences Between Grade Levels\u003c/h2\u003e \u003cp\u003eANOVA results indicate (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) that grade level showed marginally significant between-group differences for Exercise Motivation and Sports Participation Behavior: Exercise Motivation (F\u0026thinsp;=\u0026thinsp;2.131, df\u0026thinsp;=\u0026thinsp;3/696, p\u0026thinsp;=\u0026thinsp;0.095, partial η\u0026sup2; = 0.009); Sports Participation Behavior (F\u0026thinsp;=\u0026thinsp;1.769, df\u0026thinsp;=\u0026thinsp;3/696, p\u0026thinsp;=\u0026thinsp;0.152, partial η\u0026sup2; = 0.008). Post-hoc multiple comparisons (LSD and Tamhane) revealed significant differences between sophomores and seniors in Exercise Motivation and Sports Participation Behavior (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while no significant variation was found between freshmen and juniors. School physical environment (F\u0026thinsp;=\u0026thinsp;1.147, p\u0026thinsp;=\u0026thinsp;0.329, partial η\u0026sup2; = 0.005) and Developing self-efficacy (F\u0026thinsp;=\u0026thinsp;1.115, p\u0026thinsp;=\u0026thinsp;0.342, partial η\u0026sup2; = 0.005) showed no significant effects. Overall effect sizes were small (η\u0026sup2; \u0026lt; 0.01), indicating that grade level contributed minimally to variance in the variables. However, its marginal effect supports including it as a covariate in the model to control for the influence of learning stage heterogeneity on psychological mechanisms.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of One-Way ANOVA for Core Variables in Grade 6 (N\u0026thinsp;=\u0026thinsp;700)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelated variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreshman year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSophomore year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenior year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSports Participation Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreshman year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSophomore year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenior year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDeveloping self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreshman year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSophomore year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenior year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eExercise Motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreshman year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSophomore year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenior year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2 Differences in Monthly Household Income Levels Across Groups\u003c/h2\u003e \u003cp\u003eANOVA results indicate (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) that monthly household income per capita exhibited a marginally significant effect on Developing self-efficacy (F\u0026thinsp;=\u0026thinsp;1.307, df\u0026thinsp;=\u0026thinsp;3/696, p\u0026thinsp;=\u0026thinsp;0.271, partial η\u0026sup2; = 0.006), while showing no significant effects on school physical education environment (F\u0026thinsp;=\u0026thinsp;1.140, p\u0026thinsp;=\u0026thinsp;0.332, partial η\u0026sup2; = 0.005), Exercise Motivation (F\u0026thinsp;=\u0026thinsp;1.835, p\u0026thinsp;=\u0026thinsp;0.139, partial η\u0026sup2; = 0.008), and Sports Participation Behavior (F\u0026thinsp;=\u0026thinsp;1.202, p\u0026thinsp;=\u0026thinsp;0.308, partial η\u0026sup2; = 0.005). Post-hoc multiple comparisons (LSD and Tamhane) revealed a marginal difference in ESE between the low-income group (\u0026lt;\u0026yen;3,000) and the high-income group (\u0026gt;\u0026yen;10,000) (p\u0026thinsp;\u0026asymp;\u0026thinsp;0.10), but no significant variation within the middle-income group. Overall effect sizes were small (η\u0026sup2; \u0026lt; 0.01), indicating a limited gradient effect of socioeconomic status on psychological constructs. Nevertheless, these marginal effects support including socioeconomic status as a covariate in the model to control for potential moderation of the mediating pathway by economic resource constraints.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Differences in Various Variables of Monthly Household Income Among Students (Single-Factor ANOVA Analysis)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelated variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMonthly household income of students\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.332\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3000\u0026ndash;6000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6000\u0026ndash;10000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSports Participation Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3000\u0026ndash;6000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6000\u0026ndash;10000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDeveloping self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3000\u0026ndash;6000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6000\u0026ndash;10000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eExercise Motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3000\u0026ndash;6000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6000\u0026ndash;10000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10000元\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Pearson Correlation Analysis\u003c/h2\u003e \u003cp\u003ePearson correlation analysis results indicate (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) that a significant positive relationship exists between the school physical environment and exercise behavior (r\u0026thinsp;=\u0026thinsp;0.847, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Exercise Motivation also shows a significant positive correlation with exercise behavior and Sports Participation Behavior (r\u0026thinsp;=\u0026thinsp;0.856, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Developing self-efficacy also showed a significant positive correlation with Sports Participation Behavior (r\u0026thinsp;=\u0026thinsp;0.832, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, school physical environment showed highly significant positive correlations with Exercise Motivation (r\u0026thinsp;=\u0026thinsp;0.922, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Developing self-efficacy (r\u0026thinsp;=\u0026thinsp;0.900, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and Exercise Motivation with Developing self-efficacy (r\u0026thinsp;=\u0026thinsp;0.904, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese correlation results indicate stable positive linear associations among core variables, providing preliminary empirical support for the chained mediation effect hypothesized in this study. They also establish a reliable statistical foundation for subsequent multiple linear regression and Bootstrap mediation effect testing (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e for details). All correlation coefficients reached moderate to strong levels, with absolute values below 0.95, indicating no signs of extreme multicollinearity. This ensures the stability and interpretability of subsequent model estimations.The chained intermediary model is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. All four hypotheses (H1\u0026ndash;H4) proposed in this study received empirical support.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Analysis of Key Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSports Participation Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.900***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeveloping self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.922***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.904***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise Motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.847***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.832***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.85***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Multiple Linear Regression Analysis\u003c/h2\u003e \u003cp\u003eTo examine the direct predictive effect of the University Physical Education Environment on college students' Sports Participation Behavior and to investigate the independent contributions of Developing self-efficacy and Exercise Motivation, this study employed stratified multiple linear regression analysis (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). First, demographic covariates (gender, grade level, only child status, per capita monthly household income) were included. Subsequently, the decentralized University Physical Education Environment, Developing Self-Efficacy, and Exercise Motivation were sequentially introduced as predictor variables to control for potential confounders and assess incremental explanatory power [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The final full model demonstrated excellent fit: R\u0026thinsp;=\u0026thinsp;0.874, R\u0026sup2; = 0.765, adjusted R\u0026sup2; = 0.762, F(7, 692)\u0026thinsp;=\u0026thinsp;321.12, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. This model explained 76.5% of the total variance in Sports Participation Behavior, indicating strong predictive efficacy of the included variables. After controlling for demographic covariates, standardized regression coefficients for decentralized variables indicated: Developing self-efficacy also significantly and positively predicted exercise behavior (β\u0026thinsp;=\u0026thinsp;0.215, t\u0026thinsp;=\u0026thinsp;4.538, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); Exercise Motivation exhibited the strongest predictive effect (β\u0026thinsp;=\u0026thinsp;0.395, t\u0026thinsp;=\u0026thinsp;7.429, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Even when Developing self-efficacy and Exercise Motivation were included simultaneously, the University Physical Education Environment maintained a significant direct effect, supporting Hypothesis H1.\u003c/p\u003e \u003cp\u003eAmong demographic covariates, monthly household income per capita showed an independent positive prediction for exercise behavior (β\u0026thinsp;=\u0026thinsp;0.038, p\u0026thinsp;=\u0026thinsp;0.042). Being an only child exhibited marginal significance (β\u0026thinsp;=\u0026thinsp;0.034, p\u0026thinsp;=\u0026thinsp;0.071), while gender and grade level were not significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The overall contribution of covariates was minimal (ΔR\u0026sup2; \u0026asymp; 0.003), with no change in the direction or significance of the core predictor variables.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of Stratified Multicollinearity Regression (Predicting College Students' Sports Participation Behavior)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1 β (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 2 β (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 3 β (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 4 β (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.001(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.001(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.001(0.032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.001(0.032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.020(0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.020(0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.014(0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.014(0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhether you are an only child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.032(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.032(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034(0.032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.034(0.032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly household income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.041(0.018)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041(0.018)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.038(0.017)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.038(0.017)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity Physical Education Environment (Decentralized)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.848(0.022)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.440(0.036)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.290(0.056)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.954\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeveloping self-efficacy (Decentralization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.215(0.053)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.215(0.053)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.587\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise Motivation (Decentralized)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.395(0.056)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔR\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.717***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.128***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF (df)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.52(4695)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e356.70(5694)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e645.65(6693)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e321.12(7692)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Coefficients represent standardized β values, with standard errors in parentheses. VIF values are based on the full model (Model 4).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo mitigate potential multicollinearity, mean-centering was applied to the University Physical Education Environment, Developing self-efficacy, and Exercise Motivation (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). Overall model fit indices remained consistent before and after centering, with no changes in the magnitude, direction, or significance of regression coefficients. Multicollinearity diagnostics revealed variance inflation factors (VIF) for predictor variables ranging from 1.000 to 8.314, with a maximum conditional index of 7.441. This indicates moderate multicollinearity that did not reach critical thresholds. The maximum conditional index before centering reached 30.557, decreasing to 6.024 after centering, significantly improving numerical stability. Although moderate multicollinearity existed among variables (primarily stemming from the theoretical correlation between Developing self-efficacy and Exercise Motivation), VIF values remained below 10, limiting their impact on parameter estimation and Bootstrap indirect effect tests.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMulticollinearity Diagnosis Results (Complete Model, Comparison Before and After Centering)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUniversity Physical Education Environment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-centering VIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentralization Threshold Index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVIF after centering\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCentralization Threshold Index\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.940\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.557\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.954\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.441\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSports Participation Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeveloping self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise Motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: The condition index is based on eigenvalue decomposition. Centralization significantly improves numerical stability.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eResidual diagnostics revealed (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e) that the standardized residuals had a mean of approximately 0, a standard deviation of approximately 1, a skewness of -0.443 (slight left skew), and a kurtosis of 2.316 (slight heavy-tailed distribution). The Durbin-Watson statistic was 1.95, supporting residual independence. The Kolmogorov-Smirnov test (D\u0026thinsp;=\u0026thinsp;0.065, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Shapiro-Wilk test (W\u0026thinsp;=\u0026thinsp;0.968, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) rejected the assumption of strict normality. However, these tests are highly sensitive to minor deviations in large samples (N\u0026thinsp;=\u0026thinsp;700). The residual distribution approximates normality with only slight heavy tails and skewness, showing no severe heteroscedasticity or nonlinear patterns. Given the large sample size and subsequent use of Bootstrap methods, this minor non-normality has limited impact on parameter estimates and the significance of mediating effects.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResidual Diagnostic Statistics (Full Model)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue/Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCriteria for Judgment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConclusion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExpected\u003c/p\u003e \u003cp\u003e\u0026asymp; 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSatisfy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExpected\u003c/p\u003e \u003cp\u003e\u0026asymp;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSatisfy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkewness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[-1, 1] For minor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSlightly left-leaning\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeak Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 为正态, \u0026gt;3Heavy Tail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSlightly heavy-tailed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDurbin-Watson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[1.5, 2.5] non-autocorrelated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIndependence Satisfaction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKolmogorov-Smirnov\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD\u0026thinsp;=\u0026thinsp;0.065, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.05 Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRefusal (Highly Sensitive)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShapiro-Wilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW\u0026thinsp;=\u0026thinsp;0.968, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.05 Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRefusal (Highly Sensitive)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results indicate that, after controlling for demographic covariates and potential collinearity, the University Physical Education Environment exerts a significant direct predictive effect on college students' physical exercise behavior. Furthermore, both Developing Self-Efficacy and Exercise Motivation were validated as independent contributors, establishing a robust foundation for subsequent chain mediation analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Testing for Mediating Effects\u003c/h2\u003e \u003cp\u003eTo examine the chain intermediation effect of Exercise Motivation and Developing Self-Efficacy in the relationship between University Physical Education Environments and College Students' Sports Participation Behavior, this study employed Hayes (2022) PROCESS macro Model 6 for serial mediation analysis. The model simultaneously controlled for demographic covariates (gender, grade level, only child status, per capita monthly household income) and employed decentralized variable calculations. A 95% confidence interval (CI) was generated through 5,000 bias-corrected bootstrap resampling to obtain robust nonparametric indirect effect estimates [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec28\" class=\"Section3\"\u003e \u003ch2\u003e3.7.1 Analysis of Regression Relationships Among Variables\u003c/h2\u003e \u003cp\u003eThe PROCESS macro output displayed three sequential regression equations in the chained mediation model (Table\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e12\u003c/span\u003e), with the following results: First, the University Physical Education Environment significantly and positively predicted Exercise Motivation (a₁ = 0.9402, SE\u0026thinsp;=\u0026thinsp;0.0150, t\u0026thinsp;=\u0026thinsp;62.647, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95% CI [0.911, 0.970], standardized coefficient\u0026thinsp;=\u0026thinsp;0.922), explaining 85.0% of the variance in motivation (R\u0026sup2; = 0.850). Second, University Physical Education Environment and Exercise Motivation jointly significantly predicted Developing self-efficacy: University Physical Education Environment \u0026rarr; Developing self-efficacy (a₂ = 0.4181, SE\u0026thinsp;=\u0026thinsp;0.0363, t\u0026thinsp;=\u0026thinsp;11.508, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, standardized coefficient\u0026thinsp;=\u0026thinsp;0.440); Exercise Motivation \u0026rarr; Developing self-efficacy (d₂₁ = 0.4637, SE\u0026thinsp;=\u0026thinsp;0.0356, t\u0026thinsp;=\u0026thinsp;13.017, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, standardized coefficient\u0026thinsp;=\u0026thinsp;0.498), with the equation explaining 84.8% of the variance in efficacy (R\u0026sup2; = 0.848). Finally, after controlling for mediating variables and covariates, University Physical Education Environment, Developing Self-Efficacy, and Exercise Motivation all significantly and positively predicted Sports Participation Behavior: University Physical Education Environment \u0026rarr; Sports Participation Behavior (c' = 0.3112, SE\u0026thinsp;=\u0026thinsp;0.0558, t\u0026thinsp;=\u0026thinsp;5.581, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, standardized coefficient\u0026thinsp;=\u0026thinsp;0.290); Exercise Motivation \u0026rarr; Sports Participation Behavior (b₁ = 0.4151, SE\u0026thinsp;=\u0026thinsp;0.0559, t\u0026thinsp;=\u0026thinsp;7.429, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, standardized coefficient\u0026thinsp;=\u0026thinsp;0.395); Developing self-efficacy \u0026rarr; Sports Participation Behavior (b₂ = 0.2424, SE\u0026thinsp;=\u0026thinsp;0.0534, t\u0026thinsp;=\u0026thinsp;4.538, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, standardized coefficient\u0026thinsp;=\u0026thinsp;0.215). The full model R\u0026sup2; = 0.765 indicates robust relationships among variables [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAll regression paths were significant, supporting the structural validity of the chained mediation model. Among demographic covariates, only monthly household income per capita demonstrated an independent positive predictive effect (β\u0026thinsp;=\u0026thinsp;0.038, p\u0026thinsp;=\u0026thinsp;0.042), while other variables were insignificant. Overall, this did not alter the significance or direction of the core pathways.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression Relationships Among Variables in the Chain Mediation Model (N\u0026thinsp;=\u0026thinsp;700, controlling for covariates)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePredictor variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003et Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95%CI lower limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95%CI upper limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise Motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity Physical Education Environment (Centralization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e62.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.850\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDeveloping self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity Physical Education Environment (Centralization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExercise Motivation (Centralized)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSports Participation Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity Physical Education Environment (Centralization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExercise Motivation (Centralized)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeveloping self-efficacy (Centralization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eNote: All paths control for gender, grade level, only-child status, and monthly household income per capita. Coefficients represent unstandardized b values (b) and standardized β values. All paths have p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section3\"\u003e \u003ch2\u003e3.7.2 Results of the Chain Mediated Effect Analysis\u003c/h2\u003e \u003cp\u003eResults of the chained mediational effect analysis (Table\u0026nbsp;\u003cspan refid=\"Tab13\" class=\"InternalRef\"\u003e13\u003c/span\u003e): The total effect was significant (c\u0026thinsp;=\u0026thinsp;0.9085, SE\u0026thinsp;=\u0026thinsp;0.0216, t\u0026thinsp;=\u0026thinsp;42.114, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95% CI [0.866, 0.951], standardized coefficient\u0026thinsp;=\u0026thinsp;0.848), indicating that the University Physical Education Environment exerts a significant positive total influence on Sports Participation Behavior [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The direct effect remained significant though weakened after controlling for the mediating variable (c' = 0.3112, SE\u0026thinsp;=\u0026thinsp;0.0558, t\u0026thinsp;=\u0026thinsp;5.581, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95% CI [0.202, 0.421], standardized coefficient\u0026thinsp;=\u0026thinsp;0.290), supporting the existence of a direct path. The total indirect effect was 0.5973 (Boot SE\u0026thinsp;=\u0026thinsp;0.0635, 95% Boot CI [0.471, 0.723]), accounting for 65.7% of the total effect, indicating that the mediating path represents the primary mechanism of action. All three specific indirect paths were significant: University Physical Education Environment \u0026rarr; Exercise Motivation \u0026rarr; Sports Participation Behavior (Ind1\u0026thinsp;=\u0026thinsp;0.3903, Boot 95% CI [0.254, 0.528]); University Physical Education Environment \u0026rarr; Developing self-efficacy \u0026rarr; Sports Participation Behavior (Ind2\u0026thinsp;=\u0026thinsp;0.1014, Boot 95% CI [0.052, 0.162]); University Physical Education Environment \u0026rarr; Exercise Motivation \u0026rarr; Developing self-efficacy \u0026rarr; Sports Participation Behavior (chain path, Ind3\u0026thinsp;=\u0026thinsp;0.1057, Boot 95% CI [0.055, 0.163]). Path comparison revealed: Path 1 was significantly greater than Path 2 (C1\u0026thinsp;=\u0026thinsp;0.2889, Boot 95% CI [0.114, 0.458]) and Path 3 (C2\u0026thinsp;=\u0026thinsp;0.2846, Boot 95% CI [0.119, 0.447]), indicating Exercise Motivation as the strongest single mediator; Path 2 showed no significant difference from Path 3 (C3 = -0.0043, Boot 95% CI [-0.049, 0.040]).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab13\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 13\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBootstrap Test Results for Chain Mediation Effects\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEffect Type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eeffect value(b)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoot SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBoot 95% CI lower limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBoot 95% CI upper limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eProportion of the total effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStandardized indirect effect\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDirect Path\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal indirect effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIndirect effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePath1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePath2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePath3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePath Comparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC1: Path1-Pat2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC1: Path1-Pat3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC1: Path2-Pat3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: All 95% bootstrap confidence intervals for indirect effects and comparative pathways exclude zero, indicating statistical significance. Standardized indirect effects are used to compare relative contributions.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn summary, The results of the chained mediation analysis support hypotheses H1\u0026ndash;H4: The University Physical Education Environment positively influences college students' Sports Participation Behavior through both single and chained mediation pathways via Exercise Motivation and Developing Self-Efficacy. Among these, Exercise Motivation as the primary mediator makes the most significant contribution, while the chained pathway further strengthens the sequential mechanism of motivation-self-efficacy. These findings remain robust after controlling for demographic covariates, providing a solid empirical foundation for subsequent discussions.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e4.1 The Impact of University Physical Education Environments on College Students' Sports Participation Behavior\u003c/h2\u003e \u003cp\u003eThe findings of this study indicate that the University Physical Education Environment significantly and positively predicts college students' Sports Participation Behavior (β\u0026thinsp;=\u0026thinsp;0.290, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This discovery suggests that the University Physical Education Environment, as a crucial contextual condition in students' daily lives, exerts a stable and promoting effect on the formation of Sports Participation Behavior. From the perspective of behavioral formation mechanisms, the University Physical Education Environment provides students with sustained situational support for physical activities [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The accessibility of sports facilities, the institutionalized arrangement of course systems, and the campus sports culture collectively form the contextual foundation for university students' participation in physical activities. When sports resources are well-allocated, students perceive lower time costs and behavioral barriers when engaging in physical activities, making it easier to integrate such activities into their daily routines. The accessibility of environmental resources lowers the threshold for initiating behavior to some extent, enabling physical activities to become sustainable daily choices.\u003c/p\u003e \u003cp\u003eIn the university setting, the University Physical Education Environment simultaneously reinforces Sports Participation Behavior through social interaction processes. Physical education courses, campus competitions, and sports club activities provide students with diverse platforms for athletic experiences. Sustained interactive experiences enhance the social attributes of physical activities within campus life, gradually transforming sports participation into a behavior pattern imbued with group identity significance. When physical activities maintain high visibility within campus culture, students are more likely to develop stable participation behaviors within collective contexts. Research findings further indicate that the University Physical Education Environment constitutes a crucial contextual foundation for college students' physical activity behaviors [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. A favorable University Physical Education Environment continuously provides behavioral opportunities in daily life, thereby increasing the likelihood of student participation in physical activities. This discovery empirically reveals the significant role of campus contextual factors in shaping college students' physical activity behaviors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003e4.2 The Mediating Role of Developing Self-Efficacy\u003c/h2\u003e \u003cp\u003eResearch findings indicate that Developing self-efficacy plays a significant mediating role between the University Physical Education Environment and college students' Sports Participation Behavior. Analysis reveals that the University Physical Education Environment significantly and positively predicts Developing self-efficacy (β\u0026thinsp;=\u0026thinsp;0.440, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while Developing self-efficacy further significantly predicts Sports Participation Behavior (β\u0026thinsp;=\u0026thinsp;0.215, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This structural relationship indicates that the University Physical Education Environment indirectly promotes the formation of Sports Participation Behavior by influencing individuals' cognitive evaluations of their capabilities. When confronting behavioral tasks, individuals assess the relationship between their own abilities and the task requirements. When individuals perceive themselves as capable of completing a task, the probability of initiating the behavior and its persistence significantly increase [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe University Physical Education Environment provides students with stable conditions for exercise practice, enabling them to gradually accumulate successful experiences through sustained physical activity. Frequent exercise practice reinforces students' positive evaluations of their athletic abilities, thereby enhancing their ability to develop self-efficacy. As self-efficacy levels increase, students are more likely to maintain exercise behaviors when facing academic pressures, time constraints, or physical fatigue [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Concurrently, peer interactions and modeling behaviors within campus sports settings also strengthen individuals' efficacy perceptions. Through observational learning during sports participation, students acquire behavioral information that fosters positive judgments about their athletic capabilities. As these ability beliefs stabilize, physical activity gains greater prominence in individuals' daily lives. Research findings indicate that the University Physical Education Environment establishes a crucial cognitive pathway\u0026mdash;transforming environmental factors into behavioral outcomes\u0026mdash;by reinforcing individuals' perceptions of their capabilities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec33\" class=\"Section2\"\u003e \u003ch2\u003e4.3 The Mediating Role of Exercise Motivation\u003c/h2\u003e \u003cp\u003eResearch findings indicate that Exercise Motivation plays a significant mediating role between the University Physical Education Environment and Sports Participation Behavior. Specifically, the University Physical Education Environment exerts a significant positive influence on Exercise Motivation (β\u0026thinsp;=\u0026thinsp;0.922, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and Exercise Motivation further significantly predicts Sports Participation Behavior (β\u0026thinsp;=\u0026thinsp;0.395, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This finding indicates that the University Physical Education Environment promotes the formation of Sports Participation Behavior by stimulating individuals' behavioral motivation systems. Behavioral motivation serves as a crucial psychological link connecting cognitive judgments with behavioral execution [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. When individuals develop positive expectations toward a behavior, their behavioral engagement significantly increases. By providing diverse athletic resources and varied physical activity formats, the University Physical Education Environment enables students to gradually develop stable behavioral interest during participation. Both campus physical education courses and extracurricular sports activities play vital roles in this process. Diverse athletic experiences reinforce students' recognition of the value of physical activity, gradually positioning exercise as a meaningful lifestyle choice [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. When sports become a stable presence in campus life, students are more likely to reserve space for physical activity within their daily schedules.\u003c/p\u003e \u003cp\u003eEnhanced Exercise Motivation also influences behavioral maintenance. Individuals with higher motivation levels typically demonstrate greater engagement in physical activities, including more consistent participation frequency and longer duration. Sustained exercise experiences generate positive feedback loops, further reinforcing Sports Participation Behavior. Research findings indicate that the University Physical Education Environment establishes a crucial motivational mechanism\u0026mdash;transforming environmental support into behavioral outcomes\u0026mdash;by strengthening students' exercise motivation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section2\"\u003e \u003ch2\u003e4.4 The Chain Intermediation Effect of Developing Self-Efficacy and Exercise Motivation\u003c/h2\u003e \u003cp\u003eIn further mechanism testing, this study found that Developing self-efficacy and Exercise Motivation constitute a significant chained mediating pathway between the University Physical Education Environment and Sports Participation Behavior. Bootstrap analysis results indicate that this chained mediating effect is significant (indirect effect\u0026thinsp;=\u0026thinsp;0.1057, 95% CI [0.055, 0.163]). This finding reveals a sequential mechanism through which environmental factors gradually translate into individual psychological systems during the formation of college students' physical activity behaviors [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In terms of the structural relationships among variables, the University Physical Education Environment first enhances students' belief in their own athletic capabilities through resource support and exercise scenario reinforcement, thereby fostering a higher level of Developing self-efficacy. When individuals form positive judgments about their own abilities, their expectations of success in physical activities also increase. This cognitive process further promotes the formation of Exercise Motivation.\u003c/p\u003e \u003cp\u003eDuring behavior formation, self-efficacy provides the cognitive foundation for behavioral motivation. Individuals who confirm their capacity to accomplish exercise tasks are more likely to develop stable participation intentions. As behavioral motivation gradually intensifies, physical activities gain higher priority in individuals' lives, thereby driving sustained engagement in Sports Participation Behavior. This chain of relationships reveals the psychological transmission pathway for the formation of college students' physical activity behaviors [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The University Physical Education Environment, by reinforcing capability cognition, further stimulates behavioral motivation, ultimately influencing Sports Participation Behavior. Environmental factors, cognitive evaluation, and behavioral drive form a continuous structure in the behavioral formation process. Research findings indicate that college students' Sports Participation Behavior is not the result of a single factor but rather a behavioral pattern gradually shaped by the combined effects of environmental support and psychological mechanisms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec35\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Practical Significance\u003c/h2\u003e \u003cp\u003eThis study provides significant insights for university physical education promotion practices by examining the structural relationships among University Physical Education Environments, Developing Self-Efficacy, Exercise Motivation, and Sports Participation Behavior [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Findings indicate that the University Physical Education Environment exerts a significant positive influence on Sports Participation Behavior (β\u0026thinsp;=\u0026thinsp;0.290, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Optimizing the physical environment remains a crucial foundation for promoting physical activity among college students. Universities should continuously improve sports facility construction, enhance accessibility to exercise spaces, and optimize equipment allocation in their physical education development plans. A stable supply of sports resources provides students with ongoing opportunities for physical activity, making it easier to integrate exercise into daily campus life. The findings also indicate that the University Physical Education Environment significantly enhances developing self-efficacy (β\u0026thinsp;=\u0026thinsp;0.440, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Physical education practices should prioritize students' experiential development of athletic competence. Through tiered instruction, skill-based guidance, and progressive training methods, students can achieve success in physical activities. Sustained positive experiences reinforce competence beliefs, thereby increasing willingness to participate in physical activities.\u003c/p\u003e \u003cp\u003eFurthermore, Exercise Motivation plays a crucial role in shaping Sports Participation Behavior (β\u0026thinsp;=\u0026thinsp;0.395, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Universities can increase the visibility and engagement of physical activities in campus life by diversifying sports programs, expanding sports clubs, and organizing varied athletic events. Sustained participation becomes more likely when students develop stable interests in physical activity. The chained mediating pathways revealed by this study indicate that university physical activity promotion strategies should foster synergistic relationships between environmental development and psychological mechanism cultivation. By optimizing the University Physical Education Environment, strengthening perceived competence, and stimulating exercise motivation, stable behavioral promotion mechanisms can be established at the cognitive and motivational levels, thereby enhancing college students' participation in physical activities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec36\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Research Limitations and Future Prospects\u003c/h2\u003e \u003cp\u003eThis study has made some progress in revealing the psychological mechanisms through which the University Physical Education Environment influences college students' Sports Participation Behavior, while further research opportunities remain. Employing a cross-sectional survey design, this study primarily inferred relationships between variables through statistical path analysis. This methodology effectively reveals structural connections among variables, providing empirical support for understanding the formation mechanisms of college students' physical activity behaviors. The development of physical activity behaviors exhibits distinct temporal dynamics. Future research could utilize longitudinal tracking designs or experimental methodologies to further examine the causal mechanisms through which the University Physical Education Environment influences Sports Participation Behavior, thereby yielding more robust research conclusions.\u003c/p\u003e \u003cp\u003eResearch data primarily stemmed from individual self-report questionnaires. This method effectively captures students' subjective perceptions of physical activity environments and behavioral experiences. However, self-report data may be subject to individual cognitive biases. Future studies could integrate objective physical activity measurement methods, such as wearable device recordings or campus sports facility usage data, to enhance the objectivity of research findings. This study primarily focused on two psychological variables: Developing self-efficacy and Exercise Motivation. College students' Sports Participation Behavior is influenced by multiple psychological and social factors. Future research could incorporate additional psychological variables\u0026mdash;such as peer interactions, sports identity, or emotional experiences\u0026mdash;into existing models to construct more systematic behavioral explanatory frameworks. The study sample primarily originates from universities in a specific region. Differences exist in physical resource allocation and campus culture across regional institutions. Future research could further test the stability of the research model through cross-regional sample comparisons, thereby enhancing the generalizability of findings.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e The design of this study followed the guidelines and regulations of the Declaration of Helsinki and approved by Ethics Committee of Liaoning Normal University (LL20254), and all participants signed an informed consent form and were paid for their participation.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eLiaoning Provincial Social Science Planning Fund General Project\u003c/p\u003e \u003cp\u003eResearch on High-Quality Construction of Public Fitness Service System Empowered by Digital Intelligence (L25BTY004).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWenhe Zhu was responsible for the data analysis and writing of the original draft preparation. Yong Jiang was responsible for data analysis and methodology. Wenhe Zhu was responsible for the conceptualization, writing, reviewing and editing the draft. Yong Jiang was responsible for the conceptualization, writing, reviewing and editing the draft, and funding acquisition. All authors have read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eTo obtain the raw data used in this study, please contact the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhang Q L, Li Z, Jiang L, et al. Effects of an Exercise Intervention Based on mHealth Technology on the Physical Health of Male University Students With Overweight and Obesity: Randomized Controlled Trial[J]. J Med Internet Res, 2025, 27: e69451.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu C, Zeng Z, Xue A, et al. 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J Intell, 2024, 12(10):94.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"University Physical Education Environment, Sports Participation Behavior, Developing self-efficacy, Exercise Motivation","lastPublishedDoi":"10.21203/rs.3.rs-9082915/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9082915/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo explore the influence mechanism of University Physical Education Environment on college students' Sports Participation Behavior and to examine the mediating roles of Developing Self-Efficacy and Exercise Motivation, this study constructs a chained mediation model based on social cognitive theory. A combination of stratified cluster sampling and convenience sampling was employed to conduct a questionnaire survey among 700 college students from multiple universities in eastern China. Measurements were conducted using the University Physical Education Environment Scale, Developing self-efficacy Scale, Exercise Motivation Scale, and Sports Participation Behavior Scale. SPSS and the PROCESS macro (Model 6) were utilized for correlation analysis, regression analysis, and Bootstrap mediation effect testing. Results indicate that the University Physical Education Environment significantly and positively correlates with Developing Self-Efficacy, Exercise Motivation, and Sports Participation Behavior. It significantly and positively predicts students' Sports Participation Behavior. Developing Self-Efficacy and Exercise Motivation both significantly mediate the relationship between the University Physical Education Environment and Sports Participation Behavior. Furthermore, the University Physical Education Environment indirectly influences Sports Participation Behavior through the chained pathway \u0026ldquo;Exercise Motivation \u0026rarr; Developing Self-Efficacy,\u0026rdquo; with the chain intermediation effect being significant. The study demonstrates that the University Physical Education Environment not only directly promotes students' Sports Participation Behavior but also exerts indirect effects by enhancing individual Developing Self-Efficacy and stimulating Exercise Motivation. These findings deepen the psychological mechanism explanation of how the University Physical Education Environment influences students' Sports Participation Behavior, providing theoretical foundations and practical insights for optimizing Physical Education Environment provision and enhancing students' Sports Participation levels in higher education institutions.\u003c/p\u003e","manuscriptTitle":"The Influence of University Physical Education Environments on College Students' Sports Participation Behavior: The Chain Intermediation Effect of Developing Self-Efficacy and Exercise Motivation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-10 17:46:31","doi":"10.21203/rs.3.rs-9082915/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-23T12:28:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T15:17:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-17T08:58:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"67310714164783423620959420793007328855","date":"2026-04-15T03:23:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78478869283977237742863159107575246955","date":"2026-04-14T04:50:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"300913454832467817753757301806218914730","date":"2026-04-13T13:48:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-06T13:19:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92778096084117262813075626929669662427","date":"2026-04-06T11:14:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-06T11:02:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-12T03:28:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-11T09:44:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-11T09:43:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2026-03-10T10:52:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6aae0e2a-ba90-4e88-bece-c27ac749939b","owner":[],"postedDate":"April 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-10T17:46:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-10 17:46:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9082915","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9082915","identity":"rs-9082915","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}