Abstract
Objective
Guided by the Theory of Planned Behavior (TPB), this study investigates how perceived environment and social support are associated with the intention to sustain nighttime physical activity, with attitude tested as a mediating variable.
Methods
Employing a convenience sampling approach, the study conducted a questionnaire survey across various provinces in China, including Sichuan, Guangdong, Hainan, Jiangxi, Beijing, Shanghai, and Heilongjiang, in December 2024.Out of 4532 distributed questionnaires, 4032 were deemed valid after excluding the ineligible ones, achieving an effective response rate of 88.97%. The survey instrument encompassed six key variables: environmental perception, social support, subjective norms, perceived behavioral control, attitude, and sustained participation intention, all evaluated on a 5-point Likert scale. Data analysis was performed utilizing SPSS 26.0 and AMOS 24.0 software.
Results
The study indicated that both environmental perception and social support were significantly associated with attitude, with coefficients of 0.367 and 0.347 (both p<0.001), respectively. Attitude was significantly associated with sustained participation intention (β=0.196,p<0.001). Direct associations with sustained participation intention were observed for both environmental perception (β=0.164, p<0.001) and social support (β=0.222, p<0.001). The mediation-consistent indirect association via attitude was substantial, accounting for 27.211% of the total association between environmental perception and sustained participation intention, and 28.567% between social support and sustained participation intention.
Conclusion
The study demonstrates that perceived environment and social support are both significantly associated with individuals’ intention to engage in nocturnal physical activity, with attitude serving as a statistical mediator. By incorporating a social-ecological perspective that addresses environment-specific and social challenges unique to nighttime activities, our research extends the application of the Theory of Planned Behavior (TPB) to nighttime contexts. These findings provide an associative, theory-informed foundation for optimizing strategies to promote nocturnal physical activity, but do not establish causality.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-025-25512-z.
Keywords: Environmental perception, Social support, Subjective norms, Sustained participation intention, Nighttime physical activity
Introduction
With socioeconomic development and rising living standards, increased public focus on health and well-being has elevated physical activity to widespread recognition as a crucial component of a healthy lifestyle. This trend is further amplified by nationwide health promotion initiatives [1]. However, individuals in today’s demanding society frequently encounter significant challenges in balancing work, study, daily commitments, and regular exercise. Against this backdrop, nocturnal physical activity has emerged as a flexible and accessible alternative, typically conducted in public spaces such as urban parks and squares between 6:00 PM and bedtime [2–5]. In this study, “nighttime” is operationally defined as the period from 18:00 to 24:00 h. To account for seasonal variation in daylight, this definition applies year-round, with winter months (approximately November-February) characterized by earlier sunset times, which were emphasized in item instructions to ensure contextual alignment.
Current research on nocturnal physical activity primarily focuses on three domains: participation patterns [6, 7], participant demographics [8, 9], and policy/management strategies [10–12]. Nevertheless, a significant research gap persists regarding the underlying psychological and social mechanisms driving individuals’ intention to engage in nighttime exercise. Compared to daytime activities, nocturnal physical activity presents unique challenges including safety concerns, lighting conditions, time constraints, and availability of social support [8]. These factors may substantially influence individuals’ perceived behavioral control and decision-making processes, yet remain underexplored in prior research [13].
This study addresses this gap by extending the Theory of Planned Behavior (TPB) to examine the distinctive environmental and psychological factors influencing participation in nocturnal physical activity. Although TPB has been extensively applied to general exercise behavior, its utilization in the specific context of nighttime exercise remains limited [14]. This study is constructed within an integrated theoretical framework. A socio-ecological perspective provides the macro-level foundation, highlighting the significance of lighting, safety, and companionship in nighttime sports participation. The Theory of Planned Behavior (TPB) constitutes the central component, clarifying the proximal psychological variables and their path relationships. A hierarchical theoretical structure reinforces the coherence and scientific validity of the study, thereby improving the accessibility, safety, and scalability of nighttime physical activity initiatives. Understanding these mechanisms is essential for developing effective public health initiatives and designing tailored interventions to encourage broader participation in nighttime physical activity.
The theory of planned behavior and its application in physical activity
The Theory of Planned Behavior (TPB), proposed by Ajzen [11], is a well-established psychological framework for predicting and explaining human behavior. The theory posits that an individual’s behavioral intention is determined by three fundamental psychological factors:
Attitude (ATT): Refers to an individual’s positive or negative evaluation of performing a specific behavior, which significantly influences their motivation to act [15].
Subjective Norms (SN): Represent the perceived social pressure from significant others, influencing whether an individual feels encouraged or discouraged to engage in the behavior [16].
Perceived Behavioral Control (PBC): Encompasses an individual’s perception of the ease or difficulty of performing the behavior, shaped by both internal factors (e.g., self-efficacy) and external constraints (e.g., environmental factors) [17].
Although TPB has been extensively validated in physical activity research [18, 19], its application to the context of nocturnal physical activity remains limited. Nighttime exercise presents unique environmental and social challenges, such as safety concerns, lighting conditions, and the availability of social support. These factors may significantly impact individuals’ PBC and ATT.
To address these limitations, recent research has proposed extending the TPB framework by integrating Environmental Perceptions (EP) and Social Support (SS) as additional external factors influencing ATT, PBC, and ultimately, Intention Toward Persistence (ITP) [20, 21]. These extensions are particularly critical for nocturnal physical activity, as the conventional TPB model does not explicitly account for environmental and social influences, which play crucial roles in shaping nighttime exercise behavior [22].
Building upon these developments, this study further extends the TPB framework to better accommodate the unique contextual challenges of nocturnal physical activity, including lighting conditions, safety concerns, and time constraints. To address the aforementioned gaps, this study situates its theoretical framework by identifying Environmental Perception (EP) and Social Support (SS) as contextual antecedents that influence Attitude (ATT) and Perceived Behavioral Control (PBC), which in turn are associated with behavioral intention under these specific conditions [23]. The primary focus lies in examining the theoretically salient pathway of attitude within the nighttime context, while also offering a critical analysis of other potential pathways that may exist under nocturnal environmental conditions. This extended framework not only deepens the theoretical understanding of participation in nocturnal physical activity but also offers practical implications for designing more effective intervention strategies.
The impact of environmental perception on nighttime physical activity
Environmental perception (EP) is defined as an individual’s cognitive and affective appraisal of surrounding physical and social conditions, which significantly influences both capability and motivation to engage in physical activity [24]. This multidimensional construct encompasses critical factors including safety, accessibility, infrastructure quality, aesthetic appeal, and social atmosphere [25].
When integrated into the Theory of Planned Behavior (TPB), EP exerts a dual influence on perceived behavioral control (PBC) and attitude (ATT), thereby affecting intention toward persistence (ITP) [26]. The EP-PBC relationship is particularly salient, as well-maintained, accessible, and aesthetically pleasing nighttime exercise environments enhance individuals’ confidence in participation, thereby strengthening PBC [27, 28]. Similarly, EP shapes ATT: those perceiving nocturnal exercise settings as safe, attractive, and socially engaging develop more favorable participation attitudes, consequently reinforcing ITP [29].
Empirical studies consistently substantiate EP’s pivotal role in shaping physical activity behaviors. Research indicates that positive environmental evaluations (e.g., well-lit paths, properly maintained facilities, supportive social atmosphere) significantly increase participation rates [30]. Within the TPB framework, EP serves as a critical external factor influencing both PBC and ATT—key predictors of behavioral intention [11]. PBC reflects individuals’ perceived ease or difficulty of performing a behavior, influenced by internal factors (e.g., self-efficacy) and external constraints (e.g., environmental barriers) [15]. A well-designed nocturnal exercise environment substantially bolsters confidence in participation capability, thereby enhancing PBC.
Attitude (ATT), denoting an individual’s overall positive or negative evaluation of a behavior, constitutes another fundamental determinant of behavioral intention [11]. When individuals perceive nighttime exercise environments as safe, appealing, and socially conducive, they develop more positive participation attitudes, further strengthening nocturnal physical activity intentions. Multiple empirical studies demonstrate that favorable environmental appraisals (e.g., adequate lighting, well-maintained facilities, supportive ambiance) significantly elevate participation levels [31–33]. Nevertheless, most existing research focuses on daytime activities, with insufficient investigation into night-specific environmental factors (e.g., artificial illumination, safety provisions, social engagement opportunities).
Moreover, attitude functions as a psychological mediator between environmental perception and behavioral intention, highlighting EP’s indirect yet crucial role in shaping physical activity behaviors. Individuals with positive environmental evaluations demonstrate not only higher participation rates but also stronger intentions toward sustained engagement [12, 14].
The role of social support in facilitating nighttime physical activity
Social support (SS), a key determinant of physical activity participation, encompasses informational, emotional, and instrumental assistance provided by social networks (e.g., family, friends, peers) [34]. Within the TPB framework, SS enhances both attitude (ATT) and perceived behavioral control (PBC), thereby reinforcing intention toward persistence (ITP) [35].
The SS-ATT relationship manifests through positive influences from encouragement and companionship, which foster favorable perceptions of nocturnal physical activity’s benefits and feasibility, consequently improving attitudes [36]. Concurrently, SS strengthens PBC by providing actionable resources (both practical and emotional) that help overcome psychological barriers and build confidence in maintaining exercise routines [37]. Empirical evidence consistently associates higher SS levels with increased physical activity participation [38].
Numerous studies confirm a positive correlation between perceived social support and physical activity engagement [19–21]. For instance, research among university students indicates that peer and instructor support significantly predicts exercise frequency [40]. While SS’s positive impact is well-established, its specific mechanisms influencing participation intention warrant further exploration. Within TPB, SS enhances motivation and confidence, strengthening exercise attitudes and increasing behavioral likelihood [37].
Encouragement and companionship from family, friends, or peers cultivate more positive perceptions of nighttime physical activity’s value and feasibility, thereby intensifying participation intentions [41]. Additionally, SS alleviates safety concerns associated with nocturnal exercise, as supportive companionship enhances perceived security [42]. Exercise partners also facilitate time management, enabling better integration of nighttime workouts into daily routines [43].
In summary, social support not only facilitates participation but also critically reinforces exercise-related attitudes and PBC. Individuals receiving consistent encouragement and companionship are more likely to develop sustained commitment to nocturnal physical activity [44].
The influence of subjective norms and perceived behavioral control on participation intention
Subjective norms (SN) and perceived behavioral control (PBC) constitute core TPB constructs significantly influencing intention toward persistence (ITP) in nighttime physical activity. SN refers to perceived social pressure from significant others (e.g., family, friends, society) affecting behavioral decisions [45]. PBC reflects individuals’ subjective assessment of behavioral ease/difficulty, shaped by internal factors (e.g., self-efficacy) and external constraints (e.g., environmental conditions) [11].
Within TPB, SN and PBC play pivotal roles in determining ITP for nocturnal physical activity [45]. The SN-ITP linkage emerges through social encouragement and normative support strengthening behavioral commitment. Individuals perceiving greater social endorsement for nighttime exercise develop stronger participation intentions [46]. Empirical studies consistently demonstrate social norms’ significant impact on exercise behaviors, particularly in structured group or community activities.
Similarly, PBC significantly predicts ITP. High perceived control—manifested through access to safe spaces, confidence in overcoming barriers, and time-management competence—correlates strongly with sustained nocturnal physical activity [47]. Diverse population studies confirm PBC as a robust predictor of exercise maintenance, underscoring its importance for long-term engagement [11].
Empirical evidence supports the interactive effects of SN and PBC. Multiple studies confirm these constructs’ significant predictive power in shaping participation intentions [26–48]. Specifically, individuals perceiving strong support from significant others coupled with confidence in behavioral control demonstrate the highest likelihood of forming firm participation intentions.
Furthermore, SN and PBC influences are often mediated by social support. Encouragement from social networks intensifies perceived social pressure, thereby strengthening SN. A supportive environment fosters collective exercise culture, reinforcing perceptions of nocturnal activity as socially desirable. This social validation enhances individuals’ sense of obligation or motivation to conform, elevating participation intentions.
Concurrently, PBC is dually influenced by social support and environmental perception. Well-equipped, secure nighttime settings enhance confidence in participation capability, thereby strengthening PBC. For instance, illuminated pathways, safe facilities, and supportive exercise partners significantly reduce perceived barriers, boost self-efficacy, and ultimately promote stronger participation intentions.
Research hypotheses
This study integrates environmental perception (EP) and social support (SS) as contextual factors into the Theory of Planned Behavior (TPB) to investigate the determinants of intention to persist (ITP) in nighttime physical activity. According to TPB, behavioral intention is primarily influenced by three core constructs: attitude (ATT), subjective norm (SN), and perceived behavioral control (PBC), which collectively predict actual behavior [11]. Building upon this foundation, the present study incorporates EP and SS as additional factors, examining how they influence ATT and PBC, and thereby further affect ITP. To ensure the context-specific nature of nighttime participation, the scale instructions explicitly specify the temporal conditions of the activity—including lighting, safety, companionship, and time constraints. Furthermore, Environmental Perception (EP) and Social Support (SS) are framed to capture explicit situational assessments within the nocturnal setting, rather than general determinants of physical activity (PA). Research hypotheses among the various variables, specifically as shown in Fig. 1.
Fig. 1.
Research Model Hypotheses. Environmental Perception EP Social Support SS, Subjective Norms SN, Perceived Behavioral Control PBC, Attitude ATT, and Sustained Participation Intention ITP. According to the integrative extension of the Theory of Planned Behavior (TPB), contextual variables may also be associated with the Intention to Persist (ITP) through other proximal pathways (such as Perceived Behavioral Control, PBC) and may partially exert direct effects
Based on this theoretical framework, the following hypotheses are proposed:
H1: Environmental perception (EP) positively predicts individuals’ attitude (ATT) toward nighttime physical activity.
H2: Social support (SS) positively predicts individuals’ attitude (ATT) toward nighttime physical activity.
H3: Individuals’ attitude (ATT) toward nighttime physical activity positively predicts their intention to persist (ITP).
H4: Environmental perception (EP) positively predicts individuals’ intention to persist (ITP) in nighttime physical activity.
H5: Social support (SS) positively predicts individuals’ intention to persist (ITP) in nighttime physical activity.
H6: Subjective norm (SN) positively predicts individuals’ intention to persist (ITP) in nighttime physical activity.
H7: Perceived behavioral control (PBC) positively predicts individuals’ intention to persist (ITP) in nighttime physical activity.
H8: Attitude (ATT) serves as a significant and partial mediator between environmental perception (EP) and Intention to Persist (ITP).
H9: Attitude (ATT) serves as a significant and partial mediator between social support (SS) and intention to persist (ITP).
Methods
Participants
This study employed a convenience sampling method for data collection. The online survey was administered via Wenjuanxing (a popular online survey platform in China similar to Qualtrics) in early December 2024, targeting participants from seven provinces: Sichuan, Guangdong, Hainan, Jiangxi, Beijing, and Heilongjiang. Given that regional variations such as climatic conditions and cultural backgrounds may influence motivations for nighttime physical activity, province was incorporated as a contextual factor in the study design. Robustness checks were conducted during statistical analysis to assess overall regional differences.
To ensure data integrity, the questionnaire incorporated attention-check items. Responses with implausibly short completion times were excluded during data processing. From the initial pool of 4,532 collected questionnaires, 4,032 valid responses were retained after excluding those with incorrect answers on attention-check items or exhibiting abnormal response patterns, yielding a valid response rate of 88.97%. Exclusions were based on: duplicate submissions (identified via platform IDs and metadata); failed attention checks or implausibly short completion times; incomplete data on key variables (EP, SS, SN, PBC, ATT, ITP); or self-reported inability to engage in physical activity due to acute medical restrictions. Eligible participants were required to meet all the following inclusion criteria: (1) age 18 years or older; (2) current residence in one of the seven target provinces; (3) reported participation in physical activity at least once in the past three months, or an intention to engage in nighttime physical activity (ensuring relevance to the study context); and (4) ability to read Chinese and provide electronic informed consent.
The final sample comprised 1,987 male participants (49.28%) and 2,045 female participants (50.72%). Age distribution was as follows: 566 participants aged 20–29 (14.04%), 1,049 aged 30–39 (26.02%), 1,404 aged 40–49 (34.82%), and 1,013 aged 50 or above (25.12%).
Educational attainment distribution was: Associate degree or below: 3,129 participants (77.60%), Bachelor’s degree: 378 participants (9.38%), Master’s degree or above: 525 participants (13.02%). Occupational distribution was: Teachers: 399 (9.90%), Corporate employees: 643 (15.95%), Freelancers: 489 (12.13%), Civil servants: 1,347 (33.41%), Healthcare workers: 1,154 (28.62%).
The study strictly adhered to academic ethics guidelines. The research protocol received approval from the Academic Ethics Committee of Leshan Normal University (Approval No.: LSNU:1225-22−12 RO). All participants provided informed consent. All procedures were conducted in strict accordance with relevant guidelines and regulations.
Research tools
The questionnaire comprised three sections. Section 1 collected participants’ demographic information, including gender, age, education level, and occupation. Section 2 measured six key variables related to nighttime physical activity participation: Environmental Perception (EP), Social Support (SS), Subjective Norm (SN), Perceived Behavioral Control (PBC), Attitude (ATT), and Intention to Persist (ITP).
Environmental Perception (EP) refers to individuals’ cognitive and affective evaluations of the nighttime exercise environment, encompassing safety, accessibility, infrastructure quality, aesthetics, and overall atmosphere. This study utilized a 3-item scale adapted from Roux et al. (2021) [49], measured on a 5-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree). Environmental Perception (EP) was analyzed as a reflective, unidimensional construct. The scale items were contextualized with information specific to nighttime physical activity participation. Expert evaluations were conducted to ensure the cultural appropriateness of the questionnaire, which demonstrated good reliability and validity. The scale items were contextualized with information specific to nighttime physical activity participation. Consistent with our operational definition, item stems specified “between 18:00 and 24:00”, with winter (Nov–Feb) earlier sunset noted to facilitate scenario consistency.
Social Support (SS) encompasses informational, emotional, and instrumental support provided by family, friends, or peers that facilitates participation in nighttime physical activity. This study employed a 3-item scale adapted from Martin et al. (2008) [15], rated on a 5-point Likert scale. The scales, including that for Social Support (SS), were rigorously evaluated. The results indicated good overall reliability and discriminant validity.
Subjective Norm (SN) reflects the perceived social pressure from significant others that may influence an individual’s decision to engage in nighttime physical activity. This study used a 3-item scale adapted from Hagger et al. (2002) [50], measured on a 5-point Likert scale.
Perceived Behavioral Control (PBC) indicates an individual’s confidence in their ability to participate in nighttime physical activity despite external constraints. This study employed a 3-item scale adapted from Hagger et al. (2002) [50], rated on a 5-point Likert scale.
Attitude (ATT) represents an individual’s overall positive or negative evaluation of nighttime physical activity. This study utilized a 3-item scale adapted from Hagger et al. (2002) [50], with higher scores indicating a more favorable evaluation.
Intention to Persist (ITP) measures an individual’s willingness to continue participating in nighttime physical activity in the future. A 3-item scale adapted from Juliana et al. (2019) [51] was used, rated on a 5-point Likert scale.
Section 3 included additional items related to participants’ exercise habits and motivations. Based on the information above, the research team refined the questionnaire content and developed the final scale for measuring Intention to Persist in Nighttime Physical Activity.
Following questionnaire compilation, experts in the field of national fitness were invited to assess its validity, focusing on structural validity and content validity to ensure its effectiveness and reliability. After the initial assessment, suggestions for improvement were provided by the experts, and the research team made adjustments accordingly. To further validate the questionnaire’s validity, a second round of expert assessment was conducted two weeks later to confirm the completeness and accuracy of the information. Additionally, test-retest reliability was calculated using the retest method, yielding a coefficient of 0.85, indicating good temporal stability of the questionnaire. To mitigate measurement bias, scale items were constructed with both positively and negatively worded statements. During the formal survey, items were presented in a randomized order within each module to reduce response bias. The scales underwent a standardized translation-back-translation procedure and were reviewed by bilingual experts.
To ensure reproducibility, this study provides the complete wording for all constructs in both English and Chinese, including the response anchors and notation for reverse-scored items. All items were contextualized for nighttime conditions (18:00–24:00), with specific references to lighting, safety, companionship, and time constraints. Responses were captured on a 5-point Likert scale, anchored at 1 = “Strongly Disagree” to 5 = “Strongly Agree”. Items marked with [R] were reverse-scored during data processing.
Data analysis
Preliminary data processing and measurement model evaluation
The initial stage of data analysis involved preprocessing using SPSS 26.0. This included handling missing values, detecting outliers, and assessing data normality. Missing values constituting less than 5% of responses were addressed using mean imputation, while cases with excessive missing data were excluded. Sensitivity analysis using the Full Information Maximum Likelihood (FIML) method yielded consistent results. Outliers were identified using standardized z-scores (|z| >3.29), and extreme values were either winsorized or deleted. Prior to calculating mean scores for each construct, all items marked with [R] were reverse-coded (i.e., scores were transformed from 1 to 5 to 5 − 1). To ensure transparency, all reverse-scored items are explicitly identified as [R] in the item list. The absence of this notation for a construct indicates that it contained no reverse-scored items.
Following data preprocessing, Confirmatory Factor Analysis (CFA) was conducted using AMOS 24.0 to evaluate the validity and reliability of the measurement model. CFA examined factor loadings, Composite Reliability (CR), and Average Variance Extracted (AVE) to verify construct validity. Model fit was assessed using multiple indices: χ²/df (acceptable fit < 3), RMSEA (acceptable fit < 0.08), CFI (acceptable fit > 0.90), TLI (acceptable fit > 0.90), and SRMR (acceptable fit < 0.08). Furthermore, Pearson correlation analysis was employed to explore relationships among latent variables, and Variance Inflation Factor (VIF) analysis was conducted to test for multicollinearity. Results indicated all VIF values were below 10, confirming the absence of severe multicollinearity issues. To account for potential regional heterogeneity, province-level fixed effects were incorporated into the research model to control for unobserved geographic variations and enhance the robustness of the estimates.
Structural model testing and mediation analysis
After validating the measurement model, Structural Equation Modeling (SEM) was performed using Maximum Likelihood Estimation (MLE) in AMOS 24.0 to test the hypothesized relationships among variables. The overall model fit was adjusted based on Modification Indices (MI), ensuring all modifications were theoretically justified. This study compared several theoretically plausible competing models, including a fully mediated model without direct paths from Environmental Perception (EP) and Social Support (SS) to Intention to Persist (ITP), as well as a model incorporating Perceived Behavioral Control (PBC) as a parallel mediator. The final model was refined based on these comparisons. To assess direct, indirect, and total effects, bootstrapping with 1000 resamples was employed, calculating bias-corrected 95% confidence intervals to determine statistical significance. The study did not account for unmeasured individual differences, such as socioeconomic status, health status, prior physical activity, time constraints, or family responsibilities. These factors may be considered in future extensions of the model to enhance its comprehensiveness and explanatory power.
To further investigate the mediating role of Attitude (ATT) in the relationships between Environmental Perception (EP), Social Support (SS), and Intention to Persist (ITP), mediation analysis was conducted using the PROCESS macro (Model 4) in SPSS. This study, grounded in an integrated theoretical model, emphasizes the primary mediating role of attitude and seeks to elucidate potential underlying pathways, thereby examining its mediating effect within the hypothesized framework. Bootstrapping with 5000 resamples generated bias-corrected confidence intervals, providing robust estimates of the mediation effects. A systematic comparison of key coefficients between early and late respondents showed no systematic differences. Mediation effects were considered statistically significant if the confidence intervals did not include zero.
Common method bias test
Since all variable data in this study were derived from respondents’ self-reports, there was a potential for common method bias. To address this, the study employed Harman’s single-factor test [52] for examination. The results indicated that the variance explained by a single factor was 23.27%, which is below the critical value of 40%; the fit indices of the single-factor model were significantly lower than those of the theoretical model. Therefore, the impact of common method bias on the results of this study is within an acceptable range. In addition to Harman’s single-factor test, this study employed procedural remedies, including the use of both positively and negatively worded items. Comparative confirmatory factor analysis (CFA) demonstrated that the single-factor model fit significantly worse than the hypothesized measurement model. Furthermore, a common latent factor was incorporated in a sensitivity CFA, which showed that the key constructs remained stable, indicating that common method variance had limited influence on the results.
Multicollinearity test
To assess multicollinearity at the item level, this study calculated the variance inflation factor (VIF) for each measurement item, rather than solely analyzing at the construct level [53]. As shown in Table 1, all measurement items exhibited VIF values ranging from 1.215 to 2.103—significantly below the commonly accepted threshold of 10. This result indicates the absence of severe multicollinearity issues within the dataset. Consequently, each measurement item can be confirmed to contribute uniquely to its respective construct without being substantially influenced by excessive collinearity with other items.
Table 1.
Variance inflation factor (VIF) values
| Variable | VIF Value |
|---|---|
| EP-A1 | 1.432 |
| EP-A2 | 1.519 |
| EP-A3 | 1.487 |
| SS-B1 | 1.689 |
| SS-B2 | 1.731 |
| SS-B3 | 1.754 |
| SN-C1 | 1.812 |
| SN-C2 | 1.788 |
| SN-C3 | 1.801 |
| PBC-D1 | 1.650 |
| PBC-D2 | 1.702 |
| PBC-D3 | 1.745 |
| ATT-F1 | 1.907 |
| ATT-F2 | 2.103 |
| ATT-F3 | 1.982 |
| ITP-G1 | 1.823 |
| ITP-G2 | 1.856 |
| ITP-G3 | 1.791 |
Reliability and validity of the scales
As shown in Table 2, this study used Composite Reliability (CR) and Average Variance Extracted (AVE) to assess the reliability and convergent validity of the scales. The results indicate that the CR values for the latent variables of Environmental Perception, Social Support, Subjective Norms, Perceived Behavioral Control, Attitude, and Sustained Participation Intention are 0.836, 0.853, 0.833, 0.818, 0.811, and 0.796, respectively, all of which are greater than the critical value of 0.7, suggesting that the scales have good internal consistency reliability. Furthermore, the AVE values for each latent variable are 0.630, 0.659, 0.625, 0.604, 0.590, and 0.566, respectively, all of which are greater than the critical value of 0.5, indicating that the scales have satisfactory convergent validity.
Table 2.
Reliability and validity testing of the scales
| Variable | Items | Factor Loadings | Cronbach’s | CR | AVE |
|---|---|---|---|---|---|
| EP | A1 | 0.814 | 0.834 | 0.836 | 0.630 |
| A2 | 0.699 | ||||
| A3 | 0.768 | ||||
| SS | B1 | 0.821 | 0.853 | 0.853 | 0.659 |
| B2 | 0.794 | ||||
| B3 | 0.772 | ||||
| SN | C1 | 0.786 | 0.832 | 0.833 | 0.625 |
| C2 | 0.781 | ||||
| C3 | 0.752 | ||||
| PBC | D1 | 0.741 | 0.807 | 0.818 | 0.604 |
| D2 | 0.803 | ||||
| D3 | 0.713 | ||||
| ATT | F1 | 0.835 | 0.807 | 0.811 | 0.590 |
| F2 | 0.794 | ||||
| F3 | 0.690 | ||||
| ITP | G1 | 0.759 | 0.795 | 0.796 | 0.566 |
| G2 | 0.740 | ||||
| G3 | 0.693 |
Environmental Perception EP (A1-A3 are the observed items), Social Support SS (B1-B3 are the observed items), Subjective Norms SN (C1-C3 are the observed items), Perceived Behavioral Control PBC (D1-D3 are the observed items), Attitude ATT (F1-F3 are the observed items), and Sustained Participation Intention ITP (G1-G3 are the observed items), the same below
Correlation matrix
As shown in Table 3, this study calculated the Pearson correlation coefficients between each pair of latent variables and placed the square roots of AVE values on the diagonal. The results revealed that all latent variables were significantly positively correlated (p < 0.01), with correlation coefficients ranging from 0.434 to 0.566, indicating a moderate degree of correlation between Environmental Perception, Social Support, Subjective Norms, Perceived Behavioral Control, Attitude, and Sustained Participation Intention.
Table 3.
Pearson correlations and square roots of AVE
| EP | SS | SN | PBC | ATT | ITP | |
|---|---|---|---|---|---|---|
| EP | 0.794 | |||||
| SS | 0.508** | 0.812 | ||||
| SN | 0.566** | 0.488** | 0.791 | |||
| PBC | 0.564** | 0.494** | 0.499** | 0.777 | ||
| ATT | 0.458** | 0.465** | 0.479** | 0.434** | 0.768 | |
| ITP | 0.553** | 0.543** | 0.527** | 0.562** | 0.51** | 0.752 |
By further comparing the correlation coefficients with the square roots of AVE values on the diagonal, it was found that the square root of AVE (the bolded numbers in the table) for each latent variable was greater than its correlation coefficients with other latent variables. For instance, the square root of AVE for Environmental Perception is 0.794, which is greater than its correlation coefficients with Social Support (r = 0.508), Subjective Norms (r = 0.566), Perceived Behavioral Control (r = 0.564), Attitude (r = 0.458), and Sustained Participation Intention (r = 0.553). This result indicates that the latent variables have good discriminant validity, meaning that the correlations between different latent variables are lower than the correlations between each latent variable and its corresponding observed variables. The variance inflation factor (VIF) values for all item-level variables ranged from 1.215 to 2.103, indicating no evidence of multicollinearity among the study variables.
Path coefficient test
As depicted in Fig. 2, this study employed structural equation modeling (SEM) to conduct a path analysis of the relationships between the latent variables, which illustrates the model of sustained participation intention in nighttime physical activity based on the Theory of Planned Behavior (TPB). The model demonstrated a good fit to the data: χ²/df = 20.942, CFI = 0.938, TLI = 0.922, RMSEA = 0.070 (90% CI: 0.066–0.074), SRMR = 0.054. These indices collectively indicate that the model is acceptable for proceeding with subsequent hypothesis testing. The competing models—namely, the fully mediated model and the parallel mediation model incorporating Perceived Behavioral Control (PBC)—exhibited poorer model fit (detailed results available upon request), thereby supporting the superiority of the current partial mediation structure. Although all path coefficients were statistically significant, the standardized estimates ranged from 0.143 to 0.367, indicating small to moderate effect sizes with varying magnitude rather than consistently inflated associations. Due to the use of a non-probability sampling method, the path coefficients in this study should be interpreted as measures of association rather than causal effects.
Fig. 2.
Model of Sustained Participation Intention in Nighttime Physical Activity Based on TPB
Table 4 presents the results of the structural and measurement model analyses. In the structural model, the path coefficients indicate that Environmental Perception (EP) and Social Support (SS) have significant positive effects on Attitude (ATT), with standardized coefficients of 0.367 (p < 0.001) and 0.347 (p < 0.001), respectively. These results support hypotheses H1 and H2. The results remained robust across robustness checks that included province-level fixed effects and a North-South regional subgroup analysis. The direction and statistical significance of the key pathways were consistent in all specifications. Similarly, Attitude (ATT) significantly predicts Continued Participation Intention (ITP), with a coefficient of 0.196 (p < 0.001), thus validating hypothesis H3. Furthermore, Environmental Perception (EP) and Social Support (SS) also exert significant direct effects on ITP, with coefficients of 0.164 (p < 0.001) and 0.222 (p < 0.001), respectively, supporting hypotheses H4 and H5. Concurrently, Subjective Norm (SN) and Perceived Behavioral Control (PBC) also significantly predict ITP, with coefficients of 0.143 (p < 0.001) and 0.263 (p < 0.001), validating hypotheses H6 and H7.
Table 4.
Path coefficient test
| Path | Unstandardized Coefficients | S.E. | C.R. | P | Standardized Coefficients | Test Results | |||
|---|---|---|---|---|---|---|---|---|---|
| Structural Model | |||||||||
| ATT | <--- | EP | 0.306 | 0.019 | 16.12 | *** | 0.367 | Supported | |
| ATT | <--- | SS | 0.318 | 0.021 | 15.268 | *** | 0.347 | Supported | |
| ITP | <--- | ATT | 0.208 | 0.021 | 9.807 | *** | 0.196 | Supported | |
| ITP | <--- | EP | 0.145 | 0.024 | 6.064 | *** | 0.164 | Supported | |
| ITP | <--- | SS | 0.217 | 0.022 | 10.05 | *** | 0.222 | Supported | |
| ITP | <--- | SN | 0.132 | 0.022 | 6.028 | *** | 0.143 | Supported | |
| ITP | <--- | PBC | 0.305 | 0.027 | 11.352 | *** | 0.263 | Supported | |
| Measurement Model | |||||||||
| A1 | <--- | EP | 1 | 0.826 | Supported | ||||
| A2 | <--- | 0.875 | 0.018 | 49.679 | *** | 0.745 | |||
| A3 | <--- | 0.97 | 0.018 | 54.257 | *** | 0.805 | |||
| B1 | <--- | SS | 1 | 0.782 | Supported | ||||
| B2 | <--- | 1.086 | 0.020 | 53.138 | *** | 0.829 | |||
| B3 | <--- | 1.072 | 0.020 | 52.878 | *** | 0.825 | |||
| C1 | <--- | SN | 1 | 0.827 | Supported | ||||
| C2 | <--- | 1.035 | 0.019 | 53.917 | *** | 0.815 | |||
| C3 | <--- | 0.875 | 0.018 | 48.043 | *** | 0.731 | |||
| D1 | <--- | PBC | 1 | 0.622 | Supported | ||||
| D2 | <--- | 1.402 | 0.034 | 40.798 | *** | 0.862 | |||
| D3 | <--- | 1.311 | 0.033 | 40.191 | *** | 0.830 | |||
| F3 | <--- | ATT | 1 | 0.706 | Supported | ||||
| F2 | <--- | 1.138 | 0.026 | 43.624 | *** | 0.828 | |||
| F1 | <--- | 1.054 | 0.025 | 42.045 | *** | 0.769 | |||
| G3 | <--- | ITP | 1 | 0.784 | Supported | ||||
| G2 | <--- | 0.923 | 0.021 | 43.283 | *** | 0.708 | |||
| G1 | <--- | 1.034 | 0.022 | 46.385 | *** | 0.759 | |||
In the measurement model, the factor loadings linking the latent variables to their respective observed indicators range from 0.622 to 0.862, and all are statistically significant at the p < 0.001 level. The measurement model demonstrated good fit, with all indices falling within acceptable thresholds recommended in the literature. These results confirm the reliability and construct validity of the measurement model, providing a solid foundation for the subsequent structural model analysis. For example, the factor loadings for Environmental Perception (EP; items A1-A3: 0.745–0.826) and Social Support (SS; items B1-B3: 0.782–0.829) demonstrate strong associations between the latent variables and their respective indicators. This indicates that the measurement model effectively captures the target constructs, thereby validating the appropriateness of the operationalization of the latent variables.
After verifying the direct effects of environmental perception and social support on residents’ sustained participation intention in nighttime physical activities, this study further explored the mediating role of attitude. According to the mediation effect test results in Table 5, the mediation effect value of environmental perception on sustained participation intention through attitude is 0.144, with a 95% confidence interval of [0.131, 0.176], which does not include 0, indicating that attitude plays a significant mediating role between environmental perception and sustained participation intention, supporting hypothesis H8. The mediation effect value of social support on sustained participation intention through attitude is 0.149, with a 95% confidence interval of [0.132, 0.177], also indicating that attitude plays a significant mediating role between social support and sustained participation intention, supporting hypothesis H9.
Table 5.
Results of mediation effect test
| Item | c Total Effect | a*b Indirect Effect Value | a*b (95% Boot CI) | c’ Direct Effect | Effect Proportion | Test Results |
|---|---|---|---|---|---|---|
| EP = > ATT = > ITP | 0.531** | 0.144 | 0.131 ~ 0.176 | 0.387** | 27.211% | Supported |
| SS = > ATT = > ITP | 0.521** | 0.149 | 0.132 ~ 0.177 | 0.373** | 28.567% | Supported |
Further analysis reveals that the total effect of environmental perception on sustained participation intention is 0.531 (p < 0.01), with the mediating effect through attitude accounting for 27.211% of the total effect, and the direct effect being 0.387 (p < 0.01). This means that environmental perception not only directly promotes residents’ sustained participation intention but also indirectly promotes it by enhancing their positive attitudes, with attitude playing a partial mediating role. The total effect of social support on sustained participation intention is 0.521 (p < 0.01), with the mediating effect through attitude accounting for 28.567% of the total effect, and the direct effect being 0.373 (p < 0.01). This indicates that the social support felt by residents from family and friends not only directly strengthens their intention to continue participating in nighttime physical activities but also indirectly promotes sustained participation intention by improving their attitudes towards nighttime physical activities, with attitude playing a partial mediating role.
Discussion
This study employs the Theory of Planned Behavior (TPB) to construct a structural equation model examining how environmental perception, social support, subjective norms, and perceived behavioral control influence residents’ continued participation intention in nighttime physical activity (PA), with attitude further analyzed as a mediating variable. Departing from prior research focused on general PA, this work uniquely applies TPB to nighttime PA—a domain facing distinctive challenges such as safety concerns, lighting conditions, and time constraints. By integrating a social-ecological perspective, we emphasize the synergistic interplay between external contextual factors (e.g., environmental perception and social support) and individual psychological factors (e.g., perceived behavioral control and attitude). This integrated approach offers a comprehensive lens for understanding behavioral mechanisms in nighttime PA. Our findings not only enrich TPB literature but also provide novel insights for promoting PA within specific socio-environmental contexts. Crucially, the social-ecological framework deepens theoretical understanding by revealing how environmental, social, and psychological factors collectively shape PA engagement. Although all hypothesized paths in this study were statistically significant, not all represented strong effects. Furthermore, within the context of nighttime physical activity, factors such as safety, lighting, time constraints, and companionship may be particularly limiting. These constraints could lead to weakened social pressure and overall evaluative perceptions, while the relative importance of perceived control and contextual resources may be exacerbated.
The influence of environmental perception on the intention to sustain nighttime physical activity
Environmental perception significantly and positively predicts continued participation intention (supporting H4). This indicates that favorable nighttime PA conditions—including accessible facilities, adequate lighting, and robust safety measures—substantially strengthen individuals’ willingness to sustain engagement. This aligns with existing evidence: Kim et al. (2023) confirmed that perceptions of high-quality environments correlate strongly with PA intention [54]; Cho et al. (2020) demonstrated that well-structured environments lower participation barriers and boost motivation [21]; Sallis et al. (2016) found that cities with maintained public recreation spaces promote higher PA levels, especially among groups with limited access to private facilities [55, 56]; Giles-Corti et al. (2016) emphasized that perceived safety—driven by lighting and community engagement—critically sustains regular exercise, particularly for safety-vulnerable groups like women and older adults [57, 58]. Collectively, these studies reinforce our conclusion that environmental perception is a pivotal determinant of sustained nighttime PA.
To effectively promote population-wide physical activity, it is imperative to enhance the nighttime physical activity environment through an integrated approach combining infrastructure development and community initiatives. Beyond upgrading lighting systems and security patrols, municipal authorities should consider integrating smart surveillance technologies and automated lighting adjustment systems to bolster safety and accessibility. These improvements not only create a more secure exercise environment for participants but also further incentivize engagement by reducing the perceived risks associated with nighttime activities.
Furthermore, socio-psychological engagement strategies are equally critical. Research demonstrates that targeted awareness campaigns and interactive community participation programs significantly strengthen public confidence in environmental enhancements, thereby boosting participation [59]. For instance, Møller et al. (2023) found that digital platforms—such as fitness tracking applications and virtual fitness communities—effectively enhance public motivation and engagement levels [60]. Community-led initiatives, when actively promoted through social media and localized health advocacy, can additionally deepen individuals’ sense of place attachment to public fitness spaces and strengthen their belonging to active communities [61, 62].
The relationship between social support and intention to sustain participation
Social support positively predicts sustained participation intention with a significant direct effect, supporting research hypothesis H5. This means that the higher the level of social support residents receive, the more likely they are to form the intention to continuously participate in nighttime physical activities. This finding confirms the social embeddedness of individual behavioral decision-making, that is, in real life, individuals do not make behavioral choices independently but are inevitably constrained and influenced by social relations and social capital [62]. Positive social support, such as the care and encouragement from friends and family, and the company of exercise partners, can enhance individuals’ exercise confidence, help them overcome practical difficulties in the process, and stimulate their sustained motivation [63]. This effect is particularly prominent in nighttime physical activities [64]. Nighttime exercise faces special challenges such as time arrangement and security, and without understanding and support from family and friends, colleagues, and partners, individuals are easily deterred by practical resistance and find it difficult to persist in participation [65]. This suggests that relevant departments should focus on creating a pro-social, sports-oriented social atmosphere when promoting nationwide fitness. For example, carrying out various family fitness programs to enhance sports parent-child relationships; establishing various night running organizations and interest groups to stimulate individual motivation through collective participation; and carrying out nighttime fitness theme activities in communities and units to make exercise a new way of social gathering. In summary, focusing on interpersonal interaction in sports practice and actively mobilizing social support resources around residents will lay a broad mass foundation for the vigorous development of nighttime physical activities.
Subjective norms and perceived behavioral control
Subjective norms and perceived behavioral control also have significant positive predictive effects on sustained participation intention, supporting research hypotheses H6 and H7. This indicates that the greater the social norm pressure individuals perceive and the stronger their self-efficacy in participating in nighttime physical activities, the more likely they are to form the intention to participate continuously. This finding is consistent with the research results of Keegan et al. (2016) [66] and echoes the claims of the Theory of Planned Behavior [67]. From a sociological perspective, the development of every physical activity is embedded in a specific social and cultural context. If night running becomes a highly esteemed social trend, forming an intangible pressure to participate, individuals are naturally more likely to actively participate in gaining group identification. From a psychological perspective, self-efficacy is a key psychological resource that promotes individuals to undertake and persist in specific behaviors. When individuals have high confidence in their ability to participate in nighttime physical activities and believe they can handle potential difficulties, they are more likely to persistently engage in sports [68, 69] Therefore, in the process of promoting nationwide fitness, shaping a social trend that “night running is glorious” and enhancing residents’ self-efficacy perception of participating in nighttime physical activities can promote individuals to internalize social calls into participation motivation and transform external pressure into internal motivation. To this end, relevant departments should widely carry out sports culture propaganda, and through typical selection and role modeling, make night running a highly esteemed fashion, creating a strong participation atmosphere for residents.
This study confirms the significant and partial mediating role of attitude, which aligns with existing extended TPB literature indicating that both direct and indirect effects can coexist in the explanatory model. However, the study also has some limitations, such as mainly using questionnaire surveys, which can be further verified in the future by combining experimental tasks; relying mainly on subjective evaluations when measuring variables, and introducing objective indicators in the future to obtain more comprehensive results; due to space limitations, demographic variables were not included, and future studies should explore the differences among different groups; the cross-sectional design makes it difficult to reveal the dynamic changes of variables, and future studies can adopt a longitudinal design to examine the long-term impact of relevant factors.
Limitations
This study acknowledges several limitations. First, the cross-sectional design constrains the ability to infer causality. Future research should employ longitudinal methods to track changes in participation intention over time and better understand the dynamic relationships among the variables. In addition, subsequent studies will incorporate variables such as socioeconomic status, current health status, health literacy, physical activity levels, and family responsibilities to enhance the comprehensiveness and explanatory power of the model. Second, data collection relied exclusively on self-reported questionnaires, which may introduce response biases such as social desirability bias or recall errors. Future research should adopt probabilistic and mixed-method sampling designs to improve representativeness and reduce the underrepresentation of digitally marginalized and rural populations. Although this study covered seven provinces across China, regional disparities may still introduce unobserved heterogeneity. While robustness checks were applied to mitigate potential biases, subsequent studies would benefit from multi-stage or stratified sampling strategies to minimize systematic errors and enhance generalizability. Future research should expand sampling to include broader and more diverse populations to comprehensively understand factors influencing nighttime PA participation across different regions and cultural contexts. While the sensitivity and robustness checks yielded satisfactory results, it is acknowledged that incorporating covariates such as socioeconomic status, health status, physical activity levels, and family responsibilities could further enhance the model’s explanatory power. Future research should consider longitudinal or multi-wave designs to better capture temporal dynamics and causal relationships.
Conclusion
Grounded in the Theory of Planned Behavior (TPB), this study constructed a structural equation model to analyze the impact of environmental perception, social support, subjective norms, and perceived behavioral control on continued intention to participate in nighttime physical activity (PA), with particular emphasis on the mediating role of attitude. The findings confirm that these factors significantly influence behavioral intention, highlighting the importance of incorporating environmental and social dimensions into theoretical models of PA participation. Notably, this study extends the application of TPB to the domain of nighttime PA, addressing a critical gap in the existing literature. At the macro level, a socio-ecological perspective was adopted, while the proximal processes were examined using an integrated Theory of Planned Behavior (TPB) model. The results support a partial mediation and multi-path explanatory mechanism, affirming the central role of attitude in shaping intentions and behaviors within the context of nighttime physical activity. Furthermore, the results align with the social-ecological model [25], which emphasizes the interplay of individual, environmental, and policy-level factors in shaping health behaviors. This broader perspective reveals the multi-level determinants of nighttime PA participation, providing a more comprehensive understanding of behavioral formation within this specific context.
Given that this study focuses on empirical model validation, demographic variables—such as socioeconomic status (SES), health status, prior physical activity (PA), and time or family constraints—were not measured. Subsequent research will employ probability sampling and multi-wave longitudinal designs, incorporating these demographic factors to enhance the explanatory power and generalizability of the findings. From a policy perspective, these insights suggest that municipal authorities and urban planners should incorporate nighttime PA into long-term public health strategies. Specifically, urban planning policies could designate dedicated nighttime activity zones equipped with intelligent lighting, safety features, and community fitness areas to ensure safety and accessibility; Local governments could offer economic incentives to fitness centers to extend operating hours, thereby increasing availability for time-constrained populations [70].
These recommendations align with the World Health Organization’s (WHO) Global Action Plan on Physical Activity 2018–2030, which advocates for inclusive, safe, and accessible PA environments to improve public health outcomes. By integrating theoretical insights with practical policy measures, this study provides an empirical foundation for enhancing nighttime PA participation rates, contributing to broader efforts in public health and urban development. Although the conclusions of this study are supported by robustness checks, certain limitations remain. Future research should adopt multi-stage probability sampling methods to strengthen the basis for causal inference.
Supplementary Information
Acknowledgements
J.W. and M.Z. contributed to the conception and design of the study. Y.S. organized the database, conducted statistical analysis, and drafted the initial manuscript. J.C., L.L., and J.W. wrote sections of the paper. All authors participated in the revision of the manuscript, read, and approved the submitted version.
Authors’ contributions
J.W. and M.Z. contributed to the conception and design of the study. Y.S. organized the database, conducted statistical analysis, and drafted the initial manuscript. J.C., L.L., and J.W. wrote sections of the paper. All authors participated in the revision of the manuscript, read, and approved the submitted version.
Funding
This research was funded by the Sichuan Province College Students Sports Association (Grant No.: 23CDTXQ004).
Data availability
The original data presented in this study are included in the article/supplementary materials. Further inquiries can be directed to the corresponding author, Jingying Chen, at chenjy90@outlook.com.
Declarations
Ethics approval and consent to participate
The study involving human participants has been reviewed and approved by the Ethics Committee of Leshan Normal University. Participants provided written informed consent to participate in this research.All methods were performed in accordance with the relevant guidelines and regulations.
Conflict of interest
The authors declare no conflict of interest.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The original data presented in this study are included in the article/supplementary materials. Further inquiries can be directed to the corresponding author, Jingying Chen, at chenjy90@outlook.com.