Influencing Factors of Physical Activity in Chinese University Students Based on Random Forest

Influencing Factors of Physical Activity in Chinese University Students Based on Random Forest | 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 Influencing Factors of Physical Activity in Chinese University Students Based on Random Forest Ding-you Zhang, Hu Lou, Jun Liu, Bo Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6738454/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: This study investigates the key factors influencing physical activity levels among Chinese university students, employing a random forest algorithm to analyze the predictive power and relative importance of various variables. Methods: A cross-sectional study utilizing stratified cluster sampling was conducted, covering 17 provinces across China, and collecting 10,182 valid questionnaires. Physical activity levels were assessed using the International Physical Activity Questionnaire (IPAQ). A random forest algorithm was then used to analyze the importance of 39 variables in influencing physical activity. Results: Random Forest prediction showed that Exercise Adherence (Exercise Behavior), Exercise Adherence Level, Sex, and Exercise Adherence (Effort Investment) are the most significant factors affecting PA levels in university students. Mastery of Sports Skills, Exercise Motivation (Ability), Alcohol Consumption Level, Exercise Adherence (Emotional Experience), Exercise Motivation (Social), and Exercise Motivation (Fun) are other important influencing factors. The model achieved an accuracy of 0.704 and an AUC value of 0.760, indicating good predictive performance. Conclusion: Exercise Adherence, Sex, Mastery of Sports Skills, Alcohol Consumption Level, and Exercise Motivation may influence PA levels in university students. When conducting sports activities, attention should be paid to enhancing the “emotional value” and social attributes of university students participating in PA, focusing on the exercise intentions of female students, and emphasizing the mastery of more sports skills. University Students Machine Learning Logistic Regression Random Forest Physical Activity Social Ecological Model Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Physical activity (PA) refers to any bodily movement produced by skeletal muscle contraction that results in energy expenditure[ 1 ]. A substantial body of research demonstrates that maintaining a certain intensity of PA can significantly alleviate negative emotional symptoms such as depression and stress in university students[ 2 ], maintain physical health[ 3 ], and improve health-related quality of life[ 4 ]. In 2020, the World Health Organization (WHO) released guidelines on PA and sedentary behavior[ 5 ], emphasizing that adults should engage in 150–300 minutes of moderate-intensity, or 75–150 minutes of vigorous-intensity aerobic PA per week, or an equivalent combination of moderate- and vigorous-intensity activity, to mitigate the adverse effects of sedentary behavior. A 2024 study involving 5.7 million participants showed a globally increasing prevalence of physical inactivity[ 6 ]. Despite widespread calls for the importance of PA, a significant proportion of university students remain insufficiently active[ 7 ]. Research indicates that nearly one-third of university students are severely physically inactive, with overall low levels of moderate-to-vigorous PA. University students spend more time sitting each day and rarely engage in PA during leisure time[ 8 ]. Research using the Transtheoretical Model has shown that university students’ awareness of relevant physical activity guidelines is associated with higher levels of PA. Still, brief exposure to the guidelines does not alter PA levels[ 9 ]. Therefore, to improve the insufficient PA levels among Chinese university students, exploring the key factors influencing their PA is necessary. Previous studies have demonstrated correlations between factors such as self-efficacy[ 10 ], sex[ 11 ], social support[ 7 ], screen time, and stress[ 12 ] and PA in university students. However, these studies often consider only a subset of factors and do not perform an integrated analysis of variables. Incorporating these factors influencing student PA and identifying the most significant key variables is of great importance for improving PA levels and promoting the health of university students. Random Forest (RF), an important machine learning component, is an ensemble learning algorithm based on decision trees, proposed by Leo Breiman in 2001[ 13 ]. It improves the accuracy and stability of predictions by constructing multiple decision trees and aggregating their predictions through voting[ 14 ]. Existing research demonstrates that RF has achieved significant predictive results in finance[ 15 ], healthcare[ 16 – 18 ], energy management[ 19 , 20 ], and education[ 21 ], and has also been used in the sports field to predict game outcomes[ 22 , 23 ] and athletic performance[ 24 ]. Although there are numerous studies on factors influencing physical activity in university students[ 25 , 26 ], these studies often consider a limited number of variables and rarely integrate these variables into a single study. As an ensemble learning-based feature importance analysis method, RF can quantify the contribution of each factor to physical activity levels through variable importance scores, integrate and effectively identify the impact of different variables on university students’ PA, and determine their relative importance through ranking. This provides a new perspective for solving the problem of ranking factors influencing PA in university students. Bronfenbrenner(1977)[ 27 ] first systematically proposed the Social Ecological Model (SEM). McLeroy (1988)[ 28 ], based on integrating Bronfenbrenner’s social ecological systems theory, proposed a hierarchical analysis framework that uses spatial metaphors to classify influencing factors into five progressive dimensions: individual, interpersonal, organizational, community, and policy. The individual level focuses on intrinsic individual traits, including health cognition, behavioral patterns, and self-regulation abilities. The interpersonal level emphasizes supportive interactions within social relationships, such as family members and peer groups. The organizational level focuses on the structural impact of institutions such as schools and enterprises on behavior through institutional norms and resource allocation. The community level integrates social environmental elements such as cultural traditions and public facilities within a geographic space. As a macro-driving system, the policy level continuously permeates all levels through laws, regulations, cultural values, and national strategies. As a core theoretical framework in health behavior research, SEM’s multi-dimensional analysis system demonstrates significant advantages in analyzing factors influencing individual health behaviors. In this study, SEM can be used to discuss the factors influencing PA levels in a stratified manner, accurately locate the root causes of the target population, and then guide and develop precise health intervention programs. Therefore, the individual and interpersonal-organizational levels of the SEM were selected as the analytical framework to incorporate factors that may influence PA levels of university students into the SEM, explore the relationship between individuals and interpersonal organizations, and provide systematic solutions for promoting the health of university students. The community and policy levels were not included, primarily based on the following considerations: First, university students mainly live in a relatively independent environment on campus, and their daily activities, social circles, and exercise resources are primarily concentrated on campus. Individual and interpersonal-organizational-level factors can more directly reflect their current PA status and influencing mechanisms. Second, relevant data at the individual and interpersonal-organizational levels are easier to measure and collect in university student populations. In contrast, assessing the community and policy levels requires more complex community environment analysis and cross-departmental data integration, which is more difficult and may exceed the scope of this study. Based on the aforementioned research model and methods, this study explores the factors influencing PA in Chinese university students, providing a scientific basis for formulating targeted sports intervention policies and health promotion strategies. Integrating the SEM and RF enriches and expands the analytical methods in the field of PA research, providing a new perspective for related studies. Methods Participants This study’s participants were students enrolled in regular higher education institutions in mainland China. The Ministry of Education’s “List of National Regular Institutions of Higher Education (as of June 20, 2024)” was used as the list. This study strictly adhered to the Herschel Declaration, and it has been approved by the Ethics Committee of Nantong University (2022 [ 70 ]). Sampling Methods This study primarily employed epidemiological survey methods. The survey covered most regions of China, including provinces such as Jiangsu, Shanghai, Shandong, Jilin, Henan, Sichuan, Chongqing, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang, Guangxi, Inner Mongolia, and Hainan. A total of 10,182 valid questionnaires were obtained. The survey subjects were undergraduate students enrolled in regular higher education institutions in China, including both junior college and bachelor’s degree students, excluding graduate students (Master’s and Doctoral). This study used stratified, cluster, and multi-stage sampling methods to select survey subjects based on geographical area (e.g., province, city administrative level) and university type (e.g., comprehensive university vs. local college). The specific sampling steps are as follows: Determination of Sampling Locations To ensure the representativeness of the test subjects, an average of three sampling locations were allocated to each province (autonomous region, or municipality). An equal number of samples were drawn from different cities, using the following specific procedures: Prefecture-level cities under the jurisdiction of each province and autonomous region were selected as sampling locations. Among them, the provincial capital city was designated as a “Category 1” sampling location; the principles for determining the other two cities were to select one city with a general level of socio-economic development as a “Category 2” sampling location and one city with a relatively poor level of social and economic growth as a “Category 3” sampling location, while considering the geographical location of the province or autonomous region. Sample extraction in municipalities directly under the central government did not consider the above principles, with random cluster sampling being the primary method. Still, the quantity principle of three sampling locations was considered. Determination of Sampling Units The selection of sampling units mainly considered four aspects: First, the affiliated institutions of higher education should be fully established institutions of higher education registered with the Ministry of Education, including higher vocational colleges and junior colleges; second, the units should be able to meet the sampling requirements (i.e., age, number of people, grade distribution, etc.); third, there should be a specific person in charge of questionnaire distribution, who is willing to participate in long-term monitoring; and fourth, the university students in the sampling units have completed their return to school for the fall semester. Grouping The samples were divided into two groups according to sex (male, female) and then into eight categories according to grade level. Data Cleaning Rules and Selection During data preprocessing, data with logical errors, omissions, errors, and unidentifiable entries were retested or eliminated to ensure the authenticity and validity of the data. The following rules were used to include valid questionnaires: First, questionnaires with unidentifiable full names of schools were deleted. Second, questionnaires with ages below 18 or above 25 were deleted. Third, questionnaires with at least 21 consecutive “completely consistent” answers were deleted. Fourth, after eliminating the questionnaires mentioned above, the average completion time of the remaining questionnaires was 539 seconds. Questionnaires with completion times in the [0, 5%] and [95%, 100%] positions were deleted. This study selected 10,182 Chinese university students aged 18–25 as research subjects. Questionnaire data collection was conducted online, with researchers and instructors present during data collection. At the beginning of the study, researchers provided participants with an informed consent form, which clearly stated the subjects‘ purpose, methods, potential risks, and rights, ensuring that participants voluntarily participated in the study on a fully informed basis. All participants were told that the questionnaire would take approximately 12 minutes to complete, that they could withdraw from the study at any time, and that there would be no adverse consequences. A preliminary survey was conducted before the implementation of the questionnaire, and the questionnaire design was optimized based on feedback. Participants’ responses were anonymous, and the obtained sample data were kept confidential to reduce self-report data bias. Selection and Coding of Scales Physical Activity The IPAQ short form was used to measure PA in university students[ 29 ]. This study used the Chinese version translated by Qu Ningning et al.[ 30 ], and according to the scoring rules, divided university students’ PA into three levels: “Vigorous intensity PA (VPA),” “Moderate intensity PA (MPA),” and “Light intensity PA (LPA)”[ 31 ]. The specific criteria are: 1) VPA is defined as physical activity with a metabolic equivalent of 6.0 or higher in absolute terms; in terms of individual ability standards, calculated on a score range of 0–10, VPA is usually 7 or 8 points. 2) MPA is defined as moderate-intensity activity 3 to 6 times less intense than resting in absolute terms; in terms of individual ability standards, calculated on a score range of 0–10, MPA is usually 5 or 6 points. 3) LPA is defined as light-intensity physical activity with a metabolic equivalent of 1.5 to 3, meaning that energy consumption does not exceed 3 times the energy consumption at rest; such activities include strolling, bathing, or other casual activities that do not cause a significant increase in heart rate or breathing rate. The scoring results ranged from 1 (LPA) to 3 (VPA). The intra-group correlation coefficients for each physical activity item in this scale were all above 0.7[ 30 ]. It has also undergone reliability and validity tests worldwide, has good reliability and validity[ 29 ], and can well reflect the level of physical activity. The WHO 2020 guidelines on physical activity and sedentary behavior state that all adults should engage in 150–300 minutes of MPA, 75–150 minutes of VPA, or an equivalent combination of moderate- and vigorous-intensity aerobic physical activity per week[ 32 ]. Therefore, when assessing PA levels in this study, “MPA” and “VPA” from the IPAQ were combined into moderate to vigorous physical activity (MVPA), named the achieving group. Independent Variables Based on McLeroy’s hierarchical analysis framework[ 28 ], 39 variables were selected and included in the individual, interpersonal, and organizational levels, and these variables were coded. Among them, sex, grade, mastery of sports skills, screen time, exercise motivation, nearsightedness status, average monthly living expenses, self-rated health level, sleep quality, self-esteem level, student peer relationships, smoking behavior, relationship status, mobile phone addiction tendency, and alcohol consumption were categorical variables. Psychological resilience level, exercise adherence level, health literacy level, depression level, anxiety level, general self-efficacy, self-emotional management ability, life satisfaction level, and leisure guilt level were continuous variables. The variables in parentheses () are sub-dimension variables of the preceding variables. These variables were collected using previously published questionnaires. The specific questionnaires used, the reliability and validity of each questionnaire, and their classification and coding in the social ecology model are shown in the following table: Table 1 Overview of Scales and Codes for Independent Variables Variable Scale Reliability and validity indicators Coding Demographic Information Sex / 1 = Male; 2 = Female Grade / 1 = Freshman; 2 = Sophomore; 3 = Junior; 4 = Senior Individual Level Mastery of Sports Skills / 1 = 0 items; 2 = 1 item; 3 = 2 items or more Screen Time / 1 = ≤ 3h/d; 2 = 3h/d ≤ Screen Time ≤ 8h/d; 3 = > 8h/d Exercise Motivation (Health) (I want to stay healthy) Exercise Motivation Scale [ 33 ] Cronbach’α = 0.922 ꭓ 2 =3604.140 NFI = 0.950 NNFI = 0.950 CFI = 0.950 IFI = 0.950 RMSEA = 0.091 SRMR = 0.079 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree Exercise Motivation (Appearance) (I want to maintain or improve my figure) Exercise Motivation Scale [ 33 ] 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree Exercise Motivation (Fun) (I want to stay in a good mood) Exercise Motivation Scale [ 33 ] 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree Exercise Motivation (Ability) (I want to improve my current athletic performance) Exercise Motivation Scale [ 33 ] 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree Average Monthly Living Expenses / 1 = 1000 RMB and below; 2 = 1000 to 2000 RMB; 3 = 2000 to 3000 RMB; 4 = 3000–4000 RMB; 5 = Above 4000 RMB Self-Rated Health Level SF-36 (In general, would you say your health is?) [ 34 ] Cronbach’α = 0.840 1 = Poor; 2 = Fair; 3 = Good; 4 = Very Good; 5 = Excellent Sleep Quality PSQI [ 35 ] Cronbach’α = 0.994 CFI=0.980 GFI=0.970 RESEA=0.009 1 = Very Good; 2 = Fair; 3 = Average; 4 = Very Poor Self-Esteem Scale SEL [ 36 ] Cronbach’s α = 0.880 1 = Does Not Apply; 2 = Slightly Does Not Apply; 3 = Applies; 4 = Strongly Applies Nearsightedness Status / 1 = Nearsighted; 2 = Not Nearsighted Smoking Behavior / 1 = Never Smokes; 2 = Occasionally Smokes; 3 = Smokes but No Addiction; 4 = Addicted but Controlled; 5 = Addicted and Uncontrolled Mobile Phone Addiction Tendency College Student Mobile Phone Addiction Tendency Scale [ 37 ] Cronbach’s α = 0.830 ꭓ 2 /df = 2.92 RMSEA = 0.07 CFI = 0.96 NFI = 0.94 IFI = 0.96 RFI = 0.93 1 = Strongly Disagree; 2 = Relatively Disagree; 3 = Unsure; 4 = Relatively Agree; 5 = Strongly Agree Alcohol Consumption Behavior / 1 = Never Drinks; 2 = Occasionally Drinks; 3 = Drinks but No Addiction; 4 = Addicted but Controlled; 5 = Addicted and Uncontrolled Psychological Resilience (Goal Focus) Adolescent Psychological Resilience Scale (T3, 4, 11, 20, 24) [ 38 ] Cronbach’s α = 0.830 ꭓ 2 /df = 2.510 RMSEA = 0.070 CFI = 0.920 GFI = 0.830 AGFI = 0.810 NNFI = 0.910 1 = Strongly Disagree; 2 = Relatively Disagree; 3 = Unsure; 4 = Relatively Agree; 5 = Strongly Agree Psychological Resilience (Emotional Control) Adolescent Psychological Resilience Scale (T1, 2, 5, 21, 23, 27) [ 38 ] 1 = Strongly Disagree; 2 = Relatively Disagree; 3 = Unsure; 4 = Relatively Agree; 5 = Strongly Agree Psychological Resilience (Positive Cognition) Adolescent Psychological Resilience Scale (T10, 13, 14, 25) [ 38 ] 1 = Strongly Disagree; 2 = Relatively Disagree; 3 = Unsure; 4 = Relatively Agree; 5 = Strongly Agree Psychological Resilience Level Adolescent Psychological Resilience Scale [ 38 ] 1 = Strongly Disagree; 2 = Relatively Disagree; 3 = Unsure; 4 = Relatively Agree; 5 = Strongly Agree Exercise Adherence (Exercise Behavior) Physical Exercise Adherence Scale (T1-T4) [ 39 ] Cronbach’s α = 0.947 ꭓ 2 /df = 2.896 CFI = 0.945 GFI = 0.901 RESEA = 0.069 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree Exercise Adherence (Effort Investment) Physical Exercise Adherence Scale (T5-T9) [ 39 ] 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree Exercise Adherence (Emotional Experience) Physical Exercise Adherence Scale (T10-T14) [ 39 ] 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree Exercise Adherence Level Physical Exercise Adherence Scale [ 39 ] 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree Health Literacy (Health Care) HLS-SF9(T1-T3) [ 40 ] Cronbach’s α = 0.913 ꭓ 2 /df = 10.844 GFI = 0.985 AGFI = 0.971 NFI = 0.986 CFI = 0.987 RMSEA = 0.051 1 = Very Difficult; 2 = Difficult; 3 = Easy; 4 = Very Easy Health Literacy (Disease Prevention) HLS-SF9(T4-T6) [ 40 ] 1 = Very Difficult; 2 = Difficult; 3 = Easy; 4 = Very Easy Health Literacy (Health Promotion) HLS-SF9(T7-T9) [ 40 ] 1 = Very Difficult; 2 = Difficult; 3 = Easy; 4 = Very Easy Health Literacy Level HLS-SF9 [ 40 ] 1 = Very Difficult; 2 = Difficult; 3 = Easy; 4 = Very Easy Depression Level CES-D [ 41 ] Cronbach’s α = 0.850 1 = Rarely or Never; 2 = Sometimes; 3 = Often or Half the Time; 4 = Most of the Time or Constantly Anxiety Level GAD-7 [ 42 ] Cronbach’s α = 0.920 1 = Not at All; 2 = Several Days; 3 = Over a Week; 4 = Nearly Every Day Self-Efficacy College Student Physical Exercise Self-Efficacy Scale [ 43 ] Cronbach’s α = 0.908 ꭓ 2 /df = 2.688 GFI = 0.958 AGFI = 0.932 NFI = 0.970 CFI = 0.981 IFI = 0.975 RMSEA = 0.066 RMR = 0.023 1 = Does Not Apply; 2 = Slightly Does Not Apply; 3 = Applies; 4 = Strongly Applies Self-Emotional Management Ability EIS [ 44 ] Cronbach’s α = 0.840 1 = Strongly Disagree; 2 = Relatively Disagree; 3 = Unsure; 4 = Relatively Agree; 5 = Strongly Agree Life Satisfaction Level SWLS [ 45 ] Cronbach’s α = 0.780 ꭓ 2 /df = 6.710 GFI = 0.970 CFI = 0.960 RMSEA = 0.071 1 = Strongly Disagree; 2 = Disagree; 3 = Slightly Disagree; 4 = I’m Not Sure; 5 = Slightly Agree; 6 = Agree; 7 = Strongly Agree Leisure Guilt Level Rest Guilt Scale Short Version [ 46 ] Cronbach’s α = 0.960 ꭓ 2 /df = 3.580 CFI = 0.940 RFI = 0.910 TLI = 0.930 RMSEA = 0.069 1 = Strongly Disagree; 2 = Disagree; 3 = Slightly Disagree; 4 = I’m Not Sure; 5 = Slightly Agree; 6 = Agree; 7 = Strongly Agree Interpersonal-Organizational Level Exercise Motivation (Social) (I want to improve my friendship) Exercise Motivation Scale [ 33 ] Same as above 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree; 5 = Strongly Agree Student Peer Relationships Student Peer Relationship Scale [ 47 ] Cronbach’s α = 0.870 1 = Does Not Apply; 2 = Slightly Does Not Apply; 3 = Applies; 4 = Strongly Applies Relationship Status / 1 = Single; 2 = In a Relationship; 3 = In Love Psychological Resilience (Family Support) Adolescent Psychological Resilience Scale (T8, 15, 16, 17, 19, 22) [ 38 ] Same as above 1 = Strongly Disagree; 2 = Relatively Disagree; 3 = Unsure; 4 = Relatively Agree; 5 = Strongly Agree Psychological Resilience (Interpersonal Assistance) Adolescent Psychological Resilience Scale (T6, 7, 9, 12, 18, 26) [ 38 ] 1 = Strongly Disagree; 2 = Relatively Disagree; 3 = Unsure; 4 = Relatively Agree; 5 = Strongly Agree Random Forest Model Construction RF is a bootstrap aggregating algorithm composed of multiple decision trees. Each decision tree is a weak learner, and they determine the final prediction result through voting or averaging (as shown in Fig. 1). The basic parameters for building the prediction model are set by configuring different numbers of learners (n_estimators), minimum samples for splitting an internal node (min_samples_split), minimum number of samples required to be at a leaf node (min_samples_leaf), maximum depth of the tree (max_depth), maximum number of leaf nodes (max_leaf_nodes), and minimum impurity decrease (min_impurity_decrease). In this study, the training set accounted for 80%, and the test set accounted for 20%. Combining the grid search method for hyperparameter optimization[ 48 ] and the 5-fold cross-validation method[ 49 ], the RF classification model was trained, predicted, and optimized to maximize accuracy as the parameter optimization target. The specific parameters are shown in Table 2 . Table 2 Overview of Parameter Optimization Results for Random Forest Algorithm Model Parameter Name Search Value n_estimators 100.0 min_samples_split 4.0 min_samples_leaf 2.0 max_depth 4.0 max_leaf_nodes 6.0 min_impurity_decrease 0.0 Results Descriptive Analysis Table 3 shows that among university students who achieved MVPA, the proportion of males was significantly higher than that of females (28.5% vs 16.0%, p < 0.001), with a large sex difference effect size (V = 0.349). Mastery of Sports Skills was strongly correlated with PA level, with students mastering 2 or more skills having a higher proportion in the achieving group (34.6% vs 31.4%, p < 0.001). Positive attitudes towards Exercise Motivation (Ability, Social, and Fun) were more prominent in the achieving group (13.9% vs 7.6%). Regarding Alcohol Consumption Level, the proportion of "Occasionally Drinks" was higher in the achieving group (19.8% vs 20.0%). Table 3 Overview of Descriptive Analysis Variable Physical Activity (Whether MVPA is Achieved) Not Achieving Group (5653) Achieving Group (4529) n/M %/sd n/M %/sd x 2 /t V/η 2 p Sex 1238.989 0.349 < 0.001 Male 1647 16.2 2900 28.5 Female 4006 39.3 1629 16.0 Grade 60.711 0.077 < 0.001 Freshman 3400 33.4 2652 59.4 Sophomore 1862 18.3 1367 31.7 Junior 275 2.7 358 6.2 Senior 116 1.1 152 2.6 Mastery of Sports Skills 511.079 0.224 < 0.001 0 items 489 4.8 143 1.4 1 item 1963 19.3 867 8.5 2 items or more 3201 31.4 3519 34.6 Screen Time 27.783 0.052 8h/d 967 9.5 772 7.6 Exercise Motivation (Health) 468.573 0.215 < 0.001 Strongly Disagree 11 0.1 21 0.2 Disagree 98 1.0 64 0.6 Neutral 1464 14.4 780 7.7 Agree 3308 32.5 2274 22.3 Strongly Agree 772 7.6 1390 13.7 Exercise Motivation (Appearance) 405.576 0.200 < 0.001 Strongly Disagree 18 0.2 32 0.3 Disagree 153 1.5 118 1.2 Neutral 1582 15.5 945 9.3 Agree 3128 30.7 2096 20.6 Strongly Agree 772 7.6 1338 13.1 Exercise Motivation (Fun) 584.112 0.240 < 0.001 Strongly Disagree 18 0.2 23 0.2 Disagree 130 1.3 52 0.5 Neutral 1556 15.3 774 7.6 Agree 3222 31.6 2247 22.1 Strongly Agree 727 7.1 1433 14.1 Exercise Motivation (Ability) 826.822 0.285 < 0.001 Strongly Disagree 23 0.2 19 0.2 Disagree 214 2.1 80 0.8 Neutral 1953 19.2 836 8.2 Agree 2870 28.2 2178 21.4 Strongly Agree 593 5.8 1416 13.9 Exercise Motivation (Social) 578.544 0.238 < 0.001 Strongly Disagree 58 0.6 60 0.6 Disagree 381 3.7 214 2.1 Neutral 2250 22.1 1256 12.3 Agree 2465 24.2 1826 17.9 Strongly Agree 499 4.9 1173 11.5 Nearsightedness Status 132.216 0.114 < 0.001 Nearsighted 4627 45.4 3274 32.2 Not Nearsighted 1026 10.1 1255 12.3 Average Monthly Living Expenses 41.291 0.064 < 0.001 1000 RMB and below 654 6.4 457 4.5 1000 to 2000 RMB 4407 43.3 3453 33.9 2000 to 3000 RMB 520 5.1 501 4.9 3000–4000 RMB 45 0.4 59 0.6 Above 4000 RMB 27 0.3 59 0.6 Self-Rated Health Level 290.724 0.169 < 0.001 Poor 107 1.1 62 0.6 Fair 1691 16.6 987 9.7 Good 2110 20.7 1381 13.6 Very Good 1244 12.2 1322 13.0 Excellent 501 4.9 777 7.6 Sleep Quality 41.764 0.064 < 0.001 Very Good 1425 14.0 1286 12.6 Fair 2864 28.1 2044 20.1 Average 1178 11.6 979 9.6 Very Poor 186 1.8 220 2.2 Self-Esteem Level 133.541 0.115 < 0.001 Does Not Apply 61 0.6 63 0.6 887 8.7 578 5.7 Slightly Does Not Apply 3787 37.2 2745 27.0 918 9.0 1143 11.2 Student Peer Relationships 153.769 0.123 < 0.001 Does Not Apply 141 1.4 121 1.2 Slightly Does Not Apply 1166 11.5 750 7.4 Applies 3440 33.8 2492 24.5 Strongly Applies 906 8.9 1166 11.5 Smoking Behavior 255.142 0.158 < 0.001 Never Smokes 5285 51.9 3789 37.2 Occasionally Smokes 163 1.6 314 3.1 Smokes but No Addiction 124 1.2 227 2.2 Addicted but Controlled 33 0.3 100 1.0 Addicted and Uncontrolled 48 0.5 99 1.0 Relationship Status 169.449 0.129 < 0.001 Single 3343 32.8 2094 20.6 In a Relationship 1316 12.9 1348 13.2 In Love 994 9.8 1087 10.7 Mobile Phone Addiction Tendency 133.392 0.114 < 0.001 Strongly Disagree 386 3.8 536 5.3 Relatively Disagree 1241 12.2 1017 10.0 Unsure 1888 18.5 1263 12.4 Relatively Agree 1807 17.7 1312 12.9 Strongly Agree 331 3.3 401 3.9 Alcohol Consumption Level 268.181 0.162 < 0.001 Never Drinks 2899 28.5 1632 16.0 Occasionally Drinks 2032 20.0 2012 19.8 Drinks but No Addiction 531 5.2 567 5.6 Addicted but Controlled 96 0.9 150 1.5 Addicted and Uncontrolled 89 0.9 150 1.5 Addicted and Drinks Daily 6 0.1 18 0.2 Psychological Resilience (Goal Focus) 18.518 3.279 19.227 3.657 106.105 0.010 < 0.001 Psychological Resilience (Emotional Control) 17.232 3.847 16.417 4.067 107.383 0.010 < 0.001 Psychological Resilience (Positive Cognition) 15.268 2.601 15.762 2.945 80.611 0.008 < 0.001 Psychological Resilience (Family Support) 17.777 2.415 17.766 2.691 0.048 < 0.001 0.826 Psychological Resilience (Interpersonal Assistance) 17.454 3.077 17.278 3.362 7.620 0.001 0.006 Psychological Resilience Level 86.250 9.483 86.450 10.472 1.020 < 0.001 0.313 Exercise Adherence (Exercise Behavior) 50.417 7.550 56.307 8.813 1317.810 0.115 < 0.001 Exercise Adherence (Effort Investment) 9.551 1.429 9.795 1.593 66.233 0.006 < 0.001 Exercise Adherence (Emotional Experience) 9.048 1.556 9.363 1.752 91.957 0.009 < 0.001 Exercise Adherence Level 9.340 1.408 9.752 1.571 193.773 0.019 < 0.001 Health Literacy (Health Care) 27.938 3.938 28.909 4.463 135.579 0.013 < 0.001 Health Literacy (Disease Prevention) 13.546 2.602 15.866 2.884 1814.827 0.151 < 0.001 Health Literacy (Health Promotion) 18.117 2.996 20.132 3.403 1006.937 0.090 < 0.001 Health Literacy Level 18.754 2.875 20.309 3.258 653.115 0.060 < 0.001 Depression Level 15.377 4.763 15.145 5.105 5.588 0.001 0.018 Anxiety Level 10.674 3.996 10.550 4.309 2.243 < 0.001 0.134 Self-Efficacy 18.008 5.095 19.608 5.681 223.702 0.022 < 0.001 Self-Emotional Management Ability 32.382 9.458 32.242 10.954 0.478 < 0.001 0.489 Life Satisfaction Level 23.149 5.453 23.891 6.076 42.042 0.004 < 0.001 Leisure Guilt Level 29.875 4.239 30.808 4.790 108.534 0.011 < 0.001 Model Performance Metrics A Confusion Matrix and ROC Curve were selected to evaluate model performance. The four evaluation metrics in the Confusion Matrix range from 0 to 1, with larger values indicating better model performance. Table 4 summarizes the performance parameters of the test set. Overall, the model’s performance was good. The AUC (Area Under the ROC Curve) quantifies the model’s overall performance under the ROC curve. The AUC value ranges from 0 to 1, with larger values indicating better model performance. Figure 2 shows that the AUC value for this model is 0.760, indicating good model performance. Table 4 Confusion Matrix and Modeling Evaluation Score Results Confusion Matrix Modeling Evaluation Predicted Value Accuracy 0.704 0 1 Precision 0.711 Real Value 0 3760 731 Recall 0.689 1 1680 1975 F1 Score 0.696 Analysis of the Importance of Influencing Factors Figure 3 , the Feature Contribution Chart, shows the importance of each feature in the model. The higher the feature contribution, the more critical the feature’s role in the model prediction. The results show that Exercise Adherence (Exercise Behavior), Exercise Adherence Level, Sex, Exercise Adherence (Effort Investment), Exercise Motivation (Ability), Exercise Adherence (Emotional Experience), Mastery of Sports Skills, Exercise Motivation (Social), Exercise Motivation (Fun), and Alcohol Consumption Level are the top ten contributing variables. Figure 4 is a Feature Contribution Chart for Permuted Variables. This chart evaluates a feature’s importance by randomly permuting each feature’s values and observing the change in model performance. The results indicate that the variables with the most significant positive contribution are: Exercise Adherence (Exercise Behavior), Sex, Relationship Status, Mastery of Sports Skills, Exercise Motivation (Health), Alcohol Consumption Level, and Smoking Behavior. The variables with the most significant negative contribution are: Exercise Adherence (Emotional Experience), Exercise Motivation (Social), Exercise Motivation (Ability), Exercise Adherence Level, and Exercise Adherence (Effort Investment). Figure 5 is a SHAP (SHapley Additive exPlanations) summary plot. In this plot, dark green dots represent a smaller value for that feature variable. If the SHAP values of these points are negative, it indicates that the low-value feature hurts the dependent variable; if the SHAP values are positive, it suggests that the low-value feature positively impacts the dependent variable. Light green dots indicate the opposite. According to the results in Fig. 4 , Exercise Adherence (Exercise Behavior), Sex, Exercise Adherence Level, Exercise Adherence (Effort Investment), Mastery of Sports Skills, Exercise Motivation (Ability), Alcohol Consumption Level, Exercise Adherence (Emotional Experience), Exercise Motivation (Social), and Exercise Motivation (Fun) are the top 10 contributing variables. Discussion This study systematically identified the key influencing factors of PA in university students using the feature importance analysis of the RF model. Exercise Adherence (Exercise Behavior) and its sub-dimensions, Exercise Motivation, Sex, Mastery of Sports Skills, and Alcohol Consumption Level, were confirmed as the most critical predictors, consistent with previous literature findings, and deepened the understanding of PA in university students. The results of this study revealed that Exercise Adherence is the most significant predictor of PA, consistent with previous research [ 50 ]. However, this study further revealed the independent contributions of the sub-dimensions of Exercise Adherence to PA, which has been less frequently mentioned in previous studies. Exercise Adherence (Exercise Behavior) is the most critical predictor of PA. The descriptive analysis showed that university students who achieved MVPA generally had higher scores in Exercise Adherence than those who did not achieve MVPA. The SHAP summary plot of the RF model also showed that Exercise Adherence values were widely distributed and ranked highly. Therefore, whether university students can adhere to exercise makes an essential contribution to the accurate prediction of meeting PA recommendations. In this study, Exercise Adherence, as an individual-level factor in the social-ecological model, showed that individuals who actively participate in physical exercise can improve individual mental health and well-being, alleviate depression, stress, and anxiety[ 51 ] at the psychological level; and enhance cardiopulmonary function, increase muscle volume and strength, and improve learning and memory abilities[ 52 ] at the physiological level, providing numerous benefits. Current research indicates that a key challenge in promoting PA lies in the discrepancy between an individual’s intention to exercise and their actual behavior, i.e., the intention-behavior gap. Despite having a firm intention to exercise, individuals are influenced by various factors that prevent them from implementing corresponding exercise behaviors[ 53 ]. In this study, the high contribution of individual-level Exercise Adherence (Emotional Experience) and interpersonal-organizational level Exercise Motivation (Social) to the prediction model reveals possible related reasons. According to the concept of self-efficacy in Social Cognitive Theory[ 54 ], in addition to adhering to exercise, the “emotional value” that this behavior brings to individuals also provides a possible effect. This “emotional value” may include, but is not limited to, the encouragement and praise from people around them, and the social attributes brought about by finding friends to persist in physical exercise together[ 55 ]. Previous studies have also confirmed this point. For example, a study in 2021 demonstrated that enjoyment and motivation significantly affect the persistence of individual exercise[ 56 ]. Another study also demonstrated that exercisers’ perceived autonomous support positively impacts meeting basic psychological needs[ 57 ]. Therefore, to promote exercise adherence in university students, increase PA, and reduce the intention-behavior gap, and actively leverage the role of social support and emotional value in exercise adherence, methods such as organizing sports groups, sports club activities, and fun sports events can be used to integrate individual emotional experiences with social support from multiple levels of the social-ecological model, providing comprehensive exercise support for university students, developing positive exercise habits, thereby improving PA levels. Sex is the second most significant factor in predicting PA in university students, with males having a positive impact and females hurting PA prediction. This is consistent with previous research findings [ 58 ]. Although sex itself, as a physiological characteristic, is not amenable to intervention, the differences in socio-cultural preferences and behavioral patterns it reflects are still worth noting. Existing research proves that males and females are unequal in PA, with girls generally being less physically active than boys [ 59 , 60 ], and inequality is higher in high-income countries and countries with high human development index rankings[ 61 ]. Studies have also shown that the sex gap narrows in vigorous-intensity PA, while it increases in moderate-intensity PA[ 62 ]. This may be because women participate more in aerobic exercise, with lower PA intensity[ 63 ], and lack exercise energy and willpower in physical activity[ 64 ]. At the same time, it may also be related to the socialization process of gender roles. Men are more likely to regard PA as a way to display strength and compete, and are more likely to challenge high-intensity PA to prove their masculine charm, resulting in higher levels of PA. Conversely, women may be more concerned with the social attributes or appearance improvement of physical activity. A toolkit document on gender equality in the field of sports, jointly developed by the European Union and the Council of Europe, also shows that men are more likely to engage in sports or physical activity for entertainment (33%), to be with friends (22%), or to improve physical performance (29%). In comparison, women are more concerned with controlling weight (24%), improving appearance (21%), or offsetting the effects of aging (15%)[ 65 ]. Therefore, in future teaching processes, gender equality indicators can be incorporated into the school sports system, and the willingness of girls to exercise can be improved by adding diverse intensity options to the curriculum and avoiding a single competitive orientation. Alternatively, gender-mixed group courses can be offered, such as fun physical fitness challenges and team collaboration tasks, to weaken competitiveness, enhance social attributes, and cater to the needs of both men and women. The results of this study also show that Exercise Motivation (Ability), i.e., “I exercise to improve sports skills,” and Mastery of Sports Skills are also essential factors in predicting PA in university students. Studies have shown that developing sports skills is a primary potential mechanism for promoting individual participation in PA[ 66 ], and mastering more sports skills can encourage individuals to participate in more PA. A long-term randomized controlled trial also found that students in the special sports skill training group significantly outperformed the general physical education class group regarding PA and physical fitness[ 67 ]. This may be achieved through two pathways, namely the self-efficacy pathway and the social support pathway. According to Self-Efficacy Theory[ 54 ] and Social Cognitive Theory[ 68 ], university students’ PA behavior is influenced by their cognitive factors and environment. When individuals master more sports skills, they are more likely to perform well in sports activities, further enhancing their willingness to participate in PA, thereby improving PA levels. At the same time, students who master various sports skills are also more likely to engage in diverse sports, such as combining endurance training and strength training[ 69 ], to improve PA levels. In some team sports, sports that require teamwork (such as basketball and volleyball) can better promote communication and interaction among university students, enhance the fun and social attributes of PA, and are linked to Exercise Motivation (Social) at the interpersonal-organizational level of the social-ecological model, thereby reducing anxiety and depression and promoting PA[ 70 , 71 ]. Therefore, future research should focus on improving the number and proficiency of sports skills mastered by university students. It is possible to promote university students to master more sports skills and improve PA levels by organizing sports skill training classes, sports skill mutual aid groups, or amateur competitive competitions. In addition to Exercise Adherence, Exercise Motivation, and Mastery of Sports Skills, this study also found that Alcohol Consumption Level and Smoking Behavior may impact PA. There is overwhelming evidence that alcohol and smoking can cause damage to the body[ 72 – 77 ]. Long-term alcohol consumption can lead to alcohol dependence. This rewarding, chronic relapsing disease can cause significant harm to human health[ 78 ], such as the brain nerves, liver, digestive system, immune system, and cardiovascular system[ 72 ]. Smoking can lead to a variety of fatal diseases, including lung cancer, respiratory diseases, and cardiovascular diseases (such as coronary heart disease)[ 79 ]. A cross-sectional study showed that smoking and alcohol have a synergistic effect, and the two can jointly damage the liver[ 80 ]. Therefore, reducing alcohol consumption and smoking is of great significance for maintaining the physical health of university students, and participating in PA provides a possible solution to this problem. One study showed that PA level is linearly negatively correlated with alcohol consumption; that is, people who are more physically active drink less alcohol, and people who are less physically active drink relatively more alcohol[ 81 ]. Another study showed that individuals with higher levels of PA are less likely to smoke[ 82 ]. These are consistent with the results of this study, which means that participating in more PA will reduce alcohol consumption and the possibility of smoking. At the same time, regular moderate-to-vigorous physical exercise can also offset the adverse metabolic effects of alcohol on liver function, inflammation, and lipid status[ 83 ]. The possible reason for this is that PA reduces alcohol intake caused by reward properties by regulating the reward system and emotional state, thereby offsetting the adverse effects of alcohol to a certain extent, thus reducing alcohol consumption[ 84 ]. However, it should be noted that some studies have also proved that PA is positively correlated with alcohol consumption, and alcohol consumption will increase with the increase of the intensity and duration of PA[ 85 , 86 ]. This is inconsistent with the results of this study, and the possible reason for this is that both PA and alcohol can activate the reward pathway of the brain, releasing dopamine and endogenous opioids. This overlap in neurochemical effects may be a biological basis for the positive correlation between PA and alcohol[ 87 ]. The relationship between PA and alcohol needs to be further clarified in future research. The advantages of this study lie in the analysis based on large-sample cross-sectional survey data, and the innovative use of machine learning technology to reveal the influencing mechanism of PA in university students, which more effectively captures the non-linear relationship and interaction between variables compared with traditional statistical methods. The study combines the social-ecological model framework to systematically integrate measurement indicators of multiple dimensions, such as personal characteristics, interpersonal communication, and organizational environment. It constructs a multi-level influencing factor analysis system, providing multi-dimensional evidence to support the formulation of precise health intervention strategies. However, several research limitations should also be pointed out: First, the cross-sectional design has methodological limitations in revealing the causal relationship and temporal dynamic evolution between variables; secondly, some measurement indicators rely on self-assessment scales, which may lead to social desirability bias and recall bias; in addition, macro variables at the community policy level in the social-ecological model have not been included in the research framework, which may affect the systematic nature of the intervention strategy to a certain extent. Future research can improve the PA influencing mechanism’s theoretical explanation and practical application through longitudinal tracking design, multi-source data integration, and cross-level model construction. Conclusion This study used the RF algorithm in machine learning to analyze the factors affecting PA in university students. The study results showed that Exercise Adherence, Exercise Motivation, Sex, Mastery of Sports Skills, and Alcohol Consumption Level are key factors in predicting PA levels in university students. While carrying out sports activities to promote the growth of PA in university students, it is necessary to attach importance to enhancing the “emotional value” of university students participating in PA, enhancing social attributes, focusing on the exercise intentions of female students, and emphasizing the mastery of more sports skills. Declarations Ethics approval and consent to participate This study strictly adhered to the Herschel Declaration, and it has been approved by the Ethics Committee of Nantong University (2022 [70]). All subjects provided informed consent, and all methods were performed according to relevant guidelines and regulations. Consent for publication Informed consent was obtained from all the subjects involved in the study. Availability of data and materials The raw data supporting the conclusions of this article can be made available by the authors without undue reservation. If necessary, please contact the corresponding author for assistance. Competing interests The authors declare that they have no conflicts of interest. Funding This study was supported by the 2024 Postgraduate Research & Practice Innovation Program of Jiangsu Province. (NO： KYCX25_3617). Author contributions Ding-you Zhang, the first author and the main contributor, is responsible for the research design, organization of the questionnaire survey, and drafting of the manuscript, undertaking the majority of the work. Bo Li participated in the research design and data collation. Hu Lou was involved in the distribution of the questionnaires and the collection of data. Jun Liu and Bo Li took charge of data analysis and manuscript revision. All authors collectively discussed the research approach and refined the content of the paper. 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Sustainability 2021.http://doi.org/10.3390/SU13063183. Ricardo L, Wendt A, Costa C, Mielke G, Brazo-Sayavera J, Khan A, Kolbe-Alexander T, Crochemore-Silva I: Gender inequalities in physical activity among adolescents from 64 Global South countries . Journal of Sport and Health Science 2022, 11 :509-520.http://doi.org/10.1016/j.jshs.2022.01.007. Owen KB, Corbett L, Ding D, Eime R, Bauman A: Gender differences in physical activity and sport participation in adults across 28 European countries between 2005 and 2022 . Annals of Epidemiology 2025, 101 :52-57.http://doi.org/https://doi.org/10.1016/j.annepidem.2024.12.011. Morales NS, Eraso N, Eraso M, Castro YC, Doncel MM, Espinosa R, Guzmán V: Evidence of association between gender and physical fitness in physically active people in Colombia . The European Journal of Public Health 2024, 34 .http://doi.org/10.1093/eurpub/ckae144.1826. Rosselli M, Ermini E, Tosi B, Boddi M, Stefani L, Toncelli L, Modesti P: Gender differences in barriers to physical activity among adolescents . Nutrition, metabolism, and cardiovascular diseases : NMCD 2020.http://doi.org/10.1016/j.numecd.2020.05.005. ALL IN: Towards gender balance in sport [https://www.sportanddev.org/sites/default/files/downloads/toolkit_gender_equal_sports-web.pdf] Stodden DF, D. GJ, J. LS, Ann RM, E. RM, Clersida G, and Garcia LE: A Developmental Perspective on the Role of Motor Skill Competence in Physical Activity: An Emergent Relationship . Quest 2008, 60 (2):290-306.http://doi.org/10.1080/00336297.2008.10483582. Ke Y, Bao M, Qu X, Yan Y, Li L, Wang Y, Wu Y, Li X, Liu Y: The effect of diverse sports skills interventions on physical fitness and brain development among Chinese high school students: a cluster randomized controlled trial study protocol . Trials 2025, 26 (1):102.http://doi.org/10.1186/s13063-025-08788-9. Bandura: Human agency in social cognitive theory . American Psychologist 1989, 44 (9):1175-1184. Devís J, Gil-Quintana J, Lizandra J, López-Cañada E, Molina P, Peiró-Velert C, Pereira-García S, Samaniego V, Saenz A, Úbeda-Colomer J et al : Diversities in physical activity and sport ; 2023. Mcewan D, Shah EJ, Crawford KL, Jackman PC, Hoffmann MD, Cardinal E, Bruner MW, Mclaren CD, Benson AJ: The Psychometric Properties of Two Brief Measures of Teamwork in Sport . Journal of Sport Exercise Psychology 2023, 45 (6). Chi G, Wang L: The Association of Sports Participation With Depressive Symptoms and Anxiety Disorder in Adolescents . Frontiers in public health 2022, 10 :860994.http://doi.org/10.3389/fpubh.2022.860994. Varghese J, Dakhode S: Effects of Alcohol Consumption on Various Systems of the Human Body: A Systematic Review . Cureus 2022, 14 (10):e30057.http://doi.org/10.7759/cureus.30057. Zahr NM, Pfefferbaum A: Alcohol's Effects on the Brain: Neuroimaging Results in Humans and Animal Models . Alcohol research : current reviews 2017, 38 (2):183-206. Renu K, Myakala H, Chakraborty R, Bhattacharya S, Abuwani A, Lokhandwala M, Vellingiri B, Gopalakrishnan AV: Molecular mechanisms of alcohol's effects on the human body: A review and update . Journal of biochemical and molecular toxicology 2023, 37 (12):e23502.http://doi.org/10.1002/jbt.23502. Danpanichkul P, Wijarnpreecha K: Implementing public health policy to tackle alcohol-related harms . The Lancet Public Health .http://doi.org/10.1016/S2468-2667(25)00048-9. Varghese J, Muntode Gharde P: A Comprehensive Review on the Impacts of Smoking on the Health of an Individual . Cureus 2023, 15 (10):e46532.http://doi.org/10.7759/cureus.46532. Dai X, Gil GF, Reitsma MB, Ahmad NS, Anderson JA, Bisignano C, Carr S, Feldman R, Hay SI, He J et al : Health effects associated with smoking: a Burden of Proof study . Nature medicine 2022, 28 (10):2045-2055.http://doi.org/10.1038/s41591-022-01978-x. Gilpin NW, Koob GFJAR, Health: Neurobiology of alcohol dependence: focus on motivational mechanisms . 2008, 31 (3):185. West R: Tobacco smoking: Health impact, prevalence, correlates and interventions . Psychology & health 2017, 32 (8):1018-1036.http://doi.org/10.1080/08870446.2017.1325890. Park EY, Lim MK, Oh J-K, Cho H, Bae MJ, Yun EH, Kim D-i, Shin H-R: Independent and Supra-Additive Effects of Alcohol Consumption, Cigarette Smoking, and Metabolic Syndrome on the Elevation of Serum Liver Enzyme Levels . PLOS ONE 2013, 8 (5):e63439.http://doi.org/10.1371/journal.pone.0063439. Niemelä O, Bloigu A, Bloigu R, Halkola AS, Niemelä M, Aalto M, Laatikainen T: Impact of Physical Activity on the Characteristics and Metabolic Consequences of Alcohol Consumption: A Cross-Sectional Population-Based Study . Int J Environ Res Public Health 2022, 19 (22).http://doi.org/10.3390/ijerph192215048. Acar Z, Jackson S, Klosterhalfen S, Kotz D: Physical activity and tobacco smoking in the German adult population . BMJ Open Sport & Exercise Medicine 2024, 10 .http://doi.org/10.1136/bmjsem-2024-002087. Niemelä O, Bloigu A, Bloigu R, Halkola A, Niemelä M, Aalto M, Laatikainen T: Impact of Physical Activity on the Characteristics and Metabolic Consequences of Alcohol Consumption: A Cross-Sectional Population-Based Study . International Journal of Environmental Research and Public Health 2022, 19 .http://doi.org/10.3390/ijerph192215048. Castejón E, Fuentes-Verdugo E, Pellón R, Torres C: Physical activity reduces alcohol consumption induced by reward downshift . Experimental and clinical psychopharmacology 2023, 31 (2):404-413.http://doi.org/10.1037/pha0000587. Henderson C, Najjar L, Young C, Leasure J, Neighbors C, Gasser M, Lindgren K: Longitudinal relations between physical activity and alcohol consumption among young adults . Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors 2021.http://doi.org/10.1037/adb0000807. Musselman JRB, Rutledge PC: The incongruous alcohol-activity association: Physical activity and alcohol consumption in college students . Psychology of Sport and Exercise 2010, 11 (6):609-618.http://doi.org/https://doi.org/10.1016/j.psychsport.2010.07.005. Leasure JL, Neighbors C, Henderson CE, Young CM: Exercise and Alcohol Consumption: What We Know, What We Need to Know, and Why it is Important . Front Psychiatry 2015, 6 :156.http://doi.org/10.3389/fpsyt.2015.00156. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-6738454","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482201399,"identity":"68444c62-6b73-46be-9c46-1e5c5a974303","order_by":0,"name":"Ding-you Zhang","email":"","orcid":"","institution":"Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Ding-you","middleName":"","lastName":"Zhang","suffix":""},{"id":482201400,"identity":"03254843-ce88-492d-9a5d-99e44a26f3ef","order_by":1,"name":"Hu Lou","email":"","orcid":"","institution":"Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Hu","middleName":"","lastName":"Lou","suffix":""},{"id":482201401,"identity":"6f724028-df47-4f29-bfc9-2e64dae32922","order_by":2,"name":"Jun Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIie3RPwrCMByG4YRCdIjOvyLUEwjRQLGLZ0kQnKKLi2PFoQ49gEMvIUJXM/UMHZVCpzp4AP9OuiWjYN79GT4+hFyun0zg6nYnAU422pp4jJIu99JCWBMClASytVPMDvQTFQLQUHR26lo2aBIMYgPBacPHDGYLP70cogxNeagNxAM1LAUrlsNknvco0jI3EQKKgRYPedSqtiMU1MiPNZHrrSJ2BGi95DgmHKcFjzJmsaWfTPfVi7yvPJfNahIYCULtzx1A7a5pnb6IlXC5XK5/6wlggUEF3Ca4JQAAAABJRU5ErkJggg==","orcid":"","institution":"Nantong University","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"","lastName":"Liu","suffix":""},{"id":482201402,"identity":"ebf2349f-6685-4cf9-a1f6-e099f366b3ed","order_by":3,"name":"Bo Li","email":"","orcid":"","institution":"Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-05-24 10:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6738454/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6738454/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86304796,"identity":"bc04b62a-d177-467c-aab9-6a44ecdbce3b","added_by":"auto","created_at":"2025-07-09 07:00:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52653,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic Diagram of Random Forest Process\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6738454/v1/abc68aef5181e798da72bf74.png"},{"id":86303378,"identity":"9155110f-d388-48a6-ac90-9fa5aa74c4e4","added_by":"auto","created_at":"2025-07-09 06:52:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44695,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC Curve\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6738454/v1/30a2c1b9a341eac54e4f5374.png"},{"id":86303385,"identity":"0e776623-6bcc-457e-b351-cc73befe008d","added_by":"auto","created_at":"2025-07-09 06:52:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":125251,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFeature Contribution Chart\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6738454/v1/d50e73531878786787b2ed56.png"},{"id":86303390,"identity":"42accd10-c3a9-41fb-ba01-74d62852171b","added_by":"auto","created_at":"2025-07-09 06:52:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":104773,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFeature Contribution Chart for Permuted Variables\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6738454/v1/8dc172bf6e14b6856a54a0eb.png"},{"id":86304800,"identity":"fef82ab4-11ef-492e-8de5-dd2cc2c1cacc","added_by":"auto","created_at":"2025-07-09 07:00:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":116516,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSHAP (SHapley Additive exPlanations) Summary Plot\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6738454/v1/0a149d2a65c2371334be2f0f.png"},{"id":89800363,"identity":"eddc4d3a-596b-40b2-8bd9-3d33a1115807","added_by":"auto","created_at":"2025-08-25 08:02:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6346604,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6738454/v1/1e38ff2a-b29c-467a-9d0d-5ef9b5590eff.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Influencing Factors of Physical Activity in Chinese University Students Based on Random Forest","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePhysical activity (PA) refers to any bodily movement produced by skeletal muscle contraction that results in energy expenditure[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A substantial body of research demonstrates that maintaining a certain intensity of PA can significantly alleviate negative emotional symptoms such as depression and stress in university students[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], maintain physical health[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and improve health-related quality of life[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In 2020, the World Health Organization (WHO) released guidelines on PA and sedentary behavior[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], emphasizing that adults should engage in 150\u0026ndash;300 minutes of moderate-intensity, or 75\u0026ndash;150 minutes of vigorous-intensity aerobic PA per week, or an equivalent combination of moderate- and vigorous-intensity activity, to mitigate the adverse effects of sedentary behavior. A 2024 study involving 5.7\u0026nbsp;million participants showed a globally increasing prevalence of physical inactivity[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Despite widespread calls for the importance of PA, a significant proportion of university students remain insufficiently active[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Research indicates that nearly one-third of university students are severely physically inactive, with overall low levels of moderate-to-vigorous PA. University students spend more time sitting each day and rarely engage in PA during leisure time[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Research using the Transtheoretical Model has shown that university students\u0026rsquo; awareness of relevant physical activity guidelines is associated with higher levels of PA. Still, brief exposure to the guidelines does not alter PA levels[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, to improve the insufficient PA levels among Chinese university students, exploring the key factors influencing their PA is necessary. Previous studies have demonstrated correlations between factors such as self-efficacy[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], sex[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], social support[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], screen time, and stress[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and PA in university students. However, these studies often consider only a subset of factors and do not perform an integrated analysis of variables. Incorporating these factors influencing student PA and identifying the most significant key variables is of great importance for improving PA levels and promoting the health of university students.\u003c/p\u003e\u003cp\u003eRandom Forest (RF), an important machine learning component, is an ensemble learning algorithm based on decision trees, proposed by Leo Breiman in 2001[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. It improves the accuracy and stability of predictions by constructing multiple decision trees and aggregating their predictions through voting[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Existing research demonstrates that RF has achieved significant predictive results in finance[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], healthcare[\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], energy management[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and education[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and has also been used in the sports field to predict game outcomes[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and athletic performance[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Although there are numerous studies on factors influencing physical activity in university students[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], these studies often consider a limited number of variables and rarely integrate these variables into a single study. As an ensemble learning-based feature importance analysis method, RF can quantify the contribution of each factor to physical activity levels through variable importance scores, integrate and effectively identify the impact of different variables on university students\u0026rsquo; PA, and determine their relative importance through ranking. This provides a new perspective for solving the problem of ranking factors influencing PA in university students.\u003c/p\u003e\u003cp\u003eBronfenbrenner(1977)[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] first systematically proposed the Social Ecological Model (SEM). McLeroy (1988)[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], based on integrating Bronfenbrenner\u0026rsquo;s social ecological systems theory, proposed a hierarchical analysis framework that uses spatial metaphors to classify influencing factors into five progressive dimensions: individual, interpersonal, organizational, community, and policy. The individual level focuses on intrinsic individual traits, including health cognition, behavioral patterns, and self-regulation abilities. The interpersonal level emphasizes supportive interactions within social relationships, such as family members and peer groups. The organizational level focuses on the structural impact of institutions such as schools and enterprises on behavior through institutional norms and resource allocation. The community level integrates social environmental elements such as cultural traditions and public facilities within a geographic space. As a macro-driving system, the policy level continuously permeates all levels through laws, regulations, cultural values, and national strategies. As a core theoretical framework in health behavior research, SEM\u0026rsquo;s multi-dimensional analysis system demonstrates significant advantages in analyzing factors influencing individual health behaviors. In this study, SEM can be used to discuss the factors influencing PA levels in a stratified manner, accurately locate the root causes of the target population, and then guide and develop precise health intervention programs. Therefore, the individual and interpersonal-organizational levels of the SEM were selected as the analytical framework to incorporate factors that may influence PA levels of university students into the SEM, explore the relationship between individuals and interpersonal organizations, and provide systematic solutions for promoting the health of university students. The community and policy levels were not included, primarily based on the following considerations: First, university students mainly live in a relatively independent environment on campus, and their daily activities, social circles, and exercise resources are primarily concentrated on campus. Individual and interpersonal-organizational-level factors can more directly reflect their current PA status and influencing mechanisms. Second, relevant data at the individual and interpersonal-organizational levels are easier to measure and collect in university student populations. In contrast, assessing the community and policy levels requires more complex community environment analysis and cross-departmental data integration, which is more difficult and may exceed the scope of this study.\u003c/p\u003e\u003cp\u003eBased on the aforementioned research model and methods, this study explores the factors influencing PA in Chinese university students, providing a scientific basis for formulating targeted sports intervention policies and health promotion strategies. Integrating the SEM and RF enriches and expands the analytical methods in the field of PA research, providing a new perspective for related studies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipants\u003c/h2\u003e\n \u003cp\u003eThis study\u0026rsquo;s participants were students enrolled in regular higher education institutions in mainland China. The Ministry of Education\u0026rsquo;s \u0026ldquo;List of National Regular Institutions of Higher Education (as of June 20, 2024)\u0026rdquo; was used as the list. This study strictly adhered to the Herschel Declaration, and it has been approved by the Ethics Committee of Nantong University (2022 [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e]).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSampling Methods\u003c/h3\u003e\n\u003cp\u003eThis study primarily employed epidemiological survey methods. The survey covered most regions of China, including provinces such as Jiangsu, Shanghai, Shandong, Jilin, Henan, Sichuan, Chongqing, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang, Guangxi, Inner Mongolia, and Hainan. A total of 10,182 valid questionnaires were obtained. The survey subjects were undergraduate students enrolled in regular higher education institutions in China, including both junior college and bachelor\u0026rsquo;s degree students, excluding graduate students (Master\u0026rsquo;s and Doctoral). This study used stratified, cluster, and multi-stage sampling methods to select survey subjects based on geographical area (e.g., province, city administrative level) and university type (e.g., comprehensive university vs. local college). The specific sampling steps are as follows:\u003c/p\u003e\n\u003ch3\u003eDetermination of Sampling Locations\u003c/h3\u003e\n\u003cp\u003eTo ensure the representativeness of the test subjects, an average of three sampling locations were allocated to each province (autonomous region, or municipality). An equal number of samples were drawn from different cities, using the following specific procedures: Prefecture-level cities under the jurisdiction of each province and autonomous region were selected as sampling locations. Among them, the provincial capital city was designated as a \u0026ldquo;Category 1\u0026rdquo; sampling location; the principles for determining the other two cities were to select one city with a general level of socio-economic development as a \u0026ldquo;Category 2\u0026rdquo; sampling location and one city with a relatively poor level of social and economic growth as a \u0026ldquo;Category 3\u0026rdquo; sampling location, while considering the geographical location of the province or autonomous region. Sample extraction in municipalities directly under the central government did not consider the above principles, with random cluster sampling being the primary method. Still, the quantity principle of three sampling locations was considered.\u003c/p\u003e\n\u003ch3\u003eDetermination of Sampling Units\u003c/h3\u003e\n\u003cp\u003eThe selection of sampling units mainly considered four aspects: First, the affiliated institutions of higher education should be fully established institutions of higher education registered with the Ministry of Education, including higher vocational colleges and junior colleges; second, the units should be able to meet the sampling requirements (i.e., age, number of people, grade distribution, etc.); third, there should be a specific person in charge of questionnaire distribution, who is willing to participate in long-term monitoring; and fourth, the university students in the sampling units have completed their return to school for the fall semester.\u003c/p\u003e\n\u003ch3\u003eGrouping\u003c/h3\u003e\n\u003cp\u003eThe samples were divided into two groups according to sex (male, female) and then into eight categories according to grade level.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eData Cleaning Rules and Selection\u003c/h2\u003e\n \u003cp\u003eDuring data preprocessing, data with logical errors, omissions, errors, and unidentifiable entries were retested or eliminated to ensure the authenticity and validity of the data. The following rules were used to include valid questionnaires: First, questionnaires with unidentifiable full names of schools were deleted. Second, questionnaires with ages below 18 or above 25 were deleted. Third, questionnaires with at least 21 consecutive \u0026ldquo;completely consistent\u0026rdquo; answers were deleted. Fourth, after eliminating the questionnaires mentioned above, the average completion time of the remaining questionnaires was 539 seconds. Questionnaires with completion times in the [0, 5%] and [95%, 100%] positions were deleted.\u003c/p\u003e\n \u003cp\u003eThis study selected 10,182 Chinese university students aged 18\u0026ndash;25 as research subjects. Questionnaire data collection was conducted online, with researchers and instructors present during data collection. At the beginning of the study, researchers provided participants with an informed consent form, which clearly stated the subjects\u0026lsquo; purpose, methods, potential risks, and rights, ensuring that participants voluntarily participated in the study on a fully informed basis. All participants were told that the questionnaire would take approximately 12 minutes to complete, that they could withdraw from the study at any time, and that there would be no adverse consequences. A preliminary survey was conducted before the implementation of the questionnaire, and the questionnaire design was optimized based on feedback. Participants\u0026rsquo; responses were anonymous, and the obtained sample data were kept confidential to reduce self-report data bias.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSelection and Coding of Scales\u003c/h3\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003ePhysical Activity\u003c/h2\u003e\n \u003cp\u003eThe IPAQ short form was used to measure PA in university students[\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e]. This study used the Chinese version translated by Qu Ningning et al.[\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e], and according to the scoring rules, divided university students\u0026rsquo; PA into three levels: \u0026ldquo;Vigorous intensity PA (VPA),\u0026rdquo; \u0026ldquo;Moderate intensity PA (MPA),\u0026rdquo; and \u0026ldquo;Light intensity PA (LPA)\u0026rdquo;[\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. The specific criteria are: 1) VPA is defined as physical activity with a metabolic equivalent of 6.0 or higher in absolute terms; in terms of individual ability standards, calculated on a score range of 0\u0026ndash;10, VPA is usually 7 or 8 points. 2) MPA is defined as moderate-intensity activity 3 to 6 times less intense than resting in absolute terms; in terms of individual ability standards, calculated on a score range of 0\u0026ndash;10, MPA is usually 5 or 6 points. 3) LPA is defined as light-intensity physical activity with a metabolic equivalent of 1.5 to 3, meaning that energy consumption does not exceed 3 times the energy consumption at rest; such activities include strolling, bathing, or other casual activities that do not cause a significant increase in heart rate or breathing rate.\u003c/p\u003e\n \u003cp\u003eThe scoring results ranged from 1 (LPA) to 3 (VPA). The intra-group correlation coefficients for each physical activity item in this scale were all above 0.7[\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. It has also undergone reliability and validity tests worldwide, has good reliability and validity[\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e], and can well reflect the level of physical activity. The WHO 2020 guidelines on physical activity and sedentary behavior state that all adults should engage in 150\u0026ndash;300 minutes of MPA, 75\u0026ndash;150 minutes of VPA, or an equivalent combination of moderate- and vigorous-intensity aerobic physical activity per week[\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]. Therefore, when assessing PA levels in this study, \u0026ldquo;MPA\u0026rdquo; and \u0026ldquo;VPA\u0026rdquo; from the IPAQ were combined into moderate to vigorous physical activity (MVPA), named the achieving group.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eIndependent Variables\u003c/h2\u003e\n \u003cp\u003eBased on McLeroy\u0026rsquo;s hierarchical analysis framework[\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e], 39 variables were selected and included in the individual, interpersonal, and organizational levels, and these variables were coded. Among them, sex, grade, mastery of sports skills, screen time, exercise motivation, nearsightedness status, average monthly living expenses, self-rated health level, sleep quality, self-esteem level, student peer relationships, smoking behavior, relationship status, mobile phone addiction tendency, and alcohol consumption were categorical variables. Psychological resilience level, exercise adherence level, health literacy level, depression level, anxiety level, general self-efficacy, self-emotional management ability, life satisfaction level, and leisure guilt level were continuous variables. The variables in parentheses () are sub-dimension variables of the preceding variables. These variables were collected using previously published questionnaires. The specific questionnaires used, the reliability and validity of each questionnaire, and their classification and coding in the social ecology model are shown in the following table:\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOverview of Scales and Codes for Independent Variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eScale\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReliability and validity indicators\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCoding\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDemographic Information\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e/\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Male; 2\u0026thinsp;=\u0026thinsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e/\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Freshman; 2\u0026thinsp;=\u0026thinsp;Sophomore; 3\u0026thinsp;=\u0026thinsp;Junior; 4\u0026thinsp;=\u0026thinsp;Senior\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndividual Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMastery of Sports Skills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e/\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;0 items; 2\u0026thinsp;=\u0026thinsp;1 item; 3\u0026thinsp;=\u0026thinsp;2 items or more\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScreen Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e/\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;\u0026le;\u0026thinsp;3h/d; 2\u0026thinsp;=\u0026thinsp;3h/d\u0026thinsp;\u0026le;\u0026thinsp;Screen Time\u0026thinsp;\u0026le;\u0026thinsp;8h/d; 3\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;8h/d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Motivation (Health)\u003c/p\u003e\n \u003cp\u003e(I want to stay healthy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eExercise Motivation Scale\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;\u0026alpha;\u0026thinsp;=\u0026thinsp;0.922\u003c/p\u003e\n \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e=3604.140\u003c/p\u003e\n \u003cp\u003eNFI\u0026thinsp;=\u0026thinsp;0.950\u003c/p\u003e\n \u003cp\u003eNNFI\u0026thinsp;=\u0026thinsp;0.950\u003c/p\u003e\n \u003cp\u003eCFI\u0026thinsp;=\u0026thinsp;0.950\u003c/p\u003e\n \u003cp\u003eIFI\u0026thinsp;=\u0026thinsp;0.950\u003c/p\u003e\n \u003cp\u003eRMSEA\u0026thinsp;=\u0026thinsp;0.091\u003c/p\u003e\n \u003cp\u003eSRMR\u0026thinsp;=\u0026thinsp;0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Neutral; 4\u0026thinsp;=\u0026thinsp;Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Motivation (Appearance) (I want to maintain or improve my figure)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eExercise Motivation Scale\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Neutral; 4\u0026thinsp;=\u0026thinsp;Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Motivation (Fun)\u003c/p\u003e\n \u003cp\u003e(I want to stay in a good mood)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eExercise Motivation Scale\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Neutral; 4\u0026thinsp;=\u0026thinsp;Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Motivation (Ability)\u003c/p\u003e\n \u003cp\u003e(I want to improve my current athletic performance)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eExercise Motivation Scale\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Neutral; 4\u0026thinsp;=\u0026thinsp;Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage Monthly Living Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e/\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;1000 RMB and below; 2\u0026thinsp;=\u0026thinsp;1000 to 2000 RMB; 3\u0026thinsp;=\u0026thinsp;2000 to 3000 RMB; 4\u0026thinsp;=\u0026thinsp;3000\u0026ndash;4000 RMB; 5\u0026thinsp;=\u0026thinsp;Above 4000 RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-Rated Health Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSF-36 (In general, would you say your health is?)\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;\u0026alpha;\u0026thinsp;=\u0026thinsp;0.840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Poor; 2\u0026thinsp;=\u0026thinsp;Fair; 3\u0026thinsp;=\u0026thinsp;Good; 4\u0026thinsp;=\u0026thinsp;Very Good; 5\u0026thinsp;=\u0026thinsp;Excellent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePSQI\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;\u0026alpha;\u0026thinsp;=\u0026thinsp;0.994\u003c/p\u003e\n \u003cp\u003eCFI=0.980\u003c/p\u003e\n \u003cp\u003eGFI=0.970\u003c/p\u003e\n \u003cp\u003eRESEA=0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Very Good; 2\u0026thinsp;=\u0026thinsp;Fair; 3\u0026thinsp;=\u0026thinsp;Average; 4\u0026thinsp;=\u0026thinsp;Very Poor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-Esteem Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSEL\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Does Not Apply; 2\u0026thinsp;=\u0026thinsp;Slightly Does Not Apply; 3\u0026thinsp;=\u0026thinsp;Applies; 4\u0026thinsp;=\u0026thinsp;Strongly Applies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNearsightedness Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e/\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Nearsighted; 2\u0026thinsp;=\u0026thinsp;Not Nearsighted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking Behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e/\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Never Smokes; 2\u0026thinsp;=\u0026thinsp;Occasionally Smokes; 3\u0026thinsp;=\u0026thinsp;Smokes but No Addiction; 4\u0026thinsp;=\u0026thinsp;Addicted but Controlled; 5\u0026thinsp;=\u0026thinsp;Addicted and Uncontrolled\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMobile Phone Addiction Tendency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCollege Student Mobile Phone Addiction Tendency Scale\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.830\u003c/p\u003e\n \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e/df\u0026thinsp;=\u0026thinsp;2.92\u003c/p\u003e\n \u003cp\u003eRMSEA\u0026thinsp;=\u0026thinsp;0.07\u003c/p\u003e\n \u003cp\u003eCFI\u0026thinsp;=\u0026thinsp;0.96\u003c/p\u003e\n \u003cp\u003eNFI\u0026thinsp;=\u0026thinsp;0.94\u003c/p\u003e\n \u003cp\u003eIFI\u0026thinsp;=\u0026thinsp;0.96\u003c/p\u003e\n \u003cp\u003eRFI\u0026thinsp;=\u0026thinsp;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Relatively Disagree; 3\u0026thinsp;=\u0026thinsp;Unsure; 4\u0026thinsp;=\u0026thinsp;Relatively Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlcohol Consumption Behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e/\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Never Drinks; 2\u0026thinsp;=\u0026thinsp;Occasionally Drinks; 3\u0026thinsp;=\u0026thinsp;Drinks but No Addiction; 4\u0026thinsp;=\u0026thinsp;Addicted but Controlled; 5\u0026thinsp;=\u0026thinsp;Addicted and Uncontrolled\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological Resilience\u003c/p\u003e\n \u003cp\u003e(Goal Focus)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAdolescent Psychological Resilience Scale (T3, 4, 11, 20, 24)\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.830\u003c/p\u003e\n \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e/df\u0026thinsp;=\u0026thinsp;2.510\u003c/p\u003e\n \u003cp\u003eRMSEA\u0026thinsp;=\u0026thinsp;0.070\u003c/p\u003e\n \u003cp\u003eCFI\u0026thinsp;=\u0026thinsp;0.920\u003c/p\u003e\n \u003cp\u003eGFI\u0026thinsp;=\u0026thinsp;0.830\u003c/p\u003e\n \u003cp\u003eAGFI\u0026thinsp;=\u0026thinsp;0.810\u003c/p\u003e\n \u003cp\u003eNNFI\u0026thinsp;=\u0026thinsp;0.910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Relatively Disagree; 3\u0026thinsp;=\u0026thinsp;Unsure; 4\u0026thinsp;=\u0026thinsp;Relatively Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological Resilience\u003c/p\u003e\n \u003cp\u003e(Emotional Control)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAdolescent Psychological Resilience Scale (T1, 2, 5, 21, 23, 27)\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Relatively Disagree; 3\u0026thinsp;=\u0026thinsp;Unsure; 4\u0026thinsp;=\u0026thinsp;Relatively Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological Resilience\u003c/p\u003e\n \u003cp\u003e(Positive Cognition)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAdolescent Psychological Resilience Scale (T10, 13, 14, 25)\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Relatively Disagree; 3\u0026thinsp;=\u0026thinsp;Unsure; 4\u0026thinsp;=\u0026thinsp;Relatively Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological Resilience Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAdolescent Psychological Resilience Scale\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Relatively Disagree; 3\u0026thinsp;=\u0026thinsp;Unsure; 4\u0026thinsp;=\u0026thinsp;Relatively Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Adherence (Exercise Behavior)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePhysical Exercise Adherence Scale (T1-T4)\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.947\u003c/p\u003e\n \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e/df\u0026thinsp;=\u0026thinsp;2.896\u003c/p\u003e\n \u003cp\u003eCFI\u0026thinsp;=\u0026thinsp;0.945\u003c/p\u003e\n \u003cp\u003eGFI\u0026thinsp;=\u0026thinsp;0.901\u003c/p\u003e\n \u003cp\u003eRESEA\u0026thinsp;=\u0026thinsp;0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Neutral; 4\u0026thinsp;=\u0026thinsp;Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Adherence (Effort Investment)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePhysical Exercise Adherence Scale (T5-T9)\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Neutral; 4\u0026thinsp;=\u0026thinsp;Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Adherence (Emotional Experience)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePhysical Exercise Adherence Scale (T10-T14)\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Neutral; 4\u0026thinsp;=\u0026thinsp;Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Adherence Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePhysical Exercise Adherence Scale\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Neutral; 4\u0026thinsp;=\u0026thinsp;Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth Literacy (Health Care)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHLS-SF9(T1-T3)\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.913\u003c/p\u003e\n \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e/df\u0026thinsp;=\u0026thinsp;10.844\u003c/p\u003e\n \u003cp\u003eGFI\u0026thinsp;=\u0026thinsp;0.985\u003c/p\u003e\n \u003cp\u003eAGFI\u0026thinsp;=\u0026thinsp;0.971\u003c/p\u003e\n \u003cp\u003eNFI\u0026thinsp;=\u0026thinsp;0.986\u003c/p\u003e\n \u003cp\u003eCFI\u0026thinsp;=\u0026thinsp;0.987\u003c/p\u003e\n \u003cp\u003eRMSEA\u0026thinsp;=\u0026thinsp;0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Very Difficult; 2\u0026thinsp;=\u0026thinsp;Difficult; 3\u0026thinsp;=\u0026thinsp;Easy; 4\u0026thinsp;=\u0026thinsp;Very Easy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth Literacy (Disease Prevention)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHLS-SF9(T4-T6)\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Very Difficult; 2\u0026thinsp;=\u0026thinsp;Difficult; 3\u0026thinsp;=\u0026thinsp;Easy; 4\u0026thinsp;=\u0026thinsp;Very Easy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth Literacy (Health Promotion)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHLS-SF9(T7-T9)\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Very Difficult; 2\u0026thinsp;=\u0026thinsp;Difficult; 3\u0026thinsp;=\u0026thinsp;Easy; 4\u0026thinsp;=\u0026thinsp;Very Easy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth Literacy Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHLS-SF9\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Very Difficult; 2\u0026thinsp;=\u0026thinsp;Difficult; 3\u0026thinsp;=\u0026thinsp;Easy; 4\u0026thinsp;=\u0026thinsp;Very Easy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDepression Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCES-D\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Rarely or Never; 2\u0026thinsp;=\u0026thinsp;Sometimes; 3\u0026thinsp;=\u0026thinsp;Often or Half the Time; 4\u0026thinsp;=\u0026thinsp;Most of the Time or Constantly\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnxiety Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGAD-7\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Not at All; 2\u0026thinsp;=\u0026thinsp;Several Days; 3\u0026thinsp;=\u0026thinsp;Over a Week; 4\u0026thinsp;=\u0026thinsp;Nearly Every Day\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCollege Student Physical Exercise Self-Efficacy Scale\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.908\u003c/p\u003e\n \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e/df\u0026thinsp;=\u0026thinsp;2.688\u003c/p\u003e\n \u003cp\u003eGFI\u0026thinsp;=\u0026thinsp;0.958\u003c/p\u003e\n \u003cp\u003eAGFI\u0026thinsp;=\u0026thinsp;0.932\u003c/p\u003e\n \u003cp\u003eNFI\u0026thinsp;=\u0026thinsp;0.970\u003c/p\u003e\n \u003cp\u003eCFI\u0026thinsp;=\u0026thinsp;0.981\u003c/p\u003e\n \u003cp\u003eIFI\u0026thinsp;=\u0026thinsp;0.975\u003c/p\u003e\n \u003cp\u003eRMSEA\u0026thinsp;=\u0026thinsp;0.066\u003c/p\u003e\n \u003cp\u003eRMR\u0026thinsp;=\u0026thinsp;0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Does Not Apply; 2\u0026thinsp;=\u0026thinsp;Slightly Does Not Apply; 3\u0026thinsp;=\u0026thinsp;Applies; 4\u0026thinsp;=\u0026thinsp;Strongly Applies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-Emotional Management Ability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEIS\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Relatively Disagree; 3\u0026thinsp;=\u0026thinsp;Unsure; 4\u0026thinsp;=\u0026thinsp;Relatively Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLife Satisfaction Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSWLS\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.780\u003c/p\u003e\n \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e/df\u0026thinsp;=\u0026thinsp;6.710\u003c/p\u003e\n \u003cp\u003eGFI\u0026thinsp;=\u0026thinsp;0.970\u003c/p\u003e\n \u003cp\u003eCFI\u0026thinsp;=\u0026thinsp;0.960\u003c/p\u003e\n \u003cp\u003eRMSEA\u0026thinsp;=\u0026thinsp;0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Slightly Disagree; 4\u0026thinsp;=\u0026thinsp;I\u0026rsquo;m Not Sure; 5\u0026thinsp;=\u0026thinsp;Slightly Agree; 6\u0026thinsp;=\u0026thinsp;Agree; 7\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeisure Guilt Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRest Guilt Scale Short Version\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.960\u003c/p\u003e\n \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e/df\u0026thinsp;=\u0026thinsp;3.580\u003c/p\u003e\n \u003cp\u003eCFI\u0026thinsp;=\u0026thinsp;0.940\u003c/p\u003e\n \u003cp\u003eRFI\u0026thinsp;=\u0026thinsp;0.910\u003c/p\u003e\n \u003cp\u003eTLI\u0026thinsp;=\u0026thinsp;0.930\u003c/p\u003e\n \u003cp\u003eRMSEA\u0026thinsp;=\u0026thinsp;0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Slightly Disagree; 4\u0026thinsp;=\u0026thinsp;I\u0026rsquo;m Not Sure; 5\u0026thinsp;=\u0026thinsp;Slightly Agree; 6\u0026thinsp;=\u0026thinsp;Agree; 7\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpersonal-Organizational Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise Motivation (Social) (I want to improve my friendship)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eExercise Motivation Scale\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSame as above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Disagree; 3\u0026thinsp;=\u0026thinsp;Neutral; 4\u0026thinsp;=\u0026thinsp;Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent Peer Relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eStudent Peer Relationship Scale\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026thinsp;=\u0026thinsp;0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Does Not Apply; 2\u0026thinsp;=\u0026thinsp;Slightly Does Not Apply; 3\u0026thinsp;=\u0026thinsp;Applies; 4\u0026thinsp;=\u0026thinsp;Strongly Applies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRelationship Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e/\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Single; 2\u0026thinsp;=\u0026thinsp;In a Relationship; 3\u0026thinsp;=\u0026thinsp;In Love\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological Resilience (Family Support)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAdolescent Psychological Resilience Scale (T8, 15, 16, 17, 19, 22)\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSame as above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Relatively Disagree; 3\u0026thinsp;=\u0026thinsp;Unsure; 4\u0026thinsp;=\u0026thinsp;Relatively Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological Resilience (Interpersonal Assistance)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAdolescent Psychological Resilience Scale (T6, 7, 9, 12, 18, 26)\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Strongly Disagree; 2\u0026thinsp;=\u0026thinsp;Relatively Disagree; 3\u0026thinsp;=\u0026thinsp;Unsure; 4\u0026thinsp;=\u0026thinsp;Relatively Agree; 5\u0026thinsp;=\u0026thinsp;Strongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eRandom Forest Model Construction\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eRF is a bootstrap aggregating algorithm composed of multiple decision trees. Each decision tree is a weak learner, and they determine the final prediction result through voting or averaging (as shown in Fig. 1). The basic parameters for building the prediction model are set by configuring different numbers of learners (n_estimators), minimum samples for splitting an internal node (min_samples_split), minimum number of samples required to be at a leaf node (min_samples_leaf), maximum depth of the tree (max_depth), maximum number of leaf nodes (max_leaf_nodes), and minimum impurity decrease (min_impurity_decrease).\u003c/p\u003e\n \u003cp\u003eIn this study, the training set accounted for 80%, and the test set accounted for 20%. Combining the grid search method for hyperparameter optimization[\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e] and the 5-fold cross-validation method[\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e], the RF classification model was trained, predicted, and optimized to maximize accuracy as the parameter optimization target. The specific parameters are shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOverview of Parameter Optimization Results for Random Forest Algorithm\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel Parameter Name\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSearch Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en_estimators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emin_samples_split\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emin_samples_leaf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emax_depth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emax_leaf_nodes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emin_impurity_decrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eDescriptive Analysis\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that among university students who achieved MVPA, the proportion of males was significantly higher than that of females (28.5% vs 16.0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a large sex difference effect size (V\u0026thinsp;=\u0026thinsp;0.349). Mastery of Sports Skills was strongly correlated with PA level, with students mastering 2 or more skills having a higher proportion in the achieving group (34.6% vs 31.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Positive attitudes towards Exercise Motivation (Ability, Social, and Fun) were more prominent in the achieving group (13.9% vs 7.6%). Regarding Alcohol Consumption Level, the proportion of \"Occasionally Drinks\" was higher in the achieving group (19.8% vs 20.0%).\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\u003eOverview of Descriptive Analysis\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=\"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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e\u003cp\u003ePhysical Activity (Whether MVPA is Achieved)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eNot Achieving Group (5653)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eAchieving Group (4529)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en/M\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e%/sd\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003en/M\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e%/sd\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ex\u003csup\u003e2\u003c/sup\u003e/t\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eV/η\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1238.989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.349\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1647\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2900\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e4006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1629\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e60.711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFreshman\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2652\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e59.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSophomore\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e31.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJunior\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e275\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSenior\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e152\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMastery of Sports\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSkills\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e511.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 items\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 item\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1963\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e867\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 items or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3519\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e34.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eScreen Time\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e27.783\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;3h/d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e551\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e590\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3h/d\u0026thinsp;\u0026le;\u0026thinsp;Screen\u003c/p\u003e\u003cp\u003eTime\u0026thinsp;\u0026le;\u0026thinsp;8h/d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e4135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e31.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;8h/d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e967\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e772\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise Motivation (Health)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e468.573\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1464\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e780\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3308\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e772\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1390\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise Motivation (Appearance)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e405.576\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e153\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1582\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e945\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e772\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1338\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise Motivation (Fun)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e584.112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e774\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1433\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e14.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise Motivation (Ability)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e826.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1953\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e836\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2870\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e21.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1416\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise Motivation (Social)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e578.544\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.238\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e381\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeutral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2465\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e499\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNearsightedness Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e132.216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNearsighted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e4627\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e32.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot Nearsighted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAverage Monthly\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLiving Expenses\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e41.291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1000 RMB and\u003c/p\u003e\u003cp\u003ebelow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e654\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e457\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1000 to 2000\u003c/p\u003e\u003cp\u003eRMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e4407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e43.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3453\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2000 to 3000\u003c/p\u003e\u003cp\u003eRMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e520\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e501\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3000\u0026ndash;4000 RMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbove 4000\u003c/p\u003e\u003cp\u003eRMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSelf-Rated Health\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e290.724\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1691\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e987\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1381\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery Good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExcellent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e501\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSleep Quality\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e41.764\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery Good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1425\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2864\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAverage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e979\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery Poor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSelf-Esteem Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e133.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDoes Not Apply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e887\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e578\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlightly Does\u003c/p\u003e\u003cp\u003eNot\u003c/p\u003e\u003cp\u003eApply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e37.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e918\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eStudent Peer\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eRelationships\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e153.769\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDoes Not Apply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlightly Does\u003c/p\u003e\u003cp\u003eNot\u003c/p\u003e\u003cp\u003eApply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApplies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3440\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2492\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Applies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e906\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSmoking Behavior\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e255.142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.158\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNever Smokes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e5285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e51.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOccasionally\u003c/p\u003e\u003cp\u003eSmokes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e314\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmokes but No\u003c/p\u003e\u003cp\u003eAddiction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAddicted but\u003c/p\u003e\u003cp\u003eControlled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAddicted and\u003c/p\u003e\u003cp\u003eUncontrolled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRelationship Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e169.449\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIn a Relationship\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1316\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1348\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIn Love\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMobile Phone\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAddiction Tendency\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e133.392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e536\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRelatively Disagree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnsure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRelatively Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1807\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1312\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStrongly Agree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e331\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e401\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAlcohol Consumption Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e268.181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNever Drinks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2899\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1632\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOccasionally\u003c/p\u003e\u003cp\u003eDrinks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDrinks but No\u003c/p\u003e\u003cp\u003eAddiction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e567\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAddicted but\u003c/p\u003e\u003cp\u003eControlled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAddicted and\u003c/p\u003e\u003cp\u003eUncontrolled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAddicted and\u003c/p\u003e\u003cp\u003eDrinks\u003c/p\u003e\u003cp\u003eDaily\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePsychological Resilience\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(Goal Focus)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e18.518\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e106.105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePsychological Resilience\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(Emotional Control)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e17.232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.847\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.417\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e107.383\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePsychological Resilience\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(Positive Cognition)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e15.268\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.601\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.762\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.945\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e80.611\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePsychological Resilience\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(Family Support)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e17.777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.415\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.766\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.691\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.826\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePsychological Resilience\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(Interpersonal Assistance)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e17.454\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.362\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7.620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePsychological Resilience Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e86.250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.483\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e86.450\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.313\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise Adherence (Exercise Behavior)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e50.417\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e56.307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.813\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1317.810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise Adherence (Effort Investment)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e9.551\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.795\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e66.233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise Adherence\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(Emotional Experience)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e9.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e91.957\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise Adherence Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e9.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.408\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e193.773\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth Literacy (Health Care)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e27.938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e28.909\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.463\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e135.579\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth Literacy (Disease Prevention)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e13.546\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.602\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.866\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1814.827\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.151\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth Literacy (Health Promotion)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e18.117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.403\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1006.937\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth Literacy Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e18.754\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.875\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.258\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e653.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDepression Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e15.377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.763\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.588\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAnxiety Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e10.674\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.243\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSelf-Efficacy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e18.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.608\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.681\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e223.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSelf-Emotional Management Ability\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e32.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.954\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.478\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.489\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLife Satisfaction Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e23.149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.453\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23.891\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e42.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLeisure Guilt Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e29.875\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30.808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.790\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e108.534\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\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=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eModel Performance Metrics\u003c/h2\u003e\u003cp\u003eA Confusion Matrix and ROC Curve were selected to evaluate model performance. The four evaluation metrics in the Confusion Matrix range from 0 to 1, with larger values indicating better model performance. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the performance parameters of the test set. Overall, the model\u0026rsquo;s performance was good. The AUC (Area Under the ROC Curve) quantifies the model\u0026rsquo;s overall performance under the ROC curve. The AUC value ranges from 0 to 1, with larger values indicating better model performance. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that the AUC value for this model is 0.760, indicating good model performance.\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\u003eConfusion Matrix and Modeling Evaluation Score Results\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=\"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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eConfusion Matrix\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eModeling Evaluation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003ePredicted Value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAccuracy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.704\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePrecision\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.711\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eReal Value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3760\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e731\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRecall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.689\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1680\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1975\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF1 Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.696\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=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eAnalysis of the Importance of Influencing Factors\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the Feature Contribution Chart, shows the importance of each feature in the model. The higher the feature contribution, the more critical the feature\u0026rsquo;s role in the model prediction. The results show that Exercise Adherence (Exercise Behavior), Exercise Adherence Level, Sex, Exercise Adherence (Effort Investment), Exercise Motivation (Ability), Exercise Adherence (Emotional Experience), Mastery of Sports Skills, Exercise Motivation (Social), Exercise Motivation (Fun), and Alcohol Consumption Level are the top ten contributing variables.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e is a Feature Contribution Chart for Permuted Variables. This chart evaluates a feature\u0026rsquo;s importance by randomly permuting each feature\u0026rsquo;s values and observing the change in model performance. The results indicate that the variables with the most significant positive contribution are: Exercise Adherence (Exercise Behavior), Sex, Relationship Status, Mastery of Sports Skills, Exercise Motivation (Health), Alcohol Consumption Level, and Smoking Behavior. The variables with the most significant negative contribution are: Exercise Adherence (Emotional Experience), Exercise Motivation (Social), Exercise Motivation (Ability), Exercise Adherence Level, and Exercise Adherence (Effort Investment).\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e is a SHAP (SHapley Additive exPlanations) summary plot. In this plot, dark green dots represent a smaller value for that feature variable. If the SHAP values of these points are negative, it indicates that the low-value feature hurts the dependent variable; if the SHAP values are positive, it suggests that the low-value feature positively impacts the dependent variable. Light green dots indicate the opposite. According to the results in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Exercise Adherence (Exercise Behavior), Sex, Exercise Adherence Level, Exercise Adherence (Effort Investment), Mastery of Sports Skills, Exercise Motivation (Ability), Alcohol Consumption Level, Exercise Adherence (Emotional Experience), Exercise Motivation (Social), and Exercise Motivation (Fun) are the top 10 contributing variables.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study systematically identified the key influencing factors of PA in university students using the feature importance analysis of the RF model. Exercise Adherence (Exercise Behavior) and its sub-dimensions, Exercise Motivation, Sex, Mastery of Sports Skills, and Alcohol Consumption Level, were confirmed as the most critical predictors, consistent with previous literature findings, and deepened the understanding of PA in university students.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe results of this study revealed that Exercise Adherence is the most significant predictor of PA, consistent with previous research\u003c/b\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. However, this study further revealed the independent contributions of the sub-dimensions of Exercise Adherence to PA, which has been less frequently mentioned in previous studies. Exercise Adherence (Exercise Behavior) is the most critical predictor of PA. The descriptive analysis showed that university students who achieved MVPA generally had higher scores in Exercise Adherence than those who did not achieve MVPA. The SHAP summary plot of the RF model also showed that Exercise Adherence values were widely distributed and ranked highly. Therefore, whether university students can adhere to exercise makes an essential contribution to the accurate prediction of meeting PA recommendations. In this study, Exercise Adherence, as an individual-level factor in the social-ecological model, showed that individuals who actively participate in physical exercise can improve individual mental health and well-being, alleviate depression, stress, and anxiety[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] at the psychological level; and enhance cardiopulmonary function, increase muscle volume and strength, and improve learning and memory abilities[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] at the physiological level, providing numerous benefits. Current research indicates that a key challenge in promoting PA lies in the discrepancy between an individual\u0026rsquo;s intention to exercise and their actual behavior, i.e., the intention-behavior gap. Despite having a firm intention to exercise, individuals are influenced by various factors that prevent them from implementing corresponding exercise behaviors[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In this study, the high contribution of individual-level Exercise Adherence (Emotional Experience) and interpersonal-organizational level Exercise Motivation (Social) to the prediction model reveals possible related reasons. According to the concept of self-efficacy in Social Cognitive Theory[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], in addition to adhering to exercise, the \u0026ldquo;emotional value\u0026rdquo; that this behavior brings to individuals also provides a possible effect. This \u0026ldquo;emotional value\u0026rdquo; may include, but is not limited to, the encouragement and praise from people around them, and the social attributes brought about by finding friends to persist in physical exercise together[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Previous studies have also confirmed this point. For example, a study in 2021 demonstrated that enjoyment and motivation significantly affect the persistence of individual exercise[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Another study also demonstrated that exercisers\u0026rsquo; perceived autonomous support positively impacts meeting basic psychological needs[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Therefore, to promote exercise adherence in university students, increase PA, and reduce the intention-behavior gap, and actively leverage the role of social support and emotional value in exercise adherence, methods such as organizing sports groups, sports club activities, and fun sports events can be used to integrate individual emotional experiences with social support from multiple levels of the social-ecological model, providing comprehensive exercise support for university students, developing positive exercise habits, thereby improving PA levels.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSex is the second most significant factor in predicting PA in university students, with males having a positive impact and females hurting PA prediction. This is consistent with previous research findings\u003c/b\u003e[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Although sex itself, as a physiological characteristic, is not amenable to intervention, the differences in socio-cultural preferences and behavioral patterns it reflects are still worth noting. Existing research proves that males and females are unequal in PA, with girls generally being less physically active than boys [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], and inequality is higher in high-income countries and countries with high human development index rankings[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Studies have also shown that the sex gap narrows in vigorous-intensity PA, while it increases in moderate-intensity PA[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. This may be because women participate more in aerobic exercise, with lower PA intensity[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], and lack exercise energy and willpower in physical activity[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. At the same time, it may also be related to the socialization process of gender roles. Men are more likely to regard PA as a way to display strength and compete, and are more likely to challenge high-intensity PA to prove their masculine charm, resulting in higher levels of PA. Conversely, women may be more concerned with the social attributes or appearance improvement of physical activity. A toolkit document on gender equality in the field of sports, jointly developed by the European Union and the Council of Europe, also shows that men are more likely to engage in sports or physical activity for entertainment (33%), to be with friends (22%), or to improve physical performance (29%). In comparison, women are more concerned with controlling weight (24%), improving appearance (21%), or offsetting the effects of aging (15%)[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Therefore, in future teaching processes, gender equality indicators can be incorporated into the school sports system, and the willingness of girls to exercise can be improved by adding diverse intensity options to the curriculum and avoiding a single competitive orientation. Alternatively, gender-mixed group courses can be offered, such as fun physical fitness challenges and team collaboration tasks, to weaken competitiveness, enhance social attributes, and cater to the needs of both men and women.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe results of this study also show that Exercise Motivation (Ability), i.e., \u0026ldquo;I exercise to improve sports skills,\u0026rdquo; and Mastery of Sports Skills are also essential factors in predicting PA in university students.\u003c/b\u003e Studies have shown that developing sports skills is a primary potential mechanism for promoting individual participation in PA[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], and mastering more sports skills can encourage individuals to participate in more PA. A long-term randomized controlled trial also found that students in the special sports skill training group significantly outperformed the general physical education class group regarding PA and physical fitness[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. This may be achieved through two pathways, namely the self-efficacy pathway and the social support pathway. According to Self-Efficacy Theory[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] and Social Cognitive Theory[\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], university students\u0026rsquo; PA behavior is influenced by their cognitive factors and environment. When individuals master more sports skills, they are more likely to perform well in sports activities, further enhancing their willingness to participate in PA, thereby improving PA levels. At the same time, students who master various sports skills are also more likely to engage in diverse sports, such as combining endurance training and strength training[\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e], to improve PA levels. In some team sports, sports that require teamwork (such as basketball and volleyball) can better promote communication and interaction among university students, enhance the fun and social attributes of PA, and are linked to Exercise Motivation (Social) at the interpersonal-organizational level of the social-ecological model, thereby reducing anxiety and depression and promoting PA[\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Therefore, future research should focus on improving the number and proficiency of sports skills mastered by university students. It is possible to promote university students to master more sports skills and improve PA levels by organizing sports skill training classes, sports skill mutual aid groups, or amateur competitive competitions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIn addition to Exercise Adherence, Exercise Motivation, and Mastery of Sports Skills, this study also found that Alcohol Consumption Level and Smoking Behavior may impact PA.\u003c/b\u003e There is overwhelming evidence that alcohol and smoking can cause damage to the body[\u003cspan additionalcitationids=\"CR73 CR74 CR75 CR76\" citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Long-term alcohol consumption can lead to alcohol dependence. This rewarding, chronic relapsing disease can cause significant harm to human health[\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e], such as the brain nerves, liver, digestive system, immune system, and cardiovascular system[\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Smoking can lead to a variety of fatal diseases, including lung cancer, respiratory diseases, and cardiovascular diseases (such as coronary heart disease)[\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. A cross-sectional study showed that smoking and alcohol have a synergistic effect, and the two can jointly damage the liver[\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Therefore, reducing alcohol consumption and smoking is of great significance for maintaining the physical health of university students, and participating in PA provides a possible solution to this problem. One study showed that PA level is linearly negatively correlated with alcohol consumption; that is, people who are more physically active drink less alcohol, and people who are less physically active drink relatively more alcohol[\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Another study showed that individuals with higher levels of PA are less likely to smoke[\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. These are consistent with the results of this study, which means that participating in more PA will reduce alcohol consumption and the possibility of smoking. At the same time, regular moderate-to-vigorous physical exercise can also offset the adverse metabolic effects of alcohol on liver function, inflammation, and lipid status[\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. The possible reason for this is that PA reduces alcohol intake caused by reward properties by regulating the reward system and emotional state, thereby offsetting the adverse effects of alcohol to a certain extent, thus reducing alcohol consumption[\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. However, it should be noted that some studies have also proved that PA is positively correlated with alcohol consumption, and alcohol consumption will increase with the increase of the intensity and duration of PA[\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. This is inconsistent with the results of this study, and the possible reason for this is that both PA and alcohol can activate the reward pathway of the brain, releasing dopamine and endogenous opioids. This overlap in neurochemical effects may be a biological basis for the positive correlation between PA and alcohol[\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. The relationship between PA and alcohol needs to be further clarified in future research.\u003c/p\u003e\u003cp\u003eThe advantages of this study lie in the analysis based on large-sample cross-sectional survey data, and the innovative use of machine learning technology to reveal the influencing mechanism of PA in university students, which more effectively captures the non-linear relationship and interaction between variables compared with traditional statistical methods. The study combines the social-ecological model framework to systematically integrate measurement indicators of multiple dimensions, such as personal characteristics, interpersonal communication, and organizational environment. It constructs a multi-level influencing factor analysis system, providing multi-dimensional evidence to support the formulation of precise health intervention strategies. However, several research limitations should also be pointed out: First, the cross-sectional design has methodological limitations in revealing the causal relationship and temporal dynamic evolution between variables; secondly, some measurement indicators rely on self-assessment scales, which may lead to social desirability bias and recall bias; in addition, macro variables at the community policy level in the social-ecological model have not been included in the research framework, which may affect the systematic nature of the intervention strategy to a certain extent. Future research can improve the PA influencing mechanism\u0026rsquo;s theoretical explanation and practical application through longitudinal tracking design, multi-source data integration, and cross-level model construction.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study used the RF algorithm in machine learning to analyze the factors affecting PA in university students. The study results showed that Exercise Adherence, Exercise Motivation, Sex, Mastery of Sports Skills, and Alcohol Consumption Level are key factors in predicting PA levels in university students. While carrying out sports activities to promote the growth of PA in university students, it is necessary to attach importance to enhancing the \u0026ldquo;emotional value\u0026rdquo; of university students participating in PA, enhancing social attributes, focusing on the exercise intentions of female students, and emphasizing the mastery of more sports skills.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study strictly adhered to the Herschel Declaration, and it has been approved by the Ethics Committee of Nantong University (2022 [70]). All subjects provided informed consent, and all methods were performed according to relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all the subjects involved in the study.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe raw data supporting the conclusions of this article can be made available by the authors without undue reservation. If necessary, please contact the corresponding author for assistance.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis study was supported by the \u003cstrong\u003e2024 Postgraduate Research \u0026amp; Practice Innovation Program of Jiangsu Province.\u003c/strong\u003e (NO： KYCX25_3617).\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eDing-you Zhang, the first author and the main contributor, is responsible for the research design, organization of the questionnaire survey, and drafting of the manuscript, undertaking the majority of the work. Bo Li participated in the research design and data collation. Hu Lou was involved in the distribution of the questionnaires and the collection of data. Jun Liu and Bo Li took charge of data analysis and manuscript revision. All authors collectively discussed the research approach and refined the content of the paper.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe sincerely thank all the staff and students from the participating schools and our co-operators for their assistance in data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003evan Sluijs EMF, Ekelund U, Crochemore-Silva I, Guthold R, Ha A, Lubans D, Oyeyemi AL, Ding D, Katzmarzyk PT: \u003cstrong\u003ePhysical activity behaviours in adolescence: current evidence and opportunities for intervention\u003c/strong\u003e. \u003cem\u003eThe Lancet\u0026nbsp;\u003c/em\u003e2021, \u003cstrong\u003e398\u003c/strong\u003e(10298):429-442.http://doi.org/10.1016/S0140-6736(21)01259-9.\u003c/li\u003e\n \u003cli\u003eLin J, Guo T, Becker B, Yu Q, Chen S, Brendon S, Hossain M, Cunha P, Soares F, Veronese N\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eDepression is Associated with Moderate-Intensity Physical Activity Among College Students During the COVID-19 Pandemic: Differs by Activity Level, Gender and Gender Role\u003c/strong\u003e. \u003cem\u003ePsychology Research and Behavior Management\u0026nbsp;\u003c/em\u003e2020, \u003cstrong\u003e13\u003c/strong\u003e:1123-1134.http://doi.org/10.2147/PRBM.S277435.\u003c/li\u003e\n \u003cli\u003eGuerriero MA, Dipace A, Monda A, De Maria A, Polito R, Messina G, Monda M, di Padova M, Basta A, Ruberto M\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eRelationship Between Sedentary Lifestyle, Physical Activity and Stress in University Students and Their Life Habits: A Scoping Review with PRISMA Checklist (PRISMA-ScR)\u003c/strong\u003e. 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Physical activity levels were assessed using the International Physical Activity Questionnaire (IPAQ). A random forest algorithm was then used to analyze the importance of 39 variables in influencing physical activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Random Forest prediction showed that Exercise Adherence (Exercise Behavior), Exercise Adherence Level, Sex, and Exercise Adherence (Effort Investment) are the most significant factors affecting PA levels in university students. Mastery of Sports Skills, Exercise Motivation (Ability), Alcohol Consumption Level, Exercise Adherence (Emotional Experience), Exercise Motivation (Social), and Exercise Motivation (Fun) are other important influencing factors. The model achieved an accuracy of 0.704 and an AUC value of 0.760, indicating good predictive performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Exercise Adherence, Sex, Mastery of Sports Skills, Alcohol Consumption Level, and Exercise Motivation may influence PA levels in university students. When conducting sports activities, attention should be paid to enhancing the “emotional value” and social attributes of university students participating in PA, focusing on the exercise intentions of female students, and emphasizing the mastery of more sports skills.\u003c/p\u003e","manuscriptTitle":"Influencing Factors of Physical Activity in Chinese University Students Based on Random Forest","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-09 06:51:56","doi":"10.21203/rs.3.rs-6738454/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a508c859-a8f4-47f8-aa4e-7802910fe2cc","owner":[],"postedDate":"July 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-25T07:54:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-09 06:51:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6738454","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6738454","identity":"rs-6738454","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}