The Impact of Family Factors on Study Weariness among Junior School Students: the Mediating role of Self-efficacy

The Impact of Family Factors on Study Weariness among Junior School Students: the Mediating role of Self-efficacy | 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 Article The Impact of Family Factors on Study Weariness among Junior School Students: the Mediating role of Self-efficacy zhou linjuan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7415609/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 This study investigates how three core family factors—family communication patterns, family functioning, and family relationship quality—jointly influence study weariness among junior secondary school students, with self-efficacy as a mediating mechanism. Drawing upon Family Systems Theory and Self-Efficacy Theory, we propose and empirically test an integrated “Family–Self-Efficacy–Burnout” framework. A stratified cluster sample of 804 students from urban and rural schools in Taizhou, China, completed validated measures of the target constructs. Partial least squares structural equation modeling (PLS-SEM) was used to examine causal pathways, complemented by artificial neural network (ANN) analysis to assess predictive power and variable importance. Results show that conversation-oriented communication, functional adaptability, and high-quality family relationships significantly enhance self-efficacy, which in turn reduces study weariness. Self-efficacy partially mediates all three family–burnout links. ANN analysis further underscores self-efficacy as the strongest proximal predictor, while family relationship quality emerges as the most influential environmental factor. These findings advance theory by integrating multiple family-level predictors and a psychological mediator within a unified framework, and methodologically by demonstrating the complementary strengths of SEM and ANN in educational research. Policy implications include embedding structured family communication training and self-efficacy enhancement programs into school–family partnerships to address the deep psychosocial roots of study weariness. Health sciences/Health care Biological sciences/Psychology Social science/Psychology Study weariness Family communication patterns Family function Family relationships Self-efficacy Mediation analysis Figures Figure 1 Introduction Study weariness—manifesting as sustained declines in motivation, emotional engagement, and cognitive investment in learning—has become a critical barrier to adolescent educational success worldwide. In the Chinese junior secondary context, the problem is particularly acute due to the coexistence of high-stakes examination culture and transitional developmental challenges. Despite recent structural reforms, such as the “Double Reduction” policy (2021) and the Family Education Promotion Law (2022), national surveys and empirical studies reveal that academic disengagement among adolescents remains alarmingly prevalent. This persistence suggests that policy-level workload reduction alone is insufficient to address the deeper psychosocial drivers of burnout. Existing research has identified multiple risk factors for study weariness, yet three important limitations remain. First, most studies examine isolated family variables—such as communication style, cohesion, or adaptability—without integrating them into a holistic model that captures the systemic nature of family influence. Second, while self-efficacy is well-established as a determinant of academic engagement, its mediating role between diverse family processes and study weariness has rarely been systematically tested, particularly in non-Western cultural contexts. Third, methodological approaches often rely on single statistical techniques, limiting the capacity to capture both causal pathways and predictive power. These gaps constrain our ability to design interventions that are both theoretically grounded and practically effective. To address these limitations, this study develops and empirically tests an integrated “Family–Self-Efficacy–Burnout” framework, grounded in Family Systems Theory and Self-Efficacy Theory. By simultaneously examining family communication patterns, family functioning, and family relationship quality within a single model, and positioning self-efficacy as the central psychological mediator, we capture the interplay between systemic family environments and individual academic resilience. Methodologically, we combine partial least squares structural equation modeling (PLS-SEM) for hypothesis testing with artificial neural network (ANN) analysis for predictive validation and variable importance ranking. This dual approach enhances both the explanatory depth and the predictive utility of our findings. Situated in the post–“Double Reduction” policy context, the study not only advances theoretical integration but also offers actionable insights for family–school–policy coordination in reducing adolescent study weariness. Literature Review and Research Hypotheses Definition of Study Weariness Study weariness is an increasingly salient phenomenon in contemporary educational settings, particularly among adolescents navigating high-stakes academic environments. While historically discussed under labels such as study weariness (Schaufeli et al., 2002), learning fatigue (Gao, 2023), and school refusal behavior (Kearney, 2008), these terms tend to emphasize isolated aspects—emotional exhaustion, cognitive disengagement, or behavioral avoidance—without fully capturing the multidimensional nature of the construct. Building on integrative perspectives, this study conceptualizes study weariness as a sustained, multifaceted disengagement from learning across emotional, behavioral, and cognitive domains, arising cumulatively from prolonged academic stress and pressure. From an affective standpoint, study weariness manifests in chronic boredom, frustration, and anxiety during learning activities. Behaviorally, it is reflected in reduced class participation, frequent tardiness, and absenteeism. Cognitively, it involves devaluing academic tasks and endorsing maladaptive beliefs such as “studying is useless” (Zhao, 2019). These dimensions are interrelated and often reinforce one another, producing a downward spiral of motivation loss, diminished resilience, and compromised academic outcomes. In this respect, study weariness differs from transient tiredness or short-term dips in engagement; rather, it represents a progressive shift toward sustained detachment that, if unaddressed, may culminate in dropout (Salmela-Aro et al., 2009). Empirical evidence links study weariness to adverse outcomes across multiple domains, including declining academic achievement (Gao, 2023), deteriorating mental health (Salmela-Aro & Upadyaya, 2014), and lower life satisfaction (Salmela-Aro et al., 2009). The Chinese junior secondary context is particularly susceptible to the emergence of study weariness due to its combination of heightened performance expectations, competitive examination culture, and transitional developmental challenges. Notably, while recent policy interventions such as China’s “Double Reduction” initiative aim to alleviate academic burden, preliminary findings suggest that structural changes alone may not be sufficient to mitigate the deeper psychosocial drivers of disengagement (Wang & Sheikh-Khalil, 2014). In operational terms, the present study measures study weariness using the Junior High School Students’ Study Weariness Scale (Zhao, 2019), which assesses the three core dimensions—emotional weariness, behavioral distancing, and cognitive negation—on a 5-point Likert scale. Higher scores indicate greater severity of weariness. By adopting a multidimensional framework, this approach enables early detection and targeted intervention, informing strategies at the levels of school counseling, family engagement, and educational policy. Such interventions are essential for sustaining academic engagement and promoting adolescent well-being in rapidly evolving educational contexts. Theoretical Framework Family Systems Theory (FST). The present study is grounded in Family Systems Theory (FST). Prior research has often examined individual family factors in isolation, overlooking the complex interplay among these factors within real-world family systems (He et al., 2022; Zhang et al., 2023; Fan & Hui, 2025). Families function as interdependent wholes, wherein the family communication model, quality of family relationships, and family functioning represent related yet conceptually distinct dimensions (Sasser et al., 2021; Skeens et al., 2023). By disentangling these three components, the present study is able to examine their direct effects as well as their indirect effects via self-efficacy within a unified model, thereby illuminating a more comprehensive mechanism of influence. This approach also offers practical implications: it enables schools, families, and policymakers to implement targeted interventions at different levels, fostering a multidimensional support system that addresses the academic and psychosocial needs of adolescents. Self-Efficacy Theory (SET). The present study also draws upon Self-Efficacy Theory (SET). Previous research has illuminated the relationship between self-efficacy and study weariness, yet it has often been limited to examining direct effects, overlooking the potential mediating role of self-efficacy in the association between family factors and burnout (Fiorilli et al., 2017; Schaufeli et al., 2002). According to Self-Efficacy Theory, individuals’ beliefs in their capabilities to successfully execute specific tasks substantially influence their motivation, persistence, and strategies for coping with challenges (Bandura, 1997). Among adolescents, high self-efficacy can buffer the detrimental effects of academic stress and reduce the risk of burnout, whereas low self-efficacy may lead to avoidance behaviors, exacerbated stress, and diminished motivation. Incorporating self-efficacy into a unified model enables a deeper understanding of how family communication patterns, family functioning, and family relationships exert indirect effects on study weariness by shaping adolescents’ sense of personal competence. This not only enriches the theoretical explanatory framework but also offers practical implications: it identifies actionable entry points for interventions by schools, families, and policymakers to strengthen students’ psychological resources while simultaneously enhancing family support systems, thereby addressing adolescents’ academic and psychosocial challenges at multiple levels. Existing empirical evidence consistently shows that supportive family communication, functional adaptability, and high-quality relationships can buffer the negative effects of academic stress, while conformity-oriented communication, structural dysfunction, and relational conflict tend to exacerbate disengagement. However, prior studies typically examine these family dimensions in isolation, leaving their joint influence—and potential interactions—largely unexplored. Moreover, although self-efficacy is recognized as a key determinant of academic persistence, few investigations have positioned it as a central mediating mechanism linking multiple family-level factors to study weariness. This gap is particularly evident in the Chinese context, where rapid social change and evolving family structures may alter the ways in which family processes shape adolescents’ competence beliefs and academic engagement. The present study addresses these limitations by integrating Family Systems Theory and Self-Efficacy Theory into a unified framework that simultaneously models the effects of family communication patterns, family functioning, and relationship quality on study weariness, with self-efficacy as the mediating variable. This approach allows us to examine both the direct protective effects of positive family environments and the indirect psychological pathways through which they operate. By employing a dual-method strategy—Partial Least Squares Structural Equation Modeling (PLS-SEM) for causal pathway testing and Artificial Neural Network (ANN) analysis for predictive validation—we capture not only the explanatory mechanisms but also the relative predictive importance of each factor. Family Communication Patterns and Self-Efficacy Family Communication Patterns Theory (Koerner & Fitzpatrick, 2002) distinguishes between conversation orientation—characterized by open, supportive exchanges that encourage independent thinking—and conformity orientation—marked by hierarchical communication emphasizing obedience and uniformity. Empirical research shows that conversation-oriented families foster self-esteem, autonomy, and problem-solving skills, which contribute to higher self-efficacy. In contrast, conformity-oriented communication may limit self-expression, suppress divergent thinking, and undermine confidence in personal abilities. In the Chinese cultural setting, where academic success is often prioritized over emotional dialogue, striking a balance between guidance and openness is particularly challenging but crucial for promoting self-efficacy. Hypotheses: H1 : Family Communication Patterns is positively associated with self-efficacy among junior school students. Family Function and Self-Efficacy Family function refers to the family system’s capacity to fulfill its members’ physical, emotional, and social needs through adaptability, cohesion, and effective problem-solving (Olson, 2019). Functional families provide emotional security, consistent support, and constructive feedback, thereby reinforcing adolescents’ beliefs in their own competence. Dysfunctional families, characterized by role confusion, poor adaptability, and unresolved conflict, can undermine these beliefs, leaving adolescents less equipped to cope with academic demands. Hypothesis: H2 : Family function is positively associated with self-efficacy among junior school students. Family Relationships and Self-Efficacy Family relationships encompass the emotional bonds, trust, and mutual support among family members. High-quality relationships—marked by warmth, empathy, and mutual respect—foster a secure environment in which adolescents can take academic risks, learn from mistakes, and develop self-efficacy. In contrast, conflictual or emotionally distant relationships can heighten stress and reduce confidence in one’s abilities. Hypothesis: H3: Family relationship quality is positively associated with self-efficacy among junior school students. Family Factors and Study Weariness Empirical studies have demonstrated that high-quality family communication significantly alleviates psychological distress among adolescents. For instance, Geçer et al. (2023) found through structural equation modeling that open, supportive exchanges reduce mental strain both directly and indirectly by fostering approach-oriented coping strategies, which enhance overall psychological well-being. From a Family Communication Patterns Theory perspective (Koerner & Fitzpatrick, 2002), conversation orientation encourages self-expression, emotional openness, and independent thinking, thereby enabling students to manage academic stress more effectively. Similarly, functional family systems—characterized by adaptability, cohesion, and effective problem-solving—have been linked to lower levels of study weariness through their capacity to reinforce positive competence beliefs and supply consistent emotional and instrumental support. Yu et al. (2021) further demonstrated that family cohesion and adaptability indirectly reduce study weariness by strengthening positive psychological capital (PsyCap) and peer support networks, which sustain motivation and engagement. These findings collectively suggest that supportive, adaptive family environments act as buffers against academic disengagement, sustaining motivation and emotional resilience in high-pressure educational contexts. Conversely, families marked by conformity-oriented communication, structural dysfunction, and low-quality relationships may exacerbate stress, erode motivation, and accelerate withdrawal from learning. Atkinson’s (2018) doctoral research indicated that such communication climates undermine academic resilience, fostering oppositional or avoidant coping patterns that contribute to disengagement. Huang et al. (2023) identified a chain-mediating process in which poor communication increases family conflict and violence, which in turn promotes problematic internet use, amplifying anxiety, depression, and disengagement from schoolwork. Despite this evidence, existing literature rarely integrates communication style, functional capacity, and relationship quality into a unified analytical model linking family environments to study weariness. Moreover, the role of study weariness as a multidimensional outcome—encompassing emotional exhaustion, behavioral withdrawal, and cognitive devaluation—remains underexplored in the family context. Addressing these gaps, the present study proposes to examine how these three family dimensions jointly influence study weariness, and to test the mediating role of self-efficacy in this relationship. Hypotheses: H4:Family Communication Patterns is negatively associated with study weariness. H5: Family function is negatively associated with study weariness. H6: Family relationship quality is negatively associated with study weariness. The Mediating Role of Self-Efficacy Drawing from Social Cognitive Theory (Bandura, 1977), self-efficacy functions as a proximal determinant of behavior, mediating the impact of environmental inputs—such as family dynamics—on adolescents’ academic engagement. Empirical evidence supports this mechanism. For example, in a study of Chinese middle school students, social support was found to enhance academic performance indirectly through a sequential pathway in which social support increased self-efficacy, which in turn heightened learning engagement (Zhang et al., 2024). Similarly, Shao et al. (2022) demonstrated that adolescents’ peer relationships predicted learning engagement via a chain mediation involving self-efficacy and academic resilience. Research in higher education contexts further corroborates these findings; for instance, Yang et al. (2025) reported that functional family environments reduced study weariness among nursing students by elevating academic self-efficacy, which partially mediated this relationship. In addition, a large-scale investigation by Sun et al. (2025) revealed that strong parent–child relationships diminished study weariness through both direct effects and indirect pathways involving interpersonal relationships at school and academic self-efficacy, highlighting the existence of both single and chain mediation effects. Collectively, these studies affirm that competence beliefs—operationalized as self-efficacy—constitute a key conduit through which social environments influence academic adjustment. However, despite a robust theoretical foundation and substantial empirical coverage in domains such as peer influence and general family functioning, there remains a notable gap in the literature: few studies have systematically integrated family communication patterns, family functioning, and relationship quality within a unified SCT framework to examine their joint predictive roles in shaping study weariness. Moreover, existing models seldom differentiate between specific family communication orientations—such as conversation-oriented versus conformity-oriented—and how these orientations interact with other family dimensions to shape self-efficacy and, through it, vulnerability to study weariness. Addressing this gap, the present study formulates targeted research questions and hypotheses to explore these interrelationships comprehensively(Table 1). H7a: Self-efficacy mediates the relationship between Family Communication Patterns and study weariness. H7b: Self-efficacy mediates the relationship between family function and study weariness. H7c: Self-efficacy mediates the relationship between family relationship quality and study weariness. Table 1. Summary of Research Hypotheses Hypothesis Pathway Expected Direction Theoretical Basis H1 FCPs → SEf Positive (+) Family Systems Theory; Self-Efficacy Theory H2 FF→ SE Positive (+) Family Systems Theory; Self-Efficacy Theory H3 FR→ SE Positive (+) Family Systems Theory; Self-Efficacy Theory H4 FCPs→SW Negative (–) Family Systems Theory H5 FF→ SW Negative (–) Family Systems Theory H6 FR→ SW Negative (–) Family Systems Theory H7a FCPs → SE → SW Mediated (–) Self-Efficacy Theory H7b FF→ SE→SW Mediated (–) Self-Efficacy Theory H7c FR→ SE → SW Mediated (–) Self-Efficacy Theory Note: FCPs: Fmily Communication Patterns, FR: Family Relationship, FF: Family Function, SE: Self-Efficacy, SW: Study Weariness. Study’s conceptual framework From the literature discussed above, the conceptual framework (Figure 1) has been developed. Methodology Research Design. This study employed a quantitative, cross-sectional survey design to examine the relationships among family communication patterns (FCP), family functioning (FF), family relationship quality (FR), self-efficacy (SE), and study weariness (SW) in junior secondary students. The conceptual framework was grounded in Family Systems Theory and Self-Efficacy Theory, with SE modeled as a mediator linking family-level factors to SW. We adopted a multi-stage, stratified cluster sampling strategy to ensure representativeness across urban and rural settings, grades 7–9, and boarding/day-school contexts in Taizhou, Zhejiang Province, China. Data collection was conducted online via the Wenjuanxing platform, under ethical guidelines approved by the relevant institutional review board. Participation was voluntary and anonymous, with informed consent obtained from both students and their guardians. Sample Characteristics A total of 804 valid responses were retained (valid return rate ≈ 93.5%). The sample was balanced by gender (girls = 52%, boys = 48%), location (urban = 54%, rural = 46%), and included 66% boarding students. In line with national demographic patterns, 93% were from single-child households. The sample size exceeded the minimum statistical power requirements for PLS-SEM analysis (Hair et al., 2022). Variable measurement Independent variable ： Family Communication Patterns (FCPs) Measured using an adapted version of the Family Communication Patterns Scale (Koerner & Fitzpatrick, 2002), comprising two subscales: Conversation Orientation (e.g., “In our family, we often talk openly about our feelings”), Conformity Orientation (e.g., “In our family, children are expected to follow parents’ rules without question”). Items were rated on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Reliability coefficients in this study exceeded 0.85 for both subscales. Independent variable ： Family Relationship(FR) This study uses the Brief Family Relationship Scale (BFRS) (Fok et al., 2014) to measure family relationships across three dimensions: Cohesion, Expressiveness, and Conflict. Example items include “Family members really help and support one another” and “We fight a lot in our family” (reverse-coded). Responses are rated on a 5-point Likert scale, with higher total scores indicating stronger and more positive family relationships. Independent variable ： Family Function (FF) Assessed using the McMaster Family Assessment Device (FAD), focusing on adaptability, cohesion, and problem-solving capacities. The scale demonstrated strong internal consistency (Cronbach’s α = 0.87). Family Relationships (FR) Evaluated via the Family Cohesion and Adaptability Evaluation Scale (FACES), emphasizing emotional bonding, trust, and mutual support within the family unit. Internal reliability was 0.89. Items include statements such as “In times of crisis, we can turn to each other for support.” Responses are rated on a 5-point Likert scale (1= completely inconsistent to 5=completely consistent,), with higher scores reflecting better family functioning. Mediating variable : Self-Efficacy (SE) Self-efficacy is measured using the General Self-Efficacy Scale (GSE) (Scholz et al., 2002), adapted for adolescents. Items captured students’ confidence in managing learning tasks, overcoming challenges, and achieving academic goals (Cronbach’s α = 0.90).Items include “I can always manage to solve difficult problems if I try hard enough.” Participants respond on a 5-point Likert scale (1 = not at all true to 5 = extremely exactly true), with higher scores indicating greater perceived self-efficacy. Dependent variable: Study Weariness (SW) In this study, the quantitative assessment of study weariness adopts the Junior High School Students' Study Weariness Scale developed by Zhao (2019). This instrument comprises three core dimensions: first, the emotional weariness dimension (e.g., the item "I often feel bored during class learning"); second, the behavioral distancing dimension (e.g., the item "I frequently skip classes or arrive late"); third, the cognitive negation dimension (e.g., the item "I think learning is useless for future development"). All items are rated using a 5-point Likert scale (1= "strongly disagree", 5="strongly agree"), with higher scores indicating a more significant degree of students' study weariness.The scale combined items from validated study weariness measures, adapted to the junior school context. Reliability in this study was 0.91. Data analysis techniques. We estimated the research model in SmartPLS 4 using variance-based partial least squares structural equation modeling (PLS-SEM) to evaluate all hypotheses. PLS-SEM is a distribution-free approach that prioritizes the explained variance of latent (unobserved) constructs. It affords substantial modeling flexibility, works well with relatively small samples, does not require multivariate normality, and supports both formative and reflective measurement specifications without convergence difficulties. Consequently, applying PLS-SEM in SmartPLS is well suited for predicting linear relationships and analyzing complex structural frameworks (see, e.g., Becerra-Fernandez, 2001; Avkiran & Ringle, 2018). A key advantage is the direct use of R² to assess the variance accounted for in endogenous variables, which strengthens model–data alignment and the interpretability of predictive results. To examine robustness, we complemented the SEM with artificial neural network (ANN) analyses, using ANN to probe sensitivity to critical assumptions and to evaluate the stability of conclusions. In terms of software, all statistics were conducted with SPSS 24.0 and SmartPLS 4. First, SPSS provided descriptive summaries of the sample and an initial check of common method bias. Second, SmartPLS was used to assess measurement reliability and validity and to estimate the study’s main effects, mediation effects, and moderation effects. Research results Measurement model . To assess the measurement model, we examined indicator reliability, internal consistency, convergent validity, and discriminant validity (Hair et al., 2020) (see Tables 2 and 3). The Cronbach’s α, rho_A, and composite reliability values for all constructs in this study exceeded 0.70, demonstrating strong construct reliability (Hair et al., 2017). For indicator loadings, all values surpassed the threshold of 0.7, confirming robust item reliability. The average variance extracted (AVE) for each construct was above 0.60, supporting convergent validity (Hair et al., 2022). Discriminant validity was established as the square root of the AVE for each construct exceeded its correlations with other constructs (Fornell and Larcker, 1981), and all Heterotrait-monotrait ratio (HTMT) values were below 0.80, indicating clear distinction between constructs (Kline, 2011). Additionally, Harman’s single-factor test was conducted, revealing 5 factors with a cumulative explained variance of 63.083%, where the first factor accounted for 37.607% of the variance, below the 40% threshold. Thus, no significant common method bias was detected in this study. Table 2 Measurement model assessment Construct Item Loading Cronbach's alpha Composite reliability (rho_a) Composite reliability (rho_c) AVE family communication patterns FCP1 0.791 0.950 0.950 0.956 0.623 FCP2 0.808 FCP3 0.785 FCP4 0.800 FCP5 0.795 FCP6 0.772 FCP7 0.784 FCP8 0.785 FCP9 0.796 FCP10 0.772 FCP11 0.794 FCP12 0.783 FCP13 0.794 family relationships FR1 0.821 0.981 0.981 0.982 0.640 FR2 0.812 FR3 0.818 FR4 0.807 FR5 0.797 FR6 0.803 FR7 0.799 FR8 0.789 FR9 0.805 FR10 0.773 FR11 0.803 FR12 0.813 FR13 0.795 FR14 0.783 FR15 0.793 FR16 0.804 FR17 0.794 FR18 0.796 FR19 0.812 FR20 0.798 FR21 0.804 FR22 0.799 FR23 0.801 FR24 0.792 FR25 0.797 FR26 0.808 FR27 0.797 FR28 0.799 FR29 0.798 FR30 0.782 family function FF1 0.797 0.941 0.942 0.949 0.607 FF2 0.767 FF3 0.777 FF4 0.775 FF5 0.765 FF6 0.783 FF7 0.782 FF8 0.779 FF9 0.795 FF10 0.783 FF11 0.746 FF12 0.801 self-efficacy SE1 0.797 0.933 0.934 0.943 0.625 SE2 0.796 SE3 0.809 SE4 0.785 SE5 0.783 SE6 0.778 SE7 0.798 SE8 0.792 SE9 0.790 SE10 0.779 study weariness SW1 0.766 0.960 0.960 0.964 0.609 SW2 0.785 SW3 0.777 SW4 0.778 SW5 0.780 SW6 0.779 SW7 0.788 SW8 0.786 SW9 0.792 SW10 0.776 SW11 0.781 SW12 0.774 SW13 0.785 SW14 0.766 SW15 0.776 SW16 0.786 SW17 0.785 Table 3 Assessment of discriminant validity FCPS FF FR SE SW FCPS 0.769 0.430 0.553 0.480 0.495 FF 0.430 0.756 0.547 0.469 0.463 FR 0.553 0.547 0.792 0.511 0.537 SE 0.481 0.470 0.512 0.763 0.505 SW -0.496 -0.465 -0.538 -0.508 0.764 Fornell-Larcker criterion (below the main diagonal) and heterotrait-monotrait ratio (HTMT) (above the main diagonal). Main diagonal: in the bold square root of the AVE. Table 4 Structural relationships and hypothesis testing. Hypotheses Path Std beta Std error t Value P Result H1 FCPS→ SE 0.244 0.039 6.280 <.001 Supported H2 FCPS→ SW -0.188 0.038 4.931 <.001 Supported H3 FF→ SE 0.226 0.039 5.745 <.001 Supported H4 FF→ SW -0.138 0.039 3.523 <.001 Supported H5 FR→ SE 0.243 0.039 6.293 <.001 Supported H6 FR→ SW -0.212 0.037 5.643 <.001 Supported H7 SE→SW -0.212 0.039 5.390 SE -> SW -0.059 0.014 4.253 SE -> SW -0.056 0.014 3.961 SE-> SW -0.065 0.015 4.278 <.001 Supported Structural model. First, we examined collinearity within the structural model. All variance inflation factor (VIF) values were below 3, confirming the absence of multicollinearity concerns (Hair et al., 2019). Next, we evaluated the path coefficients and their significance. As shown in Table 4, all standardized beta (β) values were statistically significant with strong t-statistics. Study weariness (SW) was significantly influenced by self-efficacy (SE) (β = -0.212, t = 5.390, p < 0.001), family communication patterns (FCPS) (β = -0.188, t = 4.931, p < 0.001), family function (FF) (β = -0.138, t = 3.523, p < 0.001), and family relationships (FR) (β = -0.212, t = 5.643, p < 0.001). SE, in turn, was significantly predicted by FCPS (β = 0.244, t = 6.280, p < 0.001), FF (β = 0.226, t = 5.745, p < 0.001), and FR (β = 0.243, t = 6.293, p < 0.001). Thus, all hypotheses (H1–H10) were supported. Finally, we assessed the model’s explanatory and predictive power. The coefficient of determination (R²) for SW and SE was 0.592 and 0.548, respectively, both exceeding the threshold of 0.25, indicating substantial explanatory strength. The predictive relevance (Q²) values for SW and SE were 0.351 and 0.342, respectively, both above zero, confirming the model’s predictive capability. Additionally, the goodness-of-fit (GoF) index for the PLS-SEM was 0.529, surpassing the benchmark of 0.36, further validating the model’s robustness. Table 5 RMSE value of 10-fold ANN models. Neural network Model A Model B Input:FCP,FR,FF,Gender,Grade Input:FCP,FR,FF,SE,Sibling status,Family structure,Grade output:SE output:SW Training Testing Training Testing RMSE RMSE RMSE RMSE ANN1 0.164 0.148 0.138 0.150 ANN2 0.167 0.152 0.139 0.122 ANN3 0.164 0.152 0.135 0.141 ANN4 0.163 0.153 0.141 0.105 ANN5 0.160 0.159 0.138 0.149 ANN6 0.168 0.158 0.141 0.125 ANN7 0.164 0.156 0.139 0.144 ANN8 0.158 0.169 0.138 0.152 ANN9 0.170 0.163 0.141 0.132 ANN10 0.162 0.132 0.152 0.126 Mean 0.164 0.154 0.140 0.135 SD 0.0000 0.0001 0.0000 0.0002 Table 6 Comparison of PLS-SEM and ANN results. PLS Path Original Sample(O)/Path coefficient ANN results:Normalized relative importance(%) Ranking(PLS-SEM) [based on Path Coefficient] Ranking(PLS-SEM) [based on normalized relative importance] Remark Model A--FCP,FR,FF,Gender,Grade->SE FCP->SE 0.219 89.34% 2 2 Match FF->SE 0.193 100.00% 3 1 Not Match FR->SE 0.235 54.76% 1 3 Not Match Gender->SE 0.134 9.90% 4 5 Not Match Grade->SE 0.114 15.02% 5 4 Not Match Model B---FCP,FR,FF,SE,Sibling status,Family structure,Grade->SW FCP->SW -0.189 74.41% 3 2 Not Match FF->SW -0.137 60.98% 4 3 Not Match FR->SW -0.236 100.00% 1 1 Match Family structure->SW 0.027 6.79% 7 7 Not Match Grade->SW -0.061 8.15% 6 5 Not Match SE->SW -0.204 50.36% 2 4 Not Match Sibling status->SW -0.066 8.12% 5 6 Not Match Predictive Analysis Using ANN：An Artificial Neural Network (ANN) analysis was conducted to evaluate the predictive power and determine the relative importance of key variables. The model exhibited high predictive accuracy, with root mean square errors (RMSE) of 0.154 for self-efficacy and 0.135 for study weariness under 10-fold cross-validation. For self-efficacy, the most influential predictors were family communication patterns (89.34%), family relationship quality (54.76%), family function (100.00%), and grade (15.02%). In predicting study weariness, self-efficacy emerged as the most dominant factor (50.36%), followed by family function (60.98%), family relationship quality (100.00%), and family communication patterns (74.41%)(Table 5). These results highlight self-efficacy as the strongest proximal predictor of study weariness, while family conversation orientation and family relationship quality stand out as the most influential environmental predictors. Mediation effects. We employed the bootstrapping method (804 samples) to examine whether self-efficacy (SE) mediated the relationships between family-related constructs (FCPS, FF, FR) and study weariness (SW). To assess mediation, we first verified the significance of each path coefficient before analyzing the variance accounted for (VAF) to determine mediation type (no, partial, or complete mediation). The VAF thresholds were defined as follows: VAF 0.80 (full mediation). As presented in Table 6, family communication patterns (FCPS) exhibited a significant indirect effect on SW through SE (β = -0.059, p < 0.001, VAF = 0.239), indicating partial mediation. Similarly, family function (FF) indirectly influenced SW via SE (β = -0.056, p < 0.001, VAF = 0.229), also supporting partial mediation. Lastly, family relationships (FR) showed a significant indirect effect on SW through SE (β = -0.065, p < 0.001, VAF = 0.235), further confirming partial mediation. Thus, hypotheses H8, H9, and H10 were fully supported, demonstrating that SE partially mediates the relationships between family-related factors and study weariness. Conclusion and Discussion Main Findings Drawing on a sample of 804 junior high school students in Taizhou, this study applied partial least squares structural equation modeling (PLS-SEM) in combination with artificial neural networks (ANN) to investigate the interplay between family communication patterns (FCP), family functioning (FF), family relationships (FR), self-efficacy (SE), and study weariness (SW). The findings indicate that conversation-oriented family communication patterns, healthy family functioning, and high-quality family relationships significantly enhance students' self-efficacy, which in turn directly and indirectly reduces schoolwork burnout. By contrast, conformity-oriented communication and suboptimal family processes were associated with greater burnout risk. The SEM results revealed significant positive effects of FCP (β ≈ 0.22, p < .001), FF (β ≈ 0.19, p < .001), and FR (β ≈ 0.24, p < .001) on SE, and significant negative effects of FCP (β ≈ -0.19, p < .001), FF (β ≈ -0.14, p < .001), and FR (β ≈ -0.24, p < .001) on SW. SE itself had a significant negative path to SW (β ≈ -0.20, p < .001), supporting its role as a proximal psychological mediator between family context and burnout. Consistent with these patterns, additional analyses confirmed that the effects of FCP, FF, and FR on SW were partially mediated by SE, and that all three indirect pathways were statistically significant. ANN analysis further underscored the robustness of these results: FR and FCP emerged as the most influential predictors of SE, with normalized importance values of approximately 100% and 89%, respectively. In predicting SW, FR and FCP again ranked highly, while SE itself accounted for nearly half the predictive power—reinforcing its central role as a proximal determinant of burnout. Overall, the evidence highlights three key findings: family relationships and the communication climate serve as critical external factors shaping students' learning-related attitudes and behaviors, while self-efficacy acts as the central psychological mechanism linking family dynamics to schoolwork burnout. Notably, family relationships (FR) exert a particularly strong direct effect in mitigating burnout, and family communication patterns further enhances this protective role by positively influencing students' self-efficacy (SE). Contributions This study makes several key theoretical contributions. First, by integrating family systems theory and self-efficacy theory, it demonstrates that communication patterns, family functioning, and relationship quality synergistically shape students' self-efficacy (SE), which in turn influences academic engagement and emotional resilience. This empirically validated framework, tested in a Chinese junior high school context, advances theoretical understanding of the 'family–psychology– learning' mechanism. Second, by distinguishing between the two dimensions of family communication patterns (FCP)—conversation orientation and conformity orientation—the study reveals their asymmetrical effects: conversation orientation fosters autonomy and resilience, whereas conformity orientation may suppress self-expression and undermine capability beliefs, offering precise leverage points for family interventions. Third, the research establishes SE as the central proximal mechanism linking family factors to burnout, with both SEM mediation tests and ANN importance rankings converging on its pivotal role as an intervention target. Finally, the simultaneous examination of multiple family factors within a mediation framework, combined with a dual-method approach (SEM and ANN), provides both conceptual depth and methodological innovation for future educational research. Methodological Contributions The parallel use of PLS-SEM and ANN represents a methodological advancement: SEM identifies causal pathways and effect sizes, while ANN evaluates predictive accuracy and variable importance. This "causality–prediction" dual strategy enhances robustness, interpretability, and generalizability, offering a replicable blueprint for similar studies. Practical Contributions The findings yield actionable implications across multiple levels. At the family level, they underscore the value of structured conversation-based communication training—such as active listening, paraphrasing, and open-ended questioning—alongside enhanced emotional support skills to reduce reliance on authoritarian directives and excessive conformity demands. At the school level, the results advocate for integrating home-school collaboration into student support systems, employing coordinated strategies to strengthen self-efficacy (e.g., goal decomposition, mastery experiences, peer modeling, positive reinforcement, and emotional regulation), particularly during critical transition periods. At the policy level, the study highlights the need for community-based family education programs, complementing structural reforms like China's 'Double Reduction' policy(Ministry of Education of the People’s Republic of China, 2021), to institutionalize family capacity-building as a core component of local education governance. Discussion Why do family relationships and communication exert such strong effects? From a Family Systems Theory lens, adolescent burnout reflects systemic misalignments rather than isolated traits. Families regulate emotion and information via recurrent rules, roles, and boundaries. Conversation-oriented, cohesive, and adaptable systems generate constructive feedback loops: shared narratives supply meaning, scaffolding builds competence (self-efficacy), and secure bonds ensure connection—stabilizing the whole system under academic stress. In contrast, conformity-driven, rigid, or conflictual patterns intensify negative feedback (criticism, triangulation, emotional cutoff), yielding powerlessness, meaninglessness, and disconnection. Therefore, restructuring communication rules and relational boundaries recalibrates family homeostasis, indirectly strengthening adolescents' self-efficacy and reducing emotional exhaustion and disengagement. Self-efficacy emerges as the nexus in this process. It shapes persistence and effort while also influencing how academic stress is appraised. Family environments that provide mastery experiences, verbal encouragement, and emotional reassurance strengthen SE, reframing academic challenges as manageable and interrupting the burnout cycle. In contrast, controlling and low-trust family climates erode SE, fostering avoidance behaviors and reinforcing patterns of underachievement. Although grade level and gender exerted only modest effects in the current data, tailored interventions should still consider micro-contexts such as school transition points, gender role expectations, and boarding versus day-school arrangements. Limitations and Future Directions Several limitations warrant consideration. First, the cross-sectional design restricts the ability to draw causal inferences, underscoring the necessity of longitudinal research to examine how variations in family processes correspond with changes in self-efficacy (SE) and subjective well-being (SW) over time. Second, the exclusive reliance on self-report measures raises concerns regarding common method bias and social desirability effects; future investigations would benefit from incorporating multi-informant assessments (e.g., parent and teacher reports) alongside behavioral indicators (e.g., classroom engagement, homework completion). Third, the cultural specificity of the sample constrains the generalizability of findings, highlighting the value of cross-cultural comparative studies. Furthermore, the current model could be enriched by integrating additional mediators or moderators—such as academic resilience, perceived parental support, and emotion regulation strategies—and by evaluating low-cost, scalable interventions in ecologically valid settings. Methodologically, future research might employ Bayesian structural equation modeling (SEM) or causal forest approaches to enhance analytical robustness, while, in practical terms, randomized controlled trials or quasi-experimental designs could be used to assess the combined effects of "parent communication training" and "student self-efficacy training" programs. Conclusion This study provides consistent evidence—across both SEM and ANN analyses—that high-quality family relationships and conversation-oriented communication, by enhancing self-efficacy, substantially reduce study weariness (SW) among junior high school students. The findings advance theory, methodology, and practice by highlighting self-efficacy as a pivotal intervention target and by demonstrating the value of integrating family-based strategies into educational support systems. For families, building communication skills, emotional support, and functional capacity should be ongoing priorities. For schools, self-efficacy should occupy a central place in student development frameworks. For policymakers, institutionalizing family education services and linking them to school reform efforts can create a structure–psychology–behavior chain of governance. Through such coordinated action, the deeper psychological roots of learning burnout can be addressed, fostering sustained engagement and healthy academic development in the post–"Double Reduction" era. Final Reflections This study illuminates the centrality of family environments in shaping junior school students' academic engagement. By demonstrating that family communication, function, and relationships collectively influence self-efficacy—and, in turn, study weariness—the research offers a roadmap for holistic interventions. Strengthening family systems, nurturing self-efficacy, and aligning policy with psychosocial needs can collectively address the pervasive challenge of study weariness. As educational landscapes evolve, integrating family-focused strategies into broader reforms will be essential for fostering resilient, motivated learners in China and beyond. In conclusion, the persistence of study weariness demands multidimensional solutions. This study not only advances theoretical understanding but also provides actionable insights for families, educators, and policymakers. By bridging the gap between family dynamics and academic outcomes, it lays the groundwork for future research and practice aimed at sustaining adolescent well-being and educational success. Declarations Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Ethics Statement This study was approved by the UCSI UNIVERSITY of Ethics Committee, Malaysia. (Approval No. IEC-2025-FOSSLA-0038). All procedures involving human participants were conducted in accordance with the Declaration of Helsinki and relevant institutional guidelines. Written informed consent was obtained from all participants (or their legal guardians, where applicable). Author Contribution zhoulinjuan wrote the main manuscript text References Atkinson K (2018) The impact of family communication patterns on the academic resilience of students (Doctoral dissertation, West Virginia University) . West Virginia University Research Repository. https://researchrepository.wvu.edu/etd/5128 Bandura A (1977) Self-efficacy: Toward a unifying theory of behavioral change. 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PLoS ONE 19(12):e0311597. .https://doi.org/10.1371/journal.pone.0311597 Zhao YF (2019) Preparation and application of the Student boredom Scale for junior high school students. Shanghai J Educ Res 10:27–30 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7415609","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":514362085,"identity":"e2e594d1-d69f-417c-ac88-debf18b6ff59","order_by":0,"name":"zhou linjuan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDACCSB+YMDADKQYHyQY2MixsbcfIKwlAaKF2eBDQZoxH8+ZBCK0QJhskjM+HE6cJ+FggFeH/OzmYxIJBXfYDY6fPWzMY3A4vU0CaMSPim04tTDOOZYmkWDwjNngTF7iYx6D9Nw26cYDjD1nbuPUwiyRYwbUcpjZ4ECOMdAW69w2mQMJzIxtuLWwwbWcf2MmzWPAnM4G5OLVwgPXciPHTHKGgXMCQS0SEmnJFiAtkjfeGBt8MEgzbAMG8kF8fpGfkXzwxoc/h5P5zucYPkj4YyMv395+8MGPCtxaYCAZhXeAoHogsCNG0SgYBaNgFIxQAAATClUh5RaZXQAAAABJRU5ErkJggg==","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"zhou","middleName":"","lastName":"linjuan","suffix":""}],"badges":[],"createdAt":"2025-08-20 09:08:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7415609/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7415609/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91699931,"identity":"a1410a48-583f-4220-a01a-d337d78208de","added_by":"auto","created_at":"2025-09-19 10:21:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":43604,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual framework\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7415609/v1/dfacb97da46b8d61f18ba543.png"},{"id":99316717,"identity":"9c2aed3e-5d6f-481b-bf32-33c727208c82","added_by":"auto","created_at":"2025-12-31 16:29:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1560351,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7415609/v1/61a09fc6-2fcf-4a55-bcdf-aa333813cb0d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Family Factors on Study Weariness among Junior School Students: the Mediating role of Self-efficacy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStudy weariness\u0026mdash;manifesting as sustained declines in motivation, emotional engagement, and cognitive investment in learning\u0026mdash;has become a critical barrier to adolescent educational success worldwide. In the Chinese junior secondary context, the problem is particularly acute due to the coexistence of high-stakes examination culture and transitional developmental challenges. Despite recent structural reforms, such as the \u0026ldquo;Double Reduction\u0026rdquo; policy (2021) and the Family Education Promotion Law (2022), national surveys and empirical studies reveal that academic disengagement among adolescents remains alarmingly prevalent. This persistence suggests that policy-level workload reduction alone is insufficient to address the deeper psychosocial drivers of burnout.\u003c/p\u003e\n\u003cp\u003eExisting research has identified multiple risk factors for study weariness, yet three important limitations remain. First, most studies examine isolated family variables\u0026mdash;such as communication style, cohesion, or adaptability\u0026mdash;without integrating them into a holistic model that captures the systemic nature of family influence. Second, while self-efficacy is well-established as a determinant of academic engagement, its mediating role between diverse family processes and study weariness has rarely been systematically tested, particularly in non-Western cultural contexts. Third, methodological approaches often rely on single statistical techniques, limiting the capacity to capture both causal pathways and predictive power. These gaps constrain our ability to design interventions that are both theoretically grounded and practically effective.\u003c/p\u003e\n\u003cp\u003eTo address these limitations, this study develops and empirically tests an integrated \u0026ldquo;Family\u0026ndash;Self-Efficacy\u0026ndash;Burnout\u0026rdquo; framework, grounded in Family Systems Theory and Self-Efficacy Theory. By simultaneously examining family communication patterns, family functioning, and family relationship quality within a single model, and positioning self-efficacy as the central psychological mediator, we capture the interplay between systemic family environments and individual academic resilience. Methodologically, we combine partial least squares structural equation modeling (PLS-SEM) for hypothesis testing with artificial neural network (ANN) analysis for predictive validation and variable importance ranking. This dual approach enhances both the explanatory depth and the predictive utility of our findings. Situated in the post\u0026ndash;\u0026ldquo;Double Reduction\u0026rdquo; policy context, the study not only advances theoretical integration but also offers actionable insights for family\u0026ndash;school\u0026ndash;policy coordination in reducing adolescent study weariness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLiterature Review and Research Hypotheses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDefinition of Study Weariness\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy weariness is an increasingly salient phenomenon in contemporary educational settings, particularly among adolescents navigating high-stakes academic environments. While historically discussed under labels such as study weariness (Schaufeli et al., 2002), learning fatigue (Gao, 2023), and school refusal behavior (Kearney, 2008), these terms tend to emphasize isolated aspects\u0026mdash;emotional exhaustion, cognitive disengagement, or behavioral avoidance\u0026mdash;without fully capturing the multidimensional nature of the construct. Building on integrative perspectives, this study conceptualizes study weariness as a sustained, multifaceted disengagement from learning across emotional, behavioral, and cognitive domains, arising cumulatively from prolonged academic stress and pressure.\u003c/p\u003e\n\u003cp\u003eFrom an affective standpoint, study weariness manifests in chronic boredom, frustration, and anxiety during learning activities. Behaviorally, it is reflected in reduced class participation, frequent tardiness, and absenteeism. Cognitively, it involves devaluing academic tasks and endorsing maladaptive beliefs such as \u0026ldquo;studying is useless\u0026rdquo; (Zhao, 2019). These dimensions are interrelated and often reinforce one another, producing a downward spiral of motivation loss, diminished resilience, and compromised academic outcomes. In this respect, study weariness differs from transient tiredness or short-term dips in engagement; rather, it represents a progressive shift toward sustained detachment that, if unaddressed, may culminate in dropout (Salmela-Aro et al., 2009).\u003c/p\u003e\n\u003cp\u003eEmpirical evidence links study weariness to adverse outcomes across multiple domains, including declining academic achievement (Gao, 2023), deteriorating mental health (Salmela-Aro \u0026amp; Upadyaya, 2014), and lower life satisfaction (Salmela-Aro et al., 2009). The Chinese junior secondary context is particularly susceptible to the emergence of study weariness due to its combination of heightened performance expectations, competitive examination culture, and transitional developmental challenges. Notably, while recent policy interventions such as China\u0026rsquo;s \u0026ldquo;Double Reduction\u0026rdquo; initiative aim to alleviate academic burden, preliminary findings suggest that structural changes alone may not be sufficient to mitigate the deeper psychosocial drivers of disengagement (Wang \u0026amp; Sheikh-Khalil, 2014).\u003c/p\u003e\n\u003cp\u003eIn operational terms, the present study measures study weariness using the Junior High School Students\u0026rsquo; Study Weariness Scale (Zhao, 2019), which assesses the three core dimensions\u0026mdash;emotional weariness, behavioral distancing, and cognitive negation\u0026mdash;on a 5-point Likert scale. Higher scores indicate greater severity of weariness. By adopting a multidimensional framework, this approach enables early detection and targeted intervention, informing strategies at the levels of school counseling, family engagement, and educational policy. Such interventions are essential for sustaining academic engagement and promoting adolescent well-being in rapidly evolving educational contexts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTheoretical Framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFamily Systems Theory (FST).\u0026nbsp;\u003c/strong\u003eThe present study is grounded in Family Systems Theory (FST). Prior research has often examined individual family factors in isolation, overlooking the complex interplay among these factors within real-world family systems (He et al., 2022; Zhang et al., 2023; Fan \u0026amp; Hui, 2025). Families function as interdependent wholes, wherein the family communication model, quality of family relationships, and family functioning represent related yet conceptually distinct dimensions (Sasser et al., 2021; Skeens et al., 2023). By disentangling these three components, the present study is able to examine their direct effects as well as their indirect effects via self-efficacy within a unified model, thereby illuminating a more comprehensive mechanism of influence. This approach also offers practical implications: it enables schools, families, and policymakers to implement targeted interventions at different levels, fostering a multidimensional support system that addresses the academic and psychosocial needs of adolescents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelf-Efficacy Theory (SET).\u0026nbsp;\u003c/strong\u003eThe present study also draws upon Self-Efficacy Theory (SET). Previous research has illuminated the relationship between self-efficacy and study weariness, yet it has often been limited to examining direct effects, overlooking the potential mediating role of self-efficacy in the association between family factors and burnout (Fiorilli et al., 2017; Schaufeli et al., 2002). According to Self-Efficacy Theory, individuals\u0026rsquo; beliefs in their capabilities to successfully execute specific tasks substantially influence their motivation, persistence, and strategies for coping with challenges (Bandura, 1997). Among adolescents, high self-efficacy can buffer the detrimental effects of academic stress and reduce the risk of burnout, whereas low self-efficacy may lead to avoidance behaviors, exacerbated stress, and diminished motivation. Incorporating self-efficacy into a unified model enables a deeper understanding of how family communication patterns, family functioning, and family relationships exert indirect effects on study weariness by shaping adolescents\u0026rsquo; sense of personal competence. This not only enriches the theoretical explanatory framework but also offers practical implications: it identifies actionable entry points for interventions by schools, families, and policymakers to strengthen students\u0026rsquo; psychological resources while simultaneously enhancing family support systems, thereby addressing adolescents\u0026rsquo; academic and psychosocial challenges at multiple levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExisting empirical evidence consistently shows that supportive family communication, functional adaptability, and high-quality relationships can buffer the negative effects of academic stress, while conformity-oriented communication, structural dysfunction, and relational conflict tend to exacerbate disengagement. However, prior studies typically examine these family dimensions in isolation, leaving their joint influence\u0026mdash;and potential interactions\u0026mdash;largely unexplored. Moreover, although self-efficacy is recognized as a key determinant of academic persistence, few investigations have positioned it as a central mediating mechanism linking multiple family-level factors to study weariness. This gap is particularly evident in the Chinese context, where rapid social change and evolving family structures may alter the ways in which family processes shape adolescents\u0026rsquo; competence beliefs and academic engagement.\u003c/p\u003e\n\u003cp\u003eThe present study addresses these limitations by integrating Family Systems Theory and Self-Efficacy Theory into a unified framework that simultaneously models the effects of family communication patterns, family functioning, and relationship quality on study weariness, with self-efficacy as the mediating variable. This approach allows us to examine both the direct protective effects of positive family environments and the indirect psychological pathways through which they operate. By employing a dual-method strategy\u0026mdash;Partial Least Squares Structural Equation Modeling (PLS-SEM) for causal pathway testing and Artificial Neural Network (ANN) analysis for predictive validation\u0026mdash;we capture not only the explanatory mechanisms but also the relative predictive importance of each factor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFamily Communication Patterns and Self-Efficacy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFamily Communication Patterns Theory (Koerner \u0026amp; Fitzpatrick, 2002) distinguishes between conversation orientation\u0026mdash;characterized by open, supportive exchanges that encourage independent thinking\u0026mdash;and conformity orientation\u0026mdash;marked by hierarchical communication emphasizing obedience and uniformity. Empirical research shows that conversation-oriented families foster self-esteem, autonomy, and problem-solving skills, which contribute to higher self-efficacy. In contrast, conformity-oriented communication may limit self-expression, suppress divergent thinking, and undermine confidence in personal abilities. In the Chinese cultural setting, where academic success is often prioritized over emotional dialogue, striking a balance between guidance and openness is particularly challenging but crucial for promoting self-efficacy.\u003c/p\u003e\n\u003cp\u003eHypotheses:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH1\u003c/strong\u003e: Family Communication Patterns is positively associated with self-efficacy among junior school students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFamily Function and Self-Efficacy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFamily function refers to the family system\u0026rsquo;s capacity to fulfill its members\u0026rsquo; physical, emotional, and social needs through adaptability, cohesion, and effective problem-solving (Olson, 2019). Functional families provide emotional security, consistent support, and constructive feedback, thereby reinforcing adolescents\u0026rsquo; beliefs in their own competence. Dysfunctional families, characterized by role confusion, poor adaptability, and unresolved conflict, can undermine these beliefs, leaving adolescents less equipped to cope with academic demands.\u003c/p\u003e\n\u003cp\u003eHypothesis:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH2\u003c/strong\u003e: Family function is positively associated with self-efficacy among junior school students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFamily Relationships and Self-Efficacy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFamily relationships encompass the emotional bonds, trust, and mutual support among family members. High-quality relationships\u0026mdash;marked by warmth, empathy, and mutual respect\u0026mdash;foster a secure environment in which adolescents can take academic risks, learn from mistakes, and develop self-efficacy. In contrast, conflictual or emotionally distant relationships can heighten stress and reduce confidence in one\u0026rsquo;s abilities.\u003c/p\u003e\n\u003cp\u003eHypothesis:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH3:\u003c/strong\u003e Family relationship quality is positively associated with self-efficacy among junior school students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFamily Factors and Study Weariness\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmpirical studies have demonstrated that high-quality family communication significantly alleviates psychological distress among adolescents. For instance, Ge\u0026ccedil;er et al. (2023) found through structural equation modeling that open, supportive exchanges reduce mental strain both directly and indirectly by fostering approach-oriented coping strategies, which enhance overall psychological well-being. From a Family Communication Patterns Theory perspective (Koerner \u0026amp; Fitzpatrick, 2002), conversation orientation encourages self-expression, emotional openness, and independent thinking, thereby enabling students to manage academic stress more effectively. Similarly, functional family systems\u0026mdash;characterized by adaptability, cohesion, and effective problem-solving\u0026mdash;have been linked to lower levels of study weariness through their capacity to reinforce positive competence beliefs and supply consistent emotional and instrumental support. Yu et al. (2021) further demonstrated that family cohesion and adaptability indirectly reduce study weariness by strengthening positive psychological capital (PsyCap) and peer support networks, which sustain motivation and engagement. These findings collectively suggest that supportive, adaptive family environments act as buffers against academic disengagement, sustaining motivation and emotional resilience in high-pressure educational contexts.\u003c/p\u003e\n\u003cp\u003eConversely, families marked by conformity-oriented communication, structural dysfunction, and low-quality relationships may exacerbate stress, erode motivation, and accelerate withdrawal from learning. Atkinson\u0026rsquo;s (2018) doctoral research indicated that such communication climates undermine academic resilience, fostering oppositional or avoidant coping patterns that contribute to disengagement. Huang et al. (2023) identified a chain-mediating process in which poor communication increases family conflict and violence, which in turn promotes problematic internet use, amplifying anxiety, depression, and disengagement from schoolwork. Despite this evidence, existing literature rarely integrates communication style, functional capacity, and relationship quality into a unified analytical model linking family environments to study weariness. Moreover, the role of study weariness as a multidimensional outcome\u0026mdash;encompassing emotional exhaustion, behavioral withdrawal, and cognitive devaluation\u0026mdash;remains underexplored in the family context. Addressing these gaps, the present study proposes to examine how these three family dimensions jointly influence study weariness, and to test the mediating role of self-efficacy in this relationship.\u003c/p\u003e\n\u003cp\u003eHypotheses:\u003c/p\u003e\n\u003cp\u003eH4:Family Communication Patterns is negatively associated with study weariness.\u003c/p\u003e\n\u003cp\u003eH5: Family function is negatively associated with study weariness.\u003c/p\u003e\n\u003cp\u003eH6: Family relationship quality is negatively associated with study weariness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Mediating Role of Self-Efficacy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDrawing from Social Cognitive Theory (Bandura, 1977), self-efficacy functions as a proximal determinant of behavior, mediating the impact of environmental inputs\u0026mdash;such as family dynamics\u0026mdash;on adolescents\u0026rsquo; academic engagement. Empirical evidence supports this mechanism. For example, in a study of Chinese middle school students, social support was found to enhance academic performance indirectly through a sequential pathway in which social support increased self-efficacy, which in turn heightened learning engagement (Zhang et al., 2024). Similarly, Shao et al. (2022) demonstrated that adolescents\u0026rsquo; peer relationships predicted learning engagement via a chain mediation involving self-efficacy and academic resilience. Research in higher education contexts further corroborates these findings; for instance, Yang et al. (2025) reported that functional family environments reduced study weariness among nursing students by elevating academic self-efficacy, which partially mediated this relationship. In addition, a large-scale investigation by Sun et al. (2025) revealed that strong parent\u0026ndash;child relationships diminished study weariness through both direct effects and indirect pathways involving interpersonal relationships at school and academic self-efficacy, highlighting the existence of both single and chain mediation effects.\u003c/p\u003e\n\u003cp\u003eCollectively, these studies affirm that competence beliefs\u0026mdash;operationalized as self-efficacy\u0026mdash;constitute a key conduit through which social environments influence academic adjustment. However, despite a robust theoretical foundation and substantial empirical coverage in domains such as peer influence and general family functioning, there remains a notable gap in the literature: few studies have systematically integrated family communication patterns, family functioning, and relationship quality within a unified SCT framework to examine their joint predictive roles in shaping study weariness. Moreover, existing models seldom differentiate between specific family communication orientations\u0026mdash;such as conversation-oriented versus conformity-oriented\u0026mdash;and how these orientations interact with other family dimensions to shape self-efficacy and, through it, vulnerability to study weariness.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Addressing this gap, the present study formulates targeted research questions and hypotheses to explore these interrelationships comprehensively(Table 1).\u003c/p\u003e\n\u003cp\u003eH7a: Self-efficacy mediates the relationship between Family Communication Patterns and study weariness.\u003c/p\u003e\n\u003cp\u003eH7b: Self-efficacy mediates the relationship between family function and study weariness.\u003c/p\u003e\n\u003cp\u003eH7c: Self-efficacy mediates the relationship between family relationship quality and study weariness.\u003c/p\u003e\n\u003cp\u003eTable 1. Summary of Research Hypotheses\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypothesis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathway\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExpected Direction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTheoretical Basis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eH1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eFCPs \u0026rarr; SEf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003ePositive (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eFamily Systems Theory;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Self-Efficacy Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eFF\u0026rarr; SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003ePositive (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eFamily Systems Theory;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSelf-Efficacy Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eFR\u0026rarr; SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003ePositive (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eFamily Systems Theory;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSelf-Efficacy Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eH4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eFCPs\u0026rarr;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eNegative (\u0026ndash;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eFamily Systems Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eH5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eFF\u0026rarr; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eNegative (\u0026ndash;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eFamily Systems Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eH6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eFR\u0026rarr; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eNegative (\u0026ndash;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eFamily Systems Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eH7a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eFCPs \u0026rarr; SE \u0026rarr; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eMediated (\u0026ndash;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eSelf-Efficacy Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eH7b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eFF\u0026rarr; SE\u0026rarr;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eMediated (\u0026ndash;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eSelf-Efficacy Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eH7c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eFR\u0026rarr; SE \u0026rarr; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eMediated (\u0026ndash;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eSelf-Efficacy Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 536px;\"\u003e\n \u003cp\u003eNote: FCPs: Fmily Communication Patterns, FR: Family Relationship, FF: Family Function, SE: Self-Efficacy, SW: Study Weariness.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eStudy\u0026rsquo;s conceptual framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom the literature discussed above, the conceptual framework (Figure 1) has been developed.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e\u003cstrong\u003eResearch Design.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed a quantitative, cross-sectional survey design to examine the relationships among family communication patterns (FCP), family functioning (FF), family relationship quality (FR), self-efficacy (SE), and study weariness (SW) in junior secondary students. The conceptual framework was grounded in Family Systems Theory and Self-Efficacy Theory, with SE modeled as a mediator linking family-level factors to SW. We adopted a multi-stage, stratified cluster sampling strategy to ensure representativeness across urban and rural settings, grades 7\u0026ndash;9, and boarding/day-school contexts in Taizhou, Zhejiang Province, China. Data collection was conducted online via the Wenjuanxing platform, under ethical guidelines approved by the relevant institutional review board. Participation was voluntary and anonymous, with informed consent obtained from both students and their guardians.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eSample Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 804 valid responses were retained (valid return rate \u0026asymp; 93.5%). The sample was balanced by gender (girls = 52%, boys = 48%), location (urban = 54%, rural = 46%), and included 66% boarding students. In line with national demographic patterns, 93% were from single-child households. The sample size exceeded the minimum statistical power requirements for PLS-SEM analysis (Hair et al., 2022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariable measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eIndependent variable\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003cstrong\u003eFamily Communication Patterns (FCPs)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeasured using an adapted version of the Family Communication Patterns Scale (Koerner \u0026amp; Fitzpatrick, 2002), comprising two subscales: Conversation Orientation (e.g., \u0026ldquo;In our family, we often talk openly about our feelings\u0026rdquo;), Conformity Orientation (e.g., \u0026ldquo;In our family, children are expected to follow parents\u0026rsquo; rules without question\u0026rdquo;). Items were rated on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Reliability coefficients in this study exceeded 0.85 for both subscales.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Independent variable\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003cstrong\u003eFamily Relationship(FR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study uses the Brief Family Relationship Scale (BFRS) (Fok et al., 2014) to measure family relationships across three dimensions: Cohesion, Expressiveness, and Conflict. Example items include \u0026ldquo;Family members really help and support one another\u0026rdquo; and \u0026ldquo;We fight a lot in our family\u0026rdquo; (reverse-coded). Responses are rated on a 5-point Likert scale, with higher total scores indicating stronger and more positive family relationships.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Independent variable\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003cstrong\u003eFamily Function (FF)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAssessed using the McMaster Family Assessment Device (FAD), focusing on adaptability, cohesion, and problem-solving capacities. The scale demonstrated strong internal consistency (Cronbach\u0026rsquo;s \u0026alpha; = 0.87). Family Relationships (FR) Evaluated via the Family Cohesion and Adaptability Evaluation Scale (FACES), emphasizing emotional bonding, trust, and mutual support within the family unit. Internal reliability was 0.89. \u0026nbsp;Items include statements such as \u0026ldquo;In times of crisis, we can turn to each other for support.\u0026rdquo; Responses are rated on a 5-point Likert scale (1= completely inconsistent to 5=completely consistent,), with higher scores reflecting better family functioning.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMediating variable\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003cstrong\u003eSelf-Efficacy (SE)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSelf-efficacy is measured using the General Self-Efficacy Scale (GSE) (Scholz et al., 2002), adapted for adolescents. Items captured students\u0026rsquo; confidence in managing learning tasks, overcoming challenges, and achieving academic goals (Cronbach\u0026rsquo;s \u0026alpha; = 0.90).Items include \u0026ldquo;I can always manage to solve difficult problems if I try hard enough.\u0026rdquo; Participants respond on a 5-point Likert scale (1 = not at all true to 5 = extremely exactly true), with higher scores indicating greater perceived self-efficacy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent variable:\u003c/strong\u003e\u003cstrong\u003eStudy Weariness (SW)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the quantitative assessment of study weariness adopts the Junior High School Students\u0026apos; Study Weariness Scale developed by Zhao (2019). This instrument comprises three core dimensions: first, the emotional weariness dimension (e.g., the item \u0026quot;I often feel bored during class learning\u0026quot;); second, the behavioral distancing dimension (e.g., the item \u0026quot;I frequently skip classes or arrive late\u0026quot;); third, the cognitive negation dimension (e.g., the item \u0026quot;I think learning is useless for future development\u0026quot;). All items are rated using a 5-point Likert scale (1= \u0026quot;strongly disagree\u0026quot;, 5=\u0026quot;strongly agree\u0026quot;), with higher scores indicating a more significant degree of students\u0026apos; study weariness.The scale combined items from validated study weariness measures, adapted to the junior school context. Reliability in this study was 0.91.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis techniques.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe estimated the research model in SmartPLS 4 using variance-based partial least squares structural equation modeling (PLS-SEM) to evaluate all hypotheses. PLS-SEM is a distribution-free approach that prioritizes the explained variance of latent (unobserved) constructs. It affords substantial modeling flexibility, works well with relatively small samples, does not require multivariate normality, and supports both formative and reflective measurement specifications without convergence difficulties. Consequently, applying PLS-SEM in SmartPLS is well suited for predicting linear relationships and analyzing complex structural frameworks (see, e.g., Becerra-Fernandez, 2001; Avkiran \u0026amp; Ringle, 2018). A key advantage is the direct use of R\u0026sup2; to assess the variance accounted for in endogenous variables, which strengthens model\u0026ndash;data alignment and the interpretability of predictive results. To examine robustness, we complemented the SEM with artificial neural network (ANN) analyses, using ANN to probe sensitivity to critical assumptions and to evaluate the stability of conclusions. In terms of software, all statistics were conducted with SPSS 24.0 and SmartPLS 4. First, SPSS provided descriptive summaries of the sample and an initial check of common method bias. Second, SmartPLS was used to assess measurement reliability and validity and to estimate the study\u0026rsquo;s main effects, mediation effects, and moderation effects.\u003c/p\u003e"},{"header":"Research results ","content":"\u003cp\u003e\u003cstrong\u003eMeasurement model\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e To assess the measurement model, we examined indicator reliability, internal consistency, convergent validity, and discriminant validity (Hair et al., 2020) (see Tables 2 and 3). The Cronbach\u0026rsquo;s \u0026alpha;, rho_A, and composite reliability values for all constructs in this study exceeded 0.70, demonstrating strong construct reliability (Hair et al., 2017). For indicator loadings, all values surpassed the threshold of 0.7, confirming robust item reliability. The average variance extracted (AVE) for each construct was above 0.60, supporting convergent validity (Hair et al., 2022). Discriminant validity was established as the square root of the AVE for each construct exceeded its correlations with other constructs (Fornell and Larcker, 1981), and all Heterotrait-monotrait ratio (HTMT) values were below 0.80, indicating clear distinction between constructs (Kline, 2011).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditionally, Harman\u0026rsquo;s single-factor test was conducted, revealing 5 factors with a cumulative explained variance of 63.083%, where the first factor accounted for 37.607% of the variance, below the 40% threshold. Thus, no significant common method bias was detected in this study.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"505\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 505px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2 Measurement model assessment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eConstruct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eLoading\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003eCronbach\u0026apos;s alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eComposite reliability (rho_a)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eComposite reliability (rho_c)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eAVE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003efamily communication patterns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFCP13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003efamily relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.640\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFR30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003efamily function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.765\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eFF12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eself-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSE10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003estudy weariness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.609\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eSW17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3 Assessment of discriminant validity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFCPS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFCPS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.769\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.495\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.756\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.463\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.792\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.763\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.764\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\n \u003cp\u003eFornell-Larcker criterion (below the main diagonal) and heterotrait-monotrait ratio (HTMT) (above the main diagonal). Main diagonal: in the bold square root of the AVE.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"530\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 530px;\"\u003e\n \u003cp\u003eTable 4 Structural relationships and hypothesis testing.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eHypotheses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003ePath\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eStd beta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eStd error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003et Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eResult\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFCPS\u0026rarr; SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e6.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFCPS\u0026rarr; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e4.931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFF\u0026rarr; SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e5.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFF\u0026rarr; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e3.523\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFR\u0026rarr; SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e6.293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFR\u0026rarr; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e5.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eSE\u0026rarr;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e5.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFCPS -\u0026gt; SE -\u0026gt; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e4.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFF -\u0026gt; SE -\u0026gt; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e3.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eH10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFR -\u0026gt; SE-\u0026gt; SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e4.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStructural model.\u003cspan id=\"_Toc17652\"\u003e\u0026nbsp;First, we examined collinearity within the structural model. All variance inflation factor (VIF) values were below 3, confirming the absence of multicollinearity concerns (Hair et al., 2019). Next, we evaluated the path coefficients and their significance. As shown in Table 4, all standardized beta (\u0026beta;) values were statistically significant with strong t-statistics. Study weariness (SW) was significantly influenced by self-efficacy (SE) (\u0026beta; = -0.212, t = 5.390, p \u0026lt; 0.001), family communication patterns (FCPS) (\u0026beta; = -0.188, t = 4.931, p \u0026lt; 0.001), family function (FF) (\u0026beta; = -0.138, t = 3.523, p \u0026lt; 0.001), and family relationships (FR) (\u0026beta; = -0.212, t = 5.643, p \u0026lt; 0.001). SE, in turn, was significantly predicted by FCPS (\u0026beta; = 0.244, t = 6.280, p \u0026lt; 0.001), FF (\u0026beta; = 0.226, t = 5.745, p \u0026lt; 0.001), and FR (\u0026beta; = 0.243, t = 6.293, p \u0026lt; 0.001). Thus, all hypotheses (H1\u0026ndash;H10) were supported. Finally, we assessed the model\u0026rsquo;s explanatory and predictive power. The coefficient of determination (R\u0026sup2;) for SW and SE was 0.592 and 0.548, respectively, both exceeding the threshold of 0.25, indicating substantial explanatory strength. The predictive relevance (Q\u0026sup2;) values for SW and SE were 0.351 and 0.342, respectively, both above zero, confirming the model\u0026rsquo;s predictive capability. Additionally, the goodness-of-fit (GoF) index for the PLS-SEM was 0.529, surpassing the benchmark of 0.36, further validating the model\u0026rsquo;s robustness.\u003cbr\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 \u0026nbsp;RMSE value of 10-fold ANN models.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"578\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeural network\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 240px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInput:FCP,FR,FF,Gender,Grade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInput:FCP,FR,FF,SE,Sibling status,Family structure,Grade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eoutput:SE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eoutput:SW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTraining\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTesting\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTraining\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTesting\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.164\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.148\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.138\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.150\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.167\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.152\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.139\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.122\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.164\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.152\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.135\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.141\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.163\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.153\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.141\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.105\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.160\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.159\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.138\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.149\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.168\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.158\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.141\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.125\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.164\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.156\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.139\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.144\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.158\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.169\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.138\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.152\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.170\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.163\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.141\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.132\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eANN10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.162\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.132\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.152\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.126\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.164\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.154\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.140\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.135\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.0000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.0001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.0000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.0002\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 6 \u0026nbsp;Comparison of PLS-SEM and ANN results.\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"879\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePLS Path\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOriginal Sample(O)/Path coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANN results:Normalized relative importance(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRanking(PLS-SEM)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e[based on Path Coefficient]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRanking(PLS-SEM)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e[based on normalized relative importance]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRemark\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 879px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel A--FCP,FR,FF,Gender,Grade-\u0026gt;SE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eFCP-\u0026gt;SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.219\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e89.34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eMatch\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eFF-\u0026gt;SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.193\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e100.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eFR-\u0026gt;SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.235\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e54.76%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eGender-\u0026gt;SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.134\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e9.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eGrade-\u0026gt;SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.114\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e15.02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 879px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel B---FCP,FR,FF,SE,Sibling status,Family structure,Grade-\u0026gt;SW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eFCP-\u0026gt;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;-0.189\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e74.41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eFF-\u0026gt;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;-0.137\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e60.98%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eFR-\u0026gt;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;-0.236\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e100.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eMatch\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eFamily structure-\u0026gt;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.027\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e6.79%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eGrade-\u0026gt;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;-0.061\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e8.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eSE-\u0026gt;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;-0.204\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e50.36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eSibling status-\u0026gt;SW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;-0.066\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e8.12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eNot Match\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\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePredictive Analysis Using ANN：An Artificial Neural Network (ANN) analysis was conducted to evaluate the predictive power and determine the relative importance of key variables. The model exhibited high predictive accuracy, with root mean square errors (RMSE) of 0.154 for self-efficacy and 0.135 for study weariness under 10-fold cross-validation. For self-efficacy, the most influential predictors were family communication patterns (89.34%), family relationship quality (54.76%), family function (100.00%), and grade (15.02%). In predicting study weariness, self-efficacy emerged as the most dominant factor (50.36%), followed by family function (60.98%), family relationship quality (100.00%), and family communication patterns (74.41%)(Table 5). These results highlight self-efficacy as the strongest proximal predictor of study weariness, while family conversation orientation and family relationship quality stand out as the most influential environmental predictors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMediation effects.\u0026nbsp;\u003c/strong\u003eWe employed the bootstrapping method (804 samples) to examine whether self-efficacy (SE) mediated the relationships between family-related constructs (FCPS, FF, FR) and study weariness (SW). To assess mediation, we first verified the significance of each path coefficient before analyzing the variance accounted for (VAF) to determine mediation type (no, partial, or complete mediation). The VAF thresholds were defined as follows: VAF \u0026lt; 0.20 (no mediation), 0.20 \u0026le; VAF \u0026le; 0.80 (partial mediation), and VAF \u0026gt; 0.80 (full mediation).\u003c/p\u003e\n\u003cp\u003eAs presented in Table 6, family communication patterns (FCPS) exhibited a significant indirect effect on SW through SE (\u0026beta; = -0.059, p \u0026lt; 0.001, VAF = 0.239), indicating partial mediation. Similarly, family function (FF) indirectly influenced SW via SE (\u0026beta; = -0.056, p \u0026lt; 0.001, VAF = 0.229), also supporting partial mediation. Lastly, family relationships (FR) showed a significant indirect effect on SW through SE (\u0026beta; = -0.065, p \u0026lt; 0.001, VAF = 0.235), further confirming partial mediation. Thus, hypotheses H8, H9, and H10 were fully supported, demonstrating that SE partially mediates the relationships between family-related factors and study weariness.\u003c/p\u003e"},{"header":"Conclusion and Discussion","content":"\u003cp\u003e\u003cstrong\u003eMain Findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDrawing on a sample of 804 junior high school students in Taizhou, this study applied partial least squares structural equation modeling (PLS-SEM) in combination with artificial neural networks (ANN) to investigate the interplay between family communication patterns (FCP), family functioning (FF), family relationships (FR), self-efficacy (SE), and study weariness (SW). The findings indicate that conversation-oriented family communication patterns, healthy family functioning, and high-quality family relationships significantly enhance students\u0026apos; self-efficacy, which in turn directly and indirectly reduces schoolwork burnout. By contrast, conformity-oriented communication and suboptimal family processes were associated with greater burnout risk.\u003c/p\u003e\n\u003cp\u003eThe SEM results revealed significant positive effects of FCP (\u0026beta; \u0026asymp; 0.22, p \u0026lt; .001), FF (\u0026beta; \u0026asymp; 0.19, p \u0026lt; .001), and FR (\u0026beta; \u0026asymp; 0.24, p \u0026lt; .001) on SE, and significant negative effects of FCP (\u0026beta; \u0026asymp; -0.19, p \u0026lt; .001), FF (\u0026beta; \u0026asymp; -0.14, p \u0026lt; .001), and FR (\u0026beta; \u0026asymp; -0.24, p \u0026lt; .001) on SW. SE itself had a significant negative path to SW (\u0026beta; \u0026asymp; -0.20, p \u0026lt; .001), supporting its role as a proximal psychological mediator between family context and burnout.\u003c/p\u003e\n\u003cp\u003eConsistent with these patterns, additional analyses confirmed that the effects of FCP, FF, and FR on SW were partially mediated by SE, and that all three indirect pathways were statistically significant. ANN analysis further underscored the robustness of these results: FR and FCP emerged as the most influential predictors of SE, with normalized importance values of approximately 100% and 89%, respectively. In predicting SW, FR and FCP again ranked highly, while SE itself accounted for nearly half the predictive power\u0026mdash;reinforcing its central role as a proximal determinant of burnout.\u003c/p\u003e\n\u003cp\u003eOverall, the evidence highlights three key findings: family relationships and the communication climate serve as critical external factors shaping students\u0026apos; learning-related attitudes and behaviors, while self-efficacy acts as the central psychological mechanism linking family dynamics to schoolwork burnout. Notably, family relationships (FR) exert a particularly strong direct effect in mitigating burnout, and family communication patterns further enhances this protective role by positively influencing students\u0026apos; self-efficacy (SE).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study makes several key theoretical contributions. First, by integrating family systems theory and self-efficacy theory, it demonstrates that communication patterns, family functioning, and relationship quality synergistically shape students\u0026apos; self-efficacy (SE), which in turn influences academic engagement and emotional resilience. This empirically validated framework, tested in a Chinese junior high school context, advances theoretical understanding of the \u0026apos;family\u0026ndash;psychology\u0026ndash; learning\u0026apos; mechanism. Second, by distinguishing between the two dimensions of family communication patterns (FCP)\u0026mdash;conversation orientation and conformity orientation\u0026mdash;the study reveals their asymmetrical effects: conversation orientation fosters autonomy and resilience, whereas conformity orientation may suppress self-expression and undermine capability beliefs, offering precise leverage points for family interventions. Third, the research establishes SE as the central proximal mechanism linking family factors to burnout, with both SEM mediation tests and ANN importance rankings converging on its pivotal role as an intervention target. Finally, the simultaneous examination of multiple family factors within a mediation framework, combined with a dual-method approach (SEM and ANN), provides both conceptual depth and methodological innovation for future educational research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodological Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe parallel use of PLS-SEM and ANN represents a methodological advancement: SEM identifies causal pathways and effect sizes, while ANN evaluates predictive accuracy and variable importance. This \u0026quot;causality\u0026ndash;prediction\u0026quot; dual strategy enhances robustness, interpretability, and generalizability, offering a replicable blueprint for similar studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePractical Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings yield actionable implications across multiple levels. At the family level, they underscore the value of structured conversation-based communication training\u0026mdash;such as active listening, paraphrasing, and open-ended questioning\u0026mdash;alongside enhanced emotional support skills to reduce reliance on authoritarian directives and excessive conformity demands. At the school level, the results advocate for integrating home-school collaboration into student support systems, employing coordinated strategies to strengthen self-efficacy (e.g., goal decomposition, mastery experiences, peer modeling, positive reinforcement, and emotional regulation), particularly during critical transition periods. At the policy level, the study highlights the need for community-based family education programs, complementing structural reforms like China\u0026apos;s \u0026apos;Double Reduction\u0026apos; policy(Ministry of Education of the People\u0026rsquo;s Republic of China, 2021), to institutionalize family capacity-building as a core component of local education governance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhy do family relationships and communication exert such strong effects? From a Family Systems Theory lens, adolescent burnout reflects systemic misalignments rather than isolated traits. Families regulate emotion and information via recurrent rules, roles, and boundaries. Conversation-oriented, cohesive, and adaptable systems generate constructive feedback loops: shared narratives supply meaning, scaffolding builds competence (self-efficacy), and secure bonds ensure connection\u0026mdash;stabilizing the whole system under academic stress. In contrast, conformity-driven, rigid, or conflictual patterns intensify negative feedback (criticism, triangulation, emotional cutoff), yielding powerlessness, meaninglessness, and disconnection. Therefore, restructuring communication rules and relational boundaries recalibrates family homeostasis, indirectly strengthening adolescents\u0026apos; self-efficacy and reducing emotional exhaustion and disengagement.\u003c/p\u003e\n\u003cp\u003eSelf-efficacy emerges as the nexus in this process. It shapes persistence and effort while also influencing how academic stress is appraised. Family environments that provide mastery experiences, verbal encouragement, and emotional reassurance strengthen SE, reframing academic challenges as manageable and interrupting the burnout cycle. In contrast, controlling and low-trust family climates erode SE, fostering avoidance behaviors and reinforcing patterns of underachievement.\u003c/p\u003e\n\u003cp\u003eAlthough grade level and gender exerted only modest effects in the current data, tailored interventions should still consider micro-contexts such as school transition points, gender role expectations, and boarding versus day-school arrangements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations and Future Directions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral limitations warrant consideration. First, the cross-sectional design restricts the ability to draw causal inferences, underscoring the necessity of longitudinal research to examine how variations in family processes correspond with changes in self-efficacy (SE) and subjective well-being (SW) over time. Second, the exclusive reliance on self-report measures raises concerns regarding common method bias and social desirability effects; future investigations would benefit from incorporating multi-informant assessments (e.g., parent and teacher reports) alongside behavioral indicators (e.g., classroom engagement, homework completion). Third, the cultural specificity of the sample constrains the generalizability of findings, highlighting the value of cross-cultural comparative studies. Furthermore, the current model could be enriched by integrating additional mediators or moderators\u0026mdash;such as academic resilience, perceived parental support, and emotion regulation strategies\u0026mdash;and by evaluating low-cost, scalable interventions in ecologically valid settings. Methodologically, future research might employ Bayesian structural equation modeling (SEM) or causal forest approaches to enhance analytical robustness, while, in practical terms, randomized controlled trials or quasi-experimental designs could be used to assess the combined effects of \u0026quot;parent communication training\u0026quot; and \u0026quot;student self-efficacy training\u0026quot; programs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study provides consistent evidence\u0026mdash;across both SEM and ANN analyses\u0026mdash;that high-quality family relationships and conversation-oriented communication, by enhancing self-efficacy, substantially reduce study weariness (SW) among junior high school students. The findings advance theory, methodology, and practice by highlighting self-efficacy as a pivotal intervention target and by demonstrating the value of integrating family-based strategies into educational support systems.\u003c/p\u003e\n\u003cp\u003eFor families, building communication skills, emotional support, and functional capacity should be ongoing priorities. For schools, self-efficacy should occupy a central place in student development frameworks. For policymakers, institutionalizing family education services and linking them to school reform efforts can create a structure\u0026ndash;psychology\u0026ndash;behavior chain of governance. Through such coordinated action, the deeper psychological roots of learning burnout can be addressed, fostering sustained engagement and healthy academic development in the post\u0026ndash;\u0026quot;Double Reduction\u0026quot; era.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinal Reflections\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study illuminates the centrality of family environments in shaping junior school students\u0026apos; academic engagement. By demonstrating that family communication, function, and relationships collectively influence self-efficacy\u0026mdash;and, in turn, study weariness\u0026mdash;the research offers a roadmap for holistic interventions. Strengthening family systems, nurturing self-efficacy, and aligning policy with psychosocial needs can collectively address the pervasive challenge of study weariness. As educational landscapes evolve, integrating family-focused strategies into broader reforms will be essential for fostering resilient, motivated learners in China and beyond.\u003c/p\u003e\n\u003cp\u003eIn conclusion, the persistence of study weariness demands multidimensional solutions. This study not only advances theoretical understanding but also provides actionable insights for families, educators, and policymakers. By bridging the gap between family dynamics and academic outcomes, it lays the groundwork for future research and practice aimed at sustaining adolescent well-being and educational success.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cbr\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This study was approved by the UCSI UNIVERSITY of Ethics Committee, Malaysia. \u0026nbsp; (Approval \u0026nbsp;No. IEC-2025-FOSSLA-0038). All procedures involving human participants were conducted in accordance with the Declaration of Helsinki and relevant institutional guidelines. 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Shanghai J Educ Res 10:27\u0026ndash;30\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"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},"keywords":"Study weariness, Family communication patterns, Family function, Family relationships, Self-efficacy, Mediation analysis","lastPublishedDoi":"10.21203/rs.3.rs-7415609/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7415609/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates how three core family factors\u0026mdash;family communication patterns, family functioning, and family relationship quality\u0026mdash;jointly influence study weariness among junior secondary school students, with self-efficacy as a mediating mechanism. Drawing upon Family Systems Theory and Self-Efficacy Theory, we propose and empirically test an integrated \u0026ldquo;Family\u0026ndash;Self-Efficacy\u0026ndash;Burnout\u0026rdquo; framework. A stratified cluster sample of 804 students from urban and rural schools in Taizhou, China, completed validated measures of the target constructs. Partial least squares structural equation modeling (PLS-SEM) was used to examine causal pathways, complemented by artificial neural network (ANN) analysis to assess predictive power and variable importance. Results show that conversation-oriented communication, functional adaptability, and high-quality family relationships significantly enhance self-efficacy, which in turn reduces study weariness. Self-efficacy partially mediates all three family\u0026ndash;burnout links. ANN analysis further underscores self-efficacy as the strongest proximal predictor, while family relationship quality emerges as the most influential environmental factor. These findings advance theory by integrating multiple family-level predictors and a psychological mediator within a unified framework, and methodologically by demonstrating the complementary strengths of SEM and ANN in educational research. Policy implications include embedding structured family communication training and self-efficacy enhancement programs into school\u0026ndash;family partnerships to address the deep psychosocial roots of study weariness.\u003c/p\u003e","manuscriptTitle":"The Impact of Family Factors on Study Weariness among Junior School Students: the Mediating role of Self-efficacy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-19 10:13:50","doi":"10.21203/rs.3.rs-7415609/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":"218af47b-c850-4706-8124-3b6b0df6f631","owner":[],"postedDate":"September 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":54649572,"name":"Health sciences/Health care"},{"id":54649573,"name":"Biological sciences/Psychology"},{"id":54649574,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2025-12-30T04:39:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-19 10:13:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7415609","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7415609","identity":"rs-7415609","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}